WLI Regional Knowledge Exchange Workshop on Decision...

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WLI Regional Knowledge Exchange Workshop on Decision-support Tools and Models

23-27 September, 2013, Djerba, Tunisia

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Table of Contents Executive Summary .................................................................................................................................. 2

Introduction .............................................................................................................................................. 3

Strategic Approaches to Integrated Management of Water and Land Resources – Experiences of WLI

Partnering Countries ................................................................................................................................ 4

Tunisia .................................................................................................................................................. 4

Iraq........................................................................................................................................................ 6

Lebanon ................................................................................................................................................ 8

Palestine ............................................................................................................................................. 10

Jordan ................................................................................................................................................. 11

Yemen ................................................................................................................................................. 12

Egypt ................................................................................................................................................... 13

Expert Presentations on Selected Decision Support Tools and Models ................................................ 16

HidroMore .......................................................................................................................................... 16

Modflow ............................................................................................................................................. 17

Water Evaluation and Planning (WEAP) System ................................................................................ 18

Soil Water Analysis Tool (SWAT) ........................................................................................................ 21

CropSyst .............................................................................................................................................. 23

Soil Water Mass Balance Model and Optimization of Irrigation using Soil Water Sensors ............... 26

Field Visit ................................................................................................................................................ 27

Challenges to identify potential impacts of improved water productivity at larger spatial scales ........ 28

Information Dissemination ..................................................................................................................... 33

Economic analysis of improved water management techniques .......................................................... 33

Overview of WLI Annual Reporting and Workplanning ......................................................................... 34

Conclusion .............................................................................................................................................. 35

Appendix 1: Agenda ............................................................................................................................... 36

Appendix 2: Map for site visits ............................................................................................................... 40

Appendix 3: List of participants of the workshop .................................................................................. 41

Appendix 4: List of participants in breakout sessions ............................................................................ 42

Appendix 5: Outline for the Regional Knowledge Exchange on Decision-support Tools and Models ... 43

Appendix 6: Definitions of selected WLI FtF Indicators ......................................................................... 47

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Executive Summary

The goal of WLI is to improve the livelihoods of households and communities by pilot-testing

sustainable water, land use and livelihood strategies in selected benchmark sites of eight

participating countries for scaling up. Various decision support tools are used by partnering

countries to assess and identify the best strategies for sustainable management of water and

land resources, and present to policy makers.

The workshop created a platform for partnering countries to share their experiences with

various models for water and land management as applied in their specific context, discuss

challenges, explore compatibility and comparability of the various models used within the

WLI, and to assess their potential application to address regional water and land management

related challenges. Decision-making tools considered during the workshop include Soil and

Water Assessment Tool (SWAT), Water Evaluation and Planning (WEAP), CropSyst,

Aquacrop, Modflow, Hidromore, as well as economic analysis tools such as Cost-Benefit

Analysis for improved water management techniques.

The workshop was attended by WLI Team leaders and bio-physical team members from seven

partnering countries (Annex 3). Also in attendance was Dr. Srinivasan from Texas A&M

University (TAMU) one of the developers of SWAT. The thematic group on modeling, led by

Dr. Nahla Zaki from the National Water Resource Center (NWRC) of Egypt, was activated

during the workshop. The group is expected to encourage comparative research in cases where

there are similarities of models and contexts, promote collaboration among WLI partnering

counties including data sharing and making use of student exchange programs, facilitate

engagement of partnering US universities, and identify needs for capacity building.

The five-day workshop was also very useful in identifying common challenges that need

further research and recommendations to begin tackling them including challenges of scale

(national versus site specific data needs), uncertainty and variability especially as it applies to

downscaling climate data, inter-sectoral collaboration to assess water demand and use by

different sectors, and understanding complex water resource bases such as groundwater and

reusable water resources. Discussions of the challenges resulted in the identification of five

key topics for regional knowledge exchange as well as potential decision support tools that

could help address them (Table 7).

Future knowledge exchange workshops on the topic will build on the success of this workshop

and contribute to the advancement of scientific knowledge on modeling water and land

management strategies, as well as adaptation and application of various models to fit regional

bio-physical and socio-economic conditions.

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Introduction

The Water and Livelihood Initiative (WLI) organized the workshop in order to exchange

knowledge on decision support tools as instruments to validate and out-scale land and water

management strategies. Specifically the objectives included:

- Review available assessments of present and future water availability and use at the

watershed and basin-scale and identify scope for updates to reflect the full potential of

improvements in on-farm land and water management

- Inform regional decision-makers and other key stakeholders at the benchmark sites of

the relevance and potential further use of outputs from decision support tools to

evaluate options for improved management of land, water and livelihoods

- Stimulate knowledge exchange and research collaboration amongst WLI research

teams using and developing tools to support integrated water and land-use strategies

with key stakeholders

Discussions mainly focused on various decision-support tools that are currently used by

partnering countries, and the identification of alternative or complimentary models.

The workshop began with opening statements from Dr. Mohammed Ouessar (on-behalf of Dr.

Houcine Khatteli –Director General of IRA), Dr. Theib Oweis - Director of the Integrated

Water and Land Management Program (ICARDA), Professor Netij Ben Mechlia from INAT,

Dr. Nahla Zaki from National Water Resource Center (Egypt) representing the WLI thematic

group on Modeling, and Dr. Hamed Daly on-behalf of Dr. Ben Salem – Director General of

INRAT, and Dr. Caroline King – WLI Manager. Other participants included WLI team

leaders and bio-physical team members from partnering National Agricultural Research and

Extension Services (NARES) in Egypt, Iraq, Jordan, Lebanon, Palestine, Tunisia and Yemen;

Dr. Raghavan Srinivasan from Texas A&M University (TAMU), and selected scientists from

ICARDA‟s Integrated Water and Land Management Program (IWLMP). Participants from

Syria were not able to attend the workshop. Please refer to Appendix 3 for a complete list of

participants.

A brief presentation on the overall objectives of the workshop was given by Dr. King, who

emphasized the importance of using decision support tools to make watershed-level

projections of potential benefits of pilot tested water and land management strategies. The

tools, it was explained, can be used to influence policy makers by using current status of water

balance such as volume of water used or volume of water available, to predict future outcomes

with and without adoption of recommended water and land management practices (Figure 1).

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Figure 1: Excerpt from Dr. King‟s presentation

Strategic Approaches to Integrated Management of Water and Land

Resources – Experiences of WLI Partnering Countries

Discussions on strategic approaches to integrated management of water and land resources

were initiated by presentations from partnering WLI countries, and are summarized below in

the order of their presentations.

Tunisia

The Tunisian team presented on the three sites located in the south, central and northern part

of the country representing different gradients of aridity.

South Tunisia (Presented by Dr. Mohamed Ouessar, IRA): represents the arid site located in

Medenine/Tataouine where rainfall ranges between 160-200 mm from the east plain of Jeffara

to the central part in the mountain of Beli Khedache, and can be as low as 100 mm in the

western plateau of Dhahar. Land use in the area was characterized as covered with olives and

small scale irrigation in the East, fruit trees behind water harvesting structures in the center,

and the rangelands in the west. The team gave a broad overview of their research in the area

focusing on their experience in using HidroMore to model vulnerability of olive groves to

climate change, and AquaCrop to model effects of climate change on the production of citrus.

Follow up discussions focused on application of Deficit Irrigation (DI) for citrus trees and

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advantages of using AquaCrop. The team reported that they have found AquaCrop to be user-

friendly and a strong decision support tool to model water, crop growth and climate change as

it requires less data, accounts for carbondioxide (CO2), and salinity.

Central Tunisia (Presented by Dr. Hamed Daly, INRAT): The study site is located in Sidi

Bouzid which represents a semi-arid agro-ecosystem with about 220 mm of rainfall, hot dry

winds, and extensive dependence on groundwater resources (deep well) for drinking and

irrigation. The main source of agricultural income for the area is livestock, followed by

cereals, olives and cactus. Main challenge for farmers is high cost of inputs particularly animal

feed. The team uses CropSyst and Canadian GCM to project potential impacts of climate

change on production of selected crops. Follow up discussions focused on data collection

including amount and type of data required to use CropSyst. The team acknowledged the need

for historical data and also explained how additional data could be gathered by downscaling

climatic data and accounting for climate variability for precipitation.

North Tunisia (Presented by Dr. Asma Larsam, INAT): The site is located in a semi-arid area

with a relatively higher level of annual rainfall ranging between 350-450 mm. 85% of the

national citrus production is from this region and heavily relies on ground water extraction

through private wells or surface water purchased by farmers from the public water network.

The team is promoting Supplemental Irrigation (SI) and other strategies to manage rainfed

agriculture. They use AquaCrop to model water productivity and harvest index HI for cereals,

CropSyst and empirical relationships between yields and total water reduction for citrus, and

GR/SWAT to model runoff following adoption of various water management strategies.

Follow up discussions focused on the benefits of each model and the need to model changes in

water, CO2 and other parameters. The Egyptian team has offered to share their experience

with the team regarding model selection criteria.

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Iraq (Presented by Dr. Bassam Kanaan Abdul Jabbar)

The Abu Ghraib benchmark site, located west of Baghdad, represents an irrigated benchmark

site with an average rainfall of about 123mm/year. As in the case of most irrigated areas in the

region, water demand at the site exceeds the supply (Figure 2). According to Dr. Jabbar, 80%

of the irrigation water comes from the network, 17% from wells, and the remaining 3% from

drainage water.

Figure 2: Rate of flow in Abu Ghraib scheme during the period 2005-2013(m3/sec) –(An

excerpt from Dr. Jabbar‟s presentation)

Achievements over the past two years were summarized as follows:

Increased water productivity and yield due to changes in the number of irrigation

during filling stage (Figure 3)

Increased yield in eggplants (Solanum melongena L.) and cauliflowers grown under

subsurface drip irrigation as compared to those grown under surface drip irrigation and

furrow or traditional irrigation practices. Increase in yield and water productivity for

cucumbers and tomatoes grown under protected agriculture (Greenhouses) with

monitored application of foliar amino acids, organic extracts

Improved water productivity of Berseem, a forage crop, due to application of amino

acids and organic extracts.

Calculated gross margin per ha for a number of crops including wheat, barley, sheep

and various vegetables

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Figure 3: Water Productivity of vegetables and crops – kg/m3 (Excerpt from Dr. Jabbar‟s

presentation)

Follow up discussions highlighted the need to report on levels of water productivity with and

without application of improved technologies, and adding a time frame for the gross margin

calculations as these are bound to change with changes in price, etc. The team was also

encouraged to step up their efforts in using extension to disseminate pilot-tested and proven

technologies.

