Report No. 9888-MAI

MalawiEconomic Report on Environmental Policy(In Two Volumes) Volume Il: Technical Annexes

March 20, 1992

Country Operations DivisionSouthern Africa Department

FOR OFFICIAL USE ONLY

Document of the World Bank

This document has a restricted distribution and may be used by recipientsonly In the performance of their oiticial duties. Its contents may not otherwisebe diclosed without World Bank authorization.

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CURRENCY EQUIVALENTS

US$1 MK 2.79MK I US$0.36

WEIGHTS AND MEASURES

1 Kilogram (kg) - 2.2 Poundr1 Metric Ton (mt) = 2,204.6 Pounds1 Liter (1) 2.116 US Pints1 Hectare (ha) 2.471 Acres1 Cubic Meter (cm3) = 35.3 Cubic FeetI Kilometer (km) = 0.621 Miles

GLOSSARY OF ABBREVIATIONS

ADD - Agricultura! Development DivisionADMARC - Agricultural Development and Marketing CorporationAES - Agro-Economic Surveyaic - average incremental costsASA - Annual Survey of AgricultureASAC - Agricultural Sector Adjustment CreditCEM - Country Economic MemorandumCITES - Convention on Intl. Trade in Endangered Species of Wild Fauna and FloraDEVPOL - Statement of Development PoliciesDLV - Department of Lands and ValuationDNPW - Department of National Parks and WildlifeDWSF - District Water Supply FundEES - Estate Extension ServiceEPA - Environmental Planning Areaehu - erosion hazard unitEIA - Environmental Impact AssessmentEP&D - Economic Planning and Development DepartmentEU - Environment Unit, National Research CouncilFAO - Food and Agricultural OrganizationIITA - International Institute for Tropical AgricultureLHB - Land Husbandry Branchl/p/d - liters per daymai - main annual incrementMBS - Malawi Bureau of StandardsMOA - Ministry of AgricultureNCE - National Committee for the EnvironmentPFP - Policy Framework PaperRDP - Rural Development ProjectSACA - Smallholder Agriculture Credit AdministrationSan-Plat - sanitation platform latrineSLEMSA - Soil Loss Estimation Model for Southern Africat/ha/yr - tons per hectare per yearUSAID - United States Agency for International DevelopmentUSLE - Universal Soil Loss Estimation ModelVIP - ventilated improved pit latrine

GOVERNMENT OF MALAWIFISCAL YEAR

Anril 1 tn " reh t1

FOR OFFICIAL USE ONLY

Page No.VOLUME II:- TECHNICAL ANNEXES

Annex 1: Methodological Note on Estimation of Soil Erosion Rate .... ......... IAnnex 2: Autoregressive Trend Model of Relative Producer Price Stability .... .... 22Annex 3: Methodological Note on Estima.ion of Deforestation Rate and Value ... ... 26Annex 4: Methodological Note on Estimation of Water Extraction Rate .... ...... 62Annex 5: Methodological Note on Estimation of Average Incremental Costs in Water . 70Annex 6: Methodological Note on Estimation of Valuation of Protected Land ... ... 85Annex 7: Inventory of Malawi Environmental Legislation ................... 95Annex 8: Econometric Model of Private Sector Price Responsiveness in Afforestation 115

This report is based on the findings of a mission that visited Malawi in August 1990. Missionmembers were Richard Scobey (Mission Leader, AF6CO), Ben Kamugasha (AFTEN), SvenJacobi (RWSGEA), Edward Barbier, Joshua Bishop, J1janne Burgess, Michael Colby, MosheFinkel, William Hyde, Juan Seve, and Jane Walker (Consultants). Ben Kasomekera (BundaCollege, Malawi) and Edward Laisi (Water Department, Malawi) also contributed backgroundpapers to the report. William Magrath (ASTEN) provided valuable comments as peerreviewer, Brigida Tuason (AF6CO) assisted in analytical work, and Georgette Johnson(AF6CO) provided secretarial support.

This document has a restricted distribution and may be used by recipients only in the performanceof their official duties. Its contents may not otherwise be disclosed without World Bank authorization.

Annex 1Page 1 of 21

METHODOLOGICAL NOTE ON ESTIMATATION OF SOIL EROSION RATE

I. Introduction

1. Soil fertility .ecline results from the leas of organic matterand chemical nutrients, through leaching and the removal of crops andresidues, compaction and loss of soil structure, and physical erosion oftop soil by rainfall. In this study we use the latter as a proxy foroverall fertility decline. The justification for this simplificationcomes from studies showing that soil loss is a reliable predictor ofchanges in soil nutrient content, soil pH, and moisture retention (Lal1981). In the following pages, we will use estimates of soil erosion tocalculate expected annual crop yield losses, based on statisticalrelations experimentally derived in Nlgeria (Lal 1987). We furtherexpress yield losses in terms of foregone farm. income, to determinegross economic losses from land degradation, based on a simple modeldeveloped previously for Mali (Bishop, 1989).

II. Rates of Land Degradation and Soil Erosion

Existing Field Data

2. Data from field studies of fertility decline and soil loss inM4alawi are scanty. From the farmer's perspective, the most relevantmeasure of land degradation is yield decline. Results of continuousmaize trials at Chitedze Research Station, from 1955 to 1963 and for sixdifferent treatments of crop residues, reveal a mean decline of 492 overeight years for unfertilized maize, or a 9.12 average annual declineduring the period (Dept. of Agr. Annual Report for 1962/63, pub. 1965).A more recent depiction of yield decline for unfertilized local maizecompares average yields for four ADDIs in 1957-62 versus 1985-87,revealing a mean total decline of 41? over the period, or an averageannual decline of about 2? (Twyford, 1988).

3. Another measure of fertility decline is a decrease in organicmatter and-plat nutrients under cultivation. Analysis of soil sampledata from fertilizer trials carried out at Bvumbwe Agricultural ResearchStation, on land continuously cropped with tea over 25 years and withminimal application of fertilizer (45 kg N ha-' yr-1 ), revealed a 412total decline in organic matter, a 38Z decline in total Nitrogen, and a5? decline in total Phosphorus, relative to virgin land (Maida &

t ~~~Chll$ma, 1981).

4. The meisure of land degradation employed in this analysis isphysical soil loss, in tons per hectare. Se located five studies thatreported soil erosion under various crop cover and land husbandryregimes in Malawi. The reported soil losses are not strictly

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comparable, due to widely varying plot sizes (from 1 - 170,000 mi). Ontha average, however, annual soil loss under traditional cultivation(i.e. maize, weeded and ridged) is about 19 t/ha. Average annualrainfall recorded at the five stations was 950 mm, and the mean slopewas 142.

Predictive Models

5. The leading predictive model for soil erosion research is theUniversal Sol.l Loss Estimation (USLE) model, developed in the U.S.A.(Wischmeier and Smith, 1978). Although widely tested and corroborated,some authors dispute the validity of the USLE model under tropicalconditions (Stocking 1987).

6. Among many proposed alternative models is the Soil LossEstimation Model for Southern Africa (SLEMSA), developed in Zimbabwe(Elwell, 1978; Elwell and Stocking 1982). SLEMSA was designed for usein countries with limited capacity to generate the physical datarequired by the USLE and other models. A preliminary evaluation ofSLEMSA under Halawian conditions compared the predictions of the modelto actual soil loss measured on experimental catchments near the BvumbweAgricultural Research Station (Mwendera 1988). The results wereinconclusive from a statistical standpoint, due to insufficient data.

7. Recently a modified version of ax MSA was developed, again inZimbabwe, for reconnaissance level evaP'- ,ion of erosion hazard(Stocking et al., 1988), The methodology is designed to make relativeassessments of the risk of erosion over large areas, expressed inErosion Hazard Units (EHU). The model uses precipitation data toestimate rainfall energy (E), which is combined with an index of soilerodibility to calculate an erosion hazard index (lb). The protectionprovided by vegetal cover is also incorporated, along with average slope(X). The authors stress that the model is not designed to predict soillosses in tons per hectare, since it fails to account for the depoaltionof eroded sediments within catchments. The technique was first appliedin an Erosion Hazard Happing of Zimbabwe (Madhiri and Manyanza, 1989).

Erosion Hazard MagRina of Malawi

S. An evalu' of erosion hazard in Malawi was carried out bytwo members of tl Husbandry Branch of the Department ofAgriculture (Khon. Ad Machira, 1987), using the methodology developedin Zimbabwe. The authors prepared a 10xlO km grid map of Malawi at11,000,000 scale, which displays the mean erosion hazard (EHU) for1,044 grid squares. The results are also presented in tabular form inan appendix to their draft report, with rainfall energy (E), erosionhazard index (ld)' vegetal cover ratio (C), mean slope (X) and ENU

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listed for 1,048 grid squares. 1/ EHU values range from 0 to amaximum of 7,195, with a mean value of 328 (weighted by the estimatedproportion of each grid square falling inside the boundaries of Malawi).Mean slope on all areas is 6.32. In their report the authors-present asimplified EHU map (scale 1:3,000,000), for which EHU scores have beenconverted into eight categories. For each category they furtherestimate expected annual soil loss in tons per hectare.

9. While recognizing the danger of exaggeration inherent inconverting EHU into soil loss, we adopt the estimates of annual erosionmade by Khonje and Machira in the analysis that follows. The reader isasked to consider the argument presented below as an illustration of thepossible extent, distribution, and costs of land degradation, ratherthan as an exact representation.

10. The conversion rule used by Khonje and Machira is a stepfunction, and ignores intermediate values within categories. Wetransform their rule into a general equation for converting EHU intoexpected soil loss, by simple regression analysis. The best fit wasestablished with a set of three equations. A maximum soil loss rate of50 t/ha/yr was assumed for all grid squares with EHU > 1000.

For: 0 < EHU < 500 . . . . . . E - 1.968(EHU)04 (1)

Adj. Rs = 0.976T-statistic - 15.7

500 c EhU < 1000 . . . . . E - 30 + 0.02(EHU) (2)

1000 < MM . . . . . . . . . E - 50 (3)

Land Use Data Base

11. General information on land use was derived from 1:1,000,000maps provided by the Land Husbandry Branch, showing the limits ofDistricts, Rural Development Projects (RDP), Special ̂ rop Authorities(SCA), National Parks, Forest and Game Reserves. By tracing andoverlaying all of these maps with the erosion hazard map of Khonje andMachira, and estimating the proportion of each EHU grid square lyingwithin a particular administrative unit, we compiled a data base of1,855 land use units. The mean surface area of the map units is about

I/ Our copy of ft report was noomplete and lacked pans of the appendbL Moreover, 127 gd squaresshown on the map and listed In the report do not share the sarne values. For this analysis we genwally usethe values roported In the appendix, In preference to those on the map, except where the former are msngin our copy. We were able to reornstu mean slope values for rd squares missing In the report appendix,by exapoat from EHU values shown on the map.

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51 kM2. For each unit we recorded six attributes, of which the firstthree are taken directly from Khonje and Machira:

(i) grid coordinates,(ii) EHU score,(iii) mean slope (0.82, 2.62, 5.22, 9.02, or 13.52),(iv) estimated proportion of the grid square falling within the

boundaries of Malawi,(v) estimated proportion of the grid square falling within a

specific administrative area,(vi) the name of the specific administrative area.

12. The last of these attributes assigns each map unit one of 155labels, corresponding to the RDP, district, special crop authority, gameor forest reserve in which it lies. The data base thus generated shouldnot be considered a definitive analysis of land use in Malawi. It is--ough that our estimates of the surface area of major land usecategories correspond more or less to previously published figures.

Excluded Areas

13. The land use data base permits the distlnction of reservedareas, which are excluded from our analysis of the costs of soilerosion, on the assumption that most if not all of this land isuncultivated. We also assume that some unreserved swampy land is eithernot cultivated or receives significant deposits of eroded sediment (i.e.no net soil loss). Finally, the very steepest slopes are assumeduncultivated.

14. We consulted three sources which give estimatee of the totalarea of 3 uncultivable* swamps and steep slopes in Malawi: The NationalPhysical Development Plan (1986), Brunt, Mitchell and Zimmerman (FAO1984), and Stobbs and Jeffers (1985). Their figures were used to guidethe selection of rules for excluding certain grid squares from ouranalysis. In the end we define and exclude as uncultivated swampy landall those grid squares with mean slope equal to 0.81 and EHU scoresbelow 8. Uncultivated steep slopes were defined as all squares withmean slope equal to 13.5Z. The latter rule results in an excluded areasomewhat smaller than other estimates of land with slopes over 121,which are considered unarable by the Land Husbandry Branch, but are infact often cultivated.

15. With these rules of exclusion and the data base describedabove, we calculate the total surface of each administrative area,distinguishing uncultivated reserves, swampy land and steep slopes.Gross arable land is what remains and is the area assumed subject tocrop losses arising from erosion. A full tabulation of our resultsversus other estimates is given in Appendix 1.

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Paae S o_' 2.

Estimated Soil Loss

16. For each mar unit not excluded, we estimate the mean annualrate of soil erosion (t/ha) based on the equations derived from Khonjeand Machira. Summing across map units, we can calculate the mean rateof soil loss by RDP and by District on gross arable land (weightsd bythe surface area o_ each affected map unit). Detailed results arepresented in Appendix 2. For Malawi as a whole, we estimate a meancurrent rate of soil erosion of 20 t/ha/yr on gross arable land.Recalling that we assume a maximum rate of 50 t/ha/yr on any map unit,the highest estimates of erosion or. arable land occur in Nkhata BayDistrict (43 t/ha), Chirauzulu District (39 t/ha), and Dowa Hills RDP(36 tlha). The minimum estimate (10 t/ha) occurs in Balaka and KawingaRDP's.

II. Costs of Soil Erosion

Off-Site and On-Site Costs

17. Soil erosion can impose economic costs in two fundamental ways:through on-site reductions in crop productivity and farm income, andthrough off-site effects resulting from increased runoff, siltation, andwater flow irregularities. The latter may affect the quality andreliability of urban water supply, the life span of hydro-electric powerfacilities, dredging costs for irrigation schemes, and fisheriesproductivity,

18. Data to estimate the off-site costs of erosion in Malawi areunavailable, but a number of factors suggest that these costs may below. Ground water is plentiful in most areas, while filtering costs area very small fraction of water supply costs. Malawi also has littlehydro-electric and irrigation infrastructure. Fisheries may be moreseriously affected, but the data needed to determine costs imposed byeroded sediments are not available. On the other hand, the size of theagricultural sector, combined with apparent market failures which canlead farmers to deplete top soil at an inefficient rate, suggest thaton-site costs may be quite high.

19. The on-site costs of soil erosion may be captured and evaluatedin a number of ways: in terms of reduced crop yields, the replacementcost of eroded plant nutrients, or r-ost directly in terms of the reducedresale or rental values of agricultural land. The latter would be themost direct reflection of a reduction in the discounted present value ofthe income generating potential of a particular plot of land, relativeto alternative investments. Agricultural land markets in Malawi hardlyexist, however, and there is no data.

20. Evaluation of the replacement cost of eroded nutrients is anapproach that has been applied in Zimbabwe (Stocking, 1986). The methodis based on a set of statistical relations linking soil loss to nutrient

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losses, derived from multi-year data from across Zimbabwe. Financialanalysis estimated annual losses of Nitrogen and Phosphorus worth US$150million on arable land alone (30,000 km 2 ). As pointed out in thereport, these losses understate the true cost of erosion, sa they do notaccount for losses of soil organic matter, which can affect soilstructure, water-holding capacity and nutrient availability. 2/

21. Evaluation of yield losses has the benefit of capturing all ofthe on-site effects of soil erosion on soil fertility and thus on farmproductivity. Yields reflect not only the presence of major nutrients,but many other attributes of soil fertility. The problem is to find alink between soil loss and crop yields.

Existing Data on the Erosion-Yield Relation

22. There are few data linking crop yields to soil erosion inMalawi. Experiments at Nkhande Research Station on a 442 slope showyields under traditional cultivation falling 622 between 1985/86 and1986/87, from 815 to 308 kg/ha, where annual soil loss was 76 t/ha. Onan adjoining alley-cropped plot, soil loss averaged only 3.7 t/ha/yr,and yields rose over the same period from 2,050 to 2,700 kg/ha (Chome,1989). While tho example is illustrative of the effects of soil loss,it cannot provide a general rule for estimating yield losses arisingfrom erosion.

Predictive Models

23. For this analysis we use a simple model to predict crop yieldlosses from estimated rates of erosion. The model is a generalizedversion of statistizal relations between crop yields and soil loss,which were estimated using data from side-by-side, multi-year trialscarried out in Nigeria at the International Institute for TropicalAgriculture (Lal, 1987). The IITA equations predict the effects ofcumulative natural soil loss, in tons per hectare, on yields of maizeand cowpea, relative to yields on newly cleared (uneroded plots). Theyare of the form:

Y Q C-O (4)

wheres Y = ;ield in tons per hectareC - yield on uneroded (newly cleared) landp - coefficient varying by crop and slopex - cumulative soil loss (t/ha)

gy We do not use this approach for the present analysis, alhough data from the Soi Erosion Research Projectat Bvumbwe would permit an estimation of the relation between soil loss and nutini loss under Malawicondons (Amphlett, 1988).

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24. Lal estimated eight equations, one for each crop and fourslopes (1, 5, 10, and 15Z). The estimated coefficients (p) variedbetween 0.002 and 0.036 for cowpea, and between 0.003 and 0.017 formaize, with the greatest losses recorded on gentle slopes. All but oneof the Beta coefficients are significant to 5Z.. Correlationcoefficients (r) were between 0.66 and 0.99.

25. Agricultural conditions in Malawi and southwestern Nigeria areof course not comparable, but we can assume that the general form of thecrop response to soil erosion will be similar. Note that thespecification of the equation implies a constant elasticity of yieldwith respect to cumulative erosion. In other words, the percentageyield loss in the first year is exactly the same as the percentage lossin the tenth year, assuming a constant rate of erosion. It is enough toknow the annual rate of soil loss and mean current yields to estimatecurrent crop losses. We thus drop the constant (C) and calculate apercentage yield decline for every level of soil erosion. To accountfor the uncertain sensitivity of crop yields to soil loss under Malawiconditions, we use a range of coefficients (p) and estimate a wide rangeof yield losses. The coefficients tested here are p 0.002, 0.004,0.006, 0.010, and 0.015.

26. We apply the equation described above to every map unit in thedata base, excluding reserved and unarable land. Results by RDP and byDistrict are presented in Annex 2. For Malawi as a whole, estimatedmean annual yield losses lie between 42 and 252, for p equals 0.002 and0.015 respectively. Maximum yield loss lies between 102 and 53X, fornoil loss of 50 t/ha/yr.

Crop Budgets

27. To value yield losses arising from soil erosion, we use cropbudgets provided by the PI:nning Division of the Ministry of Agriculture(MOA). We assume that farmers will reduce the use of variable inputs inthe same proportion as gross revenues decline. Applying the estimatedpercentage yield loss directly to gross crop margins, we obtain anestimate of economic losses arising from erosion. Gross muArgins aredefined as gross revenue per hectare (mean yield multililied by officialADMARC prices), less the total cost per hectare of using all recommendedinputs (seed, fertilizer, and pesticides), but not including labourinputs. In other words, intermediate inputs are excluded, leaving valueadded. Labour is assumed here to be a fixed cost of production. An41ternative financial analysis from the farmer's point of view appliesestimated percentage yield losses to net farm income, on the assumptionthat labour is not fixed.

28. Gross margins for twelve crops or crop mixtures are taken fromcurrent MOA data tables, using values for 1989/90. Where values are notavailable for specific crops, we use figures taken from the Agro-economic Survey (AES) Report No. 55 (1987). AES gross margins are

Annex 1Pame 8 of 21

inflated from 1984/85 to 1989/90, using the growth rate of gross marginsfor the same or similar crops, as reported in the MOA data tables. AESdata also includes net farm income, which re simLlarly inflate to

1989/90. Both gross margins and net income as used here are reported inAppendix 3.

Cropping Pattern

29. Estimates of the total surface area cultivated each year varywidely among different sources. The baseline figures used &re from the1987/88 3rd Crop Estimate, prepared by the Pl_nning Division (MOA).These give the total cultivated surface area, by crop and byAgricultural Development Division (ADD). According to this source, thetotal cultivated area of Malawi in the 1987/88 crop year was 18,218 km2.

30. Our calculations also account for the relative importance ofdifferent crops in each ADD. Data on cropping patterns are taken fromthe Annual Survey of Agriculture (ASA) for 1980/81 to 1985/86, asreported by the World Bank (NRDP, 1989), combined with data from the1987/88 ASA and the AES Report No. 55. Note that unfertilized 'local'(indigenous) maize accounts for about 37? of the total cultivatedsurface area of Malawi, while all maize varieties taken together accountfor 69Z of the cultivated surface. Major cash crops, including cotton,tobacco, coffee and tea only account for about 5 of total cultivatedarea. Detail for each of sixteen crops, by ADD, is presented inAppendix 3.

31. By combining information on gross margins and cropping patternswe estimate the mean contribution of each crop to average gross marginsper hectare on cultivated land. Rice is excluded from the analysis, onthe assumption that it is grown on relatively flat lowland soils, whichare not subject to serious soil erosion. We also exclude root crops,despite their importance in cropping systems, for lack of budgetarydata.

32. Summing the contributions of each crop in each ADD, wecalculate composite gross margins fer all crops taken together, inKwacha per hectare. For Malawi as a whole, composite gross margins areestimated at 249 K/ha in 1989/90 (weighted by the baseline estimate ofcultivated surface in each ADD). 3/ Again maize accounts for about702 of this figure. The highest value is in Lilongwe ADD (302 K/ha),while the lowest is in Karonga ADD (161 K/ha). Detailed results by cropand by ADD are presented in Appendix 4.

yI Multiplying composite gss margins by the baseline cultiaed sufac aea, we obtain a value of 453 millionKwacha, whih may be considered a rough estimate of dt contuton of dth crops to total 1988 agrkulturalGDP (1.224 bilion IQ.

Annex 1Page 9 of 21

Economic Losses: Baseline Results

33. Finally we apply estimated percentage yield losses, for variousvalues of p, to composite gross margins. The resul_ is an estimate ofaverage annual losses due to erosion, in Kwacha per hectare. For Malawias a whole, estimated annual losses are in the range of 10 - 64 K/ha(for P - 0.002 and 0.015, respectively), or between 4? and 262 ofcomposite gross margins, excluding rice and root crops. The greatesteconomic losses occur in Lilongwe ADD (13 - 81 K/ha, for p - 0.0C2 and0.015), due to the relatively high gross margins obtained there.

34. Multiplving mean annual losses per hectare by baselineestimates of cultivated area, we calculate total losses by ADD, forvarious values of p. Summing across ADD's, we arrive at rough estimateof the annual loss of agricu..tural income arising from soil erosion.For 0 - 0.002 and p - 0.015, we obtain roughly 18 and 116 millionKwacha, respectively. To put these numbers in perspective, theycorrespond to 0.52 and 3.12 of Malawi's gross domestic product (GDP) in1988. This is the range within which we would expect the true value ofcurrent foregone agricultural income to fall. Results by ADD arepresented in Appendix 4.

Further ManiDulations

.1- Hiaher Estimates of-Cropped Area. Some assessments of totalcultivated area by ADD are considerably higher than the baseline 3rdcrop estimates obtained from the Ministry of Agriculture. Land use datafrom Mzuzu, Kasungu, Lilongwe, Blantyre and Ngabu ADD's suggestcultivated surface areas up to twice those reported in baselineestimates. Using these higher values where available, we obtain a totalcultivated surface area of at least 25,556 km'. Aggregate income lossesare correspondingly higher, ranging between 0.7Z and 4.52 of 1988 GDP.Detailed results by ADD and for different values of p are contained inAppendix 5.

36. Financial Anal2sis. Farmers will tend to define erosion lossesmore narrowly, in terms of reduced net revenues (i.e. farm income net ofall inputs including labour). Data on net revenues for various crops isprovided by AES Report No. 55 (1987). We assume that farmers willadjust labour and other inputs in the same degree as yields decline, andthus apply percentage yield losses directly to composite nst revenues,which are calculated in the same manner as composite gross margins. Theresulting estimates of annual financial losses range from 5 to 33 K/ha,for Malawi as a whole, or between 42 and 262 of composite net farmincome. Detailed results are presented in Appendix 5.

37. Recurrent losses. Soil eroston in one year has an effect onyields in future years as well, as soil fertility declines absolutely.For simplification we may assume that the nominal loss in the baselineyear is repeated in subsequent years. The present value of current and

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discounted future losses arising from one year of average soil loss isthus calculated as the sum of a geometric series, which simplifies as:

n+l-a 1 a ) (5)

where: L- =NPV current and future lossesL,= current one-year lossa l/l+rn time horizon (years)r D discount rate

38. The choice of a rate of time preference for discounting futureincome losses is not obvious. From a public policy perspective, a lowrate seems appropriate, since society can spread risk more effectivelythan private individuals. To suggest the social rate of timepreference, we adopt a low discount rate of 52 per year. We assume aten year planning horizon, although the scarcity of arable land inMalawi and the increasing rarity of fallowing could easily justify alonger period.

39. When we add the impact of current erosion on future yields, therange of estimated field level and aggregate losses for Malawi as awhole rise dramatically. With a 52 discount rate and a ten yearplanning horizon, estimated losses increase more than eight-foldl Usingcomposite gross margins, we thus obtain field level losses between 88and 556 KRha for every year of soil loss, or between 352 and 2242 ofcomposite (annual) gross margins (p - 0.002 to 0.015). Estimatedaggregate losses based on these figures are equivalent to 42 to 272 of1988 GDP. Detailed results of capitalizing estimated gross margin andnet revenue losses are presented in Appendix 4.

40. Private rates of time preference will generally be somewhathigher than our estimate for society as a whole. Evidence from studiesof the informal credit sector in Malawi suggest private rates ofinterest as high as 50 to 1002 per year. While interest rates are notnecessarily an accurate reflection of time preference, we can see fromequation (5) that as the discount rate (r) becomes large, L, will tendto approach L,. In other words, smallholder farmers will tend to ignoreall but current yield losses arising from soil erosion.

