The soil water balance of a mixed oak stand in the ... · the “Kc ini” for any lag between the...

137Studi Trent. Sci. Nat., Acta Biol., 81 (2004), Suppl. 1: 137-149Studi Trent. Sci. Nat., Acta Biol., 81 (2004), Suppl. 1: 137-149 ISSN 0392-0542© Museo Tridentino di Scienze Naturali, Trento 2005

1. INTroducTIoN

The general decline of oak forests has been investi-gated both in Italy (ragazzi & dellavalle 2000), and, more generally, in Europe (Thomas et al. 2002). The resistance to drought itself can be the discriminating element in the capability of many tree species of tem-perate climate to cope with climatic change effects; indeed, scenarios involve a general increase in tempe-rature and in the length of the growing season, together with a constancy or a slight decrease of water supply (Hasenauer et al. 1999; Kramer et al. 2000; Lexer et al. 2002; Sabaté et al. 2002).

A mixed deciduous forest characterizes the expe-rimental area of Savignano. due to the numerical pre-ponderance and to the ecological interest, the balance models has focused on downy oak (Quercus pubescens Willd). Even if effective physiological adaptation to

The soil water balance of a mixed oak stand in the southern Alps

Emanuele EccEL*, Giambattista ToLLEr & Luca GHIELMI

IASMA research center, Natural resources department, Via E. Mach 1, I-38010 San Michele all’Adige (TN), Italy*corresponding author e-mail: [email protected]

SuMMArY - The soil water balance of a mixed oak stand in the southern Alps - A water balance experiment has been set up in a thermophilous oak grove in the Italian Alps, useful to investigate the relationships between water stress and potential plant damages. In the experimental site a meteorological station is operated since 1993, which provided data series for models. The calculation approach has been adapted from a protocol developed for an European pilot study; a Penman- Monteith’s “one step” method has been used for calculation of evapotranspiration; resistance coefficients have been evaluated according to values found in literature and adapted to a daily time-step for the water balance model. The equipment installed ad hoc in the site and the measurements performed (under-canopy precipitation, soil moisture, LAI) allowed an experimental verification of the results of single parameterizations. The water balance model, and in particular the relative transpiration, allowed a good description of the dry periods of last years, and particularly for 2003, during which an unprecedented drought was recorded.

rIASSuNTo - Bilancio idrico in un querceto misto nelle Alpi meridionali - è stato impostato un esperimento di analisi del bilancio idrico in un querceto termofilo nelle Alpi italiane, utile per indagare la relazione tra stress idrico e potenziali danni rilevabili alle piante. Nell’area sperimentale esiste dal 1993 una stazione meteorologica che ha fornito la serie di dati per la modellistica. L’approccio seguito è stato adattato dal protocollo stabilito per uno studio pilota europeo; il metodo di calcolo per l’evapotraspirazione è quello di Penman-Monteith “ad un passo”, con calcolo dei coefficienti di resistenza all’evapotraspirazione in base a valori reperiti in letteratura e adattati a una formulazione giornaliera del bilancio. La strumentazione di misura installata ad hoc nel sito e le misure condotte (precipitazioni sotto chioma, umidità del suolo, LAI) hanno consentito di verificare sperimentalmente i risultati delle singole parametrizzazioni. Il modello di bilancio idrico, e in particolare la traspirazione relativa, consentono di descrivere bene periodi siccitosi registrati negli scorsi anni, in particolare il 2003, quando fu registrata una siccità eccezionale.

Key words: Trentino, water balance, drought, downy oak, Quercus pubescensParole chiave: Trentino, bilancio idrico, siccità, roverella, Quercus pubescens

drought are common in the genus Quercus (Abrams 1990; Thomas & Gausling 2000; Gieger & Thomas 2002), water stress has been indicated as the main damage agent for Italian oaks (cellerino & Gennaro 2000), together with other biological agents which are generally responsible for the decline of genus Quercus in our country.

The estimate of water stress has been assumed as a fundamental step in the evaluation of the effects of meteorological drivers on the forest status. The impact of the abiotic agents on the health of Trentino’s forests, even when such agents act as damage precursors to biotic agents, is discussed in Ambrosi et al. (2002); in that work the experimental area of Pomarolo-Savignano is also taken into account, being one of the two areas involved in the project EFoMI.

The aim of this work is to provide a comprehen-sive evaluation of the water stress by means of an

138 Eccel et al. Soil water balance in an oak stand

experimental water balance, developed with the measu-rements continuously performed in the area or during measuring campaigns. Water stress, evaluated by means of indices, will be discussed, particularly for the event of summer 2003.