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Lebanon (Presented by Dr. Ihab Jomaa and Eng. Randa Massaad from LARI, and Dr. Hadi Jaafar

from AUB)

The El Qaa benchmark site in Lebanon represents a rainfed agro-ecosystem. The team

reported on two major activities including:

- Investigation of water availability at the benchmark area, and water distribution

schemes analysis study (Figure 4),

- NDVI and FOV temporal and spatial changes during the 21st century – A GIS and

Remote Sensing (RS) approach

- Irrigation/rainfed (micro level water harvesting) strategies including najarims micro

catchments and Semi-circular bunds

Figure 4: Water sources for El Qaa Village (An excerpt from Dr. Jomaa‟s presentation)

Dr Jaafar presented a GIS and RS based appraoch to assess Net Difference Vegetation Index

(NDVI) and Fraction of Vegetation (FOV) temporal and spatial changes during the period

2000-2013. The study area in Qaa covered 17,838 ha and used Landsat 5, 7 and 8 as data

source (Figure 5).

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Figure 5: FOV Time Series-Mean and Std. Dev. (An excerpt from Dr. Jaafar‟s presentation)

Based on the study, Dr. Jaafar concluded that an increase in fraction of vegetation cover (due

to agricultural land expansion) will result in an increase in evapotranspiration and less

downstream flow to lower parts of the Orontes.

The third presentation was made by Eng. Massaad and focused on the team‟s efforts to

demonstrate the benefits of using conservation agriculture or zero-tillage as compared to

conventional practices. On-farm pilot testing of conservation agriculture was carried out on 2

dunum of land and compared with 2 dunum of land under conventional farming practice. The

fields were planted with durum wheat (Lahn). Preliminary results of the study showed higher

numbers of seed, biomass and straw collected from the field with zero-tillage. The team is

currently putting together a booklet to disseminate their findings.

Follow up discussions focused on difficulties related to trans-boundary characteristics of the

benchmark watershed as well as security problems related to the situation in neighboring

Syria.

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Palestine (Presented by Dr. Mohamed Selmyah)

The presentation focused on pilot tested land and water management strategies in the

rangeland and rainfed benchmark sites of Tammun and Adaherya (in Hebron). These included

construction of various water harvesting structures and development of suitability maps to

identify appropriate areas to out-scale pilot tested water and land management strategies. The

team also developed land use/land cover analysis of the benchmark on the basis of which they

classified the land as agricultural, natural, urban, and industrial areas (Table 1).

Table 1: Land use/Land cover classification for the WLI benchmark sites of Taman and

Hebron (An excerpt from Dr. Selmyah‟s presentation)

Land use/Land Cover Class

Benchmark sites

Tammun Hebron

Dunum % of total Dunum % of total

Arable land 5439 21.06 10871 41.11

Inter cropping agricultural areas 322 1.24 0 0.00

Permanent crop 466 1.80 770 2.91

Plastic houses 1 0.01 2 0.01

Agriculture 6228 24.1 11643 44

Open spaces with little or no vegetation 17758 68.74 13629 51.54

Shrub and/or herbaceous vegetation

associations 1595 6.17 0 0.00

Forests 0 0.00 34 0.13

Natural land 19353 74.9 13663 51.7

Palestinian Built-up Area 134 0.52 868 3.28

Israeli Military Base/Settlements 116 0.45 6 0.02

Wall zone 0 0.00 10 0.04

Urban Fabric 249 0.96 884 3.34

Industrial, commercial and transport unit 1 0.00 3 0.01

Mine, dump and construction sites 0.45 0.00 249 0.94

Total area 25832 100 26442 100

Security challenges related to accessing different areas outside of “Zone C” was highlighted as

a major challenge.

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Jordan (Presented by Dr. Yasser Mohawesh)

WLI in Jordan operates in the Muhareb watershed in the Jordanian Badia (Mejedeyae) that is

characterized by very low but high intensity average annual rainfall that cause runoff and

erosion. Various water harvesting technologies including contour ridges, check dams, sub-

surface dam, vallerani, and marabs are pilot tested at these sites to optimize the benefit of

available rainwater for crop production, recharge aquifers, and to reduce soil erosion. The

team is trying to adapt the SWAT model, originally designed to capture land cover impact

with weather, soil, topography, and vegetation data within the context of large-river basins, to

estimate the effect of water harvesting on the reduction of soil erosion and runoff in arid

conditions (Figure 6).

Figure 6: Parameters modified in SWAT to fit arid conditions (An excerpt from Dr. Yasser‟s

presentation)

The team is still collecting data for the SWAT model at four sites with four different water

harvesting techniques and is twigging the model to develop a robust model that can be scaled

out in similar areas in the region. Preliminary results indicate that the water harvesting

interventions are reducing soil runoff, and erosion. Follow up discussions focused on the

research time needed to build the model, and preliminary results generated to date. The team

explained that modeling will help select appropriate sites for application of different water

harvesting interventions, and to monitor runoff and sediments from areas with and without

intervention.

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Yemen (Presented by Dr. Khader Atroosh)

WLI in Yemen operates in two wadies within the Delta Abyan – Wadi Bana and Wadi Hassan

– where floods draining from the two catchments serve as the main source of both surface and

ground water resources. Water and land management strategies for the area are devised based

on multi-secotral collaboration involving both the public and private sector in the area. To date

the team has assessed water resources based on 60 years data on water flow (Table 2), updated

soil and land use classifications, and has prepared land suitability maps for the main crops in

the area. The team has also managed to improve production of forage (lipid and sorghum) by

promoting supplemental irrigation of spate irrigated fields. Follow up discussions focused on

the importance of having a good understanding of water balance in the benchmark site and

challenges in accessing historical data. Importance of collaborating with relevant ministries

and other governmental institutions working in the area was emphasized as a strategy to

strengthen data mobilization efforts.

Table 2: Overall Water Balance in the Abyan Delta (Excerpt from Dr. Atroosh‟s presentation)

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Egypt (Presented by Dr. Samar Atthar)

WLI in Egypt operates in three irrigated sites located in the Old, New and Salt affected lands

within the Nile Delta. The team strives to improve water productivity by introducing improved

water and land management strategies based on a sound understanding of the irrigation system

(about 200 years old). Over usage of water is a common problem in Egypt often exasperating

on-farm salinization problems. According to Figure 7 below the Water Use Index (WUI) is

greater than 1 in both Habib and Sabia mesqas indicating higher volume of water use as

compared to actual demand at the tertiary levels.

Figure 7: Assessing sustainability of the irrigation system (Excerpt from presentations made

by the Egypt team)

Current research activities are thus focused on modeling the sustainability of the irrigation

system, particularly looking at the gap between on-farm irrigation management and general

irrigation network management; analysis of on-farm soil degradation due to farmers‟ irrigation

and land management practices; and assessing effects of water constraint on crop selection and

subsequently farmers‟ income in the New Land. The latter is a collaborative research with the

International Water Management Institute (IWMI).

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The team is using Water Productivity (WP) Optimizer, an integrated modeling framework to

analyze water productivity and environmental impacts of irrigation practices starting from the

field-scale and progressing to the scale of tertiary canal irrigation zones. The model was

selected based on rigorous selection criteria that compared eight related models (Table 3). WP

Optimizer is developed and coded by VB.Net using ArcGIS 10 tools for Windows 7. The

model covers the entire tertiary canal system and is fed by two other models that assess - (i)

on-farm irrigation networking, and (ii) SaltMed – an on-farm water management model

developed by (Ragab 2002) as a generic model that can be used for a variety of irrigation

systems, soil stratifications, crops and trees, water management strategies (blending or cyclic),

leaching requirements and water quality. WP-Optimizer model can thus assess three levels of

water productivity – on-farm, small canal or mesqa level, and tertiary level (Figure 8). Among

the expected outputs of the model are data on current water usage including water used by end

users, water used for groundwater recharge, water lost in irrigation system, and drainage water

(quantity and quality).

The team plans to include branch canals in its next calibration of the model. Plans to use

AquaCrop to model and study effects of applying deficit irrigation on major field crops and

potential effects of climate change in the old land was also proposed.

Table 3: Criteria used for selecting most suitable on-farm model (Excerpt from presentations

made by WLI Egypt team)

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Figure 8: WP-Optimizer structure and theoretical basis (Excerpt from presentations made by

WLI-Egypt team)

Follow up discussions focused on the following key points:

Assessing sustainability of irrigation – what do we mean by it and what is the best way

to do it? It was agreed that what can be assessed is the sustainability of the „irrigation

system‟.

Model selection: the advantages and risks of building new models. It was agreed that

the added value of modeling should be clearly articulated, and the output usable to

influence policy makers.

Importance of conducting multi-sectoral research that equally engages socio-

economists, hydrologists, the community, etc. to establish a good understanding of

social and cultural conditions that influence irrigation practices, and to ensure that our

findings/recommendations are transmitted and adopted.

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Expert Presentations on Selected Decision Support Tools and Models

HidroMore Potential contributions on use of HydroMore model in olive groves vulnerability to climate

change

Ms. A Hachani, Dr. M. Ouessar, and A. Zerrim (IRA)

Thirty percent of arable land in Tunisia is used to grow olives a major contributor to the

national GDP. However, olive trees are very sensitive to climate change.

Ms Hachani presented a case study conducted in the watershed of Oum Zessar, Medenine

(South East Tunisia) where she used HidoMore to develop climate change induced adaptation

strategies for olive trees. HidroMore is a hydrological model for operational estimates of

recharge and actual evapotranspiration based on water balance equation.

Parameters of the model were based on previous studies while actual calibration was based on

other models including- Geophysical Fluid Dynamics Laboratory (GFDL) used to simulate

and improve understanding and predictability of the behavior of the atmosphere and HiRAM

C 360 – a GFDL Global High Resolution Atmospheric model. Normalized Difference

Vegetation Index (NDVI) images downloaded from USGS were also used after geometrical

and atmospherically corrections.

The modeling exercise revealed that in comparison with the reference period (1996-2005) the

years 2030 and 2090 will experience an increase in temperature (1°C) and (5°C), rainfall will

decrease by (5.4%) and (20%) respectively. Reference Crop Evapotranspiration (ET0) will

increase by (3%) and (9%), and crop evapotranspiration under non-standard conditions

(ETCadj) will reduce by (2%) and (18%) respectively. Thus, it is expected that suitable land

for olive cultivation will shrink and the cropping system become increasingly problematic and

unsustainable.

Follow up discussions focused on data selection and extrapolation, particularly daily NDVI

data that can be inferred from one-point monthly data. The practicality of using NDVI data for

baseline in climate change simulations was questioned because NDVI will change in time as

plants adapt to new climatic conditions. The possibility of using supplemental irrigation to

increase water availability for existing olive groves while discouraging expansion into

marginal lands was also discussed. Participants were encouraged to carefully consider data

limitations and the added value of using a particular model before investing their time and

resources in calibrating a model.

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Modflow Modflow utilization for the management of Saharan aquifers

Prof. Mounira Zammouri - Faculty of Sciences of Tunisia(FST)

Modflow is a modular finite difference groundwater simulation model code developed by the

US Geoplogical Surveys (McDonald and Harbaugh 1988) on the basis of which several

softwares including Visual Modflow, Processing Modflow, GMS, etc. were developed.