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Annex IPaas 11 of 21

APEDZ I LAND tt DATA

Table 1.1 KAROOA ND tUS AA CANED

TOTAL NAT PARtB COMBINE LWREBER TOTAL TOTAL SETTLE DASOS STEEP SaA,S ARDp/OI87RICT & SOWEESURFAACE & G,R. a.R. /F.R. "LPACE ARA8LE CUL-T: A INK1RS L SWAM4PS SPEB SLOPES

KARU9 ROP/DISTRICT:OUR ESTIMATE 8.870 880 1,119 2.20 960 0 1,800 1,30aMOA/BA3.INE 1.168 184N.P.D.P. 8.868 880 409 2,680 1,070 208 28 2,0O1

CI4MTPA RDP/OIMIICTzMA ESTIMATE 4,219 621 760 8.460 921 68 2.484 2,809MCA/BASNELt .,88o 124N.P.D.P. 4,290 760 1,005 8.268 1,124 16o 27 2,841

. ~~~TOTAL KADD-A 8OUR ESTIMDTE 7.898 1,171 1,8679 8720 1,881 6 8,788 8,88MGA/SA8*NIE 2,2 an 0aN.P.D.P. 7,e4J 1,1210 1,494 B,lISl 2,197 88 487STos a JgFER 7,681 .8578 478 84 1o0 491 6s

MOA Srd Crep 87/88 668

Table 1.2 MDWJ LAD use DATA

TOTAL NAT PARKS C01NED Lt9UV6 TOTAL TOTAL SErTLE DAos STEP SWAMPS ARDP/DSTRIC A SWES SURPACE A O.R. O.R./P.R. S04PAC* ARASLE CULT. A IN14AS L 8SWA8 SLOPES SLOW

STH MZIMBA 00P:OM ESTMTE 8,4185 0 64 2,861 1 ,41 130 490 620MtA/BASELSNE 8.811 848 2,968 2,092 8sa 106 775 8e8N.P.D.P. IMZIIA 8 a60 2,144 7s6HAOO/CATCHENT 3,811 0 811 2,970 190 2284 1i 497 80

CENITRAL MZIA FOP:tR ESrMATE 8,92 0 11a 8,612 ,162 180 800 480

MCA/BASELNE 8 926 118 s8eos 8,298 842 282 288 808N.P.D.P./MZIMBA S 846 2 907 1 994

"DOO/cATHMENT 8,926 0 118 8,606 8,198 8,488 16 28 278 810

MM ESTDIATE 8.479 486 804 2,48 2,848 0 640 640M.P.D.P.flqZIPe 8,2241,7

e4fl10 DISTRlcrT0* ESTIMATE 10, F0 484 1,888 9069 7,449 g0o 1,80 1,610N.P.0.P. 10,480 404 642 988 6 724 1,078 102 4,111sT O 0A J 10e,029 9.6e8 1,688 9S4 871

RJ884I DISTICr:OUR ESTIMATE 4,498 2,:28 2,928 2,.128 86 1O0 1.7U5 1,68N.P.D.P. 4.787 2,a8 1a,s 1 .210 760 471 28 1,480sT708s A JE 4,47' 4,249 107 28 1 'a 218

o0* EsTAE 7 978 2.70a 2 8a" 8, 11 2.718 100 2.SO 2,408MOA/ELINE 7,81 82024 4.268 649 211 170 a 8,989KZAW/CATQENT 7,812 2,812 21891 4.901 2,218 8.281 1N 469 1,878 A,844

NMATA SVY P/DIST.:wa ESTIMATE 4,18 0 1,188 8, a060 1.080 0 912 0 2 081M" 8L11 4,427 1.064 5,848 1.224 118 129 1,991 2,120

$m/C"TCHmmof #442 0 1,198 8.301 8 41 1.689 44 18 .8 I,msN.P.O.P. 4,088 0 1,804 2,784 480 S88 27 1.698STOOlS A J 4.879 4,27 180 as 64 68 147

TOTAL MZW Z80:an EfTMTE 19 418 21709 5.061 14 .81 86 no0 8,2 8,

16,976 4,574 14,402 7,485 1,10 68 0789 7,444MUDD/2C^MT-ENT e19.478 2 ,12 4,888 14,941 6',S0 10.660 220 988 4,a11 8,08'N.P.D.P. 10,185 21,49 4.807 14,888 7 2,t 182 7,448STOS a JEFS 1868s 16,187 1,98 o 1 806 9a8MCA 8sd Cee 87/68 1,417

- 12 -

Anmex 1Page 12 of 21

Table 1.9 KASNOU WLAN USE DATA

TOTAL MAT PARKS COWItNED UWESS TOTAL TOTAL SErTLE DAM46O STEEP SWAMPS AROP/DISTRICT A SOUKES SURFACE A O.R. C.R./P.R. URFACE ARA" CULT. A INiR>A A SWAMPS SLOPES SLOPES

44CH114.1 6DP/0ISTRIC'T:MA* ESTIMATE 3.161 0 230 2,928 2,064 627 32 889MOA/BAU LINE 3.34B 0 214 3,132 2.225 1.187 388 166 740N.P.D.P. 3.388 0 192 3,164 2.066 1.361 42 956KALOOAND USE 82 3 ,03 2.007 130 Sf 312STOOS A JEFFERS 3.217 8,090 790 63 363 25 368

OUR ESTIMATE 1 696 0 80 1.663 168 10 0 10MOA/6ASELINE 1,747 0 23 1.724 1.341 699 130 ISO 239KADo/LAW USE 82 1,490 1.014 67 200

IiOA EAST 80DP:OkR ESTIMTE 1,240 0 58 1163 470 0 713 715

: DMA/BASELI4N 1.366 0 46 1.31 M20 498 302 128 480KADD/LAND USE 62 1,428 990 8 37

DOWA DISTRICT:0M ESTDUATE 2 720 0 s 2.65 1,910 10 71 723M.P.D.P. 2.a9 0 4S 2,948 2,226 1.217 64 e31

;~~~~~ -- --- - ----------- ----- ----- - --------- - - -- -- -- -- -- -- -- -- -- -- -- -- -- - - -

NTCHSSS DISTRICT:OUR ESTIMATE 1.965 a 210 1,783 1,240 0 51S 615N.P.D.P. 1.656 0 97 1,U06 n2S 478 1 767STO8 A JEF£ER5l,JINCLUC DOVA) 4.6e9 4 ,8 1,069 24 230 1o 29004*EST. (CWA/NTI) 4,68e 0 298 4,690 3, L6 10 1.230 1,240

NTChISI RDP:OLR ESTDIATE 1,7J0 0 210 1,540 1,026 0 USI 615MCOA 6ASEINE 1,69m 0 152 1,844 980 so 34 445 479KAD/LAWN US6 2 1SNS V 673 42 17~~~~~~~~~- - -- - -- - _- -- - _- - - -- - - -- -- -- -- - -- - -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- - -- - - - -

KA*SJ DP/DSSTRSCT01* EsTIMATE 7 916 2.642 2,468 6.486 4 ,89 1.062 45 1. 27M4A/BASE.IE :5,04 ' 72 4,1I0 1,488 6SS 162 99'N,P.o.P. 7,676 2,816 2.316 5.862 4, 14 2,679 49 909KADo/LAN WE 62 7 ,61 4.658 1,624 9o 480sTr 6 S JE 7,528 7,444 700 s 9 421 16 487

TOTAL, KASUN0 AOD:OLR ETIMATE 15 764 2,842 2.9 12u,77s " 9,6 a 1919 1,07 8.226MA/6iEL46 1"858 7o? 7,n719 a,8 4.SU1 10486 1,071 2.987N.P.O.P. 1i8." 2.816 2.646 1832I9 9,40 8,782 163 8.468KADO/LAW WE 82 18 182 6,6 8.818 a82 1*046STOSUS A JE S 18,404 L8.099 2 ,m 181 1.064 81 1.118MCA 8rd Crw 67/68 2,615

Table 1.4 LILONGE LAW uE DATA

TOTAL MAT PARS CON910 UEW TTVAL TOTAL SETTLE DMO0 Si SWMS ARP/DISTRICT A S8WCES SIWFACE A G.R. G.R./P.R. SURMPACE ARABLE CULT.. A I4FA A SWMPS SLQPE SLOPES

NTOQU RDP:OUR ESTIMATE 2,221 0 1U 2,0S8 1.48s 0 616 61SumA/D,su_Io 2,861 0 in 2,449 710 6" 7 1,691 1,476HOA/aASELDS2.480 784

OIA ESTIMATE 8,22 0 214 8,0oe 2,846 10 eis es6

N.P.D.P. J,424 0 in 8,206 2 464 6e9 62 60sSTOBlS A JEFERS 8,474 2.762 1,066 aS iS 517 S82

THIWILIPZ 60P:0UR ESTIMATE 1, 83 0 281 1,104 669 200 85 238LAWD/DSCUSGS5ON 11023 a 0 1.02 722 716 279 16 297UD0m/I0 992 aa2

OEDLA 6DPt0AD ESTIMATE 1o,68 0 61s 1,263 86 0s 682 7694!soll ^~~,6 0 616 1,:51 685 67o 74 682 786

MaA/SASELIM1,670 380

DSt' DISTRICT:OUR ESTIMATE 8,862 0 981 911 1 978 200 738 9e8N.P.0.P. 8.624 0 800 6,84 1,688 980661,08T0B6 A O a 8,a24 S,276 1,869 114 1e6 40 1.066

ULONIE RW1M ESTIMATE 4.822 0 724 4.09a 8,U2 216 0 216

LA3O/DISCUSSION 4.681 0 842 4,889 6,146 2.420 89 17 570MOA/9ASELINE 4,680 2,165

ULONWE N.E. --P-O1 ESTIMATE 1,460 0 180 1610 1.110 0 200 200

IAD}D,ISCAlSION s1.1 0 107 1,474 688 781 180 579 729MQ^eI8 l___ _ _____s

UI.SNIE DISRICT:04R ESTMATE 2s2 674 8,40 4,902 216 200 416N.P.D.P. e 61 00 1,161 4.998 4,66 2,108 178 1,236STrE a JSEFRRS am 5.544 3,228 260 w0e Sao "48

TOTAL LILONXE AD1:UR ETIMATE 11,768 0 1,U4 GU .651 7,666 416 1,861 1,967A0DIC NISCUSION 11,716 0 1,197 10,1 8,901 5,488 1,148 2.617 8,630

NSA 8rd C-er 67/66: 11.818 4.145

_ 13 -

Annex 1Page 13 of 21

Tablo 1.5 SALI1A LAND USE DATA

TOTAL NAT PAU COIID UNREmvW TOTAL TOTAL SETTLE OAmS STEEP SWAMPS SItPD16ThICT a not WULAE A G.R. 0.A./F.R. MWAW ARAME OAT. & ZM A SWAIS SLOPE SLOPE

OWANJE MP:OU tTII4ATE 2. 607 0 401 2.205 2,148 10 s0 60MOA/eASELVe 2,274 10 10 .264 2.028 an 107 as 77 132

__________________________.____._____.._.._.__...._.__....__....___________________________________________________________

SALM ItDSTRXCT:OLRt EST YE 2 .2I 0 102 2.027 1,87 0 140 140MOA/BASEJXNE 2.141 100 100 2,041 634 aS 146 87a 688 1,260N.P.O.P . 2.289 0 340 1 ,69 1.689 83 40 206

M0OITA-KOTA^ RKP/0I8?0tU~IMATMU : 4 842 1.768 2,068 2.244 1.760 0 464 464

MOA/8ABSEJ?E 4.404 3.27 2.27 2,132 603 so 278 318 941 1.284N.P.D.P, 4,259 1. 22 0 1.602 1.62 842 30 1.6308TOM15 JEFFERS

(INCLNO8D SAUM) .72 6,20 65o 67 104 82 248

TOTAL SALDN AOD-OMP ETIKATE O 076 1.768 2.601 6,475 8,.12 10 68 6640A/BA3ELS ::f19 2U.8a2 2.,#2 6.437 8.262 776 s5 948 1.70S 26"8

NOA Srd Crc. 67/68 1.048

1.6 LU NE LAND USE IATAI CO"INED

TOTAL NAT P4*6 C0PM tUtVWED TOTAL OTAL SErQLE DODS STEEP SAIPS RWAIoMICT a Sol W ACs * O.R. O.R./F.R. SLMWASS UWII,E O.LT. & Z?A A SWAIS SLOPES SDOPE

Z2OA OISTRICT:O*R ISTATE 2.415 0 248 2,190 1. 6 270 240 810N.P.D.P. 2.860 0 146 2.484 1.975 so0 6e 4n7STa Aa JEFFERS 2.176 1.8l1 928 79 20? 2S4 44I

ZOIA

SALAA -DP:OUR ESTD4ATE .14 0 085 1.940 1,606 Su 100 638

*s 0rbAw s o oso117 1 2 W7 e Yo r g

MOA/SASEL 2 7 $91 63e 578 1.109N.P.O.P./HAC.INA 2062 2.062 891

KAWINDA RDPaMlP ESTIMATE S USI 490 865 Sl868 1.706 788 100 686mOA/aAsULDE 2:974 BMW 22.449 6'42 182 1,268 842 1,607N.P.D.P.//ACMO42A 8.082 1.681 881

NAO4INOA DISIR1CT:OUR ESTDATE I S , 15 SW0 O6 4929 8.888 1.810 280 1.540N.P.C.P./MCIN .A4 W US I Ut 4.085 1.102 101 989 s98 1.882STOOss a JBB 6.14e 5.491 1.67 el 998 47e 1,474

MANOOO4I ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~~~~~~~~~-------LR EsTD4ATE 8.808 so 1.106 2.106 1.8e 588, 421 7T7

NrW4ERA RDP:OUR ETDIATE 2.000 0 m8 1,26 4 270 270

NMOa?5~A8~AN0OO4I 8.11 6 .7 am 2.9 888 691 I.04MOA/A_SEL1n6 a 260 1 8.8N 148 6 48 WI 1 604

MANO004I DtSTRICT:OUR ETSIATE 6.804 in a 418 *80 8,04 86 706 1,091N.P.D.P. 272 m 4 1 4n 8 726 1 in 78 1. 2aSTOIS JEFFERS *.87 8.360 1,701 91 206 "8 1.191

ORJR ESTIMTE 1 .760 J 2 10 516 7.891 1.96 1.11t 8.126MOA/WA86..DE 18.619 .4 11. 14 a 911 2.0162 2.8 8,26SOA 3rd Crp 67/8 ',0S?

- 14 -Annex 1

Page 14 of 21

Table 1.7 DIANrYRE LAND OATA

TOTAL NAT PARKS COISNED LOESVS TOTAL TOTAL SErrTE DAM 5T 8 P SAMI R/OSTl7Cr a SoWCs SWURACE £ O.R. C.R./P.R. SIPACE AAL CLT. A INFRAS A SWAMS SLOPES SLOPS

DU EST~IMATE T 2.281 48 167 24114 1,818 0 799 799

8AO/0ASIC FACTS 2.295 140 976 297 20 1,1£4 1,154L.R.E.P. 2,29s 82 2,18? 826 26 12

OA/eASELDIE 2,no 140 1,410 182 20 720 740N.P.D.P. 2.295 248 327 1,621 170 28 670

LUNTYRE DISTRICT:OUR ESTIVATE 2.07 1o 452 1.s2 1,245 a 380 380L.R.E.P. 2,012 84 1,800 768 140 6

N.P.D.P. 2.012 0 64 1.s88 341 141 500ST01B5 Jtwwt5(INCLJOES ANZA) 4,327 8.161 1.1N8 129 25 915 940

CHSRADU. OlSTRSCT:OUR ESrSiTE 760 0 is 748 660 0 68 asN.P.D.P. 767 0 11 71S 889 38 100

_________.____________..________________ ________________________________________ ________________________________________THiOL DISTRICT:

OM E5TIMET 1 701 0 18S 1,88 815 0 951 981N.P.D.P. 1t718 0 89 919 68 8 710

CHRDWZLU ThYLOOIR SETIATE 2,481 0 IS0 2,811 1.275 0 .08e 1.3

,L,R.E.P. 2.482 70 2,824 1,8U8 E8 0N.P.D.P. 2.482 0 70 1 681 1.024 aS 818

ST08BS A JiE S 2.214 1:93O 1,829 112 2 112 114-o Z_^ - --- -__- ------------- - ---------- - ------- --------- -----------------------------------------

SHIRe HI@4ANS tP:OWR STMATE 4,88s 10 592 8,988 2.80 0 1 416 1 418BLADD/BAsIC FACTS 4.509 78 1.S85 1.808 24 2.871 2,896L.R.E.P. 4,494 184 4 1S2 2.658 228 8MCA/BAEINE. 4.498 75 8,347 1,447 284 24 308 827N4.P.D.P. 4.494 0 184 2,998 1S868 229 1S,18

OUR ESTET 1,36S8s 0 110 1,276 1.061 i0 S1 21BLADD/IASIC FACTS 1.279 48 818 5l8 172 819 691L.R.S.P. 1.279 9 1,1 sa6 24 89

iANJU ROP:OUR ESTtMAT 2.109 0 874 1.831 1.470 0 8 68OLAD0/ASIC FAC8 1,840 8w 841 971 4 88 8S8L.R.E.P. 2.171 482 1,684 1,142 as 0

;amJ---Dzmcr:------------------- -------- -----------------------.- ------i4LAWJE DISTRICT:

MM 3STDIAT7 8,494 0 884 2,810 2,880 200 80 2801LAOO/BAISC FACTS 2,019 6 687 1 487 176 1,074 1,249

L.R.R.P. 8,-480 87 1.007 79 89MOA/BAS'L 8,480 6a 2,837 1.088 280 176 408N.P.D.P. 8,480 0 2,00 878 79 6788T88 & JWFR 8.87? 2,599 1a,84 137 8S8 608 761

…-------------------------------------- ----- ~-- - …-------- -

MMR ESTATTe 10,818 6s 1,888 8.860 a,6 200 2 298 2 498BLADD/UASIC FACTS 9.17 68 886s' 8,89 220 4.879 4,79L.R.g.P. 10,289 ,9 780" 86SS aloes8 106MOA/11ASELINE 10.288 a80 7,09 2.015 284 274 1.699 1,978N.r.D.e. 10,2S9 248 1,88 7'117 2,411 884 2.668s80r A Jee 9,918 7 S8 3.'29 878 16O 1.688 1,81MA Jrd Crop 07/88 0,187

TbIla 1.6 NMWU LAW UNE DATAC8M8DG

TOTAL NAT PARNX CSED UREWNED TOTAL TOTAL SErTLE OAs STEEP SHAWS A8DP/OISTRICT A SOWC SLAPACE A G.R. G.R./F.R. SuRFACE ARA8E CULT. A I3PAS A SWAMPS SLOPS SLOPES

NSM4JE RD/DI5TRICT:OR 86TDMTI 1,88 8868 149 1,4I 010 06 8m0 68

NADo 1,9381 994 478faVatsTmDoo 1,981 1,02 900 80O 41 208HOA/BASELIW 1,W91 479 794 e8g 9W 268N.P.D.P. 1.942 348 262 1,8a2 884 388 SS 7205708I A JF5S 2,047 _1,84 822 8 882 an8 727

…------------- ---- - ---...- ------- … --- --- - … -------

O4tWAVA 0P/OIMTRICT:W ESTIVATE 4.702 I.788 148 2.,79 1 U67 698 261 1,1S0

MOAMADD ~~4.8622in1,L'OV 04t'TOCKVCO 4 an 3 0e2 2lm 1.199 e11 4S1MCA/BASELINE 4.720 972 1.458 2,29a 2 286 7118N.P.D.P. 4,788 1,426 0 3,829 2,8se 699 49 mSTO888 & JEFS , 8211 ',617 89o as 881 1,217 1.86"

------------------------------------ ---- ---- --------

NW IIDD:OU 1WSl7TE 689 2.120 292 4.278 2,447 1.00 811 1.6114AWNAD ,78s 8, n126 2.00O'OVERSTAXsINOO 11758 4 .04 1,702 159 717NOA/BASEIE 8 681 1,480 2 249 2,981 8,241 998N.P.D.P. 6,89s7 1,774 282 4.681 8.208 1,287 62 1608S7T093 A JE7.288 S8581 1.181 l1 6ea 1,812 2,298

L.R.E.P. 8,640 1,900 880 4,610 8.940 1,988 640MCA 3rd OtO 67/86 1.018

- 15 -

Pane 13 of 21

N,P.0.P.: NO.nnal Phasinal fla,alann.nt, Plan, 1988. Vol, U, Tobles 8.2. 8.1b.

SaI J£ lS $tobbb. A.R. A J.N.R. Jeffers (ad. S. Andewrn). 1983 Land Uln S5-87, Anno.o 1: Land Use Close, by*adial*etresi. dlstlrcts.

S AS Cro.11w1. S/111 Plenning Division, Mlnletrt' of AgPloulture, Sed Crop eatlmt. 1987/88 (data tables).

N.P.D,P./luul .Dlt s fL2 Inn P 198 Tebles 1 and 92

9OjCAT§etI Kenrsys, W..J. P.M. sny . 1M. JK ew B ___, Tebloo 2 and 8.

UWD/U@WIUl Land UNa11 Claa allfll sn KcunuS AM, 9M. Tables 9-18.

LAWDP/S9lA 1 ria.,ltural and lonamb.r. lm.s. In Lillo Aorel0.aIatu Ci ,laon, 190 Teblo 1.

N,P.D.P./14A : MohIn. Olate P bl r Plan, 1911. Tbl 9 2nd 8.

IO/WSC PACTIl hale ft.a*nd fIara S, xea7. Table 1.

L.IL..P. , --- I .,f rer1l,n o a'&t..f A flrt a..liwalOe2a l_Opt klnaIDn, 1989. Tables 4 and 11 darleulersl D7s10{1 r - 1c, 1. Tabl.a 9.1 and o.9

MOA/WUz fRaw dIba e.'wlded by Lte' Nka£eradw.u Unit. Nabu AsrlOultural De,alo.seon Olvlolon, 8/80.

S'iinVG§CINS'I fl.anat..bln. _ _d Land Oaa.adat.lm I, Noah.. A~, U10. Tablo t.

APENIX 2. SOIL AM _YIEL LOjS DA

Table 2.1 OIL AND YIELD LOSS ON CROSS ARABLE LAND, BY DISTRICT

TOTAL GROSS EST. AVG. WEIHE AVERAGE YIELaD LOSS (SS)SURFACE ARABLE $OIL LOSS

DISTICT (ka2) thin) (tWha/yr) 03.002 .004 .e= .010 .016

CHITIPA 4,219 921 24 4.63 0.61 18.13 20.6 20.8WKAROG 8,879 90 88 6.43 12.43 18.0W 28.13 88.8WNKHATA SAY 4,298 1,680 48 8.11 16.6W 22.43 84.43 40.7%RUWPHI 4,486 868 I6 8.2% 6.23 9.1% 14.6S 21.061UZIUSA 10,622 7,440 19 8.9S 7.41 16.8W 17.23 24.43

NORTHRN REGION 27,011 10,727 28 4.53 8.73 12.73 20.63 28.13

KASUNGU 7,018 4,889 16 8.13 6.13 9.63 14.83 20.53MO4OTA-KOTA 4,842 1,747 17 8.8W 6.63 9.-5 15.8W 21.03NTCHISI 1,90 1,240 27 6.23 16.2W 14.83 28.8X 82.63DOWA 2,72e 1,016 26 5.43 16.53 15.83 24.06 88.43SALA 2,126 1,887 11 2.23 4.45 6.5311 16.5 15.3sLILONE 6,262 4,02 10 3.6 6.05 10.1s 16.23 28.13MCHINJI 8,161 2,664 17 8.83 6.53 9.53 15.83 21.6SDEDZA 8,362 1,978 22 4.25 8.2X 12.631 19.63 26.8XNTOHEU 8,221 2,843 20 6.6X 10.7S 15.06 24.3 U8 87

CDNTRAL REGION 85,508 22,4n0 2 8.83 7.53 10.0 17.8S 24.63

MA0CNt e6,5e4 8,044 16 8.6X 6.90 3.73 18.03 29.03ACNINU 6",86 8,888 1s 1.03 8.73 S.53 9.63 18.13

ZOMBA 2,485 1,080 17 8.83X 6.5 9.53 1S.13 21.53CHIRA02UWU?7 G60 80 7.65 14.43 26.73 81.90 48.43B lA 8,e 2.677 1,246 82 6.1X 11.08 17.13 26.6X W8.43WANZA 2,2S1 1,815 20 8.03 7.63 11.23 17.73 24.90THYOLO 1,761 615 . 84 6.63 12.?3 16.4% 28.603 80.5W(ULANJE 8,494 2,586 20 6.53 16.6S 15.8 28.03 88.O6CH AWA 4,M72 1,68 13 8.53 6.03 16.0 16.63 22.73j NSAJE 1,868 81e 14 2.73 5.23 7.73 12.43 17.73

SOUTERN REGION 81,70 16,919 29 8.e8 7.43 16.08 17.13 24.13

MALAWI 94,407 59,146 20 4.63 7.73 11.8S 17.83 25.23

-16 -Anmex 1

Page 16 of 21

Table 2.2 SOIL AND YIELD LOSS ON GROSS ARABLE LAND, BY ADD

AGRICULTURAL TOTAL GROSS CULTIVATED AREA EST. AVG. WEIGHTED AVERAGE YIELD LOSS (X)DEVELOPMENT SURFACE ARABLE BSae High SOIL LOSSDIVISION (km2) (km2) (km2) (km2) (t/ha/yr) 1!.002 .004 .-0 .010 .016

KARONGA 7,698 1,981 668 N.A. 29 6.65 10.7X 15.6X 24.4X 84.01mzUZU 19,418 8,946 1,417 2,512 22 4.8a 8.41 12.23 19.83 27.1XKASUNGU 16,764 9,668 2,016 5,782 20 8.01 7.6X 11.1X 17.6X 24.9XLILONGWE 11,786 7,884 6,216 5,456 22 4.21 8.8X 12.13 19.13 26.91SALIMiA 9,076 6,779 1,046 N.A. 16 8.1X 6.61 8.8X 14.13 20.23LIWDNDE 18,769 7,891 8,067 N.A. 18 2.6X 6.01 7.43 11.9% 17.1XLAJNTYRE 16,818 6,805 8,197 5,086 29 6.6X 10.89 16.73 24.43 88.7X

NGABU 6,689 2,447 1,010 2,006 17 8.2% 6.83 9.83 14.81 21.03---------------------------------------------------------------------

MALAWI 94,407 60,146 18,218 25,556 20 4.6! 7.7X 11.83X 17.93 26.2X

Notes: 1. ADD, regional and national *oil and yield loss weighted by gross arable area.2. Baseline astimato of cultivatod area is MOA 1987/88 3rd crop estimate. Higher

estimates are: NADD and 8LADD from LREP, LADD from Environment Discussion Paper,KADD and UZADD from NPOP.

Table 2.8 KARONGA ADD: SOIL AND YIELD LOSS ON GROSS ARABIE LAND

TOTAL GROSS EST. AVG. WEIGTED AVERAGE YIELD LOSS (3)RURAL DEVELOPMENT SURFACE ARABIA SOIL LOSSPROJECT (RDP) (km2) (km2) (t/he/yr) L%.002 .004 .006 .010 .015

KARONGA ROP 8,879 960 as 6.43 12.4! 18.93 26.13 86.9xCHITIPA ROP 4,219 021 24 4.65 9.03 18.1X 20.63 28.93

KARONGA ADD 7,698 1,881 29 5.15 10.73 16.6X 24.4% 84.01

Table 2.4 MZUZU ADD: SOIL AND YIELD LOSS ON GROSS ARABLE LAND

TOTAL GROSS EST. AVO. WEI2HTED AVERAGE YIELD LOSS (X)RURAL DEVELOPMENT SURFACE ARABLE SOIL LOSSPROJECT (ROP) (kh2) (km2) (t/ha/yr) 0.002 .064 .000 .610 .01O

SOUTH MIZIMBA ROP 8,415 1,941 24 4.73 9.13 18.23 20.93 29.1XCENTRAL MZIMDA RDP 8,727 8,162 16 8.23 6.2% 9.23 14.73 21.01RUIPHI/N. MZIMBA ROP 7,975 2,718 29 8.0X 7.63 11.23 17.83 25.8XtKHATA BAY RDP 4,296 1,089 48 6.1 15.6. 22.43 8.4X 46.73

MZUZU ADD 19,418 8,846 22 4.83 60.4X 12.23 19.83 27.1X

Table 2.5 KASUNU ADD: SOIL AND YIELD LOSS ON GROSS ARABIA LAND

TOTAL GROSS EST. AVG. WEIGHTE AVERAGE YIELD LOSS (X)RURAL DEVELOPMENT SURFACE ARABIE SOIL LOSSPROJECT (RaP) (W2) (km2) (t/ha/ye) _J%-ff2 .664 .66 .010 .015

MCNINJI ROP 8,161 2,664 17 8.83X 6.65 9.65 1i.83% 21.6XDOWA WEST RDP 1,696 1,665 25 6.63 9.63 14.1% 22.2U 81.23DOWA EAST RDP 1,240 476 a6 6.9x 18.3x 19.83 29.93 41.13NTCHISI ROP 1,760 1,025 27 6.23 10.1 14.813 28.2% 82.43KASUNGU RDP 7,918 4,839 16 8.13 6.13 9.0 14.83 20.53

KASUNO ADD 15,76 9,58 2 8.9 7.6 11.13 17. 24.8

- 17 -Annex 1

PaRe 17 of 21

Table 2.6 LILONOWE ADD: SOIL AND YIELD LOSS ON CROSS ARABLE LAND

TOTAL GROSS EST. AVG. WEIGHTED AVERAGE YIELD LOSS (X)RURAL DEVELOPMENT SURFACE ARABLE SOIL LOSSPROJECT (ROP) (km2) (km2) (t/ho/yr) Ab.02 .2a4 .we .010 .016

NTCHEU RDP 2,221 1,438 32 6.2X 11!.9 1?.BX 28.9! 87.1!THIWI-LIFIDZI RDP 1,385 889 20 8.9% 7.?X 11.2X 17.8X 25.sxDEDZA ROP 1,898 685 82 6.1X 11.8% 17.2! 28.89 87.2!LILONGWE ROP 4,822 8,882 16 8.1a 6.0! 8.8X 14.2X 20.4!LILONGWE N.E. RDP 1,460 1,110 27 5.1X 10.6X 14.6X 28.0e 82.8X

LILONGWE ADD 11,786 7,884 22 4.2X 8.8X 12.1X 19.1! 26.9X

Table 2.7 SALIMA ADD: SOIL AND YIELD LOSS ON GROSS ARABLE LAND

TOTAL CROSS EST. AVG. WEIGHTED AVERAGE YIELD LOSS (!)RURAL DEVELOPMENT SURFACE ARABLE SOIL LOSSPROJECT (RDP) (km2) (km2) (t/ha/yr) p.002 .064 .206 .010 .01O

9WANJE RDP 2,607 2,146 18 8.6x 7.8x 10.3% 16.4! 28.2!SALIMA ROP 2,128 1,887 11 2.2X 4.4! 6.6! 16.5! 16.8XNXHOTA-KOTA RDP 4,842 1,747 17 8.8! 6.65 9.65 16.8! 21.9!

SALIMA ADD 9,078 6,779 16 8.1! 6.0x 8.8X 14.1X 20.2X

Table 2.8 LIWONDE ADD: SOIL AND YIELD LOSS ON GROSS ARABLE LAND

TOTAL GROSS EST. AVG. WEIGHTED AVERAGE YIELD LOSS (X)RURAL DEVELOPMENT SURFACE ARABLE SOIL LOSSPROJECT (RDP) (km2) (ki2) (t/ha/yr) pm.002 .004 .O8 .010 .016

ZOMBA ROP 8,165 2,085 15 8.6! 5.81 8.6X 18.7X 19.6X9ALAKA RDP 2,146 1,806 10 l.9X 8.9! 6.6x 9.1! 18.8!KAWINGA RDP 8,128 1,708 16 1.9! 8.8! 6.7! 9.8X 18.6XMANGOCHI ROP 3,808 1,829 18 2.6! 6.1X 7.5X 12.1X 17.5XNAMWERA ROP 2,009 964 18 8.6x 6.9X 10.1X 16.1X 22.9X

LIWONDE ADD 18,769 7,891 18 2.6X 5.01 7.4! 11.9! 17.1X

Table 2.9 BLANTYRE ADD: SOIL AND YIELD LOSS ON GROSS ARAJLE LAND

TOTAL CROSS EST. AVG. WEIGHTED AVERAGE YIELD LOSS (1)RURAL DEVELOPMENT SURFACE ARABLE SOIL LOSSPROJECT (RDP) (km2) (km2) (t/ha/yr) p.002 .004 .006 .610 .016

MWANZA RDP 2,281 1,815 20 3.9X 7.6X 11.2! 17.7X 24.9XSHIRE HIGHLANDS RDP 4,588 2,520 84 6.6S 12.7X 18.4X 28.4X 89.0!PHALOMBE ROP 1,886 1,61 24 4.6! 9.0! 18.1! 26.5! 28.5XMWLANJE RDP 2,109 1,470 82 6.1! 11.6X 17.0 26.8! 86.2!

BLANTYRE ADD 10,818 6,U86 29 5.6!5 16.6 16.7X 24.41 38.7X

Table 2.10 NKOM ADD: SOIL AND YIELD LOSS ON GROSS ARABLE LAND

TOTAL GROSS EST. AVG. WIGHTED AVERAGE YIELD LOSS (C)RURAL DEVELOPMENT SURFACE ARABLE SOIL LOSSPROJECT (RDP) (kW2) (km2) (t/ha/yr) pa.002 .004 .006 .010 .016

NSANJE RDP 1,988 810 14 2.7! 5.2! 7.7X 12.4! 17.7!CHIKWAWA RDP 4,702 1,687 18 8.1S 6.9X 10.0X 16.0% 22.71

NRO ADD 6,689 2,447 17 8.21 6.8! 9.8! 14.eX 21.0S

- 18 -

Annex IPaLe 18 of 21

APPEMIX Si CROP DAT

Table 8.1 PERCEW OP CULTIVATED AReA DOEVO TO EACH COP

tn KARON_ArRLOJ LILONPI SALIMA LO NUJ 141w.