2. MATErIALS ANd METHodS

2.1. Meteorological records

As far as the conventional meteorological data are concerned, the description of the installation has been discussed in Eccel (2005). The application of Penman-Monteith equation on a daily basis is regularly assumed as a standard of FAo’s “Irrigation and drainage paper nr. 56” (Allen et al. 1998 – from now on referred to as “FAo 56”); a constant reference has been done to this report, where the method is described in detail. Even if this simplified approach may limit the precision of evapotranspiration estimates, it has been applied for the reconstruction of missing data and to produce homogeneous time series. In particular, significant homogenization procedures have been carried out on wind velocity and solar radiation, to compare recorded data with the reconstructed ones (case of wind), or to compare data measured by the mechanical instrument with those recorded by the electronic one (case of solar radiation).

2.2. Water balance

The general methodology has been adapted from that presented in Klap et al. (1997) and applied by Klap et al. (2002); this approach will be, from now on, refer-red to as “Wageningen”. Indeed, the parameterisation of the aerodynamic and “crop” resistance is not trivial in a “one step” application of Penman-Monteith’s method. Till now, examples on the applications of this method to forest species are scarce. The reference formulation of Penman-Monteith formula for the calculation of evapotranspiration (ET) is (“FAo 56”)

D (rn - G) + r

a c

p (e

s – e

a) / r

a(1) lET = ___________________________

D + γ (1 + rs/r

a)

where l= vaporization latent heatD= pendency of the curve temperature – saturated vapour pressurer

n= net radiation

G= soil heat fluxe

s= saturated vapour pressure

ea= actual vapour pressure

ra= air density

cp= specific heat at constant pressure

γ= psychrometric constant

rs= surface canopy resistance

ra= aerodinamic resistance

According to “Wageningen”, water stress is assessed by the relative transpiration index (rE

T), calculated

during the growing season:

(2) rET = Tr

act. / Tr

pot.

where Tr act.

and Tr pot.

are, respectively, actual and potential transpiration. Potential transpiration can be calculated as:

(3) Tr pot.

= ETp – E

i - E

s

where ET

p= potential evapotranspiration

Ei= evaporation of the precipitation intercepted by

canopyE

s= soil evaporation.

For the calculation of Tr act.

, a soil water balance is required; hence, a calculation of the bulk evapotran-spiration of the soil-vegetation system is required to estimate the water loss in the balance equation. A “bucket” functioning has been assumed for the soil system: when soil is saturated, any water surplus is lost. The assumption that runoff contributions are negligible is considered acceptable for the experimental area of Savignano. Methods for the calculation of the different balance terms and for measuring the relevant quantities are discussed in the following paragraphs.

2.3. Soil evaporation

In the water balance of a deciduous forest, soil eva-poration is relevant only when leaves are not present or leaf transpiration is negligible. Soil evaporation has been used to separate the transpiration term from the total evapotranspiration of the soil-plant system. For this purpose the more robust approach is the one pro-posed in “FAo 56”, which performed better than the “Wageningen” protocol (Hendriks 1997). The method requires the application of a crop coefficient (“Kc ini”) to the potential value ET

p calculated by the Penman-

Monteith formula. Such coefficient is tabulated as a function of the time elapsed from the latest rainfall; a simple linear function has been found to interpolate the values proposed by “FAo 56”; it allows an estimate of the “Kc ini” for any lag between the latest rainfall and the calculation day.

2.4. Correcting evapotraspiration for stress condi-tions

In case the available soil water falls below the cri-tical level, an evapotranspiration reduction coefficient is applied, resulting from the ratio between the actual

139Studi Trent. Sci. Nat., Acta Biol., 81 (2004), Suppl. 1: 137-149

soil moisture content (SMc) and the “critical” one (SMc

cr). The algorithm is given in the “Wageningen”

protocol (Hendriks 1997):

(4) ETa = ET

p (SMc / SMc

cr)

with ETa= actual evapotranspiration and ET

p= “po-

tential” evapotranspiration (in no-stress conditions it corresponds to the term given in eq. (1)). The critical content is assumed proportional to ET

p, according to

doorenbos & Kassam (1979). The reference stress con-dition is that of the previous day, when all the balance terms are known.

Analyses have been carried out on the soils for the measure of:- soil texture;- available water content (AWc), resulting from the

subtraction of the water content at wilting point from the field capacity.

2.5. Evapotranspiration resistances (rs and r

a)

Aiming at the description of the yearly water balan-ce, evapotranspiration has to be estimated also in late winter - springtime period. This is a potentially dry period, substantially affecting the availability of usable soil water. For the wintertime period, going from leaf senescence to the starting of the new growing season, evapotranspiration is the sum of- evaporation of the water intercepted by the canopy;- soil evaporation.

For the growing season, equation (1) has been ap-plied with a “one step” approach, requiring an estimate of the resistances r

s e r

a.