Prof. Zammouri presented on the application of Modflow piloted by the “Observatoire du

Sahara et du Sahel (OSS)” to assess the impact of the long-term (2000-2050) implications of

existing and planned water extraction plans for the Saharan aquifer also known as Système

Aquifère du Sahara septentrional (SASS). The groundwater resource basin is shared by

Algeria, Tunisia and Libya (Figure 9). The model was calibrated for the period 1950-2000 in

order to adjust for geological and hydrological system parameters on the basis of which the

simulation model was extended to the year 2050 with various management alternatives

modeled according to the planned extraction projects in the three countries. Assessment of

current and projected levels of abstraction and recharge indicate that water outflow far exceeds

rate of inflow. Implications of this imbalance were also seen in increased level of salinity,

vanishing natural springs, degradation of groundwater quality. Based on the findings, the

study recommended that immediate measures be taken to limit salinization including –

revising planned extraction projectes in the south of the Nefzawa region, increasing irrigation

efficiency, and implementation of effective drainage measures.

Figure 9: Groundwater basin shared by Algeria, Tunisia and Libya (Excerpt from Dr.

Zammouri‟s presentation)

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Follow up discussions focused on challenges of measuring recharge as well as the benefits and

challenges of conducting cross-boundary research. For this particular case it was explained

that the current rate of recharge is already negligible and is not expected to increase

considering anticipated reduction in rainfall due to climate change.

Water Evaluation and Planning (WEAP) System Dr. Vinay Nangia (ICARDA) –Introduction and Application

WEAP is a GIS based integrated water resource planning system that uses graphical drag and

drop interface. It uses basic physical simulation of water demands and supplies but can also

accommodate additional user-created variables and modeling equations (Figure 10). It has

scenario management capabilities and can be linked with spreadsheets and other models. The

modeling process begins with defining the study area and time steps for analysis, creating the

current account, creating a future scenario, and evaluating the results. The model has a number

of elements that require data entry and calibration (Table 4).

Figure 10: WEAP system elements (Excerpt from Dr. Vinay‟s presentation)

WEAP is a very useful model to conduct high level planning and strategic analysis at local,

national and regional levels; to model demand management, and prioritize water allocation.

However, WEAP is not a practical tool for daily operations and does not calculate least-cost

optimization of supply and demand. Examples of areas where WEAP offers a comparative

advantage include sectoral demand analyses, establish water rights and allocation priorities

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simulate groundwater and streamflow, track pollution, etc. WEAP can thus be used to assess

vulnerability and predict adaptability including vulnerability of water supplies to different

demographic, technological and climatological changes; and project alternative policy

scenarios for demand and supply management, predict implications for multiple and

competing demands on water systems, and evaluate policy outcomes.

Table 4: Water Demand-Shortage (Excerpt from Dr. Vinay‟s Presentation)

Various methods of estimating demand were also discussed including the per capita “unit”

water use method, agricultural demand (soil, plant, climate, and irrigation), and urban demand

(urban indoor and outdoor). On the supply side the model considers rivers, groundwater,

diversions (e.g. canals and pipelines), reservoirs and others, including desalination.

Participants were encouraged to look into the evaluation version of the model which is freely

available at http://www.weap21.org

Follow up discussions focused on data needs and adaptability of the model. Participants were

assured that the model is indeed user friendly and does not require a lot of data but generates

outputs that can readily be used by decision makers.

http://www.weap21.org/

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Dr. Vinay also provided a practical example on how the model can be used for different

analysis using a study by Droogers et.al (2012)1 where SWAT was used to reflect on Water

Scarcity and Adaptation Options for 22 countries in the MENA Region (Water Outlook 2050).

The study, though at a general level, aimed to analyze detailed water supply and demand for

the years 2010-2050, and identify potential options to overcome water shortage. Data on water

availability (streams, reservoirs, groundwater) and needs (irrigation, domestic, and industry)

were combined with results from selected climate change and hydrological models and fed

into the WEAP model to analyze supply and demand options based on anticipated water stress

levels. The direct outputs of the model i.e. economic evaluation of the supply and demand

were used to identify potential adaptation strategies, estimate the cost of „adaptation‟, and

inform policy makers and end users of the resource.

Follow up discussion focused on challenges in accessing country specific data. Dr. Nangia

informed participants of the database on present land and water use for all countries that can

be accessed through PCR-GLOBWB. The data, however, will need to be complemented with

country specific datasets and more accurate data points.

1 Droogers, P., Immerzeel, W.W., Terink, W., Hoogeveen, J., Bierkens, M.F.P., Van Beek,

L.P.H., Debele, B. (2012) Water resources trends in Middle East and North Africa towards

2050 Hydrol. Earth Systems Science, 16, 3101–3114.

http://www.scopus.com/authid/detail.url?origin=resultslist&authorId=7003974605&zone=








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Soil Water Analysis Tool (SWAT)

Connecting SWAT to other models to identify impacts of land management on

productivity and water use in evapotranspiration, groundwater recharge and surface

runoff

Dr. Raghavan Srinivasan (TAMU) and Dr. Feras Ziadat (ICARDA)

SWAT is a product of over 40 years of model development by the United States Department

of Agriculture (USDA). It is a daily time step distributed model that divides study areas into

Hydrologic Response Units (HRUs) based on soil, slope and land use (Figure 11). It is most

widely used to assess water quality, water supply, climate changes and landuse change.

SWAT is a continuous watershed simulation model originally built to capture land cover

impact with weather, soil, topography, and vegetation data within the context of large river

basins in semi-arid areas. SWAT has algorithms to simulate weather, hydrology,

sedimentation, plant growth, nutrients, pesticides, management, and bacteria.

Figure 11: Hydrologic Balance in SWAT (Excerpt from Dr. Srini‟s presentation)

Dr. Srini presented on the international applications of SWAT referring to a number of studies

conducted in various countries. Among the studies presented were the use of SWAT for flood

and drought prediction in Africa, and its application in Iran to assess the feasibility of applying

the „virtual water trade strategy‟ to alleviate water stress in the country.

Adaptability of SWAT to respond to land use changes overtime, applicability of the model for

small scale research studies, and its ability to predict sedimentation were questioned during

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the discussion session. Dr. Srini assured all that the model does accommodate all the concerns

and also spoke of a SWAT-Modflow hybrid which is now available to researchers worldwide.

Dr. Feras‟ presentation focused on the application of SWAT in Jordan giving participants a

more specific and detailed look into the model. Dr. Feras highlighted the challenges of

adopting the model to evaluate water harvesting systems in an arid environment. He spoke of

on-going research to modify the existing SWAT database and parameters to accommodate

biophysical conditions in arid areas including high intensity, sporadic, low rainfall that result

in extensive runoff and soil erosion. Dr. Feras explained that his research team is trying to

model the benefits of water harvesting interventions in the Jordan Badia including

groundwater recharge, decreased runoff, increased crop yield, and decreased erosion which

are not easily quantified. Dr. Feras explained that his research team is now trying to introduce

a new land use class in SWAT model for contour ridges, modified curve number, and heat

unit. So far the team have collected 2 years‟ worth of data on soil erosion and hope to replicate

the study in other similar environments within the MENA region.

23

CropSyst Improving water productivity in response to climate change: Setting targets

Dr. Maria Glazirina (ICARDA)

Dr. Maria‟s presentation focused on modeling water balance and water productivity using

CropSyst. The model is a multi-year, multi-crop, daily time step cropping systems simulation

model originally programed by Prof. C. Stöckle and R. Nelson (Figure 12). The model is

freely available and can be accessed through

http://www.bsyse.wsu.edu/CS_Suite/CropSyst/index.html

Figure 12: Input-output influxes in CropSyst (An excerpt from Dr. Glazirina‟s presentation)

It is based on the understanding of management interactions between plants, soil and weather

including phonological development, photosynthesis and growth, stress effects (water, N, salt,

and potassium), as well as root water uptake. The crop and soil processes in CropSyst are

presented in Table 5 below.

http://www.bsyse.wsu.edu/CS_Suite/CropSyst/index.html

24

Table 5: Crop and soil processes in CropSyst (Extracted from Dr. Glazirina‟s presentation)

Crop Processes in CropSyst Soil Processes in CropSyst

Development

growth

light interception

net photosynthesis

biomass partitioning

leaf expansion

roots deepening

leaf senescence

water uptake

nitrogen uptake

water stress

nitrogen stress

light stress

water infiltration

water redistribution

runoff

evaporation

percolation

solutes transport

salinization

nitrogen fixation

residues fate

O.M. mineralization

nitrogen transformations

water erosion

amonia volatilization

ammonium sorption

The model provides:

generic crop-growth component as it allows adaptation/calibration to any crop, and

species and cultivars are characterized by a set of parameters which determine crop

response to the environment

link to the GIS-software Arc/Info (spatial application)

user-friendly reporting format for outputs such as MS-Excel and flexibility in levels of

reporting e.g. daily, seasonal, annual or topical

fast graphics viewer, and

CropSyst is very well documented, maintained and regularly updated. Moreover, the model

considers the influence of soil salinity and shallow groundwater table, allows using a finite

difference solution of Richard‟s equation to simulate water transport, and handles conservation

agriculture features (to some extent). Data requirements from the model include various soil,

weather, land management practices, crops, and water sources. Please see Figure 13 below for

more information on specific features of the data required.

25

Figure 13: CropSyst data requirements (An excerpt from Dr. Glazirina‟s presentation)

Among other things, CropSyst can also calculate water balance, model crop growth under

different climate scenarios.

I. Water Balance: Water balance is calculated by using precipitation and irrigation as

incoming water and Evapotranspiration, infiltration of water and surface runoff or surface

drainage as outgoing water balance components. Various evapotranspiration models including

Penman-Monteith and Priestly-Taylor were discussed. Approaches to estimate surface runoff,

models to estimate soil water infiltration and redistribution (cascade and finite difference), and

soil hydraulics were also highlighted during the presentation.

II. Crop Growth: CropSyst models crop development i.e. the progression of a crop

through phonological stages through Growing Degree Days (GDDs) that govern crop

development and taking into account temperature, photoperiod, vernalization, and water

stress.

III. Climate change impact assessment: CropSyst can calibrate and evaluate crop grown

under currently prevailing climatic conditions in a selected agro-ecosystem and model the

impact of climate change on the crop‟s productivity using various climate change scenarios

including daily time-step weather data. The model also has the capacity to account for crop

growth (CO2 response), as well as water and temperature stress. This was demonstrated using

a case study on wheat grown in Central Asia.

Follow up discussions focused on challenges in accessing required data including daily

weather data, ability of the model to accommodate salinity and its potential effect on drought

and plant growth. The model was endorsed as being especially useful for modeling on-farm

water management practices within the context of irrigated agriculture.