AuLzE CtR) 97.1 16.2 40.8 80.0 40.9 47.0 44.2 28.9 7.LOCAl. MA118 (.PIWfl a.8 92a. 9.6 17.8 10.8 18.4 8.7 ,o 199

W401D 14 MAUI .PS51) 8.1 11.4 0.0 0.4 *.1 .0 . .7 8.eoxTe^st (-F - ) s1.7 9.0 4.8 1.8 *.8 .8 .6 0 1.9

FSt! H 14.0 11.4 4.1 14.2 4.1 1.90 1.e 4.0 1.9.I

TOVAL MXAIZ 48.4 64.8 79.4 78.8 68.o 77.4 68.o 89.9 68.4--.. ------------------ . ...................... .............................. ...................... --- 2..... !2..... !2...........................

RiCG 14.9 .4 .0 .0 8.6 el 2: 1.6 16 1.MILLET 4.7 7.8 .4 1.4 .e .7 .6 17.1 2.480RC4M .2 .0 .0 .0 .2 1.6 a.9 96.8. 3.11O1TS 14.6 9.6 9.0 1.4 192. a 7.4 a8 5.001018N14fl O4LINCBM) .1 8.9 18.:1 6.4 1.0 1.4 . .04.01~.98Mft8 COTi>) 4.0 S.9 1.6 8.7 8.4 8.2 .9. 1.8 6.6PIA.S8S/SEANS 10,6 0.0 8.1 6.2 .4 .6 12.9 1.1 6.1CSorON 2.o .0 .0 .9 19.9 1.9 .9 19.1 2.4TQO8ACO tNC0Pn .0 .1 4.0 4.0 .0 .8 .4 .0 1.9TO8CCO OaTR) .0 .6 9.8 1.4 .0 .0 .0 .0 0cONEA .8 .2 .2 .0 .0 .0 .a .0 .1

....-- -- -------------- -. ------ .................... ............................. _

TOAL 100.0 100.1 100.1 100.0 100.0 100.0 100.1 100.1 100.0

Sourc: ABA 1980/t1 to 1988/80 ovorseed rmo lDP), combinad *lth date *fromSA 1S197/8 end AES Report ft. sr

Note. 1. FertilI Izer wasrfweot 4a Reort N. Mg for coaoelt end hybridvalu. a 1u 1 fortiliaadg for latureee woe "a breekdoan esfor local mazso.

2. oreasdown beteeon Cholimbeno and other ground-nut veriatie f#raeABA 1907/Sit ditto fof- NWP ve. other tobaccoe. eaa.i 100 oftobacco le fortillaod.

8. - losl overase welahted by bc_oline est. Of cultivated area by A20

Table 8.2 C.OP BLOOT (AVMAW ALL AWAS)

AM (.ATE ) l 4 IAFLAT i_ ) 19/NET CROWARDE 019 #4RJ

ROp (/HOA) (K/HA) (K/MA)

L AZZL MZE (- PERT) 104 1t7 202

:uWin MAIZe. 998a 433 4A4COWITeS2 MAZU(.PUrr) 167 e96MAIZE rIf* 842 841 a80;ASCE_iAy0 PAYA. & SIE iOOE) -148 868 489

ROOT CROPS 2as6

B PNI~~1~ 1.98 981 881

COTTON pt48 u 460TO"= (NNW) 98 740 189TOSACCO (OTN") go m8 919

.. ~~~. .. _ ....... _ ... ........... .... .... ... . . ._..... .

Sources Agro-Uconoaic Survey (a4) Report ND. 88 (187 and MCA datatables (1989/90). oh ue standard yield figures and officialAUMAR Pliea; AE3 valuee ore inflesd from 1984/8 to 1989/90,using t.e grath rate ot grose margin. for each Crp, es=rsted tn MCtA dsa tables. Sorghum under M0A io taken frm

iD,tabl U4 (it?/il).

19,Annez I.

Pate 19 of 21

Table 81.61 COW0SIT GROU witIAVIAUOQ CaNTtXSJION OP EACH MP TO MM NAOZI PE lTARE

AAOR OFS KARNA IUW KASIRM LILIWUWE &AMDA LINDE MAHRE NU M ALWA

LOCAL4A1Z (- F 84.0 32.6 o.8a 62.2 62.8 c8.4 89.0 .0 7S0 ILOCAL iE (AFERr) 7.1 64.8 27.8 49.8 22.9 43.0 so.e .0 84.4YtSD NAIS i) 12.8 47.2 41.0 38.0 4.6 8.7 2.5 2.9 22.7

COMIE HAIlS (aF1W) 4.6 7.6 12.1 8.b 19.6 .8 1.6 .0 a8lN4AW NIXfTuL 42.0 84.2 12.8 42.6 12.8 88.7 52.4 12.0 38.4

TOTAL MAIM 121.1 166.1 164.0 197.0 148.7 168.5 168.I 71.7 178.6

RICE N.A. N.A. NA^. N.A. N.A. NA^. N.A. NA^. N.A.14u11r 2.7 4.8 .a .6 .o .4 .4 10.0 1.4SOR@4I .1 .0 .0 .0 .1 .9 1.7 1i.8 1.8ROOT N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A.

aR~.M@eJtS CG&ALIIqSANA) .2 7.0 29.2 16.6 2.2 8.1 .4 .0 10.0)ACMflS COT~6~) 14.0 16.4 8.8 8.S1 10.9 16.2 18.8 4.6 18.8

iJJfl,w4 ,2e.6 8.2 2.0 S.6 .4 2.6 11.7 1.0 6.8CiO?TW U8.8 .0 .0 .e 88.2 0.7 4.1 87.9 11.1TOaACO (tNI .0 1.8 6.4 88.8 .0 4.0 8.8 0 24.7TlOACO (OWO) .0 .4 20.2 12.6 .0 .0 .0 .0 7.0

EA ALL Ot WHA) 1 21 2t8 8o2 Z22 221 2o0 191 24d.7

t 1 0r. margins fre MOA 1989/90, except cmoaeite miai. freefrom AES Report No. SO. e4ehus froe tDP table 14 (87/88).

2. No date for pest crop,; nt I t treated *a aorg)um.*. RICe i- excluded; *eeuaed to Incur no eroo,cn 1eea.4. Miela averv.age eichted by baelin* eativate of cultivated area.

Tale 8.4 COWSM lfEf Ri VOAR

AVCRM CTRIShION OP SUN CROP TO MET -SCE PER HEll!R

OAM" aCRPS KAROA 1qJ K40UN U LIL8NDB SAUFA LDVONSE STE - Aw0N KAUNI

LOCAL MAIM F r) 2t.1 16:6 47.0 82:0 42:4 49e6 48:8 29ae :2e0LOCAL KA= 2.1 18.. 7.9 U 24 687 U 2.7 81 20 10.0

9@.D UA15 { §.2 4.0 ae.i4t 28.0 J.8 2.7 1.0 .1 86.

NAl N 14 47.2 *9.0 14:0 48.6G 14.0 44.1 0?. 7 18.7 43.8

TOTAL NA 90.1 11S.2 198.2 12.0 60.8 100.7 119.4 48.0 109.6

--CE #:.A. N.A. N.A. N.A. N.A. N.A. A NA. NA.14111.1? ~~~~~~~~N.A. N4.A. N.A. N.A. N4.A. N.A. N4.A. N.A. N4.A.SSM 14~~~~~~~~~~.A. N4.A. N.A. N.A. N4.A. N4.A. N.A. N4.A. N.A.

-OOTS 14N.A. N.A. N.A. N.A. N.A. N.A. N.N.A N.A. N.A.CEOIWMITS CCEALDMM) ~~~~.1 4.6 109. 12.2 1.8 2.1 .8 .0 7.1~~S60M.ITSC0TIEA) 8~~~.0 0.6 2.0 4.7 6.6 6.8 4.9 1.0 4.7

)LSU/SENU 1N.A. N.4A. N.A. N.A. N.A. N.A. N.A. N.A. N.A.1.4 .0 .0 I 6.6 .9 .4 9.0 1.2

.0 8 10.8 1. 0 . 1.0 0 4 7v.0 .a .6 .4 .0 .0 .0 .0 .8

MM4 ALL OWS (N )9? in5 IN 186 28 10 lo0 80 1W.8

Nebtee 1. NMt league f rom AMO RePOrt NO. W8.2. is data for res cree Gad mi ll et.

. Ri e1 cluedoa "aeuad to lncur no eroion loee.4. Sorawu lo emelud" due to negtive t income.

. nlaul overee suighted by beasl Ine eatintee of cultivated areo.

- 20 -Anex 1

PaRe 20 of 21

AmelrA 42 FG4C MasT OAM

Tatbl 4.1 CL0iT WMOS3 MAROIN LOSSEE

KAROWA ZUZU KASUNCU LILONOE SALIXA L7EONDE BLANTYRE NaASU MALAWI

COW. ORStS MAROItI (K/MA) 161 231 296 302 227 221 200 191 248.7

MEAN A19.A LOS (K/NA/'m)

Data .002 9 10 12 IS 7 6 11 a 10£bta .004 17 19 22 2s 14 11 22 12 20Data * .006 28 2s 33 36 20 6 S31 18 29

ta sa.o1o 39 48 82 88 32 26 49 20 48ets a*.018 83 3S 74 e1 46 38 68 40 64

T01'AL AMJA LOSS ('080 K)(bee. estimate ofcultivated akrea)

Setas- .002 8So 1,409 S,010 6,688 724 1,727 3,88s 627 10.363Bete .004 1,148 2,739 8,871 15,020 1,421 3,394 6,916 1,227 35,738Bets2 .00* 1,667 3,996 08,92 19,010 2,000 5,002 10,01S 1,800 £2,178set .010 2,611 8,311 13,645 S0,094 3,s34 8,054 15,580 2 871 82 ,20Beta * .018 3.632 8,872 19,30. 42.402 4,80S It,687 21,us8 4 084 116 12

TOTAiL rAL LOSS ('000 K)(hi%h eot;aties ofcultivated *area)

Seta - .002 0 2,497 6,897 6,997 0 0 5,721 1 238 26,092Beta * .004 0 4,888 12,880 13,622 0 0 11,038 2,416 50,760Bets .006 0 7,083 18,832 19,897 0 0 15,980 3,544 74,096et o .010 0 11 186 29,908 81,486 0 0 24,864 , 6s8 117,115

Beta Ol1 0 18,728 42,311 44,363 0 0 34,358 8,044 164,818

Nate: U.. hue. eatia of eultiat d a-e- cho, no high *etiato ie available.

Tab le 4.2 CAPITALIZED GROSS MARGIN I

PLAtNING ORIZON (ya-rs): 10DISCNM RATE: 5.02

KARO0A IZUUL KASUOU LILONONE SALMA LIW2Q OLANrWE Nha MALAWI

EAN CAPrTALIZED LOSS (K/HA)Bets a .002 78 87 100 112 60 49 98 54 8SSeto - .004 151 169 129 218 118 97 189 105 171sets a .006 219 24i 287 918 174 143 274 184 280Bets a .010 348 3- 488 80S 2ao 230 426 248 398Bets * .015 478 t.4. 644 709 401 331 889 380 866

XTOTL CAPITALIZED LOSS ('000 K)(baeeo stimte ofcultivated area)

Sets a .082 6,170 12 266 26,288 88,8162 , 817 18 066 81 264 8,472 160,161Bets a .004 10,000 28,890 1 ,208 116,886 12,890 29,899 60,816 10.700 311,668Bets a .006 14,542 34,S8 74,940 168,669 18,230 43,628 97,882 18,696 458,087Beta a .018 22,770 8i8,042 119,010 262,471 29,254 7 .242 138,888 28,041 719,718Beta a .018 81,676 77,n79 168,7 869,818 41,912 101,089 187,738 358628 1,018,871

!~~~~~~~~~~~16 --------------------------------- _______

Table 4.8 CUREFT NETr REVSAE t.888S

KARU 8iA KRJ KASU1 LILOIE SALA,MA LUWO BLANT NAU PALAVI

CW. NEr REV&"I (K/HA) 97 1I8 138 188 98 120 126 88 V

lEAN M*4AL UISS (K/HA/'tIR)Bet .002 8 a a 6 8 3 7 2 8Betea .004 10 10 10 1s 6 a 14 4 10Bet a .00 15 1s 1i is a 9 20 8 1SBeta a .010 24 24 24 29 13 14 31 8 24Beta a .018 88 84 S4 41 19 21 42 12 33

Table 4.4 CAPITALUED NET REVENE LOSSES

PLNNSO FORIN (years): 10DSSCOUtT RATE: 8.01

KAROHOA MZU KASIM LILONGWE SALINA LIVONE SLANrVUE NAW KM4lI

. EN CAPTrALIE LOSS (KI/I)Betas .002 47 47 4? 67 28 27 62 16 4t

aet .004 91 91 91 110 49 52 119 81 £9Beta - .006 132 186 134 161 7-3 77 172 4£ ISOBeta a .010 206 210 212 258 117 124 268 72 206Beta - .018 287 298 600 389 167 179 870 102 289

- 21 -Annex I

Page 21 of 21

REFERENCES

Anon. 196I. Annual Reeort of tho Dpartment ot Aqrlcuhture for the Year 1962/63 (Part II), Govemment Printer, Zomba

Anon. 1988. Natlonal Phvseia Oevelopment Plan, Vole. 1 and 0, Dept of Tovn san Couney Planning. National Physical Development Plan Project.UNDPNUNCHS (HABITAT) Project No. MLW179/012, Ulongwe.

Anon. 1087. A Production Cost Surve of Smallholder Farmner In Malawi, Agro-economic Survey Report No 55, Ulongwe. April

Anon. 1990. Annual 8ure of Agriculture, Worktables, Natonat and A.D.D. aggregatons (or 1987/88 crop year, MOA, Ulongwe.

Ampheltn, MB. 198. Soil Erosion Research Proleet Bvumbwe, Malawi, Summary Report, Hydraulics Research, WalIlngford, UK

Bishop, J. & J. Alln. 1989. The On-Sits Costs of Soil Erosion In Mall, Envlrnnment Dept, Working Paper No. 21, The Wordd Bank, Washington, D.CNovember.

Brnt MJA, A.J.B. Mithell & R.C. Zlmmnrmnn. 1984. Environmental Effect of Development, Malawi, Phase 11 Repor, Consultant Report,AG:JDP/MLW/81(001, Food and Agriculture OrganIzation of the United NatJons, Rome.

Cthwm, V.LA. 189. A ,a,ofR ExperIence In Six Years, Ref. No. NUV25/18Nol. I176. paper presented at Agrforeetry National Workshop.

Ehle, H.A. 1978. Sol loss estimation: comP led works of the Rhodesian mutdisclilnav team on soil tos estimation, Inst. Agric. Engng., Harare,Zimbabwe.

Elwell, H.A ard MA Stoolng. 1982. Developing a simole yet oractal method of soiloss estimation, In Trop. Agric. (lrlnldad) Vol. 59, No. 1, Janup. 43A4.

Khonpe, C.S. & 8.K MachIe 1S87. Erosion Hazard Maeotna of Malawl, Land Husbandry Braneh, MOA ULlongwe, December.

Lai, R. 1981. SOD erosion orobtems on Alfols In Western NIgeri. Vl. Effect of erosion on experimental slot, In QOoderma, 25, 215.

Lai, FL 1087. Eflet d erosion on cor pirducff&, In QICal Reviews In Pnt Sens, Vol. 5, Ise 4, pp. 0-367.

Madhiut, LW. & P.C. Manyanze (M. St & J. Akwman ode.). 1989. Eroslon Hazard M8oping of ti SADCC Rgion. Part 1: Zimbabwe, Report t18, Coordaton Un SADOC Sol and Water Conservation and Land Utilization Sector, Maseru, LesotIho, March.

Maida. J.HA & Z.W. CNlilma 1981. Chne In Indices o FerWiv under Continuous Crosolna, in Luso: J. Sci. Tech. (Melawr), (1981) 2(1), p..25.

M*edre, E.J. 1988. PrellmInatry Evaluation o Sof Loss Estimaton Model for utern Afrkca (SLEMSA) under Mafawv CondIions, paper presentLaud Husbandry Senior Staff Semnr, Kaaungu, 5-10 Jun 1988.

Stesbf, AR. & J.N.R. Jeffem (ed. 1. Andermon). 1985. Mand Use Survey of Mali, 19667, Land Resours Dom Centre, OveWseasDevelopme Admlnrataon, Swbr8on, Surrey, UK

Stocking, M. 198. The Os of 901 Erosion in Zimbabwe In Terms of Oe Les of Thre M_a Nutien_t, Consulants' Worki paper No. 3, SoilConsration Programne, Land a Water Devepmnt Dlv., AOLS, FAO. Romn.

St , M. 1987. MeasurIna land dearadation. in Bah , P. & Brooleld, H. (eds.), Land degradaton and socity, Mothuen, London: 4943.

Stocking. M.. Chakela, 0. & Elwel, H., 1986. An IMRond Methodoloay for Erosion Haard Madina, PaR ;: The Technkoue, in Geograftska Annale70A (3): p. 169.180.

Twylord, I.T. 1988. Development of Smallholder Ferflier Use in Malaw& , papW for FAO/FIAC mng, Rowm, 26-29 Apr11 1068.

Wischmetu, W.H. & Smith, D.D. 1978. Predictng raifl eroslon bsses a outdo to consoetion oaLngn, U.S.DA Handboolk 53, Washingt, 0

Annex 2Page 1 of 4

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AUTOREGRESSIVE TREND MODEL OF RELATIVE PRODUCER PRICE STABILITY

1. As reviewed in Ch.'pter II of the main report, a major concernis that recent swings in relative prices in Malawi may be making itdifficult for smallholders to plan and develop viable land managementand cropping systems to counteract erosion. This is particularly thecase for the poorer smallholders who appear to rely on intercropping andrelay cropping maize, groundnuts and pulses as a means to meetingnutritional needs, maintaining soil fertility and conserving soil.However, some "progressive" farmers may abandon these mixed-croppingsystems to plant the more erosive crops, such as maize, cotton andtobacco, in pure stands if there are high relative prices for thesecrops. Thus smallholders in Malawi may be influenced by changes in therelative prices of non-erosive to erosive crops that impact on croppingsystems and land degradation through the choice of crops, croppingrotations, intercropping and relay cropping.

2. This annex examines the extent to which smallholders in Malawi* can anticipate or predict the relative price of non-erosive to erosive

crops based on past price levels and trends. As very little informationexists on actual market prices in Malawi, the price series used areofficial prices. However, as the official prices are revised every yearin light of market trends, these prices are thought to be sufficientlyrepresentative of prevailing price trends.

3. If farmers are to make significant land management investmentsin cropping patterns and systems, such as switching between arosive andnon-erosive crops or substantially improving non-erosive croppingsystems, then they would be interested in anticipating future relativeprice trends of non-erosive to erosive crops. Of particular interest isthe extent to which past relative prices and trends are an indicator offuture prices, given that the past price levels and trends are probablyall the information available t, farmers for predicting future prices.If the relative price is highly unstable, then past prices will not be agood guide to the future, and the uncertainty surrounding farmers'investments is high; on the other hand, if the relative price is stable,then past prices could be highly predictive of future trends, andfarmers would be less uncertain about the outcome of their investments.

4. Given that farmers are most likely to base their expectationsover future prices on a simple extrapolation of past price levels andtrends, fitting an autoregressive trend model to the time series ofrelative non-erosive/erosive crop prices is the most straightforwardmethod of testing the accuracy of such extrapolations. The basic modelis:

Annez 2Page 2 Of 4

- 23 -

t a + bP"1, (1)

where P. - relative price of non-erosive to erosive crops in periodt (the currert year).

Pt-, relative price of non-erosive to erosive crops in periodt-l (the previous year).

S. Additional past values of P (e.g. for years t-2, t-3, etc.) mayalso be added. Unfortunately, doing this may also add to problems ofmulticollinearity in any regression analysis, i.e. high correlationbetween two or more independent variables. However, as the major use ofthe estimated relationship is to predict future levels of P and not toprecisely estimate parameters per se, then the presence of any highmulticollinearity is less serious a problem.

6. Several versions of the basic model (1) were estimated,including adding additional past values and incorporating changes inpast values in semi-log versions of the basic model. The following werethe best results:

Pt - 4.118 + 0.44lPt,. - 0.556Pt,8 (2)(3.96) (2.35) (-2'.85)

periods 1972-90 F - .475 adj Re - .409

S.E. - 0.524 D-W W 1.77 P11^e - 7.23

Lus m 1.289 + 0.134DP, + 0.138DP,, (3)

(38.64) (2.78) (2.48)

period: 1972-90 R- - .483 adj R' - .418

S.E. - 0.140 D-W - 1.98 P:.1, - 7.48

where LP, - natural log of P.DP - P", - P,..2. i.e. difference between last year's

price and the price prevailing the year beforeDPt2 - P,2 - Pt., i.e. difference between the price two

years ago and the price prevailing the year before

7. All estimated coefficients are significant at the 95Zconfidence level or higher. The more basic model (2) indicates thatpresent relative non-erosive/erosive crop prices can be positivelyextrapolated from ptices the year before, and given the pricefluctuations, can be negatively extrapolated from prices three yearsago. For example, on average the current relative price will be around442 of last year's price minus 56Z of the price three years ago. Thesemi-log model (3) shows how this year's prices might change in response

Annex 2Page 3 of 4

- 24 -

to changes in price differentials in the post; i.e., the coefficientsindicate how a one unit change in past price differentials might be used

to predict the percentage change in this year's prices. In thisregression, the response is very low - only 0.13Z to a marginal change

in past price differentials.

8. Unfortunately. however, the explanatory power of both models

(2) and (3) is not very good, as indicated by their respective R2 and

adjusted R2 values. This suggests that it is difficult to extrapolate

future prices from past price levels. Moreover, even if equation (3) is

accurate, it indicates that past price differentials are not a very good

guide to future price changes.

9. Models (2) and (3) can also be modified to include a long-run

price trend for non-erosive and erosive crops. The assumption would be

that smallholders take into account not only more recent prices but also

the long-run relative price trend for non-erosive and erosive crops.

The long-run trend rates of growth for non-erosive crop prices, erosive

crop prices and relative non-erosive/erosive crop prices were estimated

directly from the price series data for 1968/69 to 1989/90 using an

exponential growth function:

Non-erosive crops: 11.04Z per annumErosive crops: 11.18Z per annum

Non-erosive/erosives 0.21Z per annum.

10. However, th.e estimated regressions for deriving trend rate of

growth for the non.-erosive/erosive price ratio was a very poor fit.

This is not surprising, given the extreme fluctuation in this ratio.

Thus the trend rate of growth in the relative prices was derived

indirectly from the difference between the rate of growth of non-erosive

crop and erosive crop prices, i.e 0.14X. Using this rate of growth, a

long-run constant trend in the relative pr'ce was estimated, which was

employed in the following regressiones

Pt m -29.531 + 0.285Pt - 0.757P" + 8.81ST (4)(-1.75) (1.51) (-3.69) (1.998)

period: 1972-90 R - .585 adj K2 - .502

S.E. - 0.481 D-W - 1.84 F8.X - 7.05

LPf - 0.135DPv1 + 0. 138DPta2 + 0.325T (5)(2.94) (2.90) (40.73)

periods 1972-90 ea- .502 adj RK - .439

S.E. - 0.138 D-W X 2.07 F2,1, - 8.05

Annex 2Page 4 of 4

- 25 -

11. The inter,retations of equations (4) and (5) are similar tothat of (2) and (3), although adding in the trend variable has changedthe coefficients in equation (4) and a 332 change in current prices inequation (5) is related to the long-run change in trend. However, theexplanatory power of the equations has improved only slightly, asindicated by the R2 and adjusted R2 values. Thus, even if smallholderswere aware of both long-run relative price changes for non-erosive anderosive crops as well as past price levels, it would be difficult toextrapolate future prices with much accuracy. A large degree ofuncertainty over future relative prices would remain.

Annez 3Page 1 of 36

° 26 -

METHODOLOGICAL NOTE ON ESTIMATION OF DEFORESTATION RATE AND VALUE

This annex provides the background data for the analysis inChapter III of the main report on the depletion rate and economicvaluation of deforestation in Malawi. Appendix 1 covers woodconsumption data, Appendix 2 covers wood supply data, Appendix 3 reviewsthe depletion rate calculation, and Appendix 4 reviews the valuationcalculation.

-27 -

AW= 3APPU -1: MDod Coauvpt1on Data PagLe 2 of -36

TABLE 1.13 EmmUltion Prolecti ous. 1988 2000(thousands)

Year 1987 198 198 190 l"9 1992 1993 1994 1995 1996 1997 1MI 199 20000XB.................................................... .0.... 00.... ,I....00.... 0.0.... e0....000

Southern 3887 4018 4152 4298 4448 4605 4771 4933 5101 5275 5463 5657 585

Rural 3375 3478 3581 3695 3010 3930 4057 4179 4305 443S 4577 4713 4653Urban 512 540 571 603 638 675 714 754 796 840 88 944 1005

Central 3056 3165 3276 3397 3524 3654 3794 3933 4077 4228 4375 45 4691

Rural 2711 2795 2878 2966 3062 3158 3259 3358 3459 356 366 3774 3866Urban 344 370 398 428 462 496 535 575 4618 665 709 75 805

northern 890 921 952 988 1023 100 1100. 1139 1179 1222 1266 13U 1357

Rural 7" 813 836 84 80 918 940 976 100 1037 1061 102 1124Urban 101 108 116 124 133 142 152 163 174 186 205- .219 233

.....*.O.Sfc.....a.eaaf. f. . Snaeee . ...... of... . .. *enf

Nation 7033 8105 8381 8I683 895 9319 9"66 1O004 1OS05 10725 11104 11498 1190?

Rural 6875 7086 729 7527 762 800 8265 8513 8770 904 9303 9560 963Urban 956 1019 1085 1156 13 1313 1400 1491 156M 1691 101 1918 2044

7833 8105 8361 8 io 8 9319 9"6 1000 10356 17025 11104 11490 1190

SOURCE: NalaI Evlroneot eoWt Am"toLm,"-2 Jim, "199 (fileRNSNhI.NK CIC for awegt mem; r"elsl brek4tactors calulatue fra projtlu litlmat l EerwyPlan 19881"97, p. 1,.

q4

28- AM= 3Page 3 of 36

TAlBLE 1.2: Household ConsuMtion Projections

Assumptions:

Urban household cong_ t1ona 1.13 13 solid (estimate per NEP)decreasing annually at 1.91t

Rural household consueptionz 0.85 O 3 solid (conventional estimate)decreasing annually at 1. 45t

according to the following series of specific consumptionfactors:

*glazztssrssnsanlJaaszzxsuxgsxazssstassssgzzatssstastusaxzzgs-sssaastaYsssYs$ssssssssxzalsssassasxnxt " gauxst

Year 1987 1968 1969 1990 1991 1992 1993 194 199S 1996 199? 19 1999 2000

Rural 0.85 0.8377 0.8255 0.8136 0.8018 0.7901 0.7787 0.7674 0.7563 0.7453 0.7345 0.7238 0.7133 0.703Urban 1.13 1.1084 1.0872 1.066S 1.0461 1.0261 1.0065 0.9873 0.9684 0.95 0.9316 0.914 0.8966 0.8794

........................................................................................................

BASIS: Calculations based on figures given on p. 32 ofNational Energy Naster Plan -- It mass Sector PositionPapers -- Sumry Report, IPC (R. Kronen), Harch, 1988,.

Yer 1987 1M 1969 19"0 1991 12 1993 1994 1995 19% 199 1998 19 2000* a~~............................ ... . .. …t .en e ee. .eC.e ...... ....... e.. .e......

Southern 0.000 3.395 3.459 3.523 3.594 3.665 3.739 3.818 3.80 3.96S 4.040 4.123 4.208 4.296

Rural 2.827 2.871 2.914 2.962 3.011 3.060 3.114 3.160 3.209 3.257 3.313 3.362 3.412Urban 0.561 0 517 0.609 0.631 0.5 0.679 0.705 0.730 07 0.782 0.810 0.846 0.864

Central 0.0 2.653 2.710 2.766 2.860 2.8t3 2.959 3.029 3.096 3.165 3.237 3.302 3.370 3.440

Rurai 2.271 2.307 2.341 2.380 2.419 2.459 2.501 2.53 2.S76 2.617 2.653 2.692 2.732Urban 0.362 0.403U 0.425 0.446 0.474 O.50 0.526 0.557 O.S67 0.620 0.648 0.678 0.708

Northern 0.0 0.773 0.76 O.604 0.823 0.640 O.S 0.677 0.896 0.91S 0.934 0.955 0.97S O.9S

Rural o.m 0.671 O.41 0.695 0.703 0.715 0.727 0.738 0.7SO 0.761 0.760 0.779 0.790Urban 0.112 0.11O.1 l 0.130 0.137 0.143 0.150 0.158 0.165 0.173 0.186 0.196 0.20S

........... ........... .... _................. .. ............. ... ..... 6 . 0..............

Nation 0.000 6.821 6.9 7.0M3 7.244 7.398 7.556 7.725 7.882 8.045 6.211 8.380 83.53 6.731

Rural 0.000 5.7S9 5.849 S.935 6.035 6.133 6.234 6.342 6.438 6536 6.636 6.734 6.6U4 6.934Urban 0.000 1.062 1.106 I.IS 1.209 1.265 1.322 1.363 1.444 I.509 1.575 1.646 1.720 1.797

I *st|u3a33asuu8u 33J3s333uJ33 m3uJ3u333a38su33.8333 l83.3333u33838EJslBS *l8833333333333333335g233333333l

-29- AM=N 3Page 4 of 36

TABLE 1.3: Tobacco Estate Wood Use, 1988

a) Fuelwood use (.3 st)

CATEGORY RECION

NORTHERN CENTRAL SOUTHERN TOTAL

Flue-Cured 440 264000 132000 440000Burley 0 0 0 0Fire-Cured (N.D.) 0 22295 0 22295Fire-Cured (S.D.) 0 364 896 1280Sun/Air Cured 0 0 0 0Oriental 300 0 0 300

TOTAL 44300 286679 132696 463075

b) Pole use (*3 st)

CATEGOY REGION

NORMTHEN CENTRAL SOUTHERN TOTAL

Flue-Cured 0- 0 0 0Surley 0 220000 55000 275000fire-Cured (N.D.) 0 132000 33000 W6500Fire-Cured (S.D.) 0 230.4 537.6 768un/Air Cured 0 1066 0 106Oriental 0 0 0 0

TOTAL 0 33M.4 637.6 44163

c) Total fuelmod plus pole (d it)

CATEGORY REGIS

NilU cT I TOTAL

Flue-Cured 44000 26000 132000 440000Burley 0 226010 N5100 275100Fire-ured (N1.) 0 15M 33000 16729SFire-Cured (S.D.) * 614.4 1433.6 2040Sun/Air Cured 0 1066 0 1066Oriental 300 0 0 300

TOTAL 44300 63"77.4 221433.6 90S711

30 -iANE 3

Pane 5 of 36

TABLE 1.3 Continued

8) Total fuelvood plus "as (e3 solid)

Assumption: 1.3 It * 0.55 e3 solids

CATEGORY REGION

NORTHERN CENTRAL SOUTHERN TOTAL

flue-Cured 24200 145200 72600 242000Burley 0 121000 30250 151250Fire-Cured (N.D.) 0 84862.25 10150 103012.3Fire-Cured (S.0.) 0 337.92 788.48 1126.4Sun/Air Cured 0 587.4 0 507.4Oriental 165 0 0 165

TOTAL 24365 351907.6 12178.5 498141.1

Generic factor uud in National Energ Naster Plan - BlousSeotor Position Papers, Suary Report, IPC (N. Mronen),"arch, 1981.