For the parameterization of the surface canopy resistance r

s, scientific literature referring to forest

species is not exhaustive; in general, values have been calculated for single species, among which genus Quer-cus is usually represented by Q. robur or Q. petraea.

Approximate values have been collected by Kelliher et al. (1995). According to these authors, a substantial difference exists between stomatal conductance of agri-cultural crops and those of forest trees, while, within the same category, differences are quite limited; this finding allows a calculation of conductance parameters on the basis of experiences carried out in habitats – or for species – even slightly different from those under consideration.

Kelliher et al. (1995) report values of conductance G

s= 1 / r

s for several forest categories; the quantity,

referred to the single transpirating element (stomatal con-ductance, g

s), is given in its maximum value (g

s max) as

4.6 ± 1.7 mm s-1 for “temperate deciduous forest”. The functional link between G

s and g

s max

depends on the Leaf Area Index (LAI). For a given LAI (roughly > 3.5), the ratio G

s / g

s max

can be considered a function of c

q (extinction coefficient for the attenuation of Photosyn-

thetically Active radiation, PAr, in the canopy) and

A (radiation flux). cq is the product of two terms (c

q =

K l0 ), where l

0 is a leaves’ distribution parameter, so

that the canopy gap fraction (T) is

(5) T = exp (-K l0 LAI)

The measures of LAI have been carried out with a delta-T “Sunscan” ceptometer; this instruments takes a default value of l

0= 0.6 (Potter et al. 1996); for a K

value equal to the default (K= 0.85), cq = 0,85 x 0.6

= 0.51, a value corresponding to the average of those considered in Kelliher et al. (1995).

PAr values have been calculated from the global radiation (r

si) measured by the meteorological sta-

tion, by applying a fixed coefficient PAr / rsi = 0.47

(dimensionless), known to represent an average value and confirmed also by measures done in site.

In order to apply the relationships between gs max

and G

s, the PAr value where 50% of the maximum stomatal

conductance is attained in the curve PAr vs. gs (Qa50)

is required. The suggested average value of 100 mmol m-2 s-1 has been used, according to the experiences of Yera et al. (1986) and Sharkey & raschke (1981).

during and after rains, when vegetation is wet, the evaporation of the intercepted rain can be parameterised by using eq. (1) with r

s = 0.

For the calculation of aerodynamic resistance ra

some assumptions are required about the canopy. The theoretical model, usually employed in regular crops, assumes that the “zero plane” displacement is at 2/3 of tree height; Barry & chorley (1992) show how in a mature oak grove in summer wind velocity is nearly constant in the first 20 m (with a tree height of 25 m), that is, for roughly 80% of their height; in this portion, velocity is about 20-30% of that measured above the canopy. rauner (1976) suggests that the barycentre of the canopy of a deciduous forest is at about 0.8 the mean height of trees. Such value has been applied to an estimated height of 20 m. From the same author equation (6) has been used to calculate wind velocity within the canopy, given the velocity outside; the latter is known when the morphological characteristics of the surrounding territory are known:

(6) uc / u

0 = exp (- 0.30 LAI)

where uc and u

0 are, respectively, velocities within

the canopy and in open field. Velocity values u(z) at the effective reference height z, are inferred by values measured at the height of the wind mast (5 m) by the usual logarithmic equation

(7) u(z) = (u*/ 0.41) ln [(z – d) / z0]

where u* is the friction velocity, z is the reference height (z= 0.8 x 20 m), d is the zero plane displa-cement (d/h= 0.64, with h= height of the elements responsible for roughness) and z

0 is the roughness


index (z0= 0.13 h). For h a value of 3 m has been used.

u* is calculated by an inverse application of eq. (7), assuming for z the wind measurement height (5 m). By applying eq. (6) and (7), the velocity at the representa-tive canopy height is known. These values have been corrected, where necessary, according to the suggestion by “FAo 56” not to use in the calculation of r

a, wind

velocities at 2 m less than 0.5 m s-1. This suggestion has been applied to the estimated velocity in the canopy at the height z.

Finally, for the calculation of ra, the formulation

proposed by Benincasa et al. (1991) has been used:

(8) ra = [ln (z-d)/z

0]2 / [k2 u (z)]

with k = von Karman’s constant (k= 0.41).

2.6. Soil hydrological surveys

A high inhomogeneity of soil properties charac-terize the experimental area, due to the morphological unevenness, which fosters formation of small soil pits, as well as of erosion points, where soil is more shallow. Texture analyses have been carried out for three sam-ples taken at different depths: i) 0÷10 cm; ii) 10÷20 cm; iii) 20÷30 cm. Measurements were performed accor-ding to the national standards “decreto Mini-steriale” nr.173, 1/8/1997. From an examination of pedological data it is possible to know, with some approximation, the water content that is critical for water stress (Klap et al. 1997). Nevertheless, an accurate analysis of soil properties has been carried out by execution of variable load measures with richards plates.