26

Soil Water Mass Balance Model and Optimization of Irrigation using Soil

Water Sensors (Presented by Dr. Srini on behalf of Dr. Ashok Alva)

The presentation focused on an advanced on-farm irrigation measuring tool that can monitor

continuous real time soil water content such as Capacitance Probes. The technology is a Low

Energy Pressurized (LEP) system for irrigation and can be used to assess soil water content for

trees, vegetables and row crops like corns, soy beans etc. The probes can be spaced across

different spans and depth with minimal disturbance to the soil to determine the amount of

water applied and how much of it is retained in the soil. It is thus a very useful tool to assess

irrigation efficiency at the individual sensor level. Information from the data logger can be

accessed through telemetry, USB, or can even be linked to the irrigation system to regulate

irrigation scheduling. The probe offers various levels of data output ranging from real time

data per sensor or a group of sensors. The capability of the sensor was demonstrated through

case studies that used EnviroSCAN probes for potato in USA and for date palms in Kuwait.

Follow up discussions focused on accessibility and affordability of the technology for research

use by WLI partners. It was agreed that researchers should explore all options to determine the

right instrument taking into account its cost, simplicity, benefits it offers, environmental

sustainability, etc.

27

Field Visit

A field visit was organized by IRA offering participants an opportunity to see selected water

harvesting and irrigation management practices under field research. The visit began with a

brief presentation of IRA‟s research work in Tunisia and a tour of the Head Quarters. The

team was met and welcomed by Dr. Houcine Khatteli, Director General of the Institute. Other

site visits included irrigation management in Bedoui, Gabion check dams and recharge of

wells in Koutine (Figure 14), traditional Oasis in the mountains at Ksar Hallouf and water

harvesting in Ain El Anba.

Figure 14: Field visit of research on recharge of wells in Koutine

28

Challenges to identify potential impacts of improved water

productivity at larger spatial scales (i.e. landscape and watershed scales)

and over suitable time periods (1-year, 2-year, 5-year, 10-year)

The session was initiated by a short recap of progress and remaining challenges in identifying

potential impacts of improved water productivity at larger spatial scales presented by Dr.

Caroline King. Remaining challenges and proposed solutions were briefly discussed (Table 6).

Key challenges for future regional knowledge exchange were also discussed during this

session (Table 7). Please also refer to excerpts from Dr. Caroline‟s presentation below –

Figures 15 and 16.

Table 6: Summarized list of challenges and Modeling Options as presented by Dr. King

Predicting Future Water Productivity

Remaining Challenges Modeling Options

Scale Challenge

Diversity of land and water

conditions and qualities

Diversity of cropping patterns

Integrating crops and livestock

Other uses of water

Water reuse

Definition and measurement of

water consumption

(economic aspects, prices, future

uncertainties)

GIS

GIS and SaltMod

CropSyst

Work with economists

Work with farmers

Define our approach following

FAO 66

Assessment of Water Balance

Remaining Challenges Modeling Options

Integration of WLI data elements

Scale challenges

Temporal challenges for prediction

of future water availability

Uncertainty, variability and data

access (real and perceived)

Inter-sectoral cooperation

Some water sources less understton

i.e. groundwater, reusable

wastewater

Assess state of knowledge and gaps

Scale down from national water

balance assessments

Scale down from climate change

assessments

Use statistical techniques to fill

gaps and account for

uncertainty/variability

Refer to existing applications of

WEAP, enhance and contribute

Use SWAT to deepen

understanding of complex processes

in soil and water

29

Table 7: Key Challenges for future regional knowledge exchange (summarized from Dr.

King‟s presentation)

Key Topics Decision Support Tools to be explored

Modeling climatic effects in cropping systems including

trees (global climatic changes and regulation of the

microclimate for improved soil and crop productivity)

AquaCrop and Crop Syst

Modeling surface-groundwater interactions in rainfed

and irrigated agroecosystems

SWAT and Modflow

Assessing water productivity in integrated crop and

livestock systems

SaltMed & Economic Models

Improved land use CropSyst, Aquacrop

Modeling water productivity in saline conditions SaltMed

Reaching Decision Makers (cross-cutting for all) WEAP, cost-benefit analysis

For this session participants were divided into 2 groups with one group covering the irrigated

systems (led by Dr. Srini, TAMU) and the second group focusing on rangeland and rainfed

agro-systems (led by Drs. Feras Ziadat and Vinay Nangia ICARDA). Discussions focused on

the following points:

Research achievements over the past year at the country level and plans for 2014

Identification of common challenges and approaches to resolve the issue

Identification of opportunities for potential collaborations

Figures 15 and 16: Excerpts from Dr. Caroline‟s presentation

31

I. Irrigated agroecosystems – these included Iraq, Yemen, Tunisia, Lebanon and Egypt

Table 8: Achievements, workplans for 2014 and challenges for WLI partners under irrigated agroecosystems

WLI

Country

Achievements Workplans for 2014 Challenges/Needs

Iraq – Abu

Ghraib

Field experiments on various irrigation techniques

(supplemental, subsurface and drip irrigation) to assess

their effect of water productivity of selected crops and

vegetables including wheat, maize, tomato, cucumbers,

cauliflower and bersim.

Activities will focus on growing different crops such as

barley with the same irrigation system

Connecting pilot site technology to the

calculation of water productivity at

benchmarks level, selecting suitable

decision making model for their area,

convincing decision makers, collaboration

with other WLI teams.

Yemen –

Abyan Delta

Completed bio-physical characterization including land

use planning. Supplemental irrigation was also used to

increase yield and improve water productivity for

cotton, sesame, banana and papaya

Continue land use planning, transfer of technology to

farmers (field days) and communicate success with

decision-makers, and select appropriate models for

decision making.

Training in GIS and modeling to improve

land use planning, and downscaling

climate data.

Tunisia Field experiments are underway to assess effects of drip

irrigation on selected crops and vegetables grown in

sandy soil over relatively dry seasons. These include

potatoes, carrots, green beans and pepper. Experiments

were also conducted to assess the effect of deficit

irrigation and irrigation scheduling on improving water

productivity of citrus orchards in the South (Megarine)

and North (Beni Khalled). Moreover, the team is using

Aquacrop to model climate change impact and

assessing adaptation strategies on potatoes and wheat. y

Replicate experiments in farmers‟ fields –

demonstration plots, validate calibration of Aquacrop

to determine impact of CC on potato and wheat

production, develop field activities at the watershed

scale, improve communication strategies targeting

decision makers and other stakeholders. A workshop

for decision makers for the north, center and south plus

one on modeling will be organized in Tunisia.

The purchase of equipment (sensors) takes

time with ICARDA approval and this may

delay the introduction of irrigation

management based on real time soil water

sensors. The team needs suitable models

for heat, salinity and climate change and

workshop on modelling using Aquacrop

and CropSyst models

Lebanon Distribution efficiency of surface irrigation was

evaluated at two sites in Qaa, drip irrigation was used to

grow grapes and eggplants under deficit irrigation to

asses effects on water productivity. Furrow irrigation

was tested for wheat crop. Conservation agriculture and

supplemental irrigation were also launched.

Conduct trials on potato under drip irrigation using

mulching techniques and estimate evapotranspiration.

Introduce drought resistant varieties of tomatoes, and

use either WEAP or SWAT decision making models.

The team plans to organize 1 or 2 field days/workshops

and 1 or 2 publications

Training on modeling

Egypt The team has so far managed to monitor the irrigation

system and cropping patters, and is in the process of

building a model with the aim of improving water

productivity. Effects of farming practices on soil

compaction were also assessed.

Continue assessment & evaluation of the model for the

irrigation system focusing on downstream i.e. from

branch canals to farmers‟ fields, disseminate results of

soil compaction study, study causes of soil degradation

in the Old Land, use water productivity optimized

models for rice, alfalfa and other vegetables, improve

communication strategies with decision makers to

influence policy change on water use. Plan to have two

field days and national workshops.

Regional levels for modeling

32

II. Rangeland and rainfed agroecosystems: these include Tunisia, Palestine and Jordan

Table 9: Achievements, workplans for 2014 and challenges for WLI partners under rangeland and rainfed agroecosystems

WLI

Country

Achievements Workplans for 2014 Challenges/Needs

Tunisia

(Rangeland)

Progress in studying consumption of water in relation to

feed and exploring alternative livestock feeding options

Improve calibration & validation of CropSyst;

conduct cost benefit analyses of improved

technologies; introduce alley cropping of

olives and cactus (to increase feed availability

and reduce ET); estimate the effects of CC on

forage productivity and overall cropping

systems; collaborate with ICARDA (Dr.

Feras) on adapting SWAT in their watershed,

Establish a group of researchers to work on CC

(including partners from outside of Tunisia); lack

of information on ground water recharge – need

to work out best management of water flows

Jordan

(Rangeland)

Good progress in modeling SWAT and outscaling work

to be done in collaboration with UIUC; new shrubs

plated including vetches, barley, safflower, acacia and

artiplex; supplemental irrigation; erosion reduced at field

level,

Palestine

(Rainfed)

Tested new drought varieties of wheat (3) and barley (2);

capacity building in processing and packaging of cheese;

Lack of data required to calculate simple water

productivity; lack of resources to promote

adoption of improved technologies; water is

available at no cost to farmers;

Palestine

(Rangeland)

Conducted plant inventory to calculate biomass; pilot

testing different water harvesting technologies at suitable

sites selected by using GIS;

Assess financial feasibility of tested

technologies; introduce shrubs compatible

with introduced WH strategies; develop

strategies to influence; cost benefit analysis of

silage usage (project funded through FAO) in

order to upscale the strategy; prepare

extension brochures on silage, food processing

and water harvesting

Funding; activities limited to only Area C; lack of

data for modeling; need to include livestock in

their research

Projecting impact on water balance with and without improved water management practices Information Dissemination “Communicating potential impacts of improved water productivity on water balance at the

watershed scale to decision makers” by Prof. Mongi Sghaier (IRA)

Dr. Mongi‟s presentation focused on the importance of developing a sound communication

strategy that is based on the information needs of different stakeholders including targeted

decision makers, community members, farmers, etc. Direct engagement of scientists with

decision makers and end users of the research was emphasized as an essential foundation to build

trust, accountability and to demonstrate commitment. Importance of selecting appropriate

methods of communication including language to be used and mediums of communication were

also highlighted. Follow up discussions focused on various strategies that can be used to

disseminate research findings and methodologies to measure effectiveness of communication

strategies. In the case of the latter, it was agreed that appropriate indicators should be selected

and be part of the research plan.

Economic analysis of improved water management techniques

(Presented by Dr. Hamed Daly)

Dr. Daly‟s presentation highlighted the importance of using cost-benefit analysis to assess and

demonstrate private and social profitability (net benefits) of proposed water management

technologies to policy makers and potential end-users based on comparison of “with” and

“without” intervention scenarios. The challenges of quantifying impact, and predicting the

magnitude of annual incremental costs and benefits over the life span of the technology were

discussed, and alternative strategies to estimate benefits in economic terms explored. Dr. Daly

also explained the importance of discounting and conducing Sensitivity analysis to account for

risks and uncertainty. A general guideline to identify costs and benefits was provided (Table 10).