-'C ~ ~ ~ ~ ~ ~ ~ ,S

-31- QlAM 3Page 6 of 36

TABLE 1.4: Tobacco Estate Wood Pr9lectiLons

PAELININARY 6ROVTH ASSWIPTINS:

a) lurley grwe at 3.41 annually until 2000 and realins at thatlevel (basd on National Energy Plin (MP), p. 255)

b) All other oategorle regain at the level ot 1988/89c) All potential vood cmnsueption rate art attained by 20004) Projections vill be ade separately for poles an6 fuelvood.

Poles will be projected as per burily growth rate; tuelvoodVill remain At 1980/89 levels.

Projections of Poleood Used for Tobacco fros 9M:

(Thwod a3

Teur 1"7 1980 198 19 1991 19 I2 1993 14 195 1996 1997 199 199 2M…... ...... U.C...C ..C.. C*. e........ .CCC...CC.......

TOTAL* -NOT EAN 0 0 0 0 0 0 0 0 0 0 0 0

TOTAL CENTRAL 194.3141 200.9200 207.1521 214.8157 222.119 229.6715 237.4805 245.5546 253.9095 262.5362 271.4624 200.69

TOTAL SOUTHEN 48.6954 50.35133 52.0623 53.833 55.66377 57.55633 59.51325 61.5367 63.6265 65.79233 6.02927 70.342

ToTAL VWo o. 243.0n0 251.2721 259.8154 269.6491 277.7632 287.2278 29.9936 307.0913 317.5324 328.3285 339.4917 351.03

Projections of Fuelvood Usd for Tobao fre 1M:

Year 19?1 1916 1o 190 19 192 13 19 1"S 19"6 1"7 19" I99 2000--- *.e.*C-- _ _ e_ ._ .......

TOTAL NOANTEUN 14.3 24.365 24.365 24.365 24.365 24.365 24.365 24.365 24.365 24.365 24.365 24.365

TOTAL CENTRAL 1S7 6735 157.6735 157.6735 157.6735 157.6735 157.6735 157.6735 157 6735 157.6735 157.6735 157.6735 157.67

TOTAL SOUTRN 73.09n2 73.9O26 73.0928 73.0920 73.092 0 73.2 73.092 73.092M 7MOM2 73.092 73.092 73.093

TOTAL VOOD REQ. 255.1313 255.1313 255.1313 255.1313 255.1313 255.1313 255.1313 255.1313 255.1313 255.1313 255.1313 255.13

* 32 -ANNE 3Page 7 of 36

TABLE 1.5: Wood Industry Demd Porjectious

Projected Vood Oequirments of Nechanieal Promessing (thousand e3ub)1986- 1993- 2000-

1986 1987 1988 1989 1"0 1991 1992 92 99 2009SOFTWOODSNorthern R.ChIkangava SN 22.0 31.0 40.0 44.4 44.4 44.4 33.7 44.4 44.4naIaeba 6.8 9.0 11.0 13.0 13.0 13.0 13.0 12.1 13.0 5.2Other 0.9 0.9 1.2 1.5 1.8 2.1 2.4 1.8 2.7 3.0Chikangava PO 11.5 16.1 20.7 23.0 23.0 23.0 20.0 23.0 23.0

Subtotal 9.7 43.4 59.3 75.2 82.2 82.5 82.8 72.6 83.1 75.6

Central a.Dedza SN 16.0 20.0 22.5 25.0 25.0 25.0 25.0 23.9 25.0 37.5Other 1.0 1.0 1.3 1.6 1.6 2.2 2.4 1.9 3.0 3.0

Subtotal 17.0 21.0 23.8 26.6 26.8 27.2 V2.4 25.8 28.0 40.5

Southern R.

Zomba SR 16.7 16.7 16.7 $2.5 8.3 16.7 21.9 17.1 27.1 27.1Blantyre So 8.3 8.3 8.3 8.3 8.3 6.2 3.1 6.2Nulinje SN 4.2 6.2 7.3 8.3 8.3 6.3 7.3 8.3 8.3Other 1.8 1.8 2.5 3.1 3.7 4.4 5.2 3.8 6.8 6.8TPL PB 3.6 3.6 3.4 3.5 3.6 3.8 4.0 3.8 4.8 6.4

lZoba PO 5.0 10.0 4.3 18.8 25.0

Subtotl 30.4 34.6 37.1 34.7 32.2 44.4 52.5 42.5 65.8 73.6

TOTAL SY 57.1 99.0 120.2 136.5 141.2 154.1 162.7 140.9 176.9 189.7

NAROVOODSNorthern R.Other 1.0 1.0 1.0 1.1 1.1 1.3 1.3 1.2 1.3 1.8

central f.Other 1.2 1. 1.2 1.3 1.3 1.5 1.5 1.3 1.5 2.1

Southern R.TPL Panel Sd 7.5 7.5 7.1 7.5 7.7 8.2 8.5 8.0 10.2 13.6Nulanje 0.8 0.8 0.9 0.9 1.0 1.0 0.9 1.0 1.4Other 2.4 2.4 2.4 2.6 2.6 3.0 3.0 2.7 3.0 4.2

Subtotal 9.9 10.7 10.3 11.0 11.2 12.2 12.5 11.6 14.2 19.2

TOTAL NV 12.1 12.9 12.5 13.4 13.6 15.0 15.3 14.1 17.0 23.1

TOTAL VOOD RED. 69.2 111.9 132.7 149.9 154.8 169.1 178.0 15S.0 193.9 212.8

33- AU 3Page 8 of 36

TABULE 1.5 Cont1nued

TOTAL NOINTERN 10.7 44.4 60.3 76.3 83.3 03.8 84.1 73.8 84.4 77.4

TOTAL CENTRAL 18.2 22.2 25 27.9 28.1 28.7 28.9 27.1 29.5 42.6

TOTAL SOUTHERN 40.3 45.3 47.4 45.7 43.4 56.6 65 .54.1 80 92.8

TOTAL VOOD REG. 69.2 111.9 132.7 149.9 154.8 169.1 178 155 193.9 212.0

ASSUNPTIONS AND OISERVATIONS:

1. Recovery fsctors: .48 for Clkangawa, Zoe and Blantyre sunills;.45 for Natiaoba and .40 in Dedza and iIulan3e savmllls and other oprs.;.40 for plywood

2. NWaaMba mill not expected to produce more tan 5,000 .3/yr oflumber due to log supply, handling and drying deficincies. Couldclose down In early ninaties.

3. TZoba mill Is obsolete and badly located and assumed to stop inabout 4 years. New complex planned for late 1980s If ao pulpillIs built based on Zols resurei).

4. Slantyre mil! also obsolete aRad sold stop operations m.

5. Timber Products Limited (TPL) sill faces diminslhing ailabilityof Hl so product mix will shift to-higher share of SW.

SUCE: Forestry Sub-Sector Study, table 5, p.51, VI, Sept., 142 IPL is currently oalled ITL.

VIPLY is dsigned to praduee 7,500 s/yr of plywoo and 7,500 .3/yr ofblockboard. Lumbe production ha be etteAtd at 13,000 3/yr.

ITL has an lnstalled sawmIll apaity of 24,000 e3/yr Wille the plywocapcity is 5,000 .3/yr.

SOUE: Pardo, U.S., A Review of Foret Policy for klwi, 1S

Personal comuiatim w/ 3.6. Undo, Nuagia 1retor of ML giva uvs ill roundood inpt *i v,0 s3 vith a rot Iur reoavy of40% and a plywood roundweIut o 610, 0S vith for 2,000 m3 ofend product.

Aftef discuesios wvith International Timers td. ad VICO, it will oeassumd that total raw mterial reupire ts for the forest eroo6tsindustry wIll reaifn at the 186 level a of 199.

Assumption: from 1990 until 2000, wood reqiremts will gr1A1 at It/yrwith all growth occurring In the Northwrn region. W indstry Isstagnat; only current grwth to VIPLY and only th Nothers region hslncreental ra aterial sources.

34- ANNE 3Page 9 of 36

TABLE 1.5 Continued

Projections of Vood RequlrMts for Vood Prod4cts Industry

(Thousand .3)

Year 1987 1908 1989 1990 191 1992 1993 1994 1995 1996 1997 1998 1999 2000.......................................................................... . ..................................…TOTAL NORHTERN 10.7 10.7 10.7 10.7 11.4 12.1 12.8 13.5 14.2 15.0 15.7 16.4 17.2 17.9

TOTAL CENTRAL 18.2 18.2 18.2 18.2 18.2 18.2 18.2 18.2 18.2 18.2 18.2 18.2 18.2 18.2

TOTAL SOUTHERN 40.3 40.3 40.3 40.3 40.3 40.3 40.3 40.3 40.3 40.3 40.3 40.3 40.3 40.3

TOTAL VOOD REG. 69.2 69.2 69.2 69.2 69.9 70.6 71.3 72.0 72.7 73.5 74.2 74.9 75.7 76.4

. ..

35 -ANNEX 3Page 10 of 36

TABLE 1.6: Tea Estate Demand Projectious

1987 annual consueption of tea Industry according to NEP:21000 toe, all frog self-produced tuelvood (NEP, table 5.7,

p. 244).

According to IPC IS (Kronen), seasoned firewood contains:0.345 toe/ton (P. IV).

Self-produced futlvood In tea estates coest frog eucalyptus.

Eucalyptus has a density of:0.56 ton/e3 (p. IV, IPC 8 (Kronen)).

Therefore, the annual fuelvod consueption of the tea indstryaeunts to:

60870 tons of eucalyptus fuelwood, or,1086% *3 of eucalyptus fuelvood

What is the anticipated grwth rate of the tea industryl.

According to NEKP (p.25), . low growth scenario rate of5.2% is sumd through 1 , which v w assue contines

through 2000. High and edius scNario groth rate are 5.4% and5.3t, respectively.

PROJECEO FUELVOOD CN TIIIIN GOWTN FOR TEA INDTYRT (thusn Q3

191 1916 196 1990 1 IM 1M3 1994 19" 1996 17 199 199 2000

Consumption 106.7 114.35 120.29 126.55 133.13 140.05 147.34 155 163.06 171.54 160.46 19.64 1".71 210.1(all Southen)

-36 hN3I 3Page 11 of 36

TABLE 1.7: Iutitutional Demand Projections

According to NEP, lnstitutloel tuelwood co..euwptlon in 1987 wasestimated at:

200 toe/yr using edigenous fuelvood (Table 5.7, p. 244).According to IPC 88 (gronen), seasoned firewood contains:

0.345 toe/ton (p. IV).

Indigenous fueiwod his a density of:0.6 tons/" (p. IV, IPC (Kronen)).

Therefore, institutions vould onsuse:579.7 tons of Indigenous fuelvood per year, or966.2 s3 of lndigenous fuelsood per annul.

For projection purposes, an annual rate of6.5t, which is the rate of urban population growth of the

Vorld Bank scenario per tables at the end of this file

Regional distribution will be acoarding to urban populatIon.

Projections of Vood Requiresents for Institutions

(Thousand e3I

Year 1987 1988 1989 19"0 1991 19 1993 1994 1995 199 1997 1998 1999 2000.. -0. 0. . .. . ..00 . ...... ea...... .......................

TOTAL NOINTERN 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.3

TOTAL CENTRAL 0.3 O.A 0.4 0.4 0.5 0.5 0.5 0.6 0.6 0.7 0.7 0.8 0.8 0.9

TOTAL SOUTHERN 0.5 0.6 0.6 0.6 0.' 0.7 0.7 0.8 0.8 0.9 0.9 1.0 1.0 1.1

TOTAL VOOD RED. 1.0 1.0 1.1 .1.2 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.1 2.2

- 37 - AINNE 3Page 12 of 36

TABLE 1.8: Village Iuduetries Deand fectloDa

Brick oaklng apopar to 1 the most iwortant village industryrelying exclusively on tfwoo (NIP, p. 247)

annual brick productiont for the whole country as assustO at40000 tons ptr year, whicn require a spicific amount of2.65 e3 St of indIgenOus fuelvood per ton.

is a result, current annual fuelvod coetuptfn Dy this industry.OulO be:

106000 o3 st/ year, or, astusing:0.55 .3 solid per e3 st (generic coefficient, IPC a, p.11)

51300 i3 solid per year.

Otrer village industrie are assused by NiP to contuse:134000 o3 st/year, or:73700 a3 solid per ye.

Therefore, the total annual ftuelvod conumptil for villagiIndustrl wouvld be;

1320 solid pe year.

actordifg to UEP (P. 248), the introdctiom of IW*ved pred6timette could rtduce brick bWning fuebmo demn b W.Thtrefore, for projctions ve vill atoi eoestlof rminsconstant.

ProJeetlons of Wood Rplre ts for V11lae Ilndtries

thenaM 031Year 1M6 1o 1M 19"0 1991 19I2 1993 194 1 9 I? 1" 199 2010o S f e l e a no....... ......... . ,......e.. ..

Southern 65.6 6S.5 65.4 65.4 653 65.3 65.2 65.2 65.1 65.0 64.9 64.9 6.9 64.9

Rural 57.1 56.9 56. 56.4 56.2 55.9 55.7 55.4 55.1 54.9 14.6 54.4 54.1 53.8Uran 8.5 8.6 8.6 9.0 9.2 9.4 9.6 9.? 9.9 10.1 10.3 10.S 10.0 11.1

Central 51.5 11.5 51.5 51.6 51.6 51.7 SI.A 51.8 51.9 52.0 52.0 52.0 52.0 52.0

Rural 45.9 45.7 45.5 45.3 45.1 44.9 4.7 44.S 44.3 44.1 43.9 43.6 43.3 43.1Urban 5.6 5.6 6.0 6.3 6.5 6.8 7.0 7.3 7.6 7.9 6.2 8.4 8.7 8.9

Nortern 14.9 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 11.0 15.0 Is.0

Rural 13.2 13.3 13.2 13.2 13.1 13.1 13.0S 12.9 12.9 12.0 12.8 12.6 12.5 12.5Ureu 1.7 1.7 1.6 1.6 1.9 2.0 2.0 2.1 2.1 2.2 2.3 2.4 2.5 2.6

lItlac 132.0 132.0 132.0 132.0 132.0 152.0 132.0 132.0 132.0 132.0 132.0 132.0 132.0 132.o

Rural 116.3 115.9 115.4 114.9 114.4 113.9 113.4 112.9 112.3 111.8 111.2 110.6 110.0 109.5Ur"" 15 IS6 166 6 1 s # 0,

-38- A 3

Page 13,of 36

TABLE 1.9: Buildlng Pole Demand Prolections5. BUILDING POLES $

According to the VI Foresry Subuector Study, pole consumptionis estilsted at:

700000 e3 for 1984, ad projected at:900000 u3 for £194. this laplies a growth rate of2.545% per year. this rate v11l be used initially.

Polevood use for burley has to be deducted.

Distribution by region vill be according to population.

Projections of Polevood Used for tobacco fro 1989:

(Thousand .31

Year 198 19868 199 1990 1991 19 193 194 1995 19% 1997 19"9 19 2000-00...0o0.00 ........... _.00.......00.0000000.....................................-0.0 ......... 000..0,00............ 000.00..0..0 ....................................... 0000.

TOTAL NORNTERN 0 0 0 0 0 0 0 0 0 0 0 0

TOTAL CENTRAL 194.31 200.92 207.7s 214.02 222.12 229.67 237.4 245.55 253.9 262.54 271.46 M.6

TOTAL SOUTHM 48.6% .51 52.063 53.833 55.664 57.556 59.513 61.537 63.629 65.792 68.029 70.342

TOTAL WOOD lEO. 243.01 251.27 259.62 268.65 277.78 267.23 29.9 307.09 317.53 326.33 339.49 351.03

SOUtCE: *ATTEPT TO ESTINATE VOCON TION P TOACCO INISTRY BT REGION,file KALTO8MK of this ei, ItM 7.

Projection of total polevood use(Thousad iSI

Year 196 1985 1986 1987 198 19l9 199 19 192 13 19 l9 199 1

TOTAL VOOD REG. 700 717.82 736.00 754.82 774.0 7.73 613.9 04.64 855.80 77.66 00 M.91 946.39 970.48

,1 ,

Projection of rice-to A pol Use'

Year 1967 1S 19 199 MI 192 1 199 195 199 19 19" 19 200.. 0... ..... 4.. .. . .. 0 . . .. ... .

TOTAL NICUTERN 62. 63.92 65.413 66.602 68.225 69.722 71.253 72.796 74.414 76.021 .636 79.281

TOTAL CENTRAL 215.07 219.96 224.86 230.04 235.24 240.57 246.04 251.66 257.41 262.74 268.32 274

TOTAL SOUTHERN 273.04 276.77 2.55 290.39 2%.42 302.49 308.62 314.5 321.13 328.09 35.06 342.16

TOTAL WOOD REG. 550.72 62.65 574.83 587.23 s59. 612.77 625.91 639.3 652.95 666.65 681.01 695.44

- 39 -AMEN 3Page 14 of 36

APP11DX 2: Wood Supply Data

TABLE 2.1: Forest Area in 1990(thousand heotares)

FOREST NORTHERN CENTRAL SOUTHERNCATEGORY REGION REGION REGION TOTAL

Customary Land 1639.6 913.0 505.7 30356.Forest ResWves 235.2 392.0 3431. 0 90.0

TOTAL INDIGENOUS 1075.0 1305.0 6418.7 4036.5

Governmnt plantations 53.0 19.6 1P11. 92.5

Plantations on statesTobaooo estates 4.2 6.4 1.2 11.6Tea estates 9.5 9.5

subtotal 4.2 6.4 10.6 21.2

Other priv. plantat*lonsLocal authority 0.7 1.0 1.0 2.7BcFP* *4.6 4.8

mTL 2.5 2.5

Subtotal 0.7 1.0 6.2 10.0

TOTAL PLANTATIONS 56.0 27.1 36.6 123.7

TOTAL FOREST LAND 193.0 1332.1 667.3 4162.2

maCpP * Slantyre Clty Puslwood Projeot=*ITL a Imperial T1ib Limited

~.

.40.- AN 3Page 15 of 36

TABLE 2.1 Continued

SOURCES:

1. Forest area on oustomary land obtained from ZPCz. National EnergyMaster Plan-Biomass Seotor Position Papers--Summary Report(Kronen), Maroh, 1966, p. 7.

2. Regarding Forest Reserves:Total figure obtained from various souro-e Inoluding WO SAR,p. 4; R. Pardo's Common Property Resouroe Management, 190 p.5;Forestry Department, pers. comm. per r. Bakanda.Regional breakdown obtained from Armitage, J., An EvolvingStrategy for Managing Wood Energy: A Case Study for Malawi,1966. p. 2.

3. Regarding Government Plantations:Total figure obtained from ZPC, National Eiergy Master Plan--Biomass Seotor Position Papers--Summary Report (Kronen), March,1908, p. S. These are 1967 data. Regional breakdown assumeS3,000 ha In the Northern Region (oorresponding to the Vlphyaplantations (per Forestry Dept). Remainder Is asumed to beevenly split between the Southern and Central Regions.

4. Regardlng plantations on estates:Total are of plantations on tobacoo estates obtanied from IPC,1966 (Kronen), Annex Ui.S. Plantations on tea etates (all inSouthern Region) obtalned from IPC (Kronen), p. 6. Regionalbreakdown of total plantations on estates "sum" to be 50 inSouthern, 30% in Central and 20% In Northern Reglons basd onregonal distribution of tea and tobaooo estates.

5. On other private plantations:Looal Authority Plantations baed on WH Projeot CompletlonReport, Annex 1 Table 3. BCFP figures based on BCfP plantingschedule per FORINDECO Mwrket Prios ftudy for Fuswood and Polep. 23. ITL plantation area obtained from Mr. D.G. Lloyd,Managing Diretor of MTL.

- 41 -ANNU 3Page 16 of 36

TABLE 2.2: Growing Stock Coefficients(m3la)

NORATERN CENTRAL SOUTHERNREGION REGION REGION COPOSITE

A. Indig. For. Res. 100 80 s0

B. Indig. oust. Id. 120 40 30

C. Government plant. 202 84

D. Private plantations 71 115

SOURCES:

1. For Indigenous Forest Reserves and Indigenous oustomary land,ZPC (Kronen), p. V.

2. For plantations, both Government and private, figures wereoaloulated from Romahn, S., Deforestatlon In Halawl-DisoussionPaper for the National Eoonoseo Counoil, May, B9, Table 2,p.2.

-42 -

Pa.. 17 of 36

TAIL 2.3: Stock In 1990(tbousand u3)

OEtESTO POTHERN CENTRAL SOUTHGENCATEGORY REGION REGION REGSON TOTAL

Custoary land 19%776.0 36520.0 15171 0 2447470Forest Reserve 23520.0 31360.0 27440.0 82320.0

TOTL INDIGENOUS 2202% 7O 5700.0 42611.0 30767.0

Government plantations ao706.0 1659.7 16"9.7 14025.3

Plantation. on StitSeTobaooo estates "l.7 482o5 132.6 a56.e

Toe Es9tetGo 1089.l LOS9Oa

subtotal 301.7 452.S 1221.6 1975.9

Other prly. p1antatloeasLooal authority 52.7 69.9 113.2 23.7SFp*s 54.3 54.31TL7. 287.5 207.5

subtotal 52.7 09.9 94.9 1069.5

TOTAL PLANTATIONS A1 4 2182.1 3M62.2 17070.7

TOTAL GROWING 6TOT 23135.4 7006.1 46439.2 347857?.

USCFP a Slantyre City Fuelvood ProjeotN*sTL a perlal Timesr Limited

OSSRVATIONS:

I e For Government Plantations In the Central Reglon, the growingstock seffioelent of the Swithern Region (64 mI/ha) has beeappliLed.

2. For planttats en tobaooo estates in the Northern Reglon, thegrowing eOok oeffiioent tor preovate plantatins In the CentralRegion (7TL /ha) has bem applied. Otherwise, plantations enestate us the growing stock oeffiolents for privateplantatiens In the respective reglnas.

3. Local authority plantation In the Northern R"ion use thegrowing stook coeficient foe' private plantations In the Central

tegion C71 mI/ha). Otherwis, leal authority plantatiens usethe growing stook cosfficients for private plantateons In therespeotve regions.

4. SCP and KTL use the growing stook o"fficients for privateM*l iv * 34 of I t , n -0*3 Dn '

- 43 -3

Page 18 of 36

TABLE 2.4: Mean Annual Increment Coefficients

_ _ 1sl.(/ha/yr)

NORTHERN CENTRAL SOUTHERNREGION REGION REGION COMPOSITE

A. ndi9g. For. Rie. 1.2 1 1

B. Indlg. oust. Ld. 1 0.8 0.5

C. Government plant. 20 12 12

D. Private plantatlons 10 10 20

SOURCES

* o1. For indigenous Forest Reserves MAX ooeffiolonts wer eetimatedbase on an average impliolt sustalned yield of 1.11 mS1/ha/yrcaloulated from IPC (Kronen), p. 69 and spread acrose reglonswith the Nothern region having the hlghest produotlivty, as Inthe oase of Indigenous forests 6n customary land.

2. For Indigenous forest on oustomay land, MAX ooeffioIeft@i wereobtained froe IPC (Kronen), p. V.

3. For Government plantations MAX ooeffioients wer also obtainedfroe IPC (Kronen), p. V. For the Northrn Reglon the Vlphyasoftwood plantation ooeffioient (20 3/ha/yr) was used. For theCentral and Sothern Regions, the 12 .3/ha/yr ooefficientoorresponds to softwood plantations other than Viphya orEucalyptus plantations for wood energy.

4. MAI oosffioients for private plantations were also obtained tromIPC (Kronen), p. V, with the Nothern and Central regions usingthe Euoalyptus figure for tobaooo estates (10 m3/ha/yr), and theSouthern region uslng the flgure for tsea state (20 &3/M/yr).

.44- ANNEX 3Page 19 of 36

TABLE 2.5: Mean Annual Increment In 1990(tbousand .3)

FOREST NORTHERN CENTRAL SOTHERNCATEGORY REGION REGION REGION TOTAL

Customary Land 1639.8 730.4 252.9 2623.1Forest Resrves 282.2 392.0 343.0 1017.2

TOTAL INDIGENOUS 1922.0 1122.4 595.9 3640.3

Government plantations 1060.0 237.1 237.1 1534.2

Plantations on estatesTobaooo Estates 42.5 63.7 23.1 129.3Tea Estates 169.4 189.4

Subtotal 42.5 63.7 212.5 318.7

Other priv. plantationsLocal authority 7.4 9.6 19.7 36.9SCFP& 95.0 95.0

ITLU' 50.0 50.0

Subtotal 7.4 9.6 164.7 l61.9

TOTAL PLANTATIONS 1109.9 310.7 614.2 2034.8

TOTAL ANNUAL INCREMNT 3032.0 1433.1 1210.1 5675.1

iSBCFP a Slantyrs City FuseIood Projeot**ITL a Imprial Tibr Limited

- 45.ANNEX 3Page 20 of 36

TABLE 2.6: Private Sector Afforestation Assumptions

ASSUMPTIONS ON ANNAL PLANTATION RATES

1. Blantyre City Fuelwood Project plants 1,750 ha/yr from 1989/90to 1992/93. This is assumed to continue.

2. The Forestry Extension Services Division has provided over130 million seedlings since 1976e This implies 9.3 millionseedlings per year. Assuming 2,500 trees planted per hectareand a 30% survival rate, this gives approximately 1,100hectares per year.

3. Between 1981/82 and 1985/86, Local Authority plantationsincreased at a rate of 2,710.5/4 - 677.5 per year, roundedoff to 700 ha/yr. Distribution was 27% in Northern, 36% inCentral and 36% in Southern regions.

4. Between 19.81/82 and 1985/86 Government plantations increasedat a rate of 10,899.9/4 - 2,725 ha/yr, rounded off to 3,000ha/yr.