To evaluate the performance of the water balance model, two independent kinds of soil moisture measu-rement devices have been installed in the area:- two capacitive, multilevel probes Sentek “EasyAG”,

equipped with 4 sensors, from 10 to 50 cm deep in the soil; data have been recorded every 30’ and stored in a datalogger campbell Sci. cr10x;

- a network of 17 pairs of 50 cm-long iron conductors, driven into the soil, at a distance of about 5 cm one another, for measurements with Tdr technique; a Tektronix 1502c instrument was employed. The con-ductors have been installed close to every in-the-plot rainfall collector, and two more pairs at every position of EasyAG probes, for comparison purposes.

2.7. Phenology and Leaf Area Index (LAI) model

The water stress evaluation has been limited, ac-cording to the “Wageningen” protocol, to the growing season, corresponding to the plants’ higher sensitivity to stress.

Instead of the table proposed by Klap et al. (1997), reporting a fixed calendar for climatic areas, at Savi-gnano phenological observations were available (leaf

unfolding and colouring phases). LAI assessment was carried out, allowing the estimation of a simple LAI model. Measures have been taken with a Sunscan ceptometre (Potter et al. 1996) during 10 campaigns along one year (May 2003 - May 2004). The instru-ment compares PAr measured in open field and that measured under the canopy to calculate the canopy gap fraction; LAI is finally estimated by the inversion of a light extinction model.

2.8. Radiative balance

For the application of the Penman-Monteith formula (1), the short- and long-wave components, entering and leaving the system, have to be estimated. The soil heat flux (G) has been ignored, as usually done in evapotranspiration calculation not involving instantaneous values; such possibility is suggested both in “FAo 56” and in the “Wageningen” approach. The radiative term of the ener-gy balance is so limited to net radiation r

n:

(9) rn = r

si (1 - a) + r

Li - r

Lh

where rsi is the short-wave incoming radiation, α

is albedo and rLi and r

Lh are long-wave radiation,

respectively in and out.For albedo, values proposed by rauner (1976) for

deciduous forest range from 0.15 and 0.18, the larger figure referring to winter and spring before bud burst. observations by Grulois (cited in rauner 1976) seemin-gly reach an opposite trend (lower winter figures), with values from 0.11 to about 0.20. Finally, site-specific measurements not being available, a constant value of 0.16 has been chosen.

The calculation of net long wave radiation (rLi

- rLh) has been performed according to the methods

proposed in “FAo 56”. Such formulation requires the daily values of temperature, vapour pressure, short-wave incoming radiation (global radiation) and clear-sky global radiation. The latter is not directly obtainable from measures taken by the meteorological station; it has been therefore estimated with a sinusoidal function, calculated from clear-sky measures taken in selected key days (solstices and equinoxes) with very dry atmospheric conditions.

2.9. Estimate of throughfall and stemflow

In the experimental site 15 rainwater and 3 stemflow collectors have been installed. Installation and manage-ment of this equipment have been carried out according to the protocol illustrated in Tartari et al. (2002). All the collectors have been regularly emptied and water measured weekly during the whole project EFoMI.

rain interception models generally schematise ca-nopy as a reservoir having a given capacity; when the reservoir is full, it lets water exceeding that capacity seep out of the canopy; an amount of precipitation


reaches the ground without being intercepted (clas-sical approach by Gash et al. 1995). More complex numerical models have been proposed (Mulder 1985; Watanabe & Mizutani 1995; de ridder 2001); never-theless, the advantage of a sophistication of the pa-rameterization remains questionable (dolman 1987). A model conceptually built this way presents several disadvantages: the difficulty of dealing with mixed evergreen and deciduous species; the seasonality of water capacity in the canopy, which changes from point to point according to the species; the role of wind, which can partially or almost totally shake off the water collected by leaves. These models, working at an event scale, would have presented calibration problems, being rainfall collectors emptied only once a week, but, for the sake of a water stress model, we deemed satisfactory the results obtained from a cali-bration performed on weekly data.

A simple descriptive model, of the kind of that pro-posed by Neal et al. 1980, has been chosen, inferred from measures carried out at the site. For the calcula-tion of throughfall precipitation, two approaches have been tested:- a model set up on the hypothesis of Gash et al.

(1995), with a storage in the canopy and consequent dripping;

- a simple regressive model between data measured in the collectors and rainfall data measured at the station.

Evaporation during rainfall, being the atmosphere close to saturation, has been neglected.

3. rESuLTS

3.1. Soil hydrological properties

Analyses on soil texture gave a general classifica-tion of a loamy soil, with skeleton increasing in deeper layers. The organic matter content is relatively high. details are given in table 1.