Table 10: Identification of costs and benefits (An excerpt from Dr. Daly‟s presentation)

Follow up discussions highlighted the need to consider qualitative benefits and explore other

multi-criteria analysis tools to make comprehensive assessments of accrued benefits.

34

Overview of WLI Annual Reporting and Workplanning (Ms Bezaiet Dessalegn)

An overview of the reporting guideline was presented by Ms Dessalegn the WLI Livelihood and

M&E Specialist. Different sections of the report were briefly discussed with particular emphasis

on expected reports on WLI selected Feed the Future (FTF) indicators listed below and detailed

under Annex 5:

Number of hectares under improved technologies or management practices as a result of

USG assistance

Number of farmers and others who have applied new technologies or management

practices as a result of USG assistance

Number of individuals who have received USG supported short-term agricultural sector

productivity or food security training

Number of food security private enterprises (for profit), producers organizations, water

user associations, women‟s groups, trade and business associations, and community based

organization (CBOs) receiving USG assistance

Number of stakeholders implementing risk-reducing practices/actions to improve

resilience to climate change as a result of USG assistance

Number of new technologies or management practices in one of the following phases of

development (Phase I/II/II representing work– under research/field testing/made

available for transfer)

Gross margin per unit of land, kilogram, or animal of selected product

Discussions also included definition of project beneficiaries, importance of gender and collection

of sex disaggregated data, and methods of summarizing FtF results across the quarters.

35

Conclusion

The five-day workshop was very useful in facilitating knowledge exchange on selected decision

making tools and water and land management strategies (including field visit to IRA managed

research sites on water harvesting and irrigation management), identifying common challenges

and seeking potential solutions to address them. The workshop was also very important in

identifying key topics for regional knowledge exchange. At the end of the workshop all

partnering countries confirmed that they will try to project cropping patterns, water volume, and

gross margins in their respective sites for the year 2014. The projection will be based on available

data and data to be generated in the near future.

The workshop ended with closing remarks from Dr. Nahla Zaki- leader of the WLI thematic

group on decision making tools, and Dr. King – WLI Manager. Dr. Nahla commended all

participants for their valuable contributions and expressed her confidence in continued

collaboration among the NARES, partnering US Universities and USDA. She offered a word of

encouragement to those who are building their own models and emphasized the need to explore

all other possibilities before embarking on such a rigorous task. The need to move to regional

scales through collaborative research on regional questions was also highlighted.

Dr. Feras encouraged all to tap into the expertise of US Universities through collaborative

research that could be done by graduate students from the region working with professors from

the US or vice versa. Dr. Srini confirmed his availability to provide guidance to the WLI team

should they require it. Dr. Monji stressed the importance of creating formal communication

channels among members of the thematic group and with the community to facilitate

collaboration to do comparative analysis and promote technology uptake.

Participants were encouraged to carefully consider the merits of each model, giving due attention

to their applicability in the context of specific agroecosystems, their compatibility and

comparability with other models, and the scale at which they will be most useful (field specific,

watershed scale, spatial and temporal, etc.). It was agreed that the team will explore livestock

analysis models as well as point scale models such as DSSAT which is currently used by

MAWRED across the region. Dr. Vinay was identified as a resource person for DSSAT.

36

Appendix 1: Agenda

WLI Regional Knowledge Exchange Workshop on Decision-support Tools and Models

23-27 September, 2013, Djerba, Tunisia Monday 23 September 8:00 – 9:00 Registration of participants 9:00 – 9:50 Opening session, Rapporteur: Dr. Vinay Nangia

Welcome address by Dr. Houcine Khatteli, Director General, IRA Statement by Dr. Theib Oweis, Director, Integrated Water and Land management Program (IWLMP), ICARDA Statement by Prof. Netij Ben Mechlia, on behalf of Director General, INAT Statement by Dr. Nahla Zaki, Thematic Group Leader Statement by Dr. Hamed Daly, on behalf of Director General, INRAT Overview of WLI and workshop objectives, by Dr. Caroline King, WLI Manager

9:50 – 10:00 Group picture 10:00 -10:30 Coffee break Strategic Approaches to Integrated Management of Land, Water and Livelihoods along an Aridity Gradient: Tunisia Chair: Dr. Nahla Zaki, (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Debra Turner 10:30 -11:30 Southern Tunisia

Central Tunisia Northern Tunisia

11:30 – 12:00 Discussions 12:00 – 13:00 Lunch Strategic Approaches to Integrated Management of Land, Water and Livelihoods at Different Levels of Aridity: Regional Chair: Dr. Hichem Ben Salem (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Mohamed Ouessar 13:00 – 14:00 WLI Iraq

WLI Lebanon WLI Palestine

14:00 – 14:30 Discussions

14:30 – 15:00 Coffee Break Expert Presentations on Selected Decision Support Tools and Models Chair: Dr. Theib Oweis (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Maria Glazirina 15:00 – 15:40 Hydromore – Dr. Ouessar et al. Modflow – Prof. Mounira Zammouri 15:40 – 16:10 WEAP – Dr. Vinay Nangia

37

16:00 – 16:40 Discussion Tuesday 24 September

Regional and International Exchange of Knowledge, Decision Support Tools and Models to Improve Integrated Management of Land, Water and Livelihoods Strategic Approaches to Integrated Management of Land, Water and Livelihoods: Regional Chair: Dr. Houcine Khatteli (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Hamed Daly 9:00 – 9:40 WLI Jordan

WLI Yemen 9:40 – 10:30 Discussions 10:30 -11:00 Coffee break Strategic Approaches to Integrated Management of Land, Water and Livelihoods: Regional Chair: Dr Netij Ben Mechlia, (12 minutes presentation and 8 minutes Q&A for each) Rapporteur: Dr. Maria Glazirina 11:00 – 13:00 WLI Egypt 12:00 – 13:00 Discussions 13:00 – 14:00 Lunch Challenges to set targets for effects of strategies under pilot testing on water productivity and water balance, Dr. Caroline King, WLI Manager Rapporteur: Dr. Debra Turner 14:00 - 14:30 Open Discussion 15:00 -15:30 Coffee Break Chair: Dr. Mohamed Ouessar Rapporteur: Dr. Vinay Nangia 15:30 - 17:00 Connecting SWAT to other models to identify impacts of land management on

productivity and water use in evapotranspiration, groundwater recharge and surface runoff (General overview and case study applications). Dr. R. Srinivasan, TAMU and Dr. Feras Ziadat, ICARDA

19:00 – 21:30 Group Dinner to be organized by IRA

38

Wednesday 25 September

Improving Agricultural Water Productivity in Response to Climate Change: Setting Targets Chair: Dr. Caroline King Rapporteur: Dr. Feras Ziadat 9:00 – 10:00 Technical Presentation including use of at least 2 crop-water productivity models

(aquacrop/CropSyst/DSSAT/EPIC) Dr. Debra Turner and Maria Glazirina 10:00 – 10:30 Coffee Break Short recap of progress and challenges to identify potential impacts of improved water productivity at larger spatial scales (i.e. landscape and watershed scales) and over suitable time periods (1-year, 2-year, 5-year, 10-year), Chair: Dr. Caroline King Breakout group discussion session of target setting by agroecosystem

10:30 – 12:30 Rangeland systems: Group Leader: Dr. Feras (rapporteur to be designated) Rainfed systems: Group Leader: Dr. Vinay (rapporteur to be designated) Irrigated systems Group Leader: Dr. Srini (rapporteur to be designated) 12:30 – 13:30 Lunch Reports on targets for improved water productivity at larger spatial scales (i.e. landscape and watershed scales) and over suitable time periods (1-year, 2-year, 5-year, 10-year) Facilitator: Dr. Theib Oweis (Reports 10 Minutes each) Rapporteur: Dr. Kamel Nagaz 13:30 – 14:00 Rangeland systems Rainfed systems Irrigated systems 14:00 – 15:00 Open discussion of methodological and data-related challenges for WLI Thematic

Research Group on Water Use Efficiency and Water Productivity 15:00 – 15:30 Coffee Break 15:30 – 15:45 Overview of WLI Annual Reporting and Workplanning Ms Bezaiet Dessalegn 15:45 – 16:00 Briefing on field visit Prof. Netij Ben Mechlia 16:00 – 16:30 Soil Water Mass Balance Model and Optimization of Irrigation using Soil Water Sensors.

Dr. Ashok Alva, USDA-ARS Facilitator: Dr. Caroline King Rapporteur: Dr. Mohamed Ouessar

39

Thursday 26 September

9:00 – 15:00 Field Visit. This will include:

Brief visit to IRA’s headquarters’ (missions, main programs, etc.) in the El Fjé Technological park

Field tour to visit some selected research sites of WLI Tunisia in the South of the country (WH, irrigation management)

Webinar event on the recently updated Feed the Future (FtF) Guide

08:00 Meet at the hotel lobby to take the bus arranged by IRA

Friday 27 September

Projecting Impact on Water Balance with- and without- improved water management Chair: Dr. Mohamed Ouessar Rapporteur: Dr. Maria Glazirina 9:00 – 9:40 Observations on challenges to identify potential impacts of improved water productivity

on the water balance at the watershed scale and communicate them to decision-makers Prof. Mongi Sghaier

Integrating hydrological and economic models of watershed management Dr. Hamed Daly Hassen 9:40 -10:00 Presentations and discussions on WEAP (general overview and case study applications). Dr. Vinay Nangia 10:00 -10:30 Discussions 10:30 – 11:00 Coffee Break 11:00 – 11:20 Conclusions for the WLI Thematic Research Group on Decision support tools and models

Group Leader: Dr. Nahla Zaki 11:20 – 13:00 Wrapping up and recommendations for improvement and finalization of regional and

country level research plans for WLI 2013-14 Dr. Caroline King Saturday 28 September

Participants depart to their respective destinations.