5. Based on the above, the following annual planation scenariois assumed for years 1991 to 2,000.

BCFP 0 0 1,750 1,750Other private 0 550 550 1,100Local Auth. 200 250 250 700Governent 0 1,300 1,700 3,000

TOTAL 200. 2,100 4,250 6,550

rounded off to:

300 2,200 4,500 7,000

.46- AIM 3Page 21 of 36

APPEDIX 3: Depletion Rate Data

TABLE 3.1: Wood SUPPY and Demnd In 1990

YEAR 1990

1. GROVIN6 STOCK PLUS MIA IN 190 2. NAVEST IN 1MO

[Thousnd 31 (Thougud as)

FOREST NORTH CENT. SOUTH FOREST NOuN Ciic . AUTHCATEGORY IEGCN N REGION lEI20 TOTAL CATEGoY EG1ON REGION E110ION TOTAL

CusturMy L. 198416 37250 15424 2510" Custoury L. 48 2712 3201 6393Fornt 1R. 23102 31752 27785 837 Forest ies. 282 392 343.. lo01

TOTAL INDIG. 222218 69002 43207 334427 TOTAL INOIG. 762 3104 34 741

Gov. plant. 11766 1697 1897 15560 GOv. plant. 106 23? 237 518

Plantations en lstat. PlantatIons On "tat"Tlb. fst. 344 516 156 1016 Tob. 1t. 42 64 23 129Ta ettes 0 0 1278 1278 TN states 0 0 18 16

Subtotal 344 516 1434 2295 Sub8toa 42* 64 212 319

Other pray. plantations Oter priv. plantatilLeo. author. 60 80 133 273 Lot. author. 7 10 20 37ICFPU 0 0 "1 641 WcP 0 0 5 95IlL" 0 0 330 338 ItL" 0 0 50 so

subtotal 0 60 1112 125 Subtotal 7 10 10 182

TOTAL PLAT. 12170 2493 442 19106 TOTAL LO. 156 311 614 101l

TOT. 6. ST0C 23438 71495 4761 S TOT. I9ST 918 34S 4158 0491

CmST. IAI 160 23 2623

3. CU5T0"t FOOUT LUD MM 190 lU m CuST. mm. 1160.2 -12 -2947.9 3770

[Themami butts)

MOUTH CENT. 88JTHREGION REGION 110101 TOTAL

C. MA. DU. so la14

1ts. CUS. F.L. 1640 863 40? 2911

4. INcIEIIAL PLANTATION ARIA

(Th"man att

ALL NEV PLANT. 0.3 2.2 4.5 7.0

- 47 -

hhNNEI 3Page 22 of 36

TABLE 3.2: Wood Supply and Demand in 1991

1. GROWING STOCK PLUS MAI Olt OUTONANY FOREST LAND IN 1991 3. CUSTONARY FOREST LAD AFtEI 1991 NARVESY

(Thousand a0 ,ousano heotares

FOREST NORTH CENT. SOUTHCATEGORY REGION REGION REGION TOTAL RENION REGION REGIOI TOTAL

Customary L. 199576 33247 9479 242302 C. NHA. DEf. 52 101 153

RES. CUS. F.L. 1640 812 306 27582. HARVEST IN1 19,1

[Thousatd a3] 4. INCtENENTAL PLANTATION AREA

FO*EST NORTH CENT. SOUTH (Thosn4 hectares]CATEGORY REGION REGION REGION TOTAL

Custoary L. 497 2764 3241 6502 ALL NEV PLANT. 0.6 4.4 9.0 14.0

Forest ha. 252 392 343 1017

TOTAL INDIS. 779 3156 354 7519

SoV. plant. 106 237 237 58

Plantation, on etatsTob. est. 42 64 23 129Tea estates 0 0 169 16

Subtotal 42 64 212 319

Other priV. plantatiosLOO. author. 7 10 20 3?SCFP3 0 0 f5. 9ITL2S 0 0 SO SO

Subtotal :7 Ig 165 III

New Plaitat. 3 45 70

TOTAL PLANT. 159 30 459 1151

TOT. HARVEST9I 938 3409 4243 6670

CUST. RAI 1640 691 204 253

CUST. DRON 1143 -2073.4 -303 -3967

-48- ANNEX 3Page 23 of 36

TABLE 373: Wood SUpply and Demand in 1992

PROJECTIONS OF HAVEST-COIPTION SALANCE

YEAR 1992

1. BROVING STOCK PLUS H;l ON CVS1WTAY FOREST LAND IN 1992 3. CUSTOAY FOREST LAND AFTER 199? HARVESY

(Thousand s3] - (Thousand htctUre)

FOREST NORTH CENT. SOUTH NORTH CENT. SOUTHCATEGORY REGION REGION REGION TOTAL REGION REGION REGION TOTAL

Custoary L. 199559 31040 6302 236901 C. fMHA. DEF. 54 M04 159

RES. CUS. F.L. 1640 757 202 25992. HARVEST IN 1992

[Thousand *3) 4. INCRENENTAL PLANTATION AREA

rOUEST NORTH CENT. SOUTH [Thousnd hbetares)CATEGORY REGION REGION REGION TOTAL

ALL EV PLANT. 0.9 6.6 13.5 21.0Custeary L. 514 2820 3281 6615Forest Res. 282 392 343 1017

TOTAL INDIC. 796 3212 3624 7632

Gov. Plant. 106 237 237 580

Plantations on "tatuTob. nt. 42 64 23 129Tta estate 0 0 189 189

Subtotal 42 64 212 319

Other priv. plantationsLot. authw. 7 10 20 37SCFP' 0 0 9 95ITL'8 0 0 50 SO

Subtotal 7 10 165 U2

New Plantat. 6 n 0 140

TOTAL PLANT. 162 * M4 1221

TOT. HARVIST92 958 356 4329 8855

CUST. MAI 1640 649 153 2442

CUST. DR1N 1125.9 -2170.3 -3128.2 -4173

*49 ANUM 3Page 24 of 36

TABLE 3.4: Wood Supply and Demand in 1993

1. GROVIN6 STOCK PLUS RAI 0N CuSTO ARY FOREST LAND IN 1993 3. CUSTOMARY FOREST LAND AFTER 1993 HRVEST

(ThOUSand 13] [Thouumnd hietarus

FOREST NORTH CENT. SOUTH NORtH CEI;IT SUTHCATEGORY REGION REGION REGION TOTAL REIONT RECIOT REGIN TOTAL

CuStOarfy L. 199542 20730 3031 231302 C. RHA. DEF. 57 107 164

RES. CUS. F.L. 1640 701 94 24352. HARVEST IN 1993

[Thousand a3] 4. INCREMNTAL PLANTATION AREA

FOREST NOTH CENT. SOTh (Thound heetaresCATEGORY REGION REGION REGION TOTALCostmry L. $31 2616 3325 6733 ALL NEV PLA. 1.2 8.8. 18.0 28.0Customary L. 531 2876 3325 673Forest QN. 282 392 343 1017

TOTAL INDIG. 813 3268 366 7750

WV. plant. 106 237 237 50

Plantations on estateTab. nt. 42 64 23 129Tea etates 0 0 1" 169

Subtotal 42 64 212 319

Other prlv. plantatlmLot. author. 7 10 20 V.8CFPs 0 0 95 1ITLU 0 0 so so

.. ~~~~~. ;..

Subtotal 7 IS 115 I7

Neo Plantat. 9 41 1 Q

TOTAL PLANT. 165 31 749 129

TOT. AVEST93 978 364S 4418 91

CUsT. RAI 1640 606 101 247

CUSt. DION 1108.8 -2270.3 -3224.4 -4386

FOR. iS. pIRN

ANNE 3Page 25 of 36

TABLE 3.5: Wood SUP2Ly aa,d Demd in 1994

I GROWINC STOCK PLUS NA1 06 C1T. FOIEST LAND & FOR. aS. IN 1994 3. CUSTONARY FOREST AND FOEST RESEIEV LAND AFTER 1994 HARVEST

(Thougand s3) (Thousand hectres)

FOREST NORTH CENT. SOUTN NORTH CENT. SOUtHCATEGOIY REGION REGION RE6IOi TOTAL REGION RECGI REGION TOTAL

Custosary L. 1S9525 26314 0 225839 C. INA. DEF. 5 94 153Foret Rts. 23602 317S2 27783 83337

F.R. M. DEF. 42 42

2. NAIIEST IN 1"42SaCUST LD. OUT Of TIBER IN SOWTH ,ES. CUS. F.L. 160 641 0 2281

(Thousand u3) RES. F. US. L. 235 392 301 928

FOREST NOTH CENT. SOUTHCATEGOry REGION REGION REGION TOTAL 4. INChENTAL PLANTATION A1E

Custosary L. 549 2938 -0 3487 (thouslnd hotaru)Forest n. 26 392 3718 4392

ALL HEV PLAT. 1.8 13.2 27.0 42.0TOTAL IIDI. 831 3530 3718 7t80

Gow. plant. 106 237 237 50

Plantation on estatesTob. et. 42 64 23 129Te estates 0 0 189 18

Subtotal 42 64 212 319

Other priw. plantationsLoc, author. 7 1O 20 7SCFPS 0 0 95 . 95IlLt " 0 0 so so

Subtotal 7 i1 t6 162

New PlaItat. 12 W 11 2

TOTAL PLANT. 168 39 1 1361

TOT. HAREST 9m 3729 4512 9241

CUST. RAI 1640 560 47 2248

FOR. PS. AI 282 392 343 V.0

CUST. D1D5 1090.6 -2377.7 0 -1287

FOR. S. 003N 0 0 -3375 -3375

-51 -U 3

?aen. 26 of 3

TAMA 3.6: VWoo Supply and Dmm in 1995

1. GR0V1U STOCI PLUS RAI S Mt. rEw LA ii 1 F. U. to 19" 3. CI4IOB&9V UIEIt AS FPE1t AIURR LAO AFTER 19s NMVt1T

[thou"5 631 (hivwsAd becorNpI

FOEST WITN CMit. =RN ITN Cli. WHCATEIST 11615 IECIO( IEClO TOTAL 31610 K1io fC101 1011t

CuSteuy L. 1950 2782 0 223 C. WA. K. 62 0 62Fornt in. 23802 31712 2091I 1645

F.S. WA. IV. 43 432. HilEST 19I5

mU. Cli. F.L. 1640 1 0 2219

M1S.F.L.L. 235 592 25 aSrOusT m Citi. MWGcUE RiCKI 3110 ORUIN tMAL

4. ImM AL PEATION aaCuutoia?| L. 165 2974 40 33Foret A. 2 3 316 450 a lties

T01TA IN036. 647 =6 3716 ?92A l. KPW. 2.1 15.4 S1.5 49.0

ki. pint. 106 237 23

pliatatlus on iuteTe. "t. 42 64 23 129Tu a stat 0 0 1in 169

suStoul 42 64 21 319

ohf priv. plantatioLoe. aitw. 7 10 20 VSCM' 0 0 U 1

aIiLU 1 10 soi 16

kV Pl1at. 1t 13 2,M 43

TOTAL PLNT. 174 41 am4 131

10T. VAMM 121 30 465 94

Clii. HAl 160 513 0 2153

FO. I. I 2 392 301 975

CM. Km 1075 -2461 0 -135

Va. i. no 0 0 -3411 -3415

- 52 -AM= 3F?ae 27 of 36

TAUSE 3.7: Wood SupPlY ad -Demid in 1996

I. GlOVINS STOtl PLUS AIU P VUT. FORST LA A PI. 33. to 196 3. CUSIPOY FPINESt AC FOIST hulE LAND AFTU 199 HV1ESI

(Tmmd .3) (Tiamm heolte)

FIOES? NinT CUT. SOWTI MTNTH CENT. souTHCITEQCON SfttOl NEOU 1E161 TOTAL IECtOII IECIOII 6ON TOYAL

CugCary L. 1491 2118 0 220410 C. M. DIEf. i 0Fornt on. 232 317S2 1742 7304?

f.l. IIA. DU. 44 442. HAlVltS? 111996

IfS. CU9. F.L. 160 515 0 2155(Thunm" .31

Ets. .1S. L. . 25 32 214 842PUtES? NINT CENT. onCaTECONT REGioN 62Q If N Ct IIti TOTAL

4. IEENIAL PLNATION ANDCufthgy L. 53 0u 40 3617Fungt on. 22 3 3763 4437 (Th*mm hetnes)

TOTAL iNOI. U6S 3426 3763 N0U LL V PLOT. 2.4 17.6 36.0 56.0

lOw. plait. 106 23 237 5

PlItatloa on estaeT'0. at. 42 64 23 *2To&ashate, 0 0 189 In9

subtotal 42 6 2 3

Othun pta,. plsatatamL@C. JUtflV. 7 10 a2 37ICfl,' 0 0 95 9£TL*80 0 0 5

stttitte O 1 Suolsl 7 1, 165 162

in FlAtat. 21 1 3 4

TOtAL PLAT. 117 46 9 1571

TOT. NAIS96 1042 3I 2 92

CUP. HAI 160 46 0 2106

c0g*. U. 2M 2 M 52 25 i2

C Ki. mI 105? -2Sl1 0 -1514

:0N. #. _ 0 .0 -350 -305

-53 3.age 28 of 36

TABLE 3.8: Wood SUpply and Demd in 1997

.. GR6OIN6 STOCK PLUS KAI 05 CUt. FOREST LAND I FOR. RS. IN 1997 3. CUSTOMARY FOREST AND FOIEST RESERVE LAND AFTER 1997 HARVE:

ITh@ussnd dl {T TOusand heetares)

FOREST NORTH CENT. SOUTH NORTH CENT. THCATEGORY REGION REGION REGION TOTAL REGION REGION REGION TOTAL

Customry L. 199473 16457 0 217929 C. IHA. DEf. 67 -O 67Forest Res. 23802 317S2 13654 69409

f.R. t4HA. DEf. 45 452. HARVEST INt 1997

RES. CUS. F.L. 140 448 0 2018

RES. f. S. L. 235 392 169 797fOQE8T NO- CENt T". SOUTHCATEGORY REGION REGION REGION TOTAL

4. INCENMENTAL PLANTATION AREACustOsary 1. 601 30N9 -0 3100Forest Res. 282, 392 3610 *4" (Thound hfcthruJ

TOTAL INDIS. 8 3491 3110 6184 ALL NEV PLANT. 2.7 19.6 40.5 63.0

Bow. plant. 106 237 237 510

Plantations on estate$Tob. st. 42 64 23 129nea estat 0 0 169 I"6

subtotal 42 64 212 319

Other priw. plantattionLog. author. 7 10 20 37.CFPP 0 0ITL" 0 0 so

Subtotal 7- IS la 162

Nu Plantat. 24 176 as MO

TOTAL PLANT. 1'0 487 94 141

TOT. HARVEST97 1063 3977 411 25

CUST. Al 1640 412 0 2052

FOR. RS. KAI 262 392 214 I"

CUST. 0ION 1039 -2686 0 -1640

FOR. iS. RSiD 0 0 -3596 -359%

-54 - 5AM 3Page 29 of 36

TABLE 3.9: Wood Supply and Demand in 1998

;. GRvING STOCK PLUS "Al ON MT. FOREST LAND & FOR. RS. 1i 1990 3. CUSTONARY FOREST AND FOREST RESERVE LAND AFTER 1998 MARvEST

(Thousand e53 (Thousand hotaren)

FOREST NORTH CENT. SOUTH NORTH CENT. SOUTHCATEGORY REGION REGION REGION TOTAL REGION REGION REGION TOTAL

Custourgy L. 199454 15601 0 215055 C. -NA. DEF. 70 -O 70Forest Res. 23802 31752 10123 65677

F.R. NHA. DEF. 46 462. HARVEST IN 191O

RES. CUS. F.L. 1640 378 0 2018[Thousand .3)

RES. F. OS. L. 235 392 123 750FOREST N NORTH CENT. SOUTHCATEGORY RE6ION REGION REGION TOTAL

4. INCREMENTAL PLANTATION AREACutosry L. 622 3156 0 3777Forest Rn. 282 392 3867 4541 (Thound hmctaru

TOTAL INDIG. 904 3548 3867 8318 ALL WEV PLANT. 3.0 22.0 45.0 70.0

Gov. plant. 106 237 237 50

Fi44at1eons of estatesr- o. st. 42 64 23 129T0.4 sttstls 0 0 189 189

Subtotal 42 (A 212 319

Other priv. planttau"sLoc. authv . 7 10 20 37BCFPI 0 0 95 1ITL82 0 0 50 50

Subtotal 7 . 10 1s 12

5ew Plantat. 27 15 465 40

TOTAL PLANT. 183 W 1919 1711

TOT. HARVEST" 1087 41 406 10029

CUST. NI 1640 359 0 19"

FOR. IS. AI 282 3 169 84

CUST. bRDN 1018 -2797 0 -1779

FOR. RS. DRUN 0 0 -3697 -3697

AID= 3Page 30 of 36

TABLE 3.10: Wood Supply and Demad in 1999

1. GROWING STOCK PLUS MAI Oli CST. FOREST LIND I FOR. RS. IN 1999 3. CuSTOMNRY FOREST AND FOREST ICIUVE LAND AFTER 1999 4ARVES

(Thousand 1 hThsousand setaros

FOREST NORTH CENT. SOUTH NORTH CENT. SOUTHCATEGORY REGION RECION REGION TOTAL REGION REGION REGION TOTAL

Customaty L. 199434 12637 0 212071 C. NHA. DEF. 73 -O 73Forest Res. 23802 317S2 6278 61832

F.R. RNA. DEF. 48 482. HARVEST IN 1999

RES. CUS. F.L. 1640 305 0 1945(Thousand ]3J

RES. F. IS. L. 235 392 76 703FOREST NORTH CENT. SOUTHCATECGOY REGION REGION RECION TOTAL

4. tINCREENTAL PLANTATION IARECustowy L. 641 3216 -0 3857Foret In. 282 392 3926 4600 [Thousd hctatus

TOTAL INDIG. 923 3608 3926 857 ALL NEV PLANT. 3.3 24.2 49.5 77.0

6ev. plant. 106 237 237 SW

Plantation on etateToo. at. 42 64 23 129Te estate 0 0 1i 1i9

subtotal 42 64 212 319

Other Prlv. plantationLoc. autho. 7 tO 20 37SCFPB 0 Q , " 95ITLt" 0 0 So as

Subtotal i 10 15 15

Nw Plantat. 30 23 41 780

TOTAL PLANT. 186 .NJ 17U

TOT. NRVEST" 1109 4139 4990 10238

CUSt. HI! 14 303 0 1942

FO. IS. AIU 22 392 123 797

CUST. DON9 999 -2913 0 -1915

FO13.0D51 0 0 -3803 -3603

-56 - AEN 3Page 31 of 36

TABLE 3. 1 1: Wood SUpP1V and Demand in 2000

. GR. ST PLUS MAI ON CUST. FN. LO., FOR. IS. I SOV. PL. 14 2000

(Thousand c31

FOREST NOlTH CENT. SOUTHCATEGORY REGION REGION REGION TOTAL

Custoury L. 199415 9549 0 208964Forest Res. 23802 31752 2322 S7876

2. HiARVEST IN 2000'33CUST. LO. OUT F TINER I FOR. RS. ALHOST IN SOUTH

[ThNhund 3)

FOREST NORTH CENT. SOUTHCATEGORY REGION REGION RE6101 TOTAL

Custmnry L. 660 3279 0 3939Fornt Rts. 282 392 3989 4663 3. CUSTOr FOREST AID FREST RESERVE LAND AFTER 2000 HARVEST

TOTAL 11D16. 945 3671 398 6602 (Thoad heotau

Gov. pant. 106 237 237 8 NORTH CENT, SOUT

RlE610N RIEGIOI REGIO1 TOTALPlantatlons on estatesTob. est. 42 64 25 129 C. rMA. 0F. 76 .0 76Tea estate O 0 189 189

F.e. mA DIEF *9 *9Subtotal 42 64 212 319

RES. CUS. F.L. 164 230 0 1869Other prtv. plantation,Loc. author. I 1o 20 R RES f. OS. L. 235 392 27 654BC F' 0 0 95 95ItLNI 0 0 50 50

4. PLOTATION AMA REWINED TO COVER IE TMONUNSubtotal 7 10 14,5 lot

303.472 391.303 695Rev Plantat. 33 249 40 B

TOTAL PLANT. 16 S- 1to IU

TOT. HARVESTOO 1131 4224 509 10453

CUST. NAI 1640 244 0 16O

FOR. IS. RAI 202 39? 76 750

C0ST. CDIN 979 -50 0 -2055

FOR. IS. DRN 0 0 -3913 -3913

ADNU 357 -Page 32 of 36

APPEDIX 4: Economic Valuation Data

TABLE 4.1: Valuation AssUptions

a) hud rnt m A utaindi* rim daire frcm rimitBl of

hff%lt projetfaw per ff to 1mLU9mCCTJmau il miiie.

n OA W 03 4Ic

Yr .t99 11 1992 1993 14 199 1gn 199 1E 99 am0........................... ...............................................................................................

9SUn a. 2S W 313 3 B0 3.15 M SM 3697 3

Iw:tgal R. 12 Z73 2170M 2Z ZS77 3W 2 370 5 25 23 30........ ............ __. _..... ........................... _... .................

RTIAL 9S 5110 549 5 5752 5875 6074 631 63 6715 694.

b) Snw pric for 1990 wilt emAW atK 5.61 jS pe wdste of pita rum

- of Jtiy 19M, owwat to m tiLd.

C) Rwatt ww%s of Om farq. fta ftow of,m mitt b bin refartirg Wa m Sw Omtilf ftro fbi tc be sAatiro

*D A=air ptmuafcm mof 10 diAv/w wdWd tkire Vi rAtes of f fto WMR.wl forckaddknin wr 2300 m foWtt:

Sm'. it. I3

CAM. A. X3W..................

=tAL dw

Vim so tot ov 0mpd to cw viis dmdeimAd be n'fattl:

tVd

...........................

SpAh. R. 31 SMD

C.w. a. m 4,..... ........... ---------

AL. 695 IOD.C

reultIr In a NOl d rmtfrdy 70,00 ML

558- AM= 3

Page 33 of 36

TABLE 4.1 Continued

*) Am 1 ta arms Is p t Ii in lt Witpwftiar. Fro 1WO to 2D irct1, this ispxlmswy 61 timrd hwtar to bep&ef avml,y. This wilt be bW m d. bet%nal Saothum ̂ d curast egI am i, torfialt rupinsu sas foallo:

tCumwd hcotaris r

Sahu. A. 36 56S3D

CAw. R. 28 43.674...... ,..........

TOTAL 64 MM

f) it wiLi be in.ad t 50.OM of Ute tifamt0cun to bewd for pint erioual.

IN=e io iuu " an uwuts frum filewiM d., fe 1u' d for fasnre .auLd be asfollo:

tlhsw hctw

yar 199 199 1 ¶ 1995 199 ¶995 19 ¶9 1¶99 19W 2000................................ 0.................................

smmn A. 49 51 52 54 | a Z2 22 22 22 22

ntra R. a a v 29 30 31 w 34 3 3 38

TOTAL 74 7? 79 U Os 52 54 56 S7 S 60

!amrdfrgtyflue ftaAdr tdAe dna mAsti1eieforesd hostaiwm awv td to f*Mr.

j d~~~~~Moi hwte

Yr_ 19 1991 199 1993 19 195 19 199 19 199 9 m.................................................................................................................SmAwu R. 49 100 152 2as u 295 316 DO 39 381 4u

cwutuR. 25 51 71 107 36 17 ¶9W 2 ag 3D 342............................................................... ................................................................

TTAL 76 151 z30 .312 0 461 s1s 570 62 6w. WA

g) mf asteai t miAW at1 1000 Au.bond aw hbif of co ~eu in UMIEW a tprimc Jn dr-1Wd frum fipm e. a a Z.This alLm for a t cast .iWh is applsa tslvacm hof f Vs in 1w T pimatians wdstatt in 80 to t* aR of loer plan0rg

cost of inUstI 'dr.

59 UAN 3Page 34 of 36

TABLE 4.1 Continued

h) RodI rat wits of wriaAtl uW. a gsinyielo IO kgft witl b _md (info.

4fd by Jth idcp). Priam fw miza in1"RA deuid htm ministry of Agriutuw, perih l i *p It o.a CM/k. An oum iWofto of IS.OI witll h mwifad ircnsi.

1) hpgdidr scteslitte, wmian iill axr antfmted lac Utat is rat fsnic Akm sbjwtto oria la isafols:

1wr I_O 11 1992 16 19 1992 ¶99 17 1990 199" aom

StuAhaM R. 49 51 52 54 68 22 22 22 22 22 22

raeel A. 7S 2 Z 3D 31 32 3. 5 37 3................... ............ .... ....... ..... ...... ....

TOTAL 74 77 go U 9 52 56 55 57 5 60

J) md mi mo1ptf, In Wm 7.5 of WS , it isu md On ach hscUre aLbjet to .rion mittaffect 0.5 hwcta of WiAutul WM cwirge a4.at dltirw in uvAl miz# pr*tivity. Trhfore

kith an wnAt pain yield f 1000 kaft,utl fer tlvlty lm mXt km t

*V W hsv abject to ermimi At a pie ofd, / 8w l _tst wllt K 5.2 w

h wto obJect to ormim

Or.awd hwwe

Yw 1990 19o 1 1992 1S9B 1992 195 19M 1W 1990 19M 2M10.................................................................................................................

SasUm R. 49 100 1S2 0 27 295 316 3D 59 381 a

0uul R. as 51 75 10? 1a 1 In9 22 M 306 32........................ 74 .......... 151*e............... 30.... 312 409 461 515 5 ..... ..... 74..DhxA K4 151 M 312 W 461 515 S7 62 6% 7

-60 - ANU 3

Pase 35 of 36

TABLE 4.2: NPV Calculation for South

1fi WLME AMLYSISt

1. Snaa mian

Ob.awd obld am"

Y_ 19 19P1 1992 1W 19W 19W5 M6 1997 198 19W 09

Brafits:

uWl hw t 1615 17117.63 176 18171.63 190Z.72 19248.18 19749.61 22.72 2.63 214.945 5.09Crop vlw 1911 3051 SW 79M5 1067 114 1Z. 13163 1S 01 14WO 15M

TOTAL EFITS 1Ua MM DC6 M67 2M7M 3f736 3274 0 5A 34 36M9 377D

Ixd f 308. 3W4 5864 381 56. SUM 3584 358= 564 34 356(4 3S0SBWira tl 56 S1T iM IO6 14 1531 1613 1£ 11 IM 1

TOTAL CSM 36099 36362 36 36910 37M 37376 3741 37599 37711 37M3 370

lET IEFITS -17573 -1S6 -13092 -10713 *759% -62 *56K -4174 2P72 -155 -2D1

PROM wLIm OFlEr WITS:

X of CDPWV a 5s a* 7W 1.6:wva 1M a .OW.? 1.IZIfV O s .. Wam711.9 0.A

-61 ANN- 3

Page 36 of 36

TABLE 4.3: NPY Calculation for Center

2. Cswrt rmwg

vow 9 1t 19g. 19W 19w 19w 19W 199 a

I hw t 1111 1186 12 129 IW 1S6 1V4 1513S 1SM9 1619 17101Ca %ite 975 1 30 V2 4154 9 64% 7142 908 WU13 11 1W19

wT^AL WITS 121 175 1524 IW 187M UP 27 2 1a W172 MM 19

Ca:

W np&s:. 2W 2m 77W 2 2m719 2r77 2719 Z7 27M19 2792 29 26awfr.an IN0 5 4% 1 70 7 86 ICU 1 In 1578 171M

7WAL CS 271 W Im 21 198 2 59 a 299 29181 n3m7N 25

W EMITS -IRM wtn 120 -IU9 -92 09 -169 -W1 -MOB -1115 m1

FEWIVr WLE OF

S of CDeV a s a -752 1.71PV a IC% a -61m I*A

Iv a S a -a671 O.S

3. TWALM.T OF DEFWTATICoS of aP

a s6 * -1 2 3.3a lB S -s 2a Is * Ia A

*:m .

- 62 -Annex 4

Page 1 of a

METHODOLOGICAL NOTE ON ESTIMATION OF WATER EXTRACTION RATE

1. This annex provides the background analysis for the discussionin Chapter IV of the main report on the extraction rate of waterresources.

I. Total Water SuDply

Rainfall

2. Malawi's climate is influenced by its large lake, high plateausand rugged relief. Rainfall is measured at more than 500 stations. Therainfall is seasonal from November to March in the south extending toApril and May in the center and north. Tropical cyclones occur but notfrequently. Malawi is in the high rainfall zone of Africa, with a meanannual rainfall of 1,037 mm. The rainfall/elevation distribution is asfollowst 63 percent of the country receives 650-1,000 mm, 17 percentreceives 1,000-1,200 mm, and 20 percent receives more than 1,200 mm.

3. The windward slopes of Mount Mulanje, the Shire highlands,Zomba Plateau, and the eastern slopes of the Viphya and Nyika Plateausexperience very high rainfall. The lakeshore near Nkhotakota, NkhataBay and Chintheche, where the lakeshore is set against the direction ofthe wind, are also subject to heavy annual rainfall. The remaining highplateaus are climatically defined as semi-arid. The southern lakeshoreand the Shire Valley are classified as arid.

Surface Water

4. Malawi has a broad network of river systems with substantialsurface water resources. Most of the rivers, with the exception of theShire River, have a seasonal pattern of flow. The flow begins to risein November, following the rains, with high flows occurring mainly fromJanuary to March. In April through May, the flow begins to recede.June to October are the driest months with practically no rainfall.Many of the small tributaries of the main rivers in the plateau areasand in the upper reaches of the main rivers are seasonal. Most of theShire tributaries and the streams flowing towards the Chilwa basin, too,are seasonal. All lakeshore rivers are perennial.

5. The Shire River is the only outlet from Lake Malawi. Theextent of flow in the Shire at the outlet at Mangochi is governed by thelake levels. The contribution of water to the Shire from catchmentsdownstream is small in relation to amounts of outflow from the lake.

6. The hydrology section of the Water Resources Branch of theDepartment of Water maintains a network of river gauging stations

Annez 4Page 2 of 8

- 63 -

covering all the river systems in Malawi. Water levels are observedtwice a day and discharge records cover low and high flow seasons.Processing of these records, analysis and evaluation of the basic datawere part of the National Water Resources Master Plan Project completedin 1986.

7. Table 1 gives details of rainfall, runoff and percentage ofrunoff for the 17 major watersheds of Malawi. The average annual runofffor the whole country is 19Z of the average annual rainfall. Along thelakeshore the runoff is higher. The North Rumphi river, too, has a highaverage runoff factor (33.1Z) as does the Ruo watershed. The totalrunoff can be expressed as 196 mm. or as 586 cu.m. per second.

TABLE 1: RIVER BASINS OF MALAWI, MEAN ANNUAL RAINFALL, AND RUNOFF…-- - - -- - - - -- - - - - -- - - - -- - - - - -- - - - -- - - - _

WRA/River Basin Catchment Rainfall Runoff 2Area mm mm m3/s Runoff

1 Shire 18,945 902 137 82 15.22 Lake Chilwa 4.981 1,053 213 34 20.23 South West

Lakeshore 4,958 851 169 27 19.94 Linthipe 8,641 864 151 41 15.75 Bua 10,654 1,032 103 35 10.06 Dwangwa 7,768 902 109 27 12.17 South Rukuru 11,993 873 115 44 13.2

North Rumphi 712 1,530 674 15 44.18 North Rukuru 2,091 970 252 17 26.09 Lufira 1,790 1,391 244 14 17.5

Songwe 1,890 1,601 327 20 20.410 South East Lake

Shore 1,540 887 201 10 22.711 Lake Chiuta 2,462 1,135 247 19 21.812 Likoma Island 19 1,121 280 - -13 Chisumulo Island 3 1,121 280 - -14 Ruo 3,949 1,373 538 60 39.215 Nkhotakota

Lakeshore 4,949 1,399 260 41 18.616 Nkhata Bay

Lakeshore 5,458 1,438 461 80 32.117 Raronga Lakeshore 1,928 1,028 361 22 35.1

TOTAL 94,276 1,037 196 588 18.9… …__------------------------------------------------------

SOURCE: National Water Resources Master Plan, 1986

Annex 4Page 3 of 8

- 64 -

Groundwater

8. The greater part of the country is underlain by crystallinemetamorphic and igneous rocks referred to as the Basement Complex.Younger consolidated rocks are limited to minor occurrences of Karoosedimentary and volcanic rocks at the northern and southern tips of thecountry. The most imposing structural feature is the Rift Valleyoccupied by Lake Malawi and the Shire River. Variable thicknessquaternary sediments occur along the lakeshore, around Lake Chilwa andin the Lower Shire Valley. The Rift Valley dominates the topography,and the major physiographic divisions (uplands, plateau, escarpment,alluvial plains) define the occurrenc- of groundwater.

9. There are two main aquifers: (i) the basement aquifer which isextensive but low yielding; and (ii) the alluvial aquifers that arehigher yielding but limited to the lakeshore plains and the ShireValley. The weathered zone in the basement complex is generally 15 to30 meters thick and less towards the escarpment. It is found usually 5-20 meters below the ground in most areas. The yield is usually only 1-2liters per second in the plains and on the escarpment the yields areeven lower.

10. The depth of water in the alluvial aquifers varies but they aregenerally deeper with higher yields. Yields of up to 15 liters persecond were found in the alluvial plains along the Salima Lakeshore,Bwanje Valley and the Lower Shire Valley.