The water retention curve, resulting by richards plate measures, is represented in figure 1. Available water content (difference between field capacity and wilting point contents) increases with depth.

3.2. Soil moisture measures

Measures taken in 2003 and 2004 (Figs 2, 3) point out the effects of the warm and dry summer until the first days of october 2003. Humidity in the 50 cm deep layer dropped below 50 mm. referring to a 1 m deep soil layer, this measure yields 50 mm / 0.5 m = 100 mm m-1, a value representative of the permanent wilting point. Indeed, measures carried out by the richards’ plate have found this point to be around 8-10% on a weight/weight basis; by applying an average density of 1.2 g cm-3, it corresponds to 9.6-12% on a volume/volume basis. In such situations, the lack of evident wilting signals can be explained only by water extraction from layers deeper than 50 cm.

A rainfall event of about 80 mm at the beginning of october 2003 showed variable effects at the diffe-rent micro-sites. The readiness of response at some points might be due to a lower plant sheltering, due to the inhomogeneous canopy. In any case, even in less receptive points, an increase in moisture could be detected as autumn went on. From spring 2004 stable values around a plateau represented the effective field capacity. The agreement can be appreciated with the relationship moisture-tension, drawn by richards plate, where field capacity (pF= 2) and wilting point (pF= 4.2) are represented by horizontal dashed lines (Fig. 1). The lower water availability for the more superfi-cial layer is confirmed by the steadily lower values in water content.

The comparison between measures taken by capaci-tive probes and Tdr reported in figure 3 showed a good correspondence in trends, not always in absolute values. Since Tdr measures yield an average for the whole 50 cm layer, while probes take measures at four different depths within the same layer, the expected values for Tdr were less than the maximum attained by probes. That regularly occurred for the probe installed inside the enclosure, while moisture contents measured by all exter-nal sensors were steadily lower than Tdr measures; this may be interpreted as a local anomaly in soil properties. Low values of moisture expressed on a volume/volume basis and measured in surface layers may be ascribed to the presence of a considerable quantity of organic matter, strongly increasing soil macroporosity.

Layer [cm] clay Silt Sand organic Skeletal General classification [g kg-1] [g kg-1] [g kg-1] fraction[-] fraction[-] (0, -10) 120 321 559 0.18 0.07 Loamy, tendency to loamy-sandy; non-prevailing skeleton; good organic matter content (-10, -20) 140 310 550 0.09 0.14 Loamy, tendency to loamy-sandy; non-prevailing skeleton; good organic matter content (-20, -30) 180 257 563 0.08 0.20 Loamy, tendency to loamy-sandy; average skeleton; good organic matter content

Tab. 1 - Soil texture analysis.Tab. 1 - Analisi della tessitura del suolo.


3.3. Phenological calendar and Leaf Area Index (LAI) model

Four measures were taken in every experimental campaign (following the directions N-E-S-W) for any of the 15 positions of rainwater collection. The average for any day therefore comes from 60 values represen-ting the large heterogeneity of the canopy cover. The LAI trend in one year is reported in figure 4. Standard deviations refer to the 15 points where values were the average (N-E-S-W) for every point. on the average, the largest variability occurs in spring, probably because of differences in phenology for the several species living in the area.

To consider the effects of the woody parts, not effective in transpiration, winter measures of LAI have been done, resulting in an average value of about 1.0, due to stems, branches and, at spots, leaves of evergreen species (namely pines and spruces). For the calculation of canopy resistance, this value has been subtracted to the gross values; for the calculation of aerodynamic resistance, on the contrary, average values of LAI resulting from measures have been maintained.

An attempt of associating a simple phenological model to LAI gave no appreciable results. The first dif-ficulty arises from the diversity of tree species growing

in the area. Secondly, only three year of phenological surveys were available (2002-2004). For Quercus pubescens, the dominant species, few experimental relations have been found in literature (chuine & cour, 1999) showing the insensitivity of leaf unfolding to winter temperature. Within the same genus, research on Quercus robur showed that a dependence of leaf unfolding on temperature seems weak (Kramer 1994; Menzel 2003). An application of the relations found in Menzel (2003) for Germany according to the seasonal anomalies with respect to mean values, has given con-trasting results (original dates have been anticipated by 30 days for adapting parameters to subalpine climate); and, in any case, modelled dates of leaf unfolding would display a standard deviation of only 5 days. To avoid any arbitrariness, we adopted as beginning of the growing season the average of the bud burst observed during three years (15th April). The LAI model has been developed from the observation and is represented in the figure 5. Full winter value is attained late, due to the late leaf drop of deciduous oaks.

To keep into account the forest growth along the 11 years of the monitoring period, a LAI reduction coefficient has been applied back-wise, linearly and progressively; for 1993 (first year of the series) maxi-mum summer LAI has been taken as 75% of the 2003 value (Ambrosi, pers. comm).