***********************

40

Appendix 2: Map for site visits

41

Appendix 3: List of participants of the workshop

42

Appendix 4: List of participants in breakout sessions

Break out group – Rangeland and Rainfed

Agroecosystems

Break out group Irrigated

Agroecosystems

Dr. Mohamed Annabi, Tunisia Dr. Nahla Zaki, Egypt

Dr. Hamed Daly, Tunisia Dr. Samar Attaher, Egypt

Dr. Mohamed Al Salimiya, Palestine Dr. Ibraheem Abderabdo, Egypt

Dr. Feras Ziadat, ICARDA Dr. Bassam Kanaan, Iraq

Mr. Awad Al Kaabnh, Jordan Dr. Ali Hasan Faraj, Iraq

Eng. Afaf Al-Madadha, Jordan Eng. Randa Massad, Lebanon

Mr. Monji Ben Zaied, Tunisia Dr. Ihab Jomaa, Lebanon

Dr. Yasser Mohawesh, Jordan Dr. Hadi Hfaar, Lebanon

Dr. Debra Turner, ICARDA Dr. Khader Atroosh, Yemen

Dr. Nasser Sholi, Palestine Dr. Nashwan Obeid, Yemen

Dr. Vinay Nangia, ICARDA Dr. Kamel Nagaz, Tunisia

Dr. Mohamed Ouessar, Tunisia Dr. Monji Sghaier, Tunisia

Dr. Caroline King, ICARDA Ms. Fathia El Mokh

Ms Asma Lasram

Ms Hachani Amal

Dr. Mariya Glazirina

43

Appendix 5: Outline for the Regional Knowledge Exchange on

Decision-support Tools and Models

Title: Regional Knowledge Exchange on Decision-support Tools and Models to

Project Improved Strategies for Integrated Management of Land, Water and

Livelihoods

22-27 September, 2013, Djerba, Tunisia

Purpose:

To identify scope for available watershed and basin-scale water balance assessments

to include scenarios demonstrating improvements in integrated management of

land, water and livelihoods to be achieved through upscaling of WLI pilot-tested

strategies and technologies

Objectives:

- Review available assessments of present and future water availability and use at

the watershed and basin-scale and identify scope for updates to reflect the full

potential of improvements in on-farm land and water management

- Inform regional decision-makers and other key stakeholders at the benchmark

sites of the relevance and potential further use of outputs from decision support

tools to evaluate options for improved management of land, water and livelihoods

- Stimulate knowledge exchange and research collaboration amongst WLI research

teams using and developing tools to support integrated water and land-use

strategies with key stakeholders

Key Words: Knowledge Exchange, Decision Support Tools, Models, Regional

Background:

The Water and Livelihoods Initiative (WLI) addresses the development challenge of

improving agricultural water management in water scarce agro-ecosystems in order to

address food security and improve rural livelihoods in the Middle East and North Africa

(MENA) region. This is achieved through pilot testing of integrated water and land-use

management strategies, focusing initially on selected benchmark sites, with the intention

of scaling up to larger areas where water scarcity, land degradation, water quality

deterioration, food security and health problems are prevalent.

Intended results from strategies pilot tested through WLI include reduced losses of

rainwater to runoff and evaporation; increased volumes of water retained in the soil for

uptake by crops, increased storage of water in cisterns, wells and aquifers for use in

irrigation (including supplementary irrigation and deficit irrigation); increased water

productivity of crops and livestock; increased on-farm income and improved livelihoods

of rural households at the benchmark sites. Use of scientific decision-support tools,

including Water Evaluation and Planning (WEAP), the Soil Water Assessment Tool

(SWAT), and other available tools to model future climate scenarios and crop-

productivity responses can help researchers to assess and communicate the current water

balance and potential future scenarios to communities of water users and other

stakeholders.

44

Economic assessments likely to convince national decision-makers of the merit of

outscaling strategies require decision-support model outputs that effectively quantify the

volumes of crops and livestock to be produced and valued, and the volumes water stored

and conserved. In some cases, decision-makers may also wish to know the volumes and

values of other additional ecosystem services that could be affected by different land and

water management strategies (eg soil organic carbon, biodiversity, etc). In heterogeneous

landscapes, Geographic Information Systems (GIS) can provide an effective means for

supporting and integrating these assessments on a strategic scale, and a strong visual

representation of changes to be anticipated.

Workshop Outline: (5 days)

Day 1: Strategic Approaches to Integrated Management of Land, Water and

Livelihoods in North Africa and the Middle East

- Opening Session including overview of WLI and workshop objectives

- 3 Selected WLI Country team presentations on national strategies, assessments and

models in target watersheds

-Presentations of WLI Tunisia (Overview and 3 site presentations)

-Presentation on 3 selected decision support tools and models

-Additional invited presentations on potential contributions on use of Hidromore,

Modflow and WEAP to refinement of water balance estimates (focus on water

availability)

Day 2: Regional and International Exchange of Knowledge, Decision Support Tools

and Models to Improve Integrated Management of Land, Water and Livelihoods

- 3 WLI Country team presentations on national strategies, assessments and models in

target watersheds

- Additional invited presentations on connecting SWAT to other models to identify

impacts of land management on productivity and water use in evapotranspiration,

groundwater recharge and surface runoff (General overview and case study applications)

Day 3: Improving Agricultural Water Productivity in Response to Climate Change:

Setting Targets

- Overview of WLI achievements in pilot testing strategies to improve water productivity

at field and farm levels and challenges of scaling up

- Achievements and remaining challenges in rangeland agroecosystems

- Achievements and remaining challenges in rainfed agroecosystems

- Achievements and remaining challenges in irrigated agroecosystems

-Brainstorming on challenges to identify potential impacts of improved water

productivity at larger spatial scales (i.e. landscape and watershed scales) and over suitable

time periods (1-year, 2-year, 5-year, 10-year)

- Technical presentation including use of at least 2 crop-water productivity models (e.g.:

Aquacrop/CropSyst/DSSAT/EPIC?)

-Conclusions for the WLI Thematic Research Group on Water Use Efficiency and Water

Productivity

45

- Additional invited presentation on Soil Water Mass Balance Model and Optimization of

Irrigation using Soil Water Sensors

Day 4: Field visit

This will include:

- Brief visit to IRA‟s headquarters‟ (missions, main programs, etc.) in the El Fjé

Technological park

- Field tour to visit some selected research sites of WLI Tunisia in the South of the

country (WH, irrigation management)

- A webinar event on recently launched Guide on Feed the Future (FtF) Indicators

Day 5: Water Balance with- and without- improved water management: Projecting

Impact

-Brainstorming on challenges to identify potential impacts of improved water

productivity on water balance in target systems and at the watershed scale, and

communicating them to decision-makers

-Economic analysis of improved water management

-Practical examples on WEAP,

-Open discussion on methodological and data-related challenges for WLI

-Conclusions for the WLI Thematic Research Group on Decision support tools and

models

-Wrapping up and recommendations for improvement of regional and country level

research plans for WLI 2013-14

Expected Outputs:

Enhanced annual reports and PPT presentations from 8 WLI countries and

regional team

Training materials online for other interested researchers to benefit from

Short workshop report including list of participants

Expected Outcomes:

WLI thematic research group on decision support tools and models activated

WLI thematic research group on water use efficiency activated

Improved connection of WLI pilot testing to strategic level decision-making

and improved outscaling strategies for integrated land and water management

Improved management of land, water and livelihoods in WLI countries

Expected Impacts:

Reduced threat of water scarcity for all sectoral uses, including agriculture and

reduced vulnerability to land degradation (affecting food production, water

availability and quality)

Increased on-farm income at the benchmark sites

Improved livelihoods of rural households at the benchmark sites

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Preparatory Materials for Participants:

WLI:

- Regional Reports: 1st and 2

nd Quarterly reports, 2013

-Tunisia program document

- Further information: http://temp.icarda.org/wli/

WEAP:

- Regional paper:

Droogers, P., Immerzeel, W.W., Terink, W., Hoogeveen, J., Bierkens, M.F.P., Van Beek,

L.P.H., Debele, B. (2012) Water resources trends in Middle East and North Africa

towards 2050 Hydrol. Earth Systems Science, 16, 3101–3114.

- Tunisia case study:

Hadded, R., I. Nouiri, O. Alshihabi, J. Maßmann, M. Huber, A. Laghouane, H. Yahiaoui

& J. Tarhouni (2013) A Decision Support System to Manage the Groundwater of

the Zeuss Koutine Aquifer Using the WEAP-MODFLOW Framework Water

Resources Management, 27, 1981-2000.

- Further information and manual: http://www.weap21.org/index.asp?NewLang=EN

SWAT:

-Overview paper (Gassman):

http://www.card.iastate.edu/environment/items/asabe_swat.pdf

-Tunisia case study paper:

Ouessar, M., A. Bruggeman, F. Abdelli, R. H. Mohtar, D. Gabriels & W. M. Cornelis

(2009) Modelling water-harvesting systems in the arid south of Tunisia using

SWAT. Hydrology and Earth System Sciences, 13, 2003 -2021.

- Further information and manual: http://swat.tamu.edu/

CROP Syst:

- Overview paper:

Stockle, C. O., M. Donatelli & R. Nelson (2003) CropSyst, a cropping systems

simulation model. European Journal of Agronomy, 18, 289–307.

- Tunisia case study paper (Belhouchette2008)

Belhouchette, H., E. Braudeau, M. Hachicha, M. Donatelli, R. H. Mohtar & J. Wery

(2008) INTEGRATING SPATIAL SOIL ORGANIZATION DATA WITH A

REGIONAL AGRICULTURAL MANAGEMENT SIMULATION MODEL: A

CASE STUDY IN NORTHERN TUNISIA Transactions of the American Society

of Agricultural and Biological Engineers (ASABE) 51, 1099-1109.

- Further information and

manual: http://www.bsyse.wsu.edu/CS_Suite/CropSyst/manual/index.html

AquaCrop:

- Overview publication (FAO Irrigation and Drainage paper nr. 66) and further

information available from: http://www.fao.org/nr/water/aquacrop.html

https://owa.cgiar.org/owa/redir.aspx?C=qSqiRmCyO02t_IWzve2Y6YY7P2dMTdAIMUaz3vO5c67oWaD00fN6kSAN7f_ahA5DCi8EdmKex0w.&URL=http%3a%2f%2ftemp.icarda.org%2fwli%2f









http://www.weap21.org/index.asp?NewLang=EN

http://www.card.iastate.edu/environment/items/asabe_swat.pdf

http://swat.tamu.edu/

https://owa.cgiar.org/owa/redir.aspx?C=Uu3oVs3_XkyjhsLMQm69mjRzq_4kddAIupFTWduKXn0CKVS_kV6fzchjYsFCyVMFQJdABva3Ye8.&URL=http%3a%2f%2fwww.bsyse.wsu.edu%2fCS_Suite%2fCropSyst%2fmanual%2findex.html

http://www.fao.org/nr/water/aquacrop.html

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Appendix 6: Definitions of selected WLI FtF Indicators

SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.2: Enhanced Technology Development, Dissemination, Management and Innovation

INDICATOR TITLE: 4.5.2-2 Number of hectares under improved technologies or management practices as a result of USG assistance (RiA) (WOG)