11. Groundwater levels have been monitored with autographicrecorders since 1980. These give the seasonal fluctuations of the waterlevels, which could contribute to an evaluation of changes in the volumeof groundwater. The available data has indicated that the normalseasonal fluctuations are in the range of im - 5m in the weatheredbasement aquifers and lm - 3m in the alluvial aquifers. The recordsfurther indicate that there is no evidence of declining levels over thepast 10 years in any of the aquifers. This indicates that the extractionis still lower than the recharge.

12. Estimates of the recharge of the aquifers have been made. Onthe basis of hydrological considerations the annual recharge wasestimated at 15 mm - 80 mm to basement aquifers and 3 mm - 80 mm to thealluvial aquifers. In the alluvial aquifers recharge also occursthrough seepage from the perennial river beds.

II. IMPROVED WATER SUPPLY

Urban Water SuPPly

13. The Blantyre Water Board is responsible for supplying water tothe City of Blantyre and its surrounding areas, which currently cover

Annex 4Page 4 o, 8

_ 65 -

about 38,700 ha. It serves an estimated population of about 340,000people. The main source of water supply is the Shire River about 40 km

from the city. The water is pumped after treatment to storagereservoirs for distribution. Other sources of water are minor. Theseare the Hynde and Mudi dams and reservoirs located in the Limbe area.The Blantyre Water Board presently has the capacity to supply 60,000 cu.m. per day, which is likely to meet the demand for water uxitil 1992-93.

14. The Lilongwe Water Board draws water from the Kamuzu Dam on the

Lilongwe River. The present capacity is 29,000 cu. m. per day to apopulation ,f 160,000 people.

Smaller Urban Schemes

15. Urban water supply to the siX main district centers (Karonga,Hzuzu, Kasungu. Ntcheu, Liwonde and Zomba) is the responsibility of theDepartment of Water at the Ministry of Works. The total productioncapacity of these schemes is 10,600 cu. m. per day supplying a

population of 115,000 people.

16. The water supply to the remaining semi-urban centers is alsothe responsibility of the Department of Water. These schemes have beenin operation with varying levels of service. At present these schemesproduce about 16,000 cu.m. per day supplying a population of about185,000 people.

17. Table 2 summarizes service coverage for the urban population.

TABLE 2: ESTIMATE OF URBAN POPULATION SERVED (1989)

Area Total Population Percent WaterPopulation Served Served Produced

cu.m/day

Blantyre 364,000 340,000 93 60,000Lilongwe 303,000 160,000 53 29,000District Centera 230,000 115,000 50 10,600Semi Urban Centers 370,000 185,000 50 16,000

TOTAL 1,267,000 800.000 63 115,600SOURCE:--Water--Departme-t-___ _ _

SOURCE: Water Department

Annex 4Page 5 of 8

- 66 -

Rural Water Su121l

18. In rural areas two basic water resources prevail: (i) surfacewater supplied by gravity through a piped system to communal waterpoints; and (ii) groundwater supplied from shallow dug-wells and throughboreholes equipped with handpumps. The rural water supply sub-sector isthe responsibility of the Department of Water. A considerable amount ofappropriate technology has been incorporated in system design andconsiderable effort has been devoted to encouraging communityinvolvement in planning, implementing and maintaining the systems. Therural piped schemes are under the responsibility of the Rural PipedWater Supply Section in the Water Supply Branch, whereas theborehole/well schemes come under the Groundwater Section in the WaterResources Branch.

19. A total of 55 piped gravity schemes have been completedproviding water to approximately 1.24 million people. With only a fewexceptions, the water is untreated. No charge is levied for the water,but the beneficiary communities are expected to organize themselves intocovmuttees to provide self-help labor inputs, local constructionmaterials, and long-term maintenance services. On a country-wide basisit can be found that the average service level for the piped ruralschemes is 150 people per tap, equivalent to 20-25 families.

20. Development of groundwater supplies for the rural populationdates back to the 1930s, when boreholes and open dug wells were providedin rural areas. It is estimated that there are about 9,000 boreholesand 4,000 dug wells, most of which are equipped with handpumps.However, despite substantial investment of manpower and financialresources in maintenance, it is estimated that 302 to 402 of these unitsare out of order at any given time. It is assumed that each boreholewith handpump serves 250 people and each shallow well handpump serves125.

21. The estimated rural population served through gro-mndwater isgiven in Table 3.

TABLE 3: ESTIMATED RURAL POPULATION SERVED BY GROUNDWATERe___________0_0___0______________0_________0_n_____________________

Groundwater Scheme Estimated Populatione------------------------------------e--_---------------__---------

Boreholes with handpumps 1,290,000Boreholes with motor pumps 170,000Protected shallow wells 400,000

Total 1,860,000

SOURCE: Water Department

Annex 4Page 6 of 8

- 67 -

III. WATER DEMAND

Unit Demande

22. The unit consumption figures used for planning and designpurposes in the domestic sector are shown in Table 4. The correspondingfigures for the commercial, industrial and institutional sectors arepresented in Table 5.

TABLE 4: UNIT CONSUMPTION - DOMESTIC SECTOR…------------------------------------------------------------__---

Housing Category Unit Consumption (l/cld)

Traditional housing 25Permanent housing:

- High density 75

- Medium density 125

- Low density 200

SOURCE: Water Department

TABLE 5: UNIT CONSUMPTION - NON-DOMESTIC SECTOR

User Category Unit Consumption (l/p/d)

Rest House 200Bar/restaurant as housing categoriesMarket 2.5 cu.mShope as housing categoriesIndustry differentiated demandHealth institutions:

- out-patients 10- in-patients 200

Education institutions:- non-borders 10- borders 150

Administrations- offices 30- staff housing as housing categories

SOURCE ------------ Wae Department------------------____SOURCE: Water Department

Annex 4Page 7 of 8

- 68 -

Total Domestic Demand

23. The future water demand depends on many factors. Assumptionsmust be made as to the future population growth- rates, rates ofdevelopment of the urban and semi-urban centers, development of commerceand industry, shifts in per capita water consumption with changes in thestandard of living and distribution of water points, installation ofwater-borne sewage systems, water supply efficiency and other factors.For example, in studies conducted by the Center for Social Research ofthe University of Malawi it was found that per capita water consumptionin rural areas doubles from 20 l/p/d to 40 l/p/d when individual homesare connected. This may double again when homes are connected to septictanks and a sewage system is installed.

24. The National Water Resources Master Plan has attempted toestimate the future domestic water demand for Malawi. Tables 6 and 7are based on their estimates and were amended to extend the time horizonto the year 2010. It is seen that the total demand for year 2000 isestimated to be 737,000 cu.m. per day or 269 MCM/yr, and the totaldemand for the year 2010 is estimated to be 1,567,200 cu.m. per day or572 MCM/yr.

TABLE 6: TOTAL DOMESTIC WATER DEMAND - 2000…--------------------------------------------------------------------

Population Demand Demandper capita per capital/pld cu.m/day

…_________0___________- ____________________________________________URBAN

Blantyre 853,000 200 170,600Lilongwe 722,000 200 144,400Regional Center 200,000 200 40,000Sub Regional Centers 204,000 200 41,000District/Main Centers 293,000 130 38,100Rural Market Centers 363,000 110 39,900

Total Urban 2,635,000 180 474,000RURAL

Gravity Schemes 2,250,000 36 81,000Groundwater 6,770,000 27 183,000

Total Rural 9,020,000 29 264,000

TOTAL WATER DEMAND 11,655,000 63 738,000…__------------------------------------------------------------------

SOURCE: National Water Resources Master Plan, 1986; Staff Estimates

Annex 4Page 8 of 8

- 69 -

TABLE 7: TOTAL DOMESTIC WATER DEMAND - 2010

Population Demand Demandper capita per capital/p/d cu.m/day

URBANBlantyre 1,960,000 250 490,000Lilongwe 1,660,000 250 415,000Regional Center 250,000 225 56,000Sub Regional Centers 260,000 225 58,500District/Main Centers 360,000 150 54,000Rural Market Centers 450,000 110 50,500

Total Urban 4,940,000 227 1,123,000RURAL

Gravity Schemes 3,250,000 48 156,000Groundwater 8,000,000 36 288,000

Total Rural 11,250,000 39 444,000

TOTAL WATER DEMAND 16,190,000 97 1,567,000…---------------------------------------------------------------__--

SOURCE: National Watet Resources Master Plan, 1986; Staff Estimates

25. In addition to the consumptive use of water for domesticdemand, there is also demand for water for irrigation, estimated at 300MOK/year In 2010, and for animal use, estimated at 15 MCM/year in 2010.

Annex 5Paae 1 of 15

- 70 -

METHODOLOGICAL NOTE ON ESTIMATION OF AVERAGE INCREMENTAL COSTS IN WATER

1. This annex provides the background analysis for the discussionin Chapter IV of She main report on the average incremental costs (AIC)of urban and rural water supply systems. All data is presented inconstant 1990 Malawi Kwacha.

Rural Water Supply

2. The AIC of several piped rural water supply schemes have beencalculated based on available feasibility studies and design reports.The results of this analysis indicate a wide range of real resourcecosts for rural piped water. The feasibility studies used as base dataemployed a rarge of design criteria, on average representing between 27and 36 liters per capita per day. The detailed calculations areincluded in Appendix 1.

3. As might be expected the augmentation and rehabilitationschemes, ie. Mulanje West and Zomba East, show a lower cost per m3. TheSekwa Rural Piped Water Scheme includes treatment by slow sandfiltration. This is a new development in rural gravity fed rural watersystems as previously tapped catchments were more remote and did notpresent pollution problems. Estimates indicate that including treatmentin rural gravity schemes may increase costs as much as 50Z.

4. The AIC for Mpira-Balaka is high. Mpira-Balaka can beconsidered a unique project in terms of rural water supply as itincludes a number of components such as a dam, treatment plant (threetreatment works), considerable engineering design and constructionequipment not usually associated with rural water projects. It must benoted that 202 of the water demand is intended to be used by Balaka townand therefore the project can be categorized as a joint rural-urbanproject. Further, the initial appraisal reports of the project (Danida,1986) commented that the unit costs for Mpira-Balaka are "quite high...even if components normally not included in rural water schemes areexcluded dams, treatment works etc, the unit costs are stillapproximately twice the costs reported on for instance other ongoingprojects.'

5. AIC analyses were also undertaken for two borehole pumpheadtypes, the Climax and the Afridev. The detailed calculations areincluded in Appendix 2.

6. The AICs for both pumphead choices are similar. The AICreflects the initial high front loaded costs of drilling and installingthe casings, etc. The Climax has been shown to be a robust pump, givenits relatively high maintenance costs. The pumphead is expected to be

Annex 5Page 2 of 15

- 71 -

able to last up to 20 years with correct maintenance. The Afridev hasbenefitted from a low cost maintenance requirement as it has beendesigred to be community 'self-maintained". It-is a "light" pump withplastic components. This abrogates the need for heavy lifting equipmentfor pump maintenance and replacement of parts. For the purpose of theanalysis it is assumed the pumphead has a life of 10 years. Further, anallowance for the cost of community training for the Afridev pump, whichis part of the initial component of the project and is suggested willresult in much lower maintenance, has been estimated at 152 of theinitial capital cost.

Smaller Urban Water SUPglY

7. AIC analyses for several of the new projects to be undertakenin the small urban sector are set cut in Appendix 3.

Urban Water SuDPlY

8. An indicative AIC analysis is presented for the BWB and LWBtaking into account increases in water consumption as a result of thenew program of capital works for each authority. These are presented inAppendix 4.

AMUIX 1:t AT= IICRMI L COSTS RURAL PIPD mATER

h.* .: s0i RUL PUIUD VAIU SCa

ProJlct year 1 2 3 4 i t 1 3 9 1 11 t2 13 14 Is 1I 11 1t 1t 20

Capital l1tt 453 W 4 *.! I

Operatiliuoce 0 0II 12 2 a2 2 2 2 2 2

total 000'3 4 13 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2

Ns Oi'# 19.3 U.S 32.3 33.9 31.5 ll U.S 99.4 92.1 9.9 .W 9.5 9.3 101 103 I1 107 10 III 113

Ama" lacrutatl Cut: MR 1 w 3

lot 1.1312i 1.29

Awpra c lacuestal Cut: CWITIL

lO 112t121 1.2

raWe lrOtal Cutt MINIWICEo

102 0.01

12 *.01

USAu§ s£n alral for latfr tIc K It, Fial bsia _or ps t

Study ms allowd lfo 101 liKre8se In dm to 8llo for ppltion In- -a j1nip critlerl 3.6 11

.9~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

TIAIB 1.2: IJALAE VEST RURAL PIU VATUR SCHE

;Projct year 0 1 2 3 4 S 6 I7 9 10 11 12 13 14 13 1 17 1 19 20...... ......... ....... ........ ... .... _ . .- __............................. ... ... .__........ ........... --- -------------------

oCitatl Invasteut 2134 2461 213 0 '*

*~~~~~~~~~~~~~~~~ .1.

Oeration I aintmance 0 0 5 5 5. I 1 I 8 9 11 11 12 12 14 14 14 14 14 14

Total OO'sl 234 2461 2731 55? I I I 8a 11 12 12 12 14 14 1 14 14 14

13 (000'1I 1101 1121 1154 1182 1211 120 1249 1300 1331 1363 139m 1429 1463 149 1535 1535 IS35 1535 1535 135...... ........ ._.................. _. __.. .................. -... -- -.. -----------------------------------......

Average lncrntal Cost. 1T1OTA N pet 3

at 0.42lot 0.4812? 0.55

4verage Incretental Costs CPITAL

et 0.4110t 0.4812? 0.54

A"rage lncreaeotal Cost: NAINtENI C

6? 0.01101 ' 0.0112? 0.01

Potes:Feasibilitv Study for Rehabilitation and Auqeiatibn olt Piped later Supply ScwusJanuary 199

TABUK 1.3: Z0MM RUST ROMA PIPED VA&T SCHUl

Project year o 1 2 3 *:. 5 6 1 I I 10 11 12 13 14 15 16 1i 16 1It 2

Capital lnwustaet 3114 255 311 0 14

OperatlioAl#alntmnace 0 3 A A A I a to 10 to 13 13 54 14 16 16 16 l 16 I lb

Total oorsl 31142551311 A 6 'A3 I10 10 1013 1314 1416 16 1616 1616

113 lOWil 11,2 Mt2 121 12 1311 1543 131 us 1442 1476 1112 146 IN5 1623 166? 166? 166? 1662 1662 166?

Average laccemtal Catst TOIlt 5k w o3

32 ~~0.45lot 0.52121 0.54

Average Incregetal Costo CfPITAL

St 0.44aOl 0.5112! 0.1

Average tmcreeeota Costs MIIIIIIC

101 0.01lot 0.01

U12? 0.01

notes:Feasibility Study for Rebahilitatios and mpeotatioe of U Piped EM.'t %pply fcleoeJanuary aa9oAssuoption are for population in 1990 to be about 120,000 rising -. in 2005

TABLE 1.4: fPIR DAU RURAL PIPED ATER- gCM

'roject war 0 1 2 3 4 5 1 6 9 10 t 12 13 14 15 16 1? 11 19 20 21 22 23 24 23 26 27 28 29

:apital lovisteat 14310 26500 9540 2450 -00

1paratio 1a hiluuatie 0 0 11 2126 26 V ? 4 64 641 90 80 906 0 80 90 10 80 eo 0 0 08080 0 9 10'taI INK 0's3 143l0 26500 9 2U .''1 26 26 3? 4 1 49 4 64 3090 9 0 800 80 30309080 300 0 8080

a 10800'si I 0 0 1?m 2 2132 22 22 236 2413 252? 28 a21n 290523 2115 290 2m M2 a2 13o030 M0 30 M0 0 30300 300

%erng lotnc tal Costs IDIOL 0I Pr d3

al 2.20101 2.J4121 3.41

average lacrestal Cotta UOPITM.

81 2.26101 2.92122 3.45

vera Ineresal Costs NAINlIlCIE

el 0.02101 0.02122 0.02

tg t 8 J s a f 2 sv _ 2 3 2 - 2 2 2 _S2 : : WIatfst

tF fric, 3 lomt Fids AWraisal ort lpira-blata Rkral Pipd ar ProJectcttoer 1984

ust ftdes: base an caostrciona c t alabs, lhastry of lrks, Au A.5t

i9oi00oo IrigialI 194195 cost 9k 21 silliODs 1990 cost esisated at E53 silli| o.1"t72150 Informal stimatn indicate real cost Is Aot lliln, 19 Prices

:9n1 ,sn maintenance costs based on .5 of total coast ,osts rising to 1.S1U, year 14

AFFEJIt 2: AVERAG ICOSTS IE RU GRCIIMVATER

. * .~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~4

TAKE 2.01: _OEOU VIMV AID PUMP

. :1

Project Year 0 1 2 . 1 S 9 10 11 12 13 14 15 16 17 1t 19 20loreboleComnoity Traioing IgoDrilling I aterlals 15000Pumphead (Afradevl 2500 * 2500Recurrent s0 1 0 0 0 o so s 30 5 10 50 50o so o 0 s o50total 2039 50 50 50 50 30 50 SO 10 50 23 50 50 50 50 50 50 50 50 50 50 50

fl3 Iconsused per year) 2464 2464 2464 2U4 2464 2464 2464 2464 2464 2464 2464 2464 2464 2464 2464 2464 2464 2464 2464 2464

Average Incremental Cost: tOTAL 1K per a3

9! 0.92101 1.0512Z 1.16

4verage Increental Cost: CAPITAL

et 0.90101 1.03121 1.16

AetaQe Incremental Coatt KAINTENANCE

el 0.02101 0.02121 0.02

notes:

Ctarqifl S'roejchtue for Dwreholes, Mater bpartment, Ninistry of Morks

I ar.-tia lr!qviled Surtl 6oundvater ujoplty Project, Plan of Operatior '10

TLU 2.2: BOREOI VnTs CLDIA PFIDII

rojKt uar 0 1 2 3 4 S A I a 9 10 It 12 13 14 IS IA 17 18 19 20karebole ;kwilling I eaterials Is0toitad [Cuisual 50n0 25M0earrut 300 30N 3 N .3 300 300 30030 300 300 0 300 30030 03 300 300 300 300

Total 2Q00 0 3OII 300 W0S300 3W Ob00 3001003 300 300 300 30 300 30 300

N3 lcommal dp year) 24 2Wi 24 M24A 24 M 2 2W 24M 24M 264 2 244 24 24 244 24 24 2

larap latermual Cots TOTAL 1AK wr d3

OY 1.00 10 1.12122 1.25

Average Incrmetal Costs CAPITAL

IQt 1.00122 1.13

Avrage loueautal Cuts MIUTENmI IC

0 0.12

122 0.12

llotes:tharliag Slratelare fw loreos, later Iw rtubt, Nhistry of lfrksKarongs lotqrated Rbral 6Smauater Swil Projet, a o Od wation, src I"?

APPUIX 3: AVUME INCUMIAL CO?S 13 SUAMI3 3INI UAhI SUWL

TAIL! 3. 1: MASIMI VATER SOPIL

V~~~A* z i 1 i Y U 9 10 11 1? 13 14 13 1I 11 1I It N8 71 22 23 24 IS 5 21 27 2 29

:r,t~.,z.ipenaae *0 3 1 I I3If11 14 1419 1923 2323 23233 23 23 2323 23 23 732323 7!

IV~ fIcI 227 1912 7222 101IS I I. - I If If 14 14 19 19 7 23 23 23 23 23 23 23 23 23 23 23 23 2-3 23 23 7

I~IflflAsI 0 0 110 326 04*40 4W 5201640 N1*1*40 71080lIOSOUf 00 *III "0*0 *0300N30N 0 N

*'e',qe Ircfreentel Cost: TOTAL W per el

It 2.11

IN2 4.22

4.I9

V:Drn .IiC irre*ntaI Cost: FAINT(NANC

el 0.03

lOit (J.3 (II

voltin V%ploopept fund: *pgr,asaI reooft District Oster Swoply Phase 11 Project

I *~ (p't ; .a-zIe P t otIl 'sti of the groused project not of girace :,gg. See Aimex IS of the above dwoment.

v' ~¶r!'rr 4, 1 al riclial !onsf. these star lidinq scale reaching a 21ieimu el in year, 15 of the proged.

TAUS 3.2: VtZDW TR USUPPLY

ProJectyear 0 1 2 3 4: 5 6 t 8 9 1 11 t 2t 13 14 15 16 17 is 19 20 21 22 2n 24 2Z 26 2? 28 29

Capital lovestman 396 11172 13671 1

Operaloohfta &iutennce Q ^0 0 11 11 14 14 19 19 25 23 33 3 42 42 42 42 42 42 42 42 42 42 42 242 42 42 42

Total 1000sI 396I11M 21311 l10 11 11 14 14 19 19 25 25 33 33 42 42 42 42 42 42 42 42 42 42 42 42 q2 42 42 42

(130cr) 00 *O 0 o 6 136 1MIM 0" 111 #2 20 02 2100n 21300 310 3300 330330 JOO 330 3300 MD M330330 3300 330 M 3O0S 33

Average Incremental Cost: TOTL 111K pr dl

9t 1.20 - -

lot 1.30! 21 1.95

n.erage Increnesital Costi CAPITA.

St 1.18102 1.49128 1.84

Average Inctental Costs IlIhNE[NAIC[

DI 0.01102 0.01 o a

122 0.01

Notes:4frican De-ieloceent Fund Appraisal Report listricit later Sapply Phase 11 ProjKtJanuary l9t!

TABU 3.3: MIN DAY U M SULT

Project ear 0 a 2 3 4 5 6 7 a 9 to it 12 13 14 15 16 17 10 19 20

Capitaplt lavutnot 462 415 44 0

Dpuatio Ioifhlateaac. 0 0 1' 77 7 7 I 7 7 I 7 7 7 1 7 I 7

Total 10 'si 462 415 4 I 7 7 I 7 7 I I 1 7 7 7 7 7 7 7 7

f 100s1 0 0 0 4 13 29 4 64 3 104 104 104 104 104 104 104 104 104 104 104-.-.-...........................-- . .. - - - - ------------ - ----- - ------------ - ----------

Awrap locrotal Costs TOTAL.K per d3

lot 2.32122 2.84

4Avrage lncreaental Cost CAPIlTA

el 1.77101 2.20122 2.71

Averag Incrhantal Costa IINTH C

el 0.12:01 0.13

121 0.13

llotes:Preparation of Detailed esigns of the Pro,e lProvmts to Notke Bay Vatt Supply1 Deig ip wrt (Draft), Rinistry of Sorts, later Deportamet Deceeber I9,January 9O T0loies 6.3 and 6.6

TWA 3.*4: DK1I V*TU SUPL

; frajKt Ytr 0 I 2 3 4 6 9 10 11 1 113 14 15 16 11 1 19 20

Capital Iabsstsent 127 114 13 0

Oparatian lhintenance 0 0 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3

tal 1t0a 4s1 127 114 13 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3

H1 :OO's1 4 10 15 21 27 33 0 47 53 61 60 0 d 69 66 69 68 69 69..s...... ............ ............... ................................. . .. _ ...... _... . . . ...................... ... ..... - ---... -............---------------------------

Averaqe Incraental Cost: tOTAL

0.67* ;v ~~~~0.800

12t 0.95

Average lncrasntal Cost: CAPITAL

El 0.6210? ~0.15

121 0.99

4von;, lanreaeattl Costs NAINTENAEJIC

at 0.05 L10? ~0.05

122 0.05

Notes:F-eparatiao of Detailed Design of the propsed lspraomeots to Duasi later Supply, Dhsig Report If0raft), flinistry af Works, Niter Departeot December 398

Ma:.r.lenane t:sIs are ~tstgsteg it 1? oar wear.

r*IIZ 3.S: ZtEI& ftAU VAI UnIXL

ProJect "ar 0 1 2 3 4 5 6 I * 9 10 11 12 13 14 15 I1 11 13 It 20

Cotl lmut at t 243 219 24 S

Operatimo lalitmaae 0 0 5 a I I I 5 5 5 5 a I 5 5 I 5 5 5

Total I000's) 243 219t 24 5 I V I I I 5 5 5 5 5 55 5 5 5

N l .1) 2 3 5 6 9 10 12 13 1s 11 1a 11 11 1l 11 1? 11 17 17

aerp ilurmel Ents TOTAL e wri

ft 4.%lat 5.69In1 6.94

6:4.51

in s.s.

121 6.54

eraOp lcroemtat Costs Ul?MiN10t 0,33,

101 0.3912 0.40

llotes:Preparation of bthilud Nuip of ti propud lopovemts to tobo Plata Mar SMat l1, kslp Spar (Draft)Nlinistry of wts, ltr kWrtmt kcusbr 19 TaIln 6.3 aid 6.

Naintenace costs are estimated at 11 r year.

O J~ gu'iugn 5 w3.id aum - F P. lmq a PA" _ PM* Ps q PM 11 Yp _maq

p At or ap apw n. qa sumimm ow awuimf Pa

mapgIna 461161 E tvj ipm& 885 S15 pu mq analt.,

nfnSXC*4ltZUZla2WtCZ*f @I3Sfl

*~~~~~~~~~~~~~~~~~W n

'l DIN* U.* U

* mu qug~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .uw i....... 5ns

p uria n qIq pamw isas

IO fm IsU

Ila lif a Ila lilt n.u tIu m Ila dua u an nu mu Ima uan au aU m a a mana nim g maa mm "anal U 6 UK ui n. PPail ius ail liltfl ilsStS LtZu SitS a au amu am au an an au anim ac m an Dalu amg an am au an m. "WIN an au uno UVi 411 n wuW Iu.1I own%

* * 0 0 0 S G 0 6 0 I I I I 0* 0 S 0 S * 0 * 0 * I S I 0 S I S I 0* V W" Snoa_@ egoss e 9 *gI ,I a , g *I 9 I.a I,a ,*, *m.u wN u mu smib

a It a it it u It u a n 8 69 u a a a a a a a aa a n a a & 6 I I s niva I * t uVI"

z'uuns nvm Sven Kg ULW lvUWasm :rj lgismu

TABLt 4.2: LIAIE VAT SUPPLY

-s sew*errsssslleseseat||estsxnstse_ ;__Us _________________ r s

rgjetIts * 1 2 3 4 S l6l I i Se 1l a 83 147 1? 1S 12 219 321 2 21 N n 29 3031 3n 2 34 35..... _._ ........ _.... .. . . ._.

tCaital l s,ut M 1S111 U II66 I 3 * 0*0 0 e e * e e 0 6 Q 0 00000 0 0 0 0 e 0 0 a 0Otlw lsgtmt 2&3anl33112l121f U 6 I 6 0*0 * 0 0 I a 0 9 0 0 a 0 6 I 0 i 0 0 60 0 0 0 0 09 rtlwS lalmto 231 } 4 03 2 M 93e 1 im 12 1711 111U 111 l lil m Il 1713 l 111 11 Il Ills Ills Iia iam 1 11s6 111 1 s 111 1711e Ills 1713 71 1116 1113 1713 1113 17111813

_ tal 1e0,1 21119 14o 1M 3111 393 4113 U391 1t11 31711 1711117 Is llt 111 Il17 1713 ItU 11am 3l13 Il 113 1 1U Ir7 1713a11if IG Is iIJ0 1?0 171113 I712 I113 l lIl 7113

* I{MS) 1433 2412 Sill M31 S41392 612 IS N71 O 1113 35 OM m9 3 11a111151m5l of esgm n e m91 ane 5nml159am n 11 19 mlgm3ml1got m51 859138591

& ap Imutel ists IOt U A L r pd

31 .91lt e.n6in3 1.51m2 1.23

*'e'ep Iecreuel Costs WIll.32 .11

101 0.3III 3.01

U 0.20Ut .29

121 0.26

$Pi" 1190

If miugue water min, (C.-,p.t.o is 1910-9 adimi 3.a Appail 19eo Mb pouf og!XgJitsl costs to PerIl gotta cusueti, a s am Is Capital mitlion, Prejit Istit.mii of vine,,

qioteaase costs nsleai te at 3K .NPr .3

Annex 6Page 1 of 10

- 85 -

METHODOLOGICAL NOTE ON ESTIMATION OF VALUATION OF PROTECTED LAND

1. This annex provides the background analysis for the discussion inChapter V of the main report on the costs and benefits of protecting land in

national parks and reserves.

I. Review of Costs and Benefits of Protected Land

2. There are three main types of costs of lands gazetted for wildlifeprotection: (i) Cost of protected area management, including planning &

training, infrastructure development, and poaching control (this cost is so

low relative to other types of land management in Malawi that it canpractically be ignored); (ii) Cost of crop damage by marauding wildlife; and

(iii) Opportunity costs of foregone production from agriculture, wood, and

minerals. Of course, each of these alternative uses (benefits) also entail

capital and recurrent costs, such as management and training, infrastructure,and/or extension.

3. There are several types of benefits: (i) Existence value of wildanimals, biodiversity and ecosystem resilience in general, and areas of

special aesthetic beauty; (ii) Economic value of tourism; (iii) Sustainablehusbandry of wildlife for safari hunting and live exports, particularly sable,

roan, and cichlid fishes- (iv) Sustainable harvesting of wood for energy andconstruction; (v) Regional watershed management; (vi) Non-tourism, localizedtypes of wildlife utilization, such as nyala and crocodiles for meat & hides,bees for honey & beeswax, and local fisheries for consumption; and (vii)Plant biodiversity for indigenous use, such as plants for medicinal, fiber, or

food uses.

II. Review of Protected Areas in Malawi

4. Mwabvi is the on?y remaining area in Malawi which hosts blackrhino (perhaps as many as 6-:0), a seriously endangered species throughoutAfrica. In actuality, about 60 percent of the area that appears on maps as

Mwabvi Reserve was degazetted back in 1977 and is already available for

agriculture. Portions have been settled. Tourism (and infrastructure for it)

is currently minimal, though it would be useful for some safari-trophy hunting(of species other than rhino).

5. Lengwe National Park is the only remaining habitat in Malawi forthe Nyala, a large and attractive antelope. It currently serves about 6,000

visitors per year, mostly residents from Blantyre. Parts of Lengwe may alsobe useful for sugar, but there appears to be an excess of sugar-suitable landoutside protected areas, and the sugar estate beside it has recently taken

some of its own land out of sugar production in order to ranch Nyala, forwhich the currently unutilized "western extension" of the Park is also being

considered. This area of the park could be considered for multiple use zoning

(the game ranch, wood, perhaps some agroforestry).