Fig. 1 - Water retention curves (developed by university of Brescia) for soil at three depths: 0-10 cm, 10-20 cm, 20-30 cm. upper and lower dashed lines represent, respectively, f ield capacity and wilting point.Fig. 1 - Curve di ritenzione idrica (prodotte dall’Università di Brescia) per il suolo a tre diverse profondità: 0-10 cm, 10-20 cm, 20-30 cm. Le linee tratteggiate superiore e inferiore rappresentano, rispettivamente, la capacità di campo e il punto di appassimento.


Fig. 2 - a) Average soil water content in a 0.5 m layer mea-sured by Tdr, year 2003. SEN= ext. probe, north side; SES= ext. probe, south side; SIN= int. probe, north side; SIS= int. probe, south side; X1...X15: locations by the water collec-tors 1...15. b) Same as 2a – year 2004.Fig. 2 - a) Contenuto idrico medio del suolo misurato in uno strato di 50 cm con TDR – Anno 2003. SEN= sonda esterna, lato nord; SES= sonda esterna, lato sud; SIN= sonda interna, lato nord; SIS= sonda interna, lato sud.; X1...X15: posizioni corrispondenti ai raccoglitori d’acqua 1...15. b) Come 2, anno 2004.

a)

b)

date

date


Fig. 3 - Tdr measures and capacitive probes, Sept. 2003 - May 2004. a): Internal site; b) external site. (o)= Tdr south probe; (*)= Tdr north probe. dot-dashed line= capac. probe, -10 cm; dashed (short) line= capac. probe, -20 cm; dashed (long) line= capac. probe, -30 cm; solid line= capac. probe, -50 cm.Fig. 3 - Misure condotte con TDR e con sonde capacitive, Sett. 2003 - maggio 2004. a) sito interno; b) sito esterno. (O)= TDR sonda sud; (*)= TDR sonda nord; linea punto-tratto= sonda capac., -10 cm; linea tratteggiata, corta= sonda ca-pac., -20 cm; linea tratteggiata, lunga= sonda capac., -30 cm; linea continua= sonda capac., -50 cm.

3.4. Evapotranspiration model

Values of conductance found as in 2.5 refer to instant values, not to daily means. Along the day, variation of conductance is remarkable and it differs from species to species within the genus Quercus (Gieger & Thomas 2002).

The calculation of Gs according to the described

methodology, requires first an evaluation of conduc-tance for vegetation only (G

c). Averaging the 24 values

of Gc of one day yields a value (G

c,24) which shows to be

different from the value obtained by an application of the method to daily mean meteorological values (G

c,dm),

due to the non-linearity of the involved relationships. A ratio r

Gc has been defined between the conductance

calculated in the two ways:

(10) rGc

= Gc,24

/ Gc,dm

It has been found that rGc

is well correlated with a “clearness index”, cI (the ratio between measured glo-bal radiation in any day and typical clear sky radiation for the same day of the year), approaching 1 when sky is overcast and reaching values as low as 0.6 for bright sky conditions. For the estimate of the clear sky radiation,

a sinusoidal function has been inferred from maximum values measured in days close to both solstices. For the period April-September 2003, a linear regression has been applied to estimate r

Gc as a function of the clear-

ness index cI. A highly significant linear correlation has been observed (Fig. 6), after the exclusion of few outliers characterized by low conductance values (r

Gc

> 0.8); the linear regression is expressed by:

(11) rGc

= -0.255 cI + 0.81 (r2 = 0.44, p < 0.001)

An inverse application of equation (10) gives the adjusted daily value of G

c,24. Then, considering hourly

values as representative of the instant values, the daily ones have been multiplied by the sky-cover-dependent coefficient r

Gc, resulting from the equation in figure 6.

For details on the relationships between Gc and G

s, refer

to the original paper by Kelliher et al. (1995).

For ra, a substantial difference has been found

between values obtained by averaging the 24 hourly values and those obtained by a direct application of eq. (6), (7) and (8) to mean daily values of wind velocity. From a survey on values in 2003, it came out that the ratio r

a,24 / r

a,dm (where the two terms refer to r

a calcu-

b)

a)


Fig. 5 - Model for Leaf Area Index (LAI). Solid line: for calculations of aerodynamic parameters; dashed line: for calculation of transpirative parameters.Fig. 5 - Modello per l’Indice di Area Fogliare (LAI). Lin-ea continua: per calcoli di parametri aerodinamici; linea tratteggiata: per cal-coli di parametri traspi-rativi.