DEFINITION: This indicator measures the new and continuing area (in hectares) of land under new technology during the current reporting year. Any technology that was first adopted in a previous reporting year and continues to be applied should be marked as “Continuing” (see disaggregation notes below). Technologies to be counted here are agriculture-related technologies and innovations including those that address climate change adaptation and mitigation (e.g. carbon sequestration, clean energy, and energy efficiency as related to agriculture). Relevant technologies include: • Mechanical and physical: Irrigation, new land preparation, harvesting, processing and product handling technologies, including biodegradable packaging; • Biological: New germ plasm (varieties, breeds, etc.) that could be higher-yielding or higher in nutritional content and/or more resilient to climate impacts; affordable food-based nutritional supplementation such as vitamin A-rich sweet potatoes or rice, or high-protein maize, or improved livestock breeds; soil management practices that increase biotic activity and soil organic matter levels; and livestock health services and products such as vaccines; • Chemical: Fertilizers, insecticides, and pesticides safe storage application and disposal of agricultural chemicals, effluent and wastes, and soil amendments that increase fertilizer-use efficiency (e.g. soil organic matter); • Management and cultural practices: Information technology, conservation agriculture, improved/sustainable agricultural production and marketing practices, increased use of climate information for planning disaster risk strategies in place, climate change mitigation and energy efficiency, and natural resource management practices that increase productivity (e.g. upstream watershed conservation or bio-diesel fueled farm equipment) and/or resilience to climate change including soil and water conservation and management practices (e.g. erosion control, water harvesting, low or no-till); sustainable fishing practices (.e.g. ecological fishery reserves, improved fishing gear, establishment of fishery management plans); Integrated Pest Management (IPM), and Integrated Soil Fertility Management (ISFM), and Post-Harvest Handling (PHH) related to agriculture should all be included as improved technologies or management practices. Significant improvements to existing technologies should be counted. If a hectare is under more than one improved technology type (e.g. improved seed (crop genetics) and IPM (pest management), count the hectare under each technology type (i.e. double-count). In addition, count the hectare under the total w/one or more improved technology category. Since it is very common that more than one improved technology is disseminated and applied, this approach allows FTF to accurate count the uptake of different technology types, and to accurately count the total number of hectares under improved technologies. If a hectare is under more than one improved technology, some of which continue to be applied from the previous year and some of which were newly applied in the reporting year, count the hectare under the relevant technology type as new or continuing, depending on the technology, and under new for the total w/one or more improved technology category (i.e. any new application of an improved technology

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categorizes a hectare as new, even if other technologies being applied are continuing.)

RATIONALE: Tracks successful adoption of technologies and management practices in an effort to improve agricultural productivity, agricultural water productivity, sustainability, and resilience to climate impacts.

UNIT: Hectares

DISAGGREGATE BY: Technology type:

crop genetics (including nutritional enhancement), animal genetics, pest management, disease management, soil-related (fertility and conservation, including tillage), irrigation, water management, post-harvest handling and storage, processing, climate mitigation or adaptation, fishing gear/technique, other, total w/one or more improved technology

Duration: --New = this is the first year the hectare came under improved technologies or management practices --Continuing = the hectare being counted continues to be under improved technologies or management practices from the previous year Sex: --male --female --association-applied

TYPE: Outcome

DIRECTION OF CHANGE: Higher is better

DATA SOURCE: Implementing Partners will collect this data through census or survey of program participants, direct observations of land, and report into program documents.

MEASUREMENT NOTES: LEVEL of COLLECTION: Project-level; only those hectares affected by USG assistance, and only

those brought or continuing under new technologies/management during the current reporting year

WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Via survey or other applicable method FREQUENCY of COLLECTION: Annually reported

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�_

SPS LOCATION: Program Area 4.5 Agriculture INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity

INDICATOR TITLE: 4.5-4 Gross margin per unit of land, kilogram, or animal of selected product (crops/animals/fisheries selected varies by country)

DEFINITION: The gross margin is the difference between the total value of sales of the agricultural product (crop, livestock, fish) and the cost of producing that item, divided by the total number of units (hectares of crops, kilograms of fish, number of animals for livestock) in production. Gross margin per hectare, or per animal, or per kilogram of fish for targeted commodities, is a measure of net income for that farm/fishery/livestock-use activity. Input costs included should be those significant input costs that can be easily ascertained. These are likely to be the cash costs. Most likely items are: purchased water, fuel, electricity, seed, feed or fish meal, fertilizer, pesticides, hired labor, hired enforcement, and hired machine/veterinary services. Reporting of current-year results for individuals and firms who have benefited in previous years from this same USG assistance should be included along with current-year results of current beneficiaries. Reporting all data elements (Area, Production, Quantity of Sales, Value of Sales, and Purchased Input Cost) requested is critical to the ability to aggregate results across missions. In addition, a sixth data element – water consumption in cubic meters – can be obtained in order to calculate water productivity (see measurement notes).

RATIONALE: Improving the gross margin of value chains for farming commodities or animals contributes to increasing agricultural GDP, will increase income, and thus directly contribute to the IR of improving production and the goal indicator of reducing poverty. Also assessing the gross margin of fisheries – through assessing biomass of fish caught - is an appropriate measure of the productivity of a fishery and the impacts of fisheries management interventions.

UNIT: dollars/hectare (crops); dollars/animal (livestock); or kilograms of fish (fishery); Note: convert local currency to USD by using an average of the market foreign exchange rate for the reporting period

DISAGGREGATE BY: --Targeted commodity (type of crop, type of animal, or type of fish – freshwater or marine) --Gendered household type: female no male (FNM); male no female (MNF); male and female (M&F) --Rain-fed v. irrigated areas System note: These disaggregations will not necessarily be available in FACTS Info, but will be available in the FTF Monitoring System in a drop-down menu.

TYPE: Outcome


DATA SOURCE: Implementing partners

MEASUREMENT NOTES: Gross margin is calculated by applying a formula against these 5 data points: 1) Area (hectares) or Kilograms (for fish) or Number of animals (for livestock), 2) Production, 3) Value of Sales (USD), 4) Quantity of Sales , and 5) purchased input costs (report only those costs that are at least 5% of total cost, i.e. do not report miniscule costs). Price = value of sales divided by quantity of sales; gross revenue = price x production; net revenue = gross revenue minus purchase input cost; gross margin (per ha, per kg of fish, or per animal) = net revenue divided by area (for crops), by animals (for livestock), It is strongly recommended that data also be gathered on the m3 of water consumed since the inclusion of this sixth data point in addition to the five data points used for Gross Margin allows for the calculation of water productivity. Provision of data on water consumption should be mandatory for Implementing Partners to report in irrigated areas, and strongly encouraged in rain-fed areas. Increasing Agricultural Production per unit of water consumed is an important way to improve food security. Current constraints on collection of data on water consumption in rain-fed areas are nonetheless acknowledged. FTF System Note: Simply enter the 5 data points into the FTF Monitoring System (FTFMS), and it will do the calculation of gross margin automatically. This calculation cannot be done without all 5 data points. Adding the

50

6th data point will also enable the system to automatically calculate water productivity. LEVEL of COLLECTION: Project-level, in targeted commodities/fisheries/livestock

WHO COLLECTS DATA FOR THIS INDICATOR: Implementing Partners HOW SHOULD IT BE COLLECTED: Through farmer/fisher/rancher surveys FREQUENCY of COLLECTION: Implementing partners should obtain this data annually (required). Data will be collected through standardized approaches wherein implementing partners/extension workers collect data quarterly through producer organization meetings using standardized group questionnaire. Note: If the item is home consumed then the market price received by farmers selling the product is used to value it. Cost includes all purchased inputs, purchased transportation (including fuel), or hired labor, but does not include any imputed value of family or community labor.

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SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1 Improved Agricultural Productivity / Sub IR 1.1 Enhanced human and institutional capacity development for increased sustainable agriculture sector productivity

INDICATOR TITLE: 4.5.2-11 Number of food security private enterprises (for profit), producers organizations, water users associations, women’s groups, trade and business associations, and community-based organizations (CBOs) receiving USG assistance (RiA) (WOG)

DEFINITION: Total number of private enterprises, producers’ associations, cooperatives, producers organizations, fishing associations, water users associations, women’s groups, trade and business associations and community-based organizations, including those focused on natural resource management, that received USG assistance related to food security during the reporting year. This assistance includes support that aims at organization functions, such as member services, storage, processing and other downstream techniques, and management, marketing and accounting. “Organizations assisted” should only include those organizations for which implementing partners have made a targeted effort to build their capacity or enhance their organizational functions. In the case of training or assistance to farmer’s association or cooperatives, individual farmers are not counted separately, but as one entity.

RATIONALE: Tracks civil society capacity building that is essential to building agricultural sector productivity.

UNIT: Number

DISAGGREGATE BY: Type of organization (see indicator title for principal types) New/Continuing: --New = the entity is receiving USG assistance for the first time during the reporting year --Continuing = the entity received USG assistance in the previous year and continues to receive it in the reporting year System note: In the FTF Monitoring System (FTFMS), you will enter the number of each type of organization receiving assistance for your projects, and the system will aggregate the total number for this indicator across all projects.

TYPE: Output

DIRECTION OF CHANGE Higher is better


MEASUREMENT NOTES:

LEVEL of COLLECTION: Project-level WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Project records of training and various USG assistance for these

specific types of organizations/associations FREQUENCY of COLLECTION: Annually reported

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SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.1: Enhanced human and institutional capacity development for increased sustainable agriculture sector productivity

INDICATOR TITLE: 4.5.2-7 Number of individuals who have received USG supported short-term agricultural sector productivity or food security training (RiA) (WOG

DEFINITION: The number of individuals to whom significant knowledge or skills have been imparted through interactions that are intentional, structured, and purposed for imparting knowledge or skills should be counted. This includes farmers, ranchers, fishers, and other primary sector producers who receive training in a variety of best practices in productivity, post-harvest management, linking to markets, etc. It also includes rural entrepreneurs, processors, managers and traders receiving training in application of new technologies, business management, linking to markets, etc., and training to extension specialists, researchers, policymakers and others who are engaged in the food, feed and fiber system and natural resources and water management. In-country and off-shore training are included. Include training on climate risk analysis, adaptation, mitigation, and vulnerability assessments, as it relates to agriculture. Delivery mechanisms can include a variety of extension methods as well as technical assistance activities. An example is a USDA Cochran Fellow. Training should include food security, water resources management/IWRM, sustainable agriculture, and climate change resilience, but should not include nutrition-related trainings, which should be reported under indicator #3.1.9-1 instead. This indicator is to count individuals receiving training, for which the outcome, i.e. individuals applying new practices, should be reported under #4.5.2-5

RATIONALE: Measures enhanced human capacity for increased agriculture productivity, improved food security, policy formulation and/or implementation, which is key to transformational development.

UNIT: Number

DISAGGREGATE BY: Type of individual: -Producers (farmers, fishers, pastoralists, ranchers, etc.) -People in government (e.g. policy makers, extension workers) -People in private sector firms (e.g. processors, service providers, manufacturers) -People in civil society (e.g. NGOs, CBOs, CSOs, research and academic organizations)

Note: While producers are included under MSMEs under indicators 4.5.2-30 and 4.5.2-37, only count them under the Producers and not the Private Sector Firms disaggregate to avoid double-counting. While private sector firms are considered part of civil society more broadly, only count them under the Private Sector Firms and not the Civil Society disaggregate to avoid double-counting.