Annex 6Page 2 of 10

- 86 -

6. The Hajete Reserve, which has very stony and steep terrain, is animportant watershed in the Lower Shire Valley. There is some encroachment for

firewood. It could be quite useful for trophy hunting, with a littledevelopment, perhaps through joint government-private sector ventures (no

economic benefits are currently derived from Majete). There may be some

agricultural potentiul on the eastern side; the western part might be useful

for some grazing or forestry, but not agriculture.

7. Liwonde Park is flooded throughout the rainy season, and the

boundaries were established after an extensive survey of agriculturalsuitability, explicitly to avoid conflicts with agriculture. In the late

1980s. it was discovered that up to 1,000 people had moved into a 10 square km

area inside the eastern boundary. This area was degazetted for them, although

there are reports that they may already be abandoning this land asunproductive. Poaching became a severe problem in 1988, but seems to be

declining substantially since enforcement efforts were strengthened.Currently, poaching seems to be mostly for subsistence fishing and animal

trapping -- activities that might even be considered for legalization if

efforts to increase the benefits to local populations were to include

recognition of traditional utilization.

8. Basically, the only productive use of Liwonde's land is forwildlife. The Malawi Government is beginning a three year, US$ 1 million

project to upgrade Liwonde's roads and facilities for this purpose. Itcontains perhaps the world's highest concentration of the rare, spectacularSable antelope, which could serve as a lucrative species to export live to

other countries (negotiations with South Africa are already in progress).

Crocodile farming appears to have high potential on the Shire River, whichflows along the western side of the park. An attempt has been made to

introduce bee-keeping, but it appears to be unviable in Liwonde, both socially

and ecologically.

9. In addition, some of the wildlife (Uspecially elephante) mayeventually need to be cropped (or more lucratively, trophy-hunted),particularly as the park is now being fenced to reduce the problem of crop

damage. Some preliminary research, to be expanded upon in the next growing

season, indicates that the total value of damage to the maize crop around

Liwonde may be around MK3S,000 per year). Such fencing is likely to reduce

the effective wildlife carrying capacity of the Park, as there are indications

that some animals, particularly elephants, may migrate between the park and

the forest reserves to its northeast.

10. Lake Malawi Park, which has been designated a World Heritage Sitebecause of its unique biodiversity value, already allows pre-existingsettlements to remain in the park. Much of the remaining land is extremelysteep and rocky. It is the most popular camping site in the country and hasconsiderable potential for increased tourism revenues, if its facilities areimproved. Certainly much would be lost, and nothing gained, from degazettingeither Lake Malawi or Liwonde. There is plenty of scope for increasing theirbenefits to the people who live around them, while maintaining their protectedstatus.

Annex 6Page 3 of 10

- 87 -

11. There are only two wildlife areas in the Central Region, though they areboth considerably larger than those in the south. Nkk'otakota Reserve on theeastern side is very important for watershed and soil protection for centralLake Malawi and the Bua River, the one remaining river that the Lake Salmonspawn in. There is a crocodile farm nearby which has depended on this riverfor its stock. The land, at least iA the southern portion, is very poor foragriculture, and presently is visited by few tourists, but it has considerablepotential for safari hunting.

12. On the western side, opposite Nkhotakota, Kasungu Park has someagricultural potential, mainly for tobacco. However, tobacco is aparticularly erosive crop, and Kasungu is the headwater for the Dwangwa River,which provides irrigation water for a major sugar estate. Kasungu is also thearea with the most investment so far in tourism infrastructure and wildlifemanagement. The western side of the Park is in the process of being fenced soas to reduce crop damage by wildlife. It has the largest elephant and buffalopopulations in Malawi (800-1,000 for the former), and together withNkhotakota, provides the only remaining Brachyetegia woodland ecosystem (whichonce covered most of the central region).

13. There are also two large protected areas in the Northern Region. Nyikalark is experiencing the fastest growth in tourism and serves as a vitalwatershed for the Lake. Bee-keeping by local reeidents has been allowedinside the Park and is proving quite profitable. Vwasa Marsh Reserve hassuffered from some encroachment. Multiple use zoning, and fencing the easternside to reduce crop damage, might reduce most of this pressure. Safarihunting again has potential to provide revenues and development for the localcommunities.

1I1. Asseslina the Agricultural Value of Protected Areas

14. Using the maps of the Land Resources Evaluation Project (LREP), one canestimate the relative suitability and value of agriculture production inprotected areas. These maps indicate that some portions of two areas in thefar south, Mwabvi Reserve and Lengw6 Park, are moderately suitable for somecrops such as sorghum and millet, and also cotton (see Table 1). I/ Theprojected value of agriculture production in Mwabvi and Lengwe National Park(with the latter divided into two portions, the small core "Old '-engwen andthe larger more

j/ Lad Resoure Evaluation Project, Maawl, 1B89. 'Larid Resources Appraial of Ngabu AgrbculuralD.vopment DMsion." (Ministry of Agriculture-Land Husbandry Branch/ UNDP-FAO Project Technica ReportNo. 1).

Annex 6Page 4 of 10

a 88 -

recent "Extension,") was estimated based on the following equation:

GMx - (SUM(xi1n4): rA*Siz*Yiz*Pl) - A*I

AMx - GMx I A

where:

x = type of crop:i - the suitability level for that crop (High, Moderate, Marginal,

Zero);GMx - gross margin of area for crop x;The underlined term is the total production of crop x for the givenarea (figures obtained from "Improved Traditional Technology" maps aredivided by 5 to obtain yields expected under "traditional" farmingmethods);A - total area in hectares;S - fraction of the area at suitability level i for crop x;Y - average yield (kg/ha) for suitability level i, crop x;P - producer price for crop x (MK/kg);I - input costs (MK/ha);AMx - average margin (profit) in MK/ha for area for crop x.

The resulting estimates of agricultural production value are summarized inTables 2 and 3.

IV. Assessing the Tourism and Safari Hunting Values of Protected Areas

15. Current government revenues from tourism are provided in Table 4. Itshould be noted that this is a considerable under-estimation of the currentvalue of tourism, as it includes only park entrance fees and in-park lodging,while it excludes all other expenditures by tourists. Unfortunately, thestatistics needed to make an accurate assessment of the true economic value oftourism in Malawi, by the "travel cost methodology", for instance, are notavailable.

16. Table 5 provides the Department of National Parks and Wildlife's (DNPW)most recent estimates of the potential proceeds from safari hunting in thefour game reserves. They estimate that including parts of the national parksfor hunting would increase revenues from this activity by a factor of 4. Ofcourse, this would have to be very carefully managed, as Malawi has had badexperience in the past with safari hunting programs.

17. These estimates of the value of hunting may be low, however, for fourreasons. First, the value of meat and hides, which are usually left behind byhunters, was not included. Second, the proposed unit trophy fees are low byinternational standards (Zimbabwe rates are assumed in our analysis). Third,the proposed hunting charges of USS 450/day for the big four game andUS$200/day for everything else are also low by international standards (ouranalysis assumes $750/day for cats and/or elephant hunts, $500/day forbuffalo, and $250/day for all

Annez 6Page S of 10

- 89 _

ot.hers, but including some of the rarer/larger animals only in a longer huntthan the basic 7-day). Fourth, the proposed hunting system, comprising huntso.' 7 days for the basic animals (antelope, zebra, and hippo) and 21 days fora1l of them plus the rarer game (buffalo, leopard, lion, elephant), results ina sub-optimal return from the harvest. Since the rarer game safaris generatehigher daily hunting charges (US$500 for buffalo and US$750 for cats andelephant), it would be more efficient to create Ointermediate" hunts of 10-15days. This would allow bunters to take just one or two of the rarer game inaddition to the antelopes, which results in a greater number of total huntingdays at the higher rates, and thus, much higher revenues.

18. Table 6 lists the unit value of the different kinds of hunts. Table 7provides the grand total from several combinations of hunts reaching the totalquota of each species proposed. The DNPW proposal is provided as the firstscenario. All of them include the revenue from skins and meat, plus theincreased trophy fees as described in Table 5. 2/

19. As noted above, DNPW estimates that total revenues from safari huntingwould increase by a factor of 4 if national parks were used in this way too.Since Mwabvi is the smallest reserve, if one assumes that only one-eighth ofthe total game reserve hunting was done in Mwabvi, under the more flexiblehunting scheme outlined in tables 6-7, this would yield an average annualreturn of US$47,000. Thus, this direct use of the reserve alone is of thesame order of magnitude in value as the food crops investigated in Table 4($55,000-126,000), before including the protection of rhino, watershed, andother harder-to-quantify values (see below). If Parks are included and Lengwenets a 1/8 share, for $190,000 plus increasing tourism, the return is also inthe same range as it might be from agriculture ($143,00-379,000).

y Se Agnes Kss {Ed.). 1990, LMna with Wildlife: Widlife Resource Management with Local ParticiPation infrba, Would Bank; Chapter by F. Mur ndagomo on 'CAMPFIRE Program - Zimbabwe' and B. Child, "Annex 4:

Notes en te Safar Hunting Indusby."

90 Annex 6Page 6 of 10

TABLE 1: AGRICULTURAJ. SUITABILITY OF LENGWE AN) b7ABVI

Old LengweArea> Mwabvi Lengwe Extension

Crop Hectares> 15000 13500 75200

Suitability ._,__ _ _

MAIZE High 0 0 0Moderate 5 0 1Marginal 95 80 50

None 0 20 49 _

MILLET High 0 0 0Moderate 57 67 7Marginal 43 25 75

None 0 8 18

GROLNONLJrS High 0 0 0Moderate 5 0 5Marginal 95 80 60

None 0 20 35

source: Land Resource Evaluation Project, 1989

TABLE 2: AMCULTURAL VALUE OF L fGWE MiD IEIWBVI(US$)

A) Total Vaue (U$) if area compl!telv nder crop x

- Aroa, Mwabvi Old Lengwe Lengwe ParkCrop Reserve Park Extension

Maize $126,000 $85,000 $294,000Groundnuts $76,000 $35.000 $108.000

Millet $55,000 $50,000 $152,000source: ministry of Agriculture Crop Budgets and Staff Estimates

- 91 - Annex 6Page 7 of 10

TABLE 3: AGRICULTURAL VALUE OF LENGWE AND MWABVI(MK/hectare)

_ B) Average val e (MK. ha) if ompletely un er crop x

Area> Mwabvi Old Lengwe Lengwe Park National AverageReserve Park Extension for "Suitable'

CroP (150000 ha) (13500 ha) ha) Areas

Maize 109 82 51 202Groundnuts 66 83 19 351

Millet 48 48 1 26 71

source: Ministry of Agriculture Crop Budgets-and Staff Estimates

TABLE 4: TOURISM REVENE FOR PROTECTED AREAS

v# isitor-days Revenue Revenue $ perArea 1989 _ (US$) visitor-da-y

Lengwe 3,077 14,400 $5,538 $1.80Llwonde 6,018 34,700 $13,346 $2.22Lake Malawi 5,393 87,780 $33,762 $6.26Mwabvi 0 0 $0Majete 0 0 $0Kasungu 3,100 22,000 $8,462 $2.73Nyika 2,692 322,857 $124,176 $46.13IVwaza Marsh 910 4,400 $1,692 $1.86Nkthotakota 121 563 $217 $1.79

totals 2_,3 486,-70 $187.192 $8.78,

source: Department of National Parks and Wlldlife

-92 - Annex 6

Page 8- of 10

TABLE 5: SAFARI HUNTING RATES AND QUOTAS

DNPW Proposal Zimbabwe RatesTrophy (actually paid by hunters -1988)

Spec es Quota Un,t Fee Reverne Adjusted Unit Fee Trophy Products Produc's(u S ) (US S) Quota (USS) Revenue USS Unit Reve-.e

Elephant 5 3,500 17,500 5,000 25,000 2,000 10,000Lion 5 1,500 7,500 2,000 10,000 375 1,875Leopard 5 1,000 5,000 1,500 7,500 335 1,675Buffalo 15 1,000 15,000 800 12,000 170 2,550

Sable 10 800 8,000 1.250 12;500 aa dO Roan 6 800 4,800 1,250 7,500 80 480Eland 6 800 4,800 750 4,500 125 750Zebra 6 800 4.800 500 3,000 125 750Crocodile 0 0 10 1,000 10,000 235 2,350

Hippo 20 750 15,000 1,000 20,000 450 9,000Nyala 10 500 5,000 20 800 16,000 60 1,200Waterbuck 20 300 6,000 750 15,000 75 1,500Kudu 10 500 5,000 600 6,000 8 0 800Hartebeeste 1 0 500 5,000 500 5,000 40 400Reedbuck 15 250 3,750 20 300 6,000 17 340Duiker 10 100 1,000 100 1,000 8 80Bushbuck 10 150 1,500 300 3.000 20 200Warthog 20 150 3,000 125 2,500 30 600Bushpig 20 150 3,000 125 2,500 30 600Impala 20 125 2.500 20 400Trophy total 115,650 171,500 36,350

Safari fees:# hunts # days US$/day.

5 21 450 47,25015 7 200 21,00020 7 200 280.9Q0

-- - 68,250Hunt total - or 75,250

Grand Total 183,900 from Tables minimum 272,000or 190,900 6 and 7: maximum 423,000

______ _______________________ average 380,000source: Deaprtuent of Natioal Parks and Wildlife

World Bank, "Livilng with Wildlife," 1990Staff Estimates

_ 93 - Annex 6Page 9 of 10

TABLE 6: OPTIMAL SAFARI HUNTIRG PROGRAM

Type of VALUES(US$) Per Hunt If # PotentialSafari Species_M Trophy Products Hunting Total Hunts Gross

7 day Hippo - 20 $10000 $450Nyala 20 $800 $60Waterbuck20 $600 $75 7 daysReedbuck 20 $300 $17 x250 2 11,442Warthog 20 $125 $30 5 28,605Bushpig 20 $125 $30 7 40,047Impala 20 $125 $20 12 68,6528'JSUibcki 1 O $300 $20 15 85,815Ouiker 10 $100 $8 20 114,420totals $3,275 $696 $1.750 $5,721

10 day 7 day plus $3,275 $696 10x500BUFFALO Buffalo 15 $800 $170 15

totals $4,075 $866 $5,000 $9,941 149,115

12 Day 7 day PLUS $3,275 $696 $1,750SABLE Sable 10 $1,250 $80 & 5 days

Roan 6 $1,250 $80 x250Eland 6 $750 $125Zebra 6 $500 $125 3 37,113Crocodile 10 $1,000 $235 5 61,855Kudu 10 $800 $80 7 P6,597Hartebees 1 0 $500 $40 10 123,710Subtotal $4,800 $600 $1,250 $6,65012 day totals $8,075 $1,296 $3,000 $12,371

12 day 7 day plus $3,275 $696 12x750LEOPARD 5 $1,500 $335 2 29,612

totals $4,775 $1,031 $9,000 $14,806 5 74,030

14 day 12 day Sable 14x500SABLE+v us 10 $8,075 $1,296BUFFALO $800 $170 5 86,705

totaali - 18,875 $1,466 $7,000 $17,341 10 173,410

.14 day 7 day plus $3,275 $696 14x750LEOPARD + 5 $1,500 $335BUFFALO $800 $170 2 34,552

total $5,575 $1,201 $10,500 $17,276 5 86,380

15 day 12 day plus 15x750SABLE + $8,075 $1,296LEOPARD 5 $1,500 $335 2 44,912

total $9,575 $1,631 $11,250 $22,456 5 112,280

source! Staff Kstiates

-94 - Annex 6Page 10 of 10

TABLE 6 Continued

Type of VALUES(US$) Per Hunt If # Potential

Safari Species Max Trophy Products Hunting Total Hunts Gross

18 day 12 sable-+ 1 8x750

SABLE + $8,075 $1 ,296LION 5 $2,000 $375 2 50,492

total $10,075 $1,671 $13,500 $25,246 5 126,230

21 day 12 Sable + $8,075 $1,296 21 x750ALL BUT Buffalo $800 $170ELEPHANT Leopard 5 $1.500 $335

Lion $2,000 $375 2 60,602

total $12,375 $2,176 $15,750 $30,301 5 151,505

21 day 12 sable + 21x750SABLE + $8,075 $1 ,296

ELEPHANT 5 $5,000 $2,000

totals $13,075 $3,296 $15.750 $32,121 ..

21 day ALL 5ALL BUT + $12,375 $2,176

ELEPHANT $5,000 $2,000. $17,375 $4,176 $15,750 $37,301 5 186,505

28 day ALL 5 $17,375 $4,176 $21,000 $42,551 5 212,755

TABLE 7: SAFARI TINMG RE}UD IN DI}IT SCAIOS

Type of Sajari Value # of hunts

Each ONPW Other Scenarios

7 day $5,721 15 5

10 day Buffalo $9,941 10 10 5 5 5

12 Day Sable -_1-. $12,371 512 day Leopard - $14,806 5

14 day Sable8u8ffalld $17,341 5

14 day Leop+Buffalo $17,276 5

15 day Sable+Leop $22,456

18 day Sable + Lion $25,246 5 5

21 day ALL but Eleph $30,301 5

21 day Sable.Eleph $32,121 5 5 5

21 day ALL $37,301 5 5 S

28 day ALL $42,551

TOTALGROSSVALUE(US$) 272,320 411,520 347,770 422,920 351,520 410.570

source: Staff Estiates

INVNTOQR OF NALM! NIRONKE AL LECIS!ATIONUs. LEOZILA?1g UmY o UWisIs pSUiIs COMernucMMA,wst

I SM ACT Prelde for mbbe. rStoos.e tlew TheW UI1et9 1 Ieepeed to faeted 1 1le, th et CAP: WStO in blesl, ahebe eebewp, p6gb roeistetm mad preulet... tor reveod es_ 1Gl tbl_As. The IN&

Ot Pivatbe eed. Te ot ftebbw pseelti., I.e. sa time of N0 a"d rVIm Wee In 1361. All _ooesbeprovtd.e" C4o W0I& ef lea NW Ioep ett ehe. bmve bow oIncorporatd Is Act.- 1*prelblbAee st Wbadpe, ef _eer.mt ste a.y orders zsd. whie1h eoeb't thew eP .tel eeepetloe of lad. moe of certain apecilIc *ers, ea

thee have alee bos lecorpored.

2 hSOISlU Preeldee tee re Ss1belee of titlg of Ap e.abwatbe Of pwovlelo. of, the act mm e_octe is too A sads 1iWe ACT 1 ead sadell Is ead so Act easetsa time of MM &leprloesb 1970,11,61. All asdsonto have to doCAP, 811e lregbebed. sr 0 yre. Esfereset .f cewe.ot Is e with th rogistration et land. Lad

prh'm doe be loch of rolotretlon Ison oupoalvo procedureoesapwodoquet trsaepsrt a NWd mppere tO he h sale hedilcep.oerdilotlea by *1I relevant Dept. inditfterat ectors.

S OSTOUM? Pregds tee whea fl _eerwstl_ . Pr ampeea6tswe' tleefmo peaSty of. Thle Act mm seatod la 1361 sa hasLM r1obe I lebes la custom" lead a flee of up te 610 sad Ieprbe.n..t up nct bn revwled ela1 th_a. "oad_(DI ems et ohe ebjestwe Is t bprobe to 0 a sete Ie provided. revIse.ACt bber we1colurl do _e pato.

We 5001 WM ebeay lea. LeW Cmittes eedhweee be l ead elSetlb_

p_l__iplee. ____ I_8 e) Ll1S This ede deerlhe the boeladee'et

AGRICULL eusteasir lea Is, Llemps Obebtleb.

MIA amsede sador

ctlea a

_- ------------------------- ------------------------------------- -- ----- ,--------------------------------------------------------------

Aex 7-96 -Pase 2 of 20

sXis : i tilEl i in~~~~~~~~~~~~~~L f

, l E 1 g 5 1 g j ffi l~~~~~~~~~~~~~~~~~~~~~r

aI ttl ,§2 l t jit

ji' '>gi 'i § *t58" '

' I it|l li }]{1'S i .l,,.X- ,s,X,~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~4

| jtis-s jie3tat! 1l ii 2i1 Es~~~aL IL |3 3 il |$

INVUTORY OF NAIMI ENVIRONNENTML LECISLATION

lb. LESIATM _A7 U POVISIWUS pSATIES COAlTS/RECU0ADIDTIoo~~~~~~~~~~~~~~~ -w_ - A -9*__-_ --- *--------------------'----------------*-------______ _______-____

et U% inienimp

* Um Prvdge for conte A we of ster A pine she coatrsvo the The Act m essed to Ig Nd kwRSICS ACT mrcof Usbluli. Part V provide proleioe of te Act say be senteneed bew relomd orly three til.

CAPt M2t0S for ,.Il..* voerleblee tm lnstlon to a fine of up to K1,000 and Prop"lIs to revew the Act sar Ina 1 dmleltteo ets. r Isteo l, iprieeent for e year. advrnced stage.pollatleo of P*bi1e wset. Thor lafurther pr"WOOI ter as d.cter.loeof controlle14e1 s t foW PupOSe of Act

... f

* o8) vatsr Plovde afw as met of est Poselti wilt *o be viewed as the he for levtes.Gelorao pet ntl.e. The dloohe. me of sar prepel to revew the Act la wtor

(Water ow ofe leastIle, publie Mse set cosedo let.ptll ttioe assent to preibltd. Wr are elseControl) prowlolen sIth respec to ameelyol ofRegettloeo0 st" w offleant.weds, under 1oetie4. -

* WAEW'JHI P1rvides fow thestebllslowms of Any eotevoftlen of the provisieo of This Act we enecd Is IMS end hasAC wate Seards a wter Ares a fo me te Act oxmct. e slate.. flne o f X4 sinc been reiew several ties to

CAP2 11:0 msetabi I.smt Am sote0e1 8e of end a asalmun fie of X20. take Into accoet p"oe lndspendenesear,orhs to euc won. Also ebsoge.. Reqlres furthr rview.Pr1010 fOlOtIN % IDJV67,p r o l o t n o r l e t l s t o l a ) rPoolutlose of Wr eNW the serart.

10 MM fAS P idest fo rP seay ooa eoe f th Enacted tn t1wo0, rviewe tce aSNPM ACT A,ur.mwleel eIo of the Act, the monism lwoked en 211617 a 6/1/70. Repoe

CAP. :lifot f elt vesslse poelty la a fine of f600 and propse . Oheft bIll esbmltted bythe saft*y of p _osngs a corpe tuprisEoneet for two years. conga Ilte to Umlaul Govoti vt forhe conpetecy of ew . ft V proes eonsideration. Ad&tI. propesoIfor dsclsretiee f nleld voters a provides fort ew, dmilinetratles AeBremoto s/other centries,per to Intl egreete effecting _ritles i1v.evempee poWvision. incoemletonts/trestles.

_____________________________________--- ---- …

IVM3lJKV OF KAWL KUVIENTAL LUMSIATLON

lb. UUEAIN MwO W PUISI(INS PENALTIES CS11INRShC1AnTION

, 51 inUX,

10 ) tal P d 9. f pw bl, atr .etle ef e pastle d l. lelele*1atere earring of simle, meet carryln reptatlae Omte a tin, at S. so atted aboe. atIt e100 etfect Urn.Shbipplag meled 1- 'l*l corrA *f slung ubsIdIry lIegItle. it to(brbe*or) pobo. - be saw ubath r of Mtbptatl 56" Govessmmt wIll acomptthe prpil i

d er bitt.

I0 b) aIsead owlsI mertals tea 1t* beSbers hasb he OA rpoet te Lob.Shtppieg

of Areas _Harbour.)

owtiom~~~~~~~~~~~~~~~~~~~

11 ULMItRE WTe Lo proldee for eod.iebratie Sectie 411 nb.. it as offee to Tb Act e mac lad 1 A2. It _.d.UATUS *11d _oberbtea of he Slmbyre Water peolls ewat. revUe en otr.ngtIwemg of theACT oe s ftr bard end for the entorcemn,t machinery.

CAP, lIgU2 dmo.ItIegmatad mseat m atoneooastaser Is the enter are.e

13 LILUI Pe'e,top eav .deto blee of The ton" rag Ie1 RIO ned Kfl_. This ts a fierty a Lot _amle hoeUT|1 _S loupet1 later Area. eotehitm of so"_ of the offenc_n ho penales encted In 1so.n

ACT Li leaso later Saued A dew $PMt A which cao accru by mS per dayCa PSIm *elotanmee. of weterwoebl In throgu the dertlae of tm#relatng to pr_v_6tlee of pot ltion.

as FISEIES ACT Prods tfe reg.aloti _d control For say ceeravelem Ohw. In a Act enaced la 1073. Ide OfCAP: Wa8S of fshing9 & ?fr penalty of a elee of up to MMO a perittleg cortal flsherles Off

purcb I-,eolo.WIZatlng,Plio,alqhg. lap leprlmeemet. for I ypr Proawlae for to he progatere in1 ffenes mudeorb A ouport and ceesrvatlen of fish. fortolt.uro of feAct, 1 god o. Such OffleGns aN to

IUMYUOU OF 1AIAMI DVLIONIfZAL UMISIATIOU -

lb. UULsATIU SpinY U PUSYiSS PLTIE CO~NIMTS/R!CSfNIIDAIOSS_._ _ _ _ _____~~~~~~- ___--_-----___----------------------------------------__________--

Prehibloo me of .*le,ewelee on sed We .emlttl.o effeec. reseli. be pro"pei bsed of the ame bt

flae,l.11MC4Us pleh.wors. am tom to be l*edequto A I.t of diechere thig fuecti. ofecttl,olg.

presommie eeele oftomne c..rdinettee In ofee_t eectors ewipeuelse of Ch P.A. probem.

n Ad--_ ----------------------- =

Is ) FPle i PrlIbIts th _e o e1s New to(P.blblte Let biee1.

rooieMag)

suds emlefteso

a3 b) Plehsele ProhIbitbte Wmeam of %MI st in the(ProbiblIleos stemp of Lake Bolee.

ofTeePleMme)Order. me"

_ .

is *) pletwe.'e obgslste fishleg em a eemeweleI(Cesescelel heel. Is ase satoe of obleel.Plues")

mo and

egotIsm as

14 UnSma Preldiem fer Wme emeel a proteetlee Peeeltp for sap osetravemblo.t of the The Aet see amete Is 136.

ACT of evc doleo, the .ooIetiee of the pr"owlele.s of the Act Is.e fine of upCVS 6011se hetleg s.d veering of ercdI too sem to kIO NWd Impr leemment for eOm per.,

redias to ereaeile, prdeste.*MAtIe ithest.a fiee"" le

Ib%Ie S rohIbIte.

IMEY MTOR OF NAIAVI UVIROU WAL LEGISlATIONlb. ILEiAn SIM, V SvImt PENALTIES CMMftS/ECO ^DATIOM

Cs fLMW MSMM s

as PSU ACT Pelde for am oaled A mletis Camprehnive provistes fare TWIN Act wee eaced no 14 t siamCAPs S5a1 of foret preodcte. E*pee inIser nonecsplince slit Act. Mamlm fine the th"'a have bee. gertgl pest

to declre say public er customary 100 1 yr Ve- rsp l_ensnt. Provide for IndePendence _ at. to It. Filein" to be a forest reseve. Provide. enfoeremet by fest or polce sod enforcemet mechanim requireiWAtent .ulinhla@ powe by Vlinoter officers but et effewtivoly review.to aOW tt.n foret I'plemene.prded_U I teplanting

16 a) Thero are Mainly deeI .5th the dsscriptles of Ther Is nowi to declar re rmseveral the _arn ¢ feabt reserve in In order to lacose pereeteg ofo t0 e_ l ide for forest r_esurces.

reservesdeclared byWme Minete

*of teLt

specified isthe echedeletot

-- -- -- ---- --as b) Forest Preulda for pretest, of fercete by Any centroeveatles of Uteae Rules or There have bees reseonable efftert to

tepees meade, prohbiting felling of trese*lightlng coditimon ce"tOised therein is review thee. rlse regularly, the amos% under seties firsee1 & for regulating greaing punishable with a fine of up to ffI36 reeet revise wa In 193.

a end la esmalms. Sch activities can be doe. and Imprieftemmnt for teolve o set.underV the auhrity et the proper

ceataine list of special prolectodseceies

--- - ---------------------------- ----

10 PLMGT Provide for th, oerdication of pests The penalty provided for any The Act mee enacted In 1360 VWd sinceMIIECTION OAad dles,a destructive, to Plante. contravention of the Act Is a flonw of then it Nee, not bwee reviewed. It

ACT Conseoin provisions to prewent up to N~OW end lmprieonsent for 4 fee. ehould be reviewed so eoon asoCAP: 64:01 introduction A spread of pests a The Act provides for the confieCetion possible.

diesese destructive to plants. such of the growing medium Plant. or other

IUVItR!t UOP ULAWII LRVIUIUlA IA LA iblAtiU -

b. UEWSU? UinY P N!siIeS PUMUSSTB COMMIS/KCONUEIATIIS

Co ftm WUcos

det Is Ismes opsen ead sowes". thiap e on default.

6 a) Plean Prvid for tWe empe of plsat only Thaw reile1m were mede la 1&61.

PretwMeft *e ada I lo ,1_ lta In so.rd_ma They hould be riewed as tbs appea

(Rupert) with the repllehm. Thmee to be Inedeate to meet the cheged

ietlsa% egletime de *IF te he epti s es.

made ug,ds of hun oII, Mea sete SAU lat. oeefe

getlee 12 cu flemer, fro* fruit ad,egetablee.

as b) Pleat Preldb fo tWe prutibitsa1 of The Sspect*er appoldl Under the Act T_es reuiIsleae were mad to 111

Prote" slee INPert1ets Of O*etei pleat mi4heet he"s pesoee to eseare that Its. eldnce the they have not busn

(Impor) thewit. Cortala pleate se eww*pte prevsonse ad retatlo are reviewd. Rteis ia r1 qured.