Fig. 6 - rGc

vs. “clearness index” (see text for ex-planation). “outliers” (open dots) have been excluded in the derivation of regression line.Fig. 6 - R

Gc vs. “indice di

serenità” (vedere il testo per spiegazioni). Il calcolo della retta di regressione è stato eseguito senza tener conto degli “outliers” (punti bianchi).

Fig. 4 - Leaf Area Index (LAI) measures, May 2003 - May 2004. Standard devia-tions are marked.Fig. 4 - Misure di Indice di Area Fogliare (LAI), mag-gio 2003 - maggio 2004. Sono indicate le deviazioni standard.

0

1

2

3

4

5

6

7

8

1-52003

31-5 30-6 30-7 29-8 28-9 28-10 27-11 27-12 26-12004

25-2 26-3 25-4 25-5

LA

I [m

2 m

-2]

0

1

2

3

4

5

6

1-1

16-1

31-1

15-2 2-3

17-3 1-4

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31-5

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30-6

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28-9

13-1

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28-1

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27-1

2dATE

LA

I

transpiration only

aerodynamics

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clearness index (cI)

rG

c

rGc = - 0.255 cI + 0.81r2 = 0.44p < 0.001


lated, respectively, as average of 24 hourly values and as a direct application to velocity daily means), spans from 0.6 to 1.0. Nevertheless, in this case no significant correlation has been found with wind velocity, but rather with the standard deviation of the hourly values within one single day. A fixed coefficient of 0.8 has been applied to account for this feature.

3.5. Rain interception model

Weekly data of rain interception have been quality checked to keep into account two important factors:- the filling of all or some of the collectors (in this

case the datum is refused, being affected by under-estimation);

- evaporation from collectors; from measures perfor-med during the summer-autumn 2003, lump-sum ra-tes have been estimated to compensate the evaporated amount; such values have been considered dependent on the season (summer or winter) and on the number of days elapsed from the rainy days recorded in the week.

The suggestions of “Wageningen” report (Hendriks 1997) have been tested, using for the canopy storage ta-bulated values (0.3 mm in winter and 0.9 mm in summer). From an analysis of results it can be inferred that:- no improvement can be appreciated when making use

of a model that encompasses a reservoir-type canopy like the one proposed in the “Wageningen” protocol;

- a regression of the weekly aggregated precipitation, measured under the canopy (P

i) and outside (P

e)

yields practically the same results in winter and in summer:

(12) Pi = 0.81 P

e – 0.2 (r2 = 0.96, p < 0.001)

The intercept value of the regression line (0.2 mm) represents the weekly canopy storage and, on a daily basis, is fully negligible. rain throughfall has been set equal to 80% of the values measured at the station, with an upper limit of interception changeable with LAI: from a maximum of 1.2 mm to a minimum of 0.6 mm.

As far as stem flow is concerned, this term is often neglected in simple models of rain interception; also the “Wageningen” report does not consider it. Neal et al. (1993) suggest for an oak grove average values of 5% (1 to 2 % in summer, 6 to 16% in winter). Gash et al. (1995) for a pine forest found average stem flow values of 3%. Being this information available for the area of Savignano, we have calculated simple linear models by regression lines, obtained from 4 years of observation (1999-2003), divided into two seasons: winter (Novem-ber to April) and summer (May to october). data have been analysed with two different approaches:- rough rainfall data;- subtraction of assumed interception values (0.3 and

0.9 mm).

correlation coefficient (r2) increases not more than 0.01 when the “interception approach” is used, so, any sound basis being missing, it was discarded. Finally, the relations linking stem flow (P

s, expressed in mm

after division by the estimated interception area), and rainfall measured outside the canopy (P

e) are:

(13a) winter: Ps = 0.026 P

e (r2 = 0.82, p < 0.001)

(13b) summer: Ps = 0.038 P

e (r2 = 0.74, p < 0.001)

After all, stem flow has been set equal to 3% and 4% of the rainfall measured at the station, respectively for winter and for summer.

Altogether, the estimate of water present after a rainfall event on the canopy (P

c) is carried out by the

following equation:

(14) Pc = P

e (1 – P

i / P

e – P

s / P

e)

Application of eq. (14) in winter and in summer yields for (P

c), respectively 16% and 15% of the rainfall

height measured at the station. From a practical point of view, we chose to adopt one equation all over the year (P

c= 0.15 P

e), with the limit of the maximum value of

interception (function of LAI) already explained.

3.6. Water balance model

only a short period is available for a comparison between soil water content measured by probes and model simulation (from 22nd August to 31st october, 2003). Nevertheless, this period is of the highest inte-rest, since it includes the 2003 summer drought. Any soil water content measured by probes at one depth refers to a 0.1 m deep layer; summing values at the four measuring depths (-10, -20, -30 and -50 cm) and adding fictitious values at -40 cm by averaging values at -30 and -50 cm, the whole water content in mm can be evaluated in the 50 cm deep soil layer. From figure 7 the good agreement can be appreciated between the simulated balance and data retrieved by the probe in-stalled within the enclosure. only in last weeks did the model overestimate soil water content, while the trend in water content followed very well the experimental data for the drying up period.