Sex: Male, Female

TYPE: Output



MEASUREMENT NOTES: LEVEL of COLLECTION: Project-level; individuals targeted by USG program WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Program training records FREQUENCY of COLLECTION: Annually reported

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SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.2: Enhanced Technology Development, Dissemination, Management and Innovation

INDICATOR TITLE: 4.5.2-39 Number of technologies or management practices in one of the following phases of development:

….in Phase I: under research as a result of USG assistance

….in Phase II: under field testing as a result of USG assistance

….in Phase III: made available for transfer as a result of USG assistance (S)

DEFINITION: Technologies to be counted here are agriculture-related technologies and innovations including those that address climate change adaptation and mitigation (including carbon sequestration, clean energy, and energy efficiency as related to agriculture), and may relate to any of the products at any point on the supply chain. Relevant technologies include:

• Mechanical and physical: New land preparation, harvesting, processing and product handling technologies, including packaging, sustainable water management practices; sustainable land management practices; sustainable fishing practices; • Biological: New germ plasm (varieties, breeds, etc.) that could be higher-yielding or higher in nutritional content and/or more resilient to climate impacts; biofortified crops such as vitamin A-rich sweet potatoes or rice, or high-protein maize, or improved livestock breeds; soil management practices that increase biotic activity and soil organic matter levels; and livestock health services and products such as vaccines; • Chemical: Fertilizers, insecticides, and pesticides sustainably and environmentally applied, and soil amendments that increase fertilizer-use efficiencies; • Management and cultural practices: Information technology, improved/sustainable agricultural production and marketing practices, increased use of climate information for planning risk management strategies, climate change mitigation and energy efficiency, and natural resource management practices that increase productivity and/or resiliency to climate change. IPM, ISFM, and PHH as related to agriculture should all be included as improved technologies or management practices

Significant improvements to existing technologies should also be counted; an improvement would be significant if, among other reasons, it served a new purpose or allowed a new class of users to employ it. Examples include a scaled-down milk container that allows individuals to carry it easily, a new blend of fertilizer for a particular soil, tools modified to suit a particular management practice, and improved fishing gear.

…in Phase I: under research as a result of USG assistance

New technologies or management practices under research counted should be only those under research in the current reporting year. Any new technology or management practice under research in a previous year but not under research in the reporting year should not be included. Technologies under research are as follows:

a. For biotech crop research: When technologies are under research, the process is contained in a laboratory or greenhouse; once the possibility of success is judged high enough, a permit is required to move to field testing. The change of location from a contained laboratory or greenhouse to a confined field and the receipt of a permit indicate that the research has completed the “under research” stage.

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b. For non-biotech crop research: When technologies are under research, plant breeders work on developing new lines on research plots under controlled conditions. All research should have a target, often expressed in terms of traits to be combined into a specific cultivar or breed. When the research achieves “proof of concept” (by accumulating technical information and test results that indicate that the target is achievable), the “under research” phase is completed. Note that for crops, much or all of this phase might be conducted outdoors and in soil; these attributes do not make this work “field testing.”

c. For non-crop research: “under research” signifies similarly research conducted under ideal conditions to develop or support the development of the product or process.

…in Phase II: under field testing as a result of USG assistance

“Under field testing” means that research has moved from focused development to broader testing and this testing is underway under conditions intended to duplicate those encountered by potential users of the new technology. This might be in the actual facilities (fields) of potential users, or it might be in a facility set up to duplicate those conditions. More specifically:

a. For biotech crop research: Once a permit has been obtained and the research moves to a confined field, the research is said to be “under field testing.”

b. For non-biotech crop or fisheries research: During this phase the development of the product or technology continues under end-user conditions in multi-location trails, which might be conducted at a research station or on farmers’/producer’s fields/waters or both. Note that for crops, all of this phase would be conducted outdoors and in soil, but this is not what makes this work “field testing.”

c. For non-crop research: “under field testing” signifies similarly research conducted under user conditions to further test the product, process, or practice. In the case of research to improve equipment, the endpoint of field testing could be sales of equipment (when the tester is a commercial entity). In other cases it could be distribution of designs (when the tester is a noncommercial entity) and also distribution of publications or other information (on the force of the good results of field testing).

…in Phase III: made available for transfer as a result of USG assistance.

Note that completing a research activity does not in itself constitute having made a technology available. In the case of crop research that developed a new variety, e.g., the variety must have passed through any required approval process, and seed of the new variety should be available for multiplication. The technology should have proven benefits and be as ready for use as it can be as it emerges from the research and testing process. In some cases more than one operating unit may count the same technology. This would occur if the technology were developed, for instance, in collaboration with a U.S. university and passed through regional collaboration to other countries. Technologies made available for transfer should be only those made available in the current reporting year. Any technology made available in a previous year should not be included.

RATIONALE: This indicator tracks the three stages in research and technology investments and progress toward dissemination.

UNIT: Number

DISAGGREGATE BY: Phase of development: -Under research as a result of USG assistance;

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-Under field testing as a result of USG assistance; -Made available for transfer as a result of USG assistance

Type: Output



MEASUREMENT NOTES:

LEVEL of COLLECTION: Project-level; only those technologies made available under field research as a result of the USG project

WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Project records or survey FREQUENCY of COLLECTION: Annually reported

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SPS LOCATION: Program Element 4.5.2: Agricultural Sector Productivity INITIATIVE AFFILIATION: FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.1: Enhanced human and institutional capacity development for increased sustainable agriculture sector productivity

INDICATOR TITLE: 4.5.2-5 Number of farmers and others who have applied new technologies or management practices as a result of USG assistance (RiA) (WOG)

DEFINITION: This indicator measures the total number of farmers, ranchers and other primary sector producers (food and non-food crops, livestock products, wild fisheries, aquaculture, agro-forestry, and natural resource-based products are included), individual processors (not firms), rural entrepreneurs, managers and traders, natural resource managers, etc. that applied new technologies anywhere within the food and fiber system as a result of USG assistance. This includes innovations in efficiency, value-addition, post-harvest management, sustainable land management, forest and water management, managerial practices, input supply delivery. Any technology that was first applied in a previous year and that continues to be applied should be included as ‘continuing’. Technologies to be counted here are agriculture-related technologies and innovations including those that address climate change adaptation and mitigation (including, but not limited to, carbon sequestration, clean energy, and energy efficiency as related to agriculture). Relevant technologies could include: • Mechanical and physical: New land preparation, harvesting, processing and product handling technologies, including biodegradable packaging • Biological: New germ plasm (varieties, breeds, etc.) that could be higher-yielding or higher in nutritional content and/or more resilient to climate impacts; affordable food-based nutritional supplementation such as vitamin A-rich sweet potatoes or rice, or high-protein maize, or improved livestock breeds; soil management practices that increase biotic activity and soil organic matter levels; and livestock health services and products such as vaccines; • Chemical: Fertilizers, insecticides, and pesticides sustainably and environmentally applied, and soil amendments that increase fertilizer use efficiencies; • Management and cultural practices: sustainable water management; practices; sustainable land management practices; sustainable fishing practices; information technology, improved/sustainable agricultural production and marketing practices, increased use of climate information for planning disaster risk strategies in place, climate change mitigation and energy efficiency, and natural resource management practices that increase productivity and/or resiliency to climate change. IPM, ISFM, and PHH as related to agriculture should all be included as improved technologies or management practices Significant improvements to existing technologies should be counted. In the case where, for example, a farmer applies more than one innovation as a result of USG assistance, they are still only counted once. Also, if more than one farmer in a household is applying new technologies, count all the farmers in the household who apply. This indicator is to count individuals who applied new technologies, whereas indicator #4.5.2-28 is to count firms, associations, or other group entities applying new technologies.

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RATIONALE: Technological change and its adoption by different actors in the in the agricultural supply change will be critical to increasing agricultural productivity which is the Intermediate Result which this indicator falls under.

UNIT Number

DISAGGREGATE BY: Duration --New = This reporting year is the first year the person applied the new technology or management practice --Continuing = The person first applied the new technology or practice in the previous year and continues to apply it Sex: Male, Female

TYPE: Outcome


DATA SOURCE: Implementing Partners

MEASUREMENT NOTES: LEVEL of COLLECTION: Project-level; only those individuals targeted by USG programs WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Survey of all targeted individuals, Project or association

records, farm records FREQUENCY of COLLECTION: Annually reported

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SPS LOCATION: Program Element 4.5.2:Agricultural Sector Productivity INITIATIVE AFFILIATION: GCC and FTF – IR 1: Improved Agricultural Productivity / Sub IR 1.1: Enhanced human and institutional capacity development for increased sustainable agriculture sector productivity

INDICATOR TITLE: 4.5.2-34 Number of stakeholders implementing risk-reducing practices/actions to improve resilience to climate change as a result of USG assistance (S)

DEFINITION: There is strong scientific and evidence-based information that stakeholders (in the case of this indicator defined as “producers”) involved in sectors such as agriculture, livestock, fishing, other areas of natural resources can mitigate the effects of climate change by using appropriate new and tested management practices or implement measures that reduce the risks of climate change impacts. For example, risk-reducing management practices in agriculture and livestock might include changing the exposure or sensitivity of crops (e.g., switching crops, using a greenhouse, or changing the cropping calendar), soil management practices that reduce rainwater run-off and increase infiltration, changing grazing practices, or adjusting the management of other aspects of the system. Risk reducing measures might include applying new technologies like improved seeds or irrigation methods, diversifying into different income-generating activities or into crops that are less susceptible to drought and greater climatic variability. Any adjustment to the management of resources or implementation of an adaptation action that responds to climate-related stresses and increases resilience can be considered. Practices and actions will aim to increase predictability and/or productivity of agriculture under anticipated climate variability and change.

RATIONALE: While many management practices and technologies exist and can be diffused, others may not be well suited to perform under emerging climate stresses. Improved management and new technologies are available and others are being developed to perform better under climate stresses. Resource management experiences from other parts of the world may be useful as climate conditions shift geographically.

UNIT: Number of stakeholders

DISAGGREGATE BY: Type of Risk reducing practice: -Agriculture – practices and actions will aim to increase predictability and/or productivity of agriculture under anticipated climate variability and change. -Water – practices and actions will aim to improve water quality, supply, and efficient use under anticipated climate variability and change. -Health – practices and actions will aim to prevent or control disease incidence and outcomes under anticipated climate variability and change outcomes. -Disaster Risk Management – practices and actions will aim to reduce the negative impacts of extreme events associated with climate variability and change. -Urban – practices and actions will aim to improve the resilience of urban areas, populations, and infrastructure under anticipated climate variability and change. Sex: Male, Female

Type: Outcome

DIRECTION OF CHANGE Higher is better

DATA SOURCE: Field surveys by local project partners, including extension agents and farmer/producer organizations (and other types of organizations)

MEASUREMENT NOTES: LEVEL of COLLECTION: Project-level; only those stakeholders involved in USG programs WHO COLLECTS DATA FOR THIS INDICATOR: Implementing partners HOW SHOULD IT BE COLLECTED: Via Implementing Partner records, survey or other applicable

method FREQUENCY of COLLECTION: Annually reported

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