Reguiehiee, free such requrmt A prewielea Cp o_Id with.stb e6 lletlw 1qw *"_ al

* ed undter 11 estritin i_rt tr I eb led * .. b...-.-. Tbese ee .sw 1 .. -

Prtetiem me pleat cemedity, building for pres*t at fumlistilon a nsr eialpot

(Pum"iei) th peepse of dnetsp ljureu se"d Is isI r rd atndrd. Row. ce"sla

eletlioe e- lit of fmigation qwlpat. Rep. adeb

made undP ert i d pa%sold be revIewd. V1ei K

sectice Isits 1 nesto nw _mre te desl wfrecent O J

meslyb u *tater lajuriee ttce P

1?t UIIIWS beerelip previge Pet the ordilclatle eliletO to cmply With pro641-Isns 1 The ACt we enacte In I61 but bee

ACT of Rseieeo Weeds. Act Is punlehable by a tfine of t69 elnee bee relewe to take leto

CA ee2 lmliseomt for a mnths. Inpector a t

app_Inted uner the Act esre that The lest reiew Wa In 196. Thie Act

the provisleos of the Act are compiled should be reviewed.with.

IIVQRT OF IAIAI LEZISIATIOlb. &MIIUT S? Uv PsVIS PTlES pTScoU

aeeeeeeeee.O Cee------------------- _

51 a bs o flowe RIdlinmISw, Estop fla b mmwos et reuesd aw in .eml"U bwo o is m a ,..io Shmuld row be du for esethe rewlow.of NMI)..

eds, mad

aider~~~~~~~~~~~~~~~~~ ._ tI._OS ____ meel6 tlX-1" sof. tdi es*tU"te

1i

eabeeee ab- -O O ____ _ _ _ _ - - -ISb PECIAL tWS Pldms fee us developmentb sod Pal ears to alyp with pr,I.ee. of This 1to0 v er l * rt s Act. It

ACTrhl.g of sp.la erop aid for the Act carries a l *o .f up to *2e00 A replethe th g Ing of m CAPS SllsOl dsSoobIas @ eopesli are". Isi_OM for S pre. It swct Impeortt crops In the cooatrp, which

el_ s "orItlwe for prdef seg offence Conti"" a time of K20 a day fore tth ecoelc backb_e ef *Mlail.OA tfechelag e ob f A Impr igmest for a.m wook for teahspeslol on". day dories ibech th Ofloes cOV-Nome

to provided for.

- - -- -- ,,- - - - - - ,*

a) $pselaS The eo %bot he" so top 0Crepe u*.re special Oer. ar . s

Dec _leslo cOffD _etes G ste, in_acsdasMads "WdM aruo, ts, sad flee cared tobacco.

betsleee oRe-

I9 b) Kamm gm1m atrlty for Flue-IFlueCurd ued lob.. sa t eleari dot isag

Aetsl toe or"

Is c) a seletlee pod far a tbe poeities for .e-_osiIss_ with'Fleo-Cured .Orecmr' glceez. the provisions o. Wh regletlcee areTobacco a floe of RICO se lopelcinmet forAutherltp three sete.LiclealaRegalatios.

Annex 7-3103 - Page 9 of 20

§ 1 I ~~~~~~i sEE i l'

'jI I! 'It l *i,{ 1.Il li

14~~~~~~~ 'VSI11S]a { }Siv11

IR Mm O! KAUMI VJRtoDIIAL LECISLATIONlb. LEZUtSAIA u v or ,sw PE TIES ClA _ Cn I

-_- -------------- -- ----

Ordwe, atol eil thOoeI ess o or"wsgrwd eashs 1ewe asI hel wadra "le

4 *ri heega _,g Cog. Ltd.

St TlOM ACf A1 " t As d A" h I. AMy e..tr.,O.s of th Mt e be law VW 4eee il 317 "A weuap SU robstiag nt i4%asd"I ., flee of 51000 WAd iuptie.mmt 1fr sinm boe rwlemed ores I .

msste.seo sa mvt.tbS of . ebes.. as pee.The Ash esle grsime* hEs Woseproeblog ef Imewn plaos oebId be

.)9 Tebes Proestbo D_e w_of eoriewlg taebeee Pameties for say .eatrev.m.al. of r. ft. lot),. Vleft Os s 10,I tf7(ebed of _ es" em cwetemor lend. fretIde th rfeg tbesere a fine oi up to hove been rfFol **C., IsiM.Cielng) emangl=3 fr so& r1oplr . RIsteO 5100 eand IupuIet for thmeeSussletieme, et.modsl undeseelh l,, .

tS IN CTol Preol. fo ts smeIldotlef gh Amp ceetseetl.e of the pirolole. of this At - eted 1t1o sat WAMACT I_ o roetleg to the Pedt ISO, Wm Act Is eeble wt e a lie of be" relm seveal WIm to take

CMP, ISa1W _r1"eeel sa serhte of sette. up t. MM00 Na l.pr I*e.Ai 1.ster a ota sceesat _e ps iI Ace'O Illlteletee to _psred under th Pet*d of hreel seeth. _, esthe or dewelpeat. Do At sbeid heAA t orde Wh dsetlee of s pipast w fa be dmotreqs_". rmisse.*01es tor epw len hu,m _f.

It CeCIL P5 Pm A prides for Vs domepeemt l ffle"ITe low. Etsesrchfollow WAd msemftv % t oaf etrtss eNd pwie slones shod he strs.gtheesd byIENSAIU Me betaftesiogds a.s so mtVlsI her lt.i eatmaodla mit. .49 theo cae) J.S1ANlC et Sleol. It ablbebee e W Cou,loOARMD O fOr Wat NIo 11Herhevis s1 d W *et..

1M A"C Gos olfa st .bl lCAP# ?,tf1

INVEATO or 0 UWA1! LI=vuwmAI LUSL&TIUUNo. LIIMA?tU ElSE OF PMIWISIU POSALvtIs COon?SiWIcOMSr

u miww.L pr.,te .I..e fohe bflo A of a p1Seali of * tles of vp to M1.000 The 1c mm .o9eto 1WO. Revl.?..pAW ACT ma.ilea. pSAt, Woo .. cw,et1 s of ga" tnocleeoms for IV* l yeors Ie at real ,M.wwy.CAP: 6s:0? smlea. vas, tabla 1Ad .bjet of proJwidd for Day coetroveetion of thU

specIa l _ 1terest Ist moer path. Act.

"~~~~~~ ~~ ~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ *) -l -- -o - - -l" - -St a) Utmiles ksnle aesu'Wa. a.ma3aIs hmi to be"a blo i PM e.g. P1 _1

(Es%bS_ Pok%) OFAh,

~~~~~~~~~~~~~~~~~- -- -- -- -- -- -- -- -- -- -- -- -- -- - -- - - - -

22 b) iotlol Peloo fe *b We psew _e of Us Amp untrarnilen of the RoplatiseP par PM.* by lopealesetale esliles same" a flto of 3100 end laprle.ment.gIctI^eao, ta h is be beoevd. for .1. meat).._edt _ de

.

sods~ ~ ~ ~ ~ ~ ~ ~embloo~~~~~~~~~~~~~~~~~~~~~~~ 0

------------ ~ ~ ~ ~ ~ ~ ~~~

1W Mro OF RALAVI ENVIIRONIEUL LEGISIATIO-lb. LWULATRI anmY U mOVisIU6 PENtALTIES COMMETS/RECOLUMIATION

~~~~~~~~~~- - ^- - - - - -o- -- -- -- -- -- -- - -- - - - - - -

13 UK ACT Pmlds ter the pro1ervetlae Sa Pesaitle tfartgo ceetraveethe of rh This Aet mm meted in Im 1a haCAPmI esu ct&i f pm.. Vh.th, Is te Act are a fine St VP to K1.S "a s bees reiw" d levar t1ime. TM lest

* ek "mmse ad_ _p ewe rlo for feThe rerhe w. ln 1161. SVield be.Wmest * ome to probibited. are also previes relating to hU stt etr m tloed t brie It to flew lith

torfeitere of agape" or ean ve ie proposed teravis .? the Nttlulan"d In t celeslee of ms effsoc. Patr Act.

oflelee atlmm it ' t mddla of hethee h_1ee.path, mad.o

1s b) one T_e loals mks pewIslme fw th6bles, Made pr.htbit.e . hest op oteld _nde m se selmle. cstteg ad beveg op

4. ~~wegoetieth.

e a) Provides fer as pro lbltioe otNIpp..tms bestale hlgpMepein.

Rols, maobeader osete40 (b)

to rewde foa the peblstie at ophtsPPrebblhl s esmle mtetapmbof 1WAIIF

40 M V1G

_ f_ __ _ __ _ _ __ _ __ _ __ _ _ __ _ __ _ _ _ _ _ _ _ _ _ _ _ _ __ _ _ _ _ _ _ __ _ _ _ _ _ _ __ _ _ _ _ _ _

tDvEUTO OF KALAII LFIISIATIOhe. UtSLAYiW 'aT wV PWUSS$ PUSTIES COWAENTS/PCgUJAIIUs

___w___~~~~~~~~~~~~~~ --------------- - ---- - - -_ ----

as 8, muSm, onici, P,aMM, oA.

fl .) Taapdat Pm.Ido for orehIbIlle of uanklas

of IaigRues, _id

40

n f) m er 0o P"MMUS of %Mats,

.9 Ihattsg.of "ti.

Aree.) i

settle% 40

-3 CUNIN be Co sin ideoe NW me l . ascmp WV _at.grveall a flue of up to The Act mseectd to 136. is *

*ISEA OIF V elati,3 tome seatui sW dlma IUOO l.prlsomon_t for slx mei shold be r.o,ld.MIMS ACV of s.l.ui.. Them or pm,leiea peelded.

CAP$ 086 r1241tS to the Go-vow of mebleiWAd dmotler of lafeeed am. TM

AC% sloe promdu for the maw toeblhi ewcm_n cm be d)mpsuW of.

34 a) Sims._ Pomdo for Wo 41dimes t. Wm _ulm _oe nI.c s.. la am of Aeluue teotmtof eSt a sie from VW$.. and NO" bam rewIo.ad wol _tlma

leeo adds dlarees St dipping tombe. to take oate accout the palo

une sadieI I dm oelIsPo I ot th. lb e

* now to rwel tme. tfrther.

16UIE -mm leegulol thme amemeb a Olson of Vileatleseof time to. la memo can" This Aft mem uIde Ft la3 m NWU11M9S ACT mlsemie. Part VII Ants wth cerri e a tlme et of op to 0,000 end rouesed once In 1s36. Thin la 0

CAP: 61201 prOtlettle of mWteame It metersl laelomnt for too years. oemplo of a very e.mpr.ientv medroeresm modern Act.protetlo Ceeits"sroibtlltttlon of ores d_magd by

INV OF PALAWI EMIV NThL LECISLATIOUlb. LMUU TI U mI5I6PA PEALIIE S COMuNS/12CcO.NA,I.S

_ _o...........................-....-...--....- __--...._____.----__---------------------------------- . . . . . . . . . . . . .......... -...--.....-...--------------------- _._--*

TS U I., 11:, OmIMCLI FOLPTR1 ohs.

peespeetta of s1.1mg. Pre,ld. ftoeslalfe I. e 1e ll.s.iq s6.

~~~~~~~~~~~~~~~~~~~Z.cn.c. _ -.....- __ _...........d.i..&.M..e..-. .__ e e . __........................e........_

#* ") hs. sad dI he 3.b .me1 heellm*huemI a otaO w e|@ .........(Calam)

no" tIm,

aesUse In

.15 3) 311mm s.d Pr,Ie for hoeuilag diepeme adur"towels Pt XI of VA Act.

_.d. e .... , stlez asa*

3 e) "ims NW SUpalah she. Glows$ Pismo cm boMm"eole am d bw the himle sad th(lliaerlo donresetl of th one. It oleomght) prvdmo foe to. Wht wo payble

hiewrle A".(Proesebihd

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114 - Anex 7Page 20 of 20

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Annex 8Page 1 of 13

- 115 _

ECONOMETRIC MODEL OF PRIVATE SECTOR PRICE RESPONSIVENESS INAFFORESTATION

1. As reviewed in Chapter III of the main report, the privatesector iA Malawi is extremely responsive to price changes for woodssmall relative price increases appear to induce large in^reases inplanting, even under the most conservative assumptions about seedlingsurvival and forest yield. This finding reinforces the critical role ofcontinued price reform in addressing Malawi's deforestation problem.The underlying analysis behind the conclusion of strong priceresponsiveness is summarized below.

Conceptual Model

2. Figure 1 summarizes the conceptual model. Aggregate demandD(t) is the sum of sectoral demands for wood at time t. It shifts withtime as the sum of demands from individual wood consuming economicsectors shift.

3. There are two important components to supply: the supply ofindigenous trees MC;(t), which is drawn down over time, and thesustainable supply of exotic plantings MC.. Together, these sum tocurrent supply MC,(t) at time t. The private cost if indigenousharvests is simply the wood collection cost (or the collection cost plussome small royalty paid to the Forestry Department). Indigenous growthcannot keep up with harvests. As the indigenous growing stock is drawndown, the residual stock becomes more remote and collection costs rise.Therefore, the supply for indigenous trees MC, must shift left overtime. Furthermore, indigenous tree removal without replacement impliesoff-site environmental (watershed) costs of unknown magnitude.Therefore, the social marginal cost of indigenous harvests is somewhereto the left of MC, at all times.

4. The sustainable supply schedule MC. does not change over time(in the absence of cost-reducing technical change in tree growth).,Sustainable supply implies both growing and collecting costs.Therefore, it occurs at a higher cost for any output level than theinitial indigenous harvest (collecting) costs MC;(t). Sustainablesupply creates an unidentified level of off-site environmental benefits.Therefore, the social marginal cost curve for plantation wood issomewhere to the right of MC,.

5. As time passes, aggregate demand shifts outward, and theindigenous stock will be drawn down. Wood collection costs rise and M.Cshifts to the left. Prices probably rise from the initial marketequilibrium at pt and the market will reach a sustainable equilibriumwhere eventual demand D(t+n) equilibrates with MC.. The mostaccessible, lower cost, indigenous forest cover will be gone.

Annex 8PaRe 2 of 13

- 116 -

Some less-accessible, higher-c.:lection-cost, indigenous forest coverwill remain, but no one will hdrvest it in preference to the lower cost,more accessible and sustainable, introduced forest. The indigenousstock, while it may be part of the physical forest inventory, is not animportant part of effective aggregate supply at the eventual marketclearing price Ptn-

6. The two components of supply also imply something aboutproperty rights. Sustained supply occurs on managed land with secureproperty rights--otherwise there would be no incentive to manage it on along-term sustainable basis. Indigenous supply may occur on land whichis open access or on which access restrictions are incompletelyenforced. As the indigenous supply is drawn down (as collection costsrise and MC, shifts left), open access harvest opportunities diminish.The open access market failure for wood resources must eventuallydisappear as prices rise (to Ptn in Figure 1) and sustainable supplyeventually comes to dominate all harvests. Indeed, while the openaccess availability of some current supply hastens the drawdown of theindigenous forest, it also precipitates the price rise and induces morerapid conversion to sustainable supply.

Empirical Specification

7. Tables 1-3 record the input data, which are based on supply anddemand data presented in Annex 3. The important demand sectors arerural and urban households (Table 1) and tobacco estates (Table 2'. Theform of our basic household demand functions is

Qd = (bO + bl*price) (b2*gl),_ (g2),_

where bO is a constant, bl is the price elasticity, b2 is the incomeelasticity, gl is the income growth factor, and g2 is a populationgrowth factor. The subscripts in t refer to the time period. Specificregional data create four regional household demand functions, two eachfor urban and rural households.

8. ' The household price elasticities are speculative. They reflectthe greater opportunity for rural household substitution cf 1)agricultural residues for fuelwood and 2) household labor co collectfuelwood for fuelwood purchased with discretionary income. The incomeelasticities derive from survey data from the Centre for SocialResearch. Fuel income elasticities for low income households in otherparts of the world are commonly in the neighborhood of 1.1. Thisgeneral observation is consistent with the upper limit of our urbanincome elasticities. Lower income urban households and for ruralhouseholds may have more discretionary time than discretionary income.Our lower income elasticities, particularly in the rural areas, mayreflect the greater opportunities of lower income households tosubstitute household labor for fuelwood collection. Household

Annex 8Pare 3 of 13

- 117 -

technology in Table 2 refers to opportunities to use more efficientstoves. Positive rates of technological change reflect data from theEnergy Unit of EP&D about improved stoves in urban areas, as well as thepresumption that increasing scarcity must induce some technicalresponse. The analytical results will be checked for sensitivity toeach of these uncertain elasticity and technology estimates.

9. The tobacco estate data originate with a sample of twenty loanapplicants to a local commercial bank. Econometric estimates from thesesample data show no significant level of price responsiveness for eitherfuelwood or pole demand by the estates. The absence of a price responseconverts the tobacco demand functions into simple growth paths. Thisconclusion contrasts with the Tobacco Research Authority's evidence offuelwood technology adoption and with more casual observations ofeucalyptus plantings on tobacco estates. The remaining demand sectorsare either self-sufficient (tea plantations) or smaller consumers ofwood.

10. Supply is composed of indigenous supply and sustainable,plantation supply. Indigenous supply is the residual stock of standinghardwood timber at any year in time. The indigenous supply is adjustedeach year for prior year harvests and prior year growth. Sustainablesupply is always harvested first in our analysis because it is moreaccessible. Sustainable supply is

Q. = b4 + bS*price + b5*price 2

where b4 is a constant and b5 is the supply price elasticity. Specificregional data explain two regional sustainable supply functions.

11. The noteworthy supply assumption (Table 3) is plantation priceresponsiveness (or the plantation supply price elasticity). The lowestimate of twelve depends on thirty percent survival of all seedlingsdistributed by the Forestry Department to smallholders, 2500 seedlingsplanted per hectare, and 6 m3 /ha annual growth. The higher priceresponse estimate of twenty depends on thirty percent survival of 2500seedlings/ha, but 10 me/ha annual smallholder growth.' This range of12-20 reflects private plantation price responsiveness only--but in thepresence of the current public and donor plantation structure.

12. The high elasticity estimate of 144 adds all ForestryDepartment and international donor plantations and assumes 12 mr/ha

The Forestry Department distributed 130 million seedlings between 1976 and 1990. At 2500 seedlings/ha andthirty percent survival, approximately 110 smailholder hectares were planted in an average year.

Annex 8Page 4 of 13

- 118 -

annual growth. 2 Surely the market would induce some plantings now madeby donors and the Forestry Department. On the other hand, some ForestryDepartment plantations are intended to protect watersheds. These willprobably be unavailable for future legal harvests and, consequently, areexcluded from the analysis.

13. In sum, even in the most cautious case, plantation growth andlong-term sunply are remarkably price responsive. This observationbears particular notice, as it will largely explain the optimism of themodeling results. It also supports our anticipations about Malawi'srapid reforestation response.

14. Finally, one important modeling simplification must beintroduced. There is inadequate data about 1) the substitution betweena) the collection time to extract harvests from indigenous naturalstands and b) the timber growth and management costs for new plantationsas well as 2) the rate indigenous forests are drawn down in response torelative fuelwood price increases. Without one of these pieces ofinformation, the economic solution path for demand and supply equilibriaover time cannot be assessed (that is, annual price and quantityestimates).

15. As an alternative to projecting the estimated "real" path, itis possible to review what would hiappen to prices, harvests, growth, andresidual indigenous stock if it 'is assumed that aggregate annualharvests never fall below some "acceptable" level; say, their currentlevel. Since harvests have fallen approximately thirty percent infourteen years, this would be a conservative policy. That is, thesocial fabric of Malawi, and the market alone, have permitted even morerapid response in the recent past than this conservative analysisanticipates for the near future.

16. This policy rule says that we will never allow the economy tobecome physically worse off for wood than it is now. This ruleanticipates further harvests of indigenous forests and further priceincreases -- just as we observe occurring now. It should alsoanticipate some additional planting in response to the price increase.The important questions become: Is there enough indigenous forest tosupport the market until plantations can replace the indigenous supply?How long will that take? How high must relative fuelwood prices risebefore that can happen?

2 Annual growth estimates between 6 m3/ha and 12 m3/ha are conservative, at least for public plantations. Thecurrent average yields for all public and private plantations are greater than 14 m3/ha for the southem region and 11m31ha for the central region. Smallholder yields may be less and they may pull the regional averages down.

Annex 8Pase 5 of 13

- 119 -

17. For technical purposes, this means that the analytical modelfirst searches for the demand price that yields a demand quantity equalto tr.e current (1990) level of consumption. It then determinessustainable supply at this price and takes as much of this consumptionas possible from any year's available sustainable supply. Residualconsumption, if there is any, is taken from the residual stand ofindigenous forest. Higher prices induce more sustainable production andreduced harvest levels from the residual indigenous stand. Eventually,prices rise such that all harvests become sustainable, even at thecurrent level of annual consumption.

Analytical Results

18. Table 4 summarizes the results for each region -- and forsensitivity tests of the various demand and supply assumptions.

19. Table 5 shows the analytical results for one sample case, theSouthern Region with a base case supply elasticity of 12. This tablemay help show the adjustments occurring in various of our criticalparameters. Year 1 refers to 1990 with an indigenous forest stock of39,640,000 in, an urban household market clearing price of approximately120 KIm8, and regional demand of 4,031,000 ne originating mostly fromindigenous forest (3,556 n3 ) but including some sustainable plantationsupply (475 m). Demand remains conitant at the current level set byour policy/equilibrating rule. The indigenous forest is drawn down, ascut exceeds growth, for nine years. This drawdown occurs at an everdeclining rate, however, as the sustainable supply of plantation woodgrows and replaces more indigenous supply each year. By the tenth year,year 2000, sustainable production satisfies the full market demand.Further indigenous harvests become unnecessary. Price has risen toMX196 per in.

20. Botlh regional result sets are relatively insensitive toindependent tests for various sectoral demand elasticities and rates oftechnical change. The results for all sensitivity tests cluster around60-75 percent price increases in just over one decade, or about fourpercent annually. In just over one decade, sustainable tree plantingssatisfy the full market demand for wood. The notable regionaldifference in these demand sensitivity results shows up in the southernindigenous forest loss of approximately one-quarter of its currentstanding volume (from 42.6 to 30-32 million in) in the adjustmentprocess. Central Region indigenous forests dQcline by only eightpercent from their 1990 level (from 67.9 to 63-55 million te).

21. The regional result sets are more sensitive to variations insupply. The regional demand sensitivity cases use a supply elasticityof 12. This is the supply price responsiveness for private plantingsonly -- assuming 30 percent seedling survival, 2500 seedlings/ha, and 6me/ha annual yields. More realistic supply responses might include

Annex 8Page 6 of 13

- 120 -

better survival and greater annual yields. Therefore, the solution pathfor a moderately more responsive supply with an elasticity of 20 is alsoexamined. Table 4 shows that the more elastic supply causes theadjustment period to drop below one decade in both regions. Prices donot rise as much before they induce a sustainable yield from plantationsand the final indigenous stock is slightly larger in both regions.3

22. Changing the policy rule to allow demand and supplyequilibration at some decreasing level of annual physical yield would bemore in keeping with recent history and with economic expectations.This would decrease the adjustment period, and decrease the temporarydrawdown of indigenous forest. Changing the policy rule to allowequilibrium at an increasing level of annual physical yield would onlyextend the adjustment period. It may also increase the temporarydrawdown of indigenous stock during the adjustment period. In thislatter case, the regional forest economies would still go through aprocess of price increases inducing planting, but inducing somewhatlater sustainable yields.

23. In all realistic cases, for all demand and supply scenarios andall policy solution rules, Malawi's rate of deforestation tapers off,plantation harvests begin to replace harvests of indigenous trees, anddeforestation eventually disappears as an issue. Relative wood pricesdo increase, however, and the new plantings of introduced speciesprobably occur on higher quality and more accessible land than the oldindigenous forest.

24. Price increases are an indicator of greater potential socialburden. If per capita income grows at a rate greater than the rate ofwood price increase, then the wood pricn increase is no real burden. Ifincome growth is less than the relative wood price increase, thenincreasing hardship may be anticipated, particularly for the lowestincome households for whom wood energy for heating and cooking comprisea large budget share. Assuming an annual GDP growth rate of 4-5 percentand an annual population growth rate 3.5 percent, per capita incomegrowth of 0.5-1.5 is expected. Together with the projected wood priceincreases of 4 percent per annum for the next decade, these imply an

3 More realistic supply responses yet would include some Forestry Department and donor plantations yields, andan improved annual yield level, perhaps as great as 12 m3/ha. The results from our first two supply sensitivity analysesare impressive enough. Sensitivity analyses reflecting these final uncertain adjustments are unnecessary.

Annex 8Page 7 of 13

- 121 -

increasing wood price burden on Malawian society.4 Undoubtedly thiswill induce some conservation, some substitution to wood alternativesand, perhaps, some unanticipated technical change.

25. In sunmary, it appears that rising prices induce tree plantingand a largely sustainable wood supply, regardless of variations in ourdemand or supply aseumptions. In both the Southern and Central Regions,the drawdown of indigenous forests continues past the year 2000, but therate of drawdown slackeis. Indeed, our analysis projects only a smallincrement of additional deforestation in the central region. At least3/4 of the current indigenous forest will remain, even in the South,after the economy becomes more dependent on steady plantation yieldssometime before 2010.

4 The burden would be less for less conservative projection scenarios where seedling survival or annual plantationyields per hectare are greater; therefore, where supply price responsiveness Is greater. The burden would also be lessfor a less conservative policy adjustment scenario that allows diminished consumption in response to Increasing prices.Therefore, we have probably overestimated the annual rate of price increase and the anticipated equity problem.

-122- AIM= 8

Paae 8 of 13

FIGUR 1:. Forestry sector Supply AdDemand Kodel

Price/ms

McX (t+n) ( (+n)

Mc (t) _ +MCKi (t)

tt / \ ) D(t)

0 volume (m3)

Table 1: Household Demand Assumptions

ii _______ South CentLal

Urban householdstotal quantity: soli mO (firewood and 609,000 m3 425,000 .3

charcoal) wood equivalentprice (delivered to urban market) 120 K/r 3 168 K/3price elasticity .4-.7 5-.8income elasticity .6-1.10 .6-1.15at household income 123 K,mo. 130 K/mo.

income growth rate 5 x 52population growth rate 5.82 Z 7.30 Xrate of technical changein consumption 2-5 Z 2-5 Z

-ral householdsLotal quantity 2.914.000 w3 2.341,000 ml'price (comparable urban price) 120 K/43 168 K/r 3

price elasticity .7-1.0 .7-1.0income elasticity .3-.6 .3-.6at household income 63 K/mo. 63 K/mo.

Income growth rate 5.0 3 5.0 1population growth rate 3.09 2 3.05 1rate of technical change

in consumption 0-4 Z 0-4 Z

Refu&229 (?)

Table 2: Couercial Demand Assumptions

o South Central

obacce - Doles (construci)total quantity: solid"" equivalent 50,300 03 200,900 o9price of poles 99 K/r3 145.5 K/a3

price elasticity 0 0output elasticity * 0 production growth rate 3.5 Z 3.5 1rate of technical change 2-7 X 2-7 Sin pole cbnsumption

Tobacco - flue cured fuelwoodtotal quantity 73.100 m3 157,700 *9price of fuelwood 110 K/r3 153 K/r3

price elasticity 0 0output elasticity 0 0production growth rate 0 1 0 1rate of technical change 4-7 1 4-7 Z

Tea estates self sufficient

Non- tobacco construct iontotal quantity 279,000 o3 220,000 mgrowth rate 2.0 X 2.1 1

Solidwood productstotal quantLty 40,300 m 18,200 mgrowth rate (growth is in North) 0 X O X

Misc. village industriestotal quantity: urban 9,000 m3 6,300 o3

rural 56,400 r3 45,300 mWgrowth rate (offset by technical change

in brickuaking) 0 2 0 X

- Ien

Table 3: Supply AssumptLons

Plantations South SentraL

land-area (1990, total public & private) 29,100 ha 27,100 hastanding volume (1990) 2.74 miliLon rn 2.18 million u3volume growth (1990) 425,000 o3 311.000 .3

growth rate: mean and annual increment 6-12 m3/ha 6-12 *m/ha

volume price responseprivate 12-20 12-20total 120-144 120-144

plantation growth rate (ha)* private 2X 2 Xtotal 121 12 1

lndigenous forest

land area (1990) 848.700 ha 1,305,000 hastanding volume (1990) 42.6 mIllion mo 67.9 millilon m3current growth (1990) 596,000 m3/yr. 19122,00 m3/yr.growth rate 1.4 Z 1.65 X

hAricultural land conversion: assume all wood from land being converted to agriculture io usedin either household or comercLal consumption.

co

Table 4: Analytical Results

Demand Sensitivity

adjustmnt nltial final indiflous StoSW& satanabile 2unle private

Southern 9-12 yrs 120 t/)3 193-7 f/1.3 42.600 *2 30-32.000 a 425 wa 4.1-4,300* 9. 3 KIa 700 haCentral 12-15 yrs 166 ff1.3 256-312 f/.3 67.900 .' 63-65.000 s3 311 s3 3,4-3,500 S 3 7.3 be 575 ha

Sunnlv Sensitivity e. - 12. 20 !Southern 7-10 yrs 120 It/.s 174-96 ff/.3 42,600 m3 31-35,000 m3 425 a' 4,200 w' '9.3 ha 700 haCentral 8-14 yrs 168 K/a3 256-312 KJW3 67,900 .' 64-65.800 a 311 .' 3,500 a' 7.3 ha 575 ha

* in thousands

- 127. ARM 8Page 13 of 13

Table 5: Sample reaults: Southern region vith base case supply Tespone of 12.

-r Z" ; CK t W'- H Pr-CE DEMA,4; X

: 39,34"..6 355'. 76 596.4 '21.005 4031.0. 47 * . 249S1: 6.8 3,%,38.85 5S4.969 130.743 4031.01 962.l5r

35041.', 2e01.27 519.775 140.095 4031 1429.734 33383.7 2!52.22 490.634 149.076 4031.01 &4878.79

321-0.3 l720.73 467.372 157.706 4031.01 231U.286 3;^74.2 13Cb.98 449.825 166 4031 2725.0"'7 330804.8 907.254 437.839 173.975 40,11 3123.758 30712.3 523.742 *431.267 181.645 4031 35t7.Z59 30987.5 154.764 429.972 189.025 4031 3876.23

10 31421.3 0 433.825 196.128 4030.99 4231.411 31861.2 0 439.899 202.968 4031 4573.412 32307.3 0 446.057 209.558 4030.99 4900 .88*3 32759.6 0 452.302 215.908 4031.01 5220.4114 332-18.2 0 458.634 222.032 4031 5'26.6215 33683.3 0 465.055 227.94 4031 5822.01