It can be observed that water content never drops below 30- 40 mm; these figures remain higher than the measured wilting point for the soil, but it must be kept in mind that all surveys have been carried out on the first 30 cm (soil properties) or 50 cm (soil moisture measures). Trees having the possibility of relying on deeper soils can cope with more severe droughts; the highest sensitivity to drought is to be looked for in contests of more shallow soil, where the maximum theoretical water storage is not attained in wet periods.

The application of the water balance allows the


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20

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28-8 3-9

9-9

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21-1

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27-1

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17-1

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23-1

2

29-1

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10-1

16-1

22-1

28-1 3-2

soil

wat

er c

onte

nt [

mm

]

capacitive probe (inside)

capacitive probe (outside)

balance simulation

0,0

0,2

0,4

0,6

0,8

1,0

1,2

3Months

rel

ativ

e tr

ansp

irat

ion

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11

0

25

50

75

100

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175

200

225

Months

Soi

l wat

er c

onte

nt (

mm

)

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

permanent wilting point (50 cm depth)

3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11 3 7 11

Fig. 7 - comparison between soil moisture values mea-sured by capacitive probes (internal and external to the enclosure) and water balance model simulation (Aug. 2003 - Febr. 2004).Fig. 7 - Confronto tra valori di umidità del suolo misu-rati dalla sonde capacitive (interna ed esterna all’area recintata) e modello di bilan-cio idrico (Ago. 2003 - Feb. 2004).

Fig. 8 - relative transpi-ration simulated by the wa-ter balance model for the period 1993-2003.Fig. 8 - Traspirazione rela-tiva simulata del modello di bilancio idrico per il perio-do 1993-2003.

Fig. 9 - Soil water content simulated by the water ba-lance model for the period 1993-2003. The approxi-mate value of the permanent wilting point is reported for a 50 cm deep layer.Fig. 9 - Contenuto idrico del suolo simulato del mod-ello di bilancio idrico per il periodo 1999-2003. è ripor-tato il valore indicativo del punto di appassimento in uno strato di 50 cm.


evaluation of the stress potential during the 11-years observation period. results can be summarized in two parameters: relative transpiration and water content (Figs 8, 9). While the second allows an easy tracking of the warm season in any year, being water depletion pattern quite similar from one year to another, relative transpiration allows a deeper insight in the potential water stress mechanism for plants. It can be seen that summer 2003 has been unprecedented in the previous 11 years, both for the lowest values attained in the relative transpiration (values lower than 0.1) and for the length of the stress period, covering the whole summer with a suspension in July. The rough value of the permanent wilting point has been assessed, for a 50 cm deep layer, as 50 mm; soil water contents as low as such value have been attained, according to the model, only in 1995 and in 2003, but in the latter case, water content passed the threshold several times during the summer.

4. coNcLuSIoNS

The application of the soil water balance model proposed in this work to the deciduous forest of Savignano (Pomarolo) was successful, despite its parameterisation is based on several assumptions. Pro-bably, a better parameterisation of throughfall could improve the accuracy of the water balance, adding details to the mechanism of rainfall filtering through the canopy. For its accomplishment, daily measures of throughfall would be required in the plot. As well, being the spring start-up of vegetative period a poten-tially delicate period for the wood, an application of a phenological model could help to gain insight, year by year, into the time of leaf unfolding; this period coincides with the change in the parameterisation of evapotranspiration in the water balance model.

Looking at the results of the soil water simulation, the model proved to be reliable in following the pro-gressive soil drying-up during 2003’s drought. rela-tive transpiration index seems suitable for detecting water stress episodes. Water deficit – whose origin can be tracked back to spring – spread to the month of october. other relatively dry summer periods occurred in 2000 and 2001, but above all in 1995; in this year a water stress period could be detected in autumn. Nevertheless, the extent of 2003’s drought remains peculiar, due to two particularly long, hot periods and the low precipitation rates which marked an exceptional climatic feature in all Europe (rebetez et al. 2004).

AcKNoWLEdGEMENTS

Thanks for the collaboration to: Alessandro cescatti (centro di Ecologia Alpina, Trento); Mario ramponi,

Aldo Biasi, Emanuel Endrizzi, Flavio Marchetti (Isti-tuto Agrario di S. Michele), Stefano Barontini and roberto ranzi (università di Brescia).

The present study was carried out in the frame of the Special Project “EFoMI”, run by Istituto Agrario di S. Michele and funded by the “Fondo unico per la ricerca” of the Autonomous Province of Trento.

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