Simulation studies of long-term saline water use: model validation and evaluation of schedules

Agricultural Water Management 54 (2002) 123±157

Simulation studies of long-term saline water use: model validation and evaluation of schedules A. Tedeschia,*, M. Menentib,1 a CNR-ISPAIM, Irrigation Institute, Via Patacca 70, 80056 Ercolano, Naples, Italy ALTERRA, Green World Research Institute, Droevendaalsesteeg 3a, P.O. Box 47, 6700 AA Wageningen, The Netherlands

b

Accepted 9 July 2001

Abstract In the Mediterranean environment characterized by hot, dry summers, a hydrologically oriented ®eld experiment on vegetable crops was carried out between 1988 and 1993 at a site near Naples, Italy. The objective of the experiment was to study the impact of saline water on crop yield and soil properties. The research was carried out on a clay loam soil classi®ed as Haplustolls. Irrigation water was applied at concentrations: 0, 1.25, 2.5, 5, 10 g l 1 of NaCl and at three irrigation intervals of 2, 5 and 10 days. The increasing concentrations were obtained by adding NaCl to fresh water. The irrigation treatments (i.e. solute concentration and irrigation intervals) were repeated consistently over the same plots throughout the experiment. Irrigation schedules alternating sodic and fresh water were evaluated using a numerical simulation model (SWAP) and taking into account the impact of sodic water on soil physical properties. Measurements done during the ®eld trials were used to calibrate and validate the numerical simulation model and to illustrate the consequences on salt and water balance of the irrigation schedules considered in the study. The electrical conductivity of the saturated extracted of soil paste (ECe), the structure stability index and the in®ltration rate indicated observable changes in soil physical properties between the irrigation treatments 0 and 1% over the duration of the experiment. Over the years there is clear evidence that no signi®cant change in ECe was observed in the plots irrigated with fresh water (0% T2 and T10). On the other hand, ECe increased linearly with time for the treatments irrigated with saline water (1% T2 and T10). Degradation of soil structure was evident in the observed in®ltration rate: <1 mm h 1 in the treatment 1% versus >10 mm h 1 in the treatment 0%. Changes in soil hydrological properties were evaluated by determining the h(y) and K(h) relationships of undisturbed soil cores for four irrigation treatments and using the van Genuchten parametric model of these relationships. For the 2- and 10-day irrigation frequencies, the h(y) curve of the 1% treatment had lower values of y than the 0% treatment at the same pressure head in the range 2.0± * Corresponding author. Tel.: ‡39-81-5746606/5746575; fax: ‡39-81-7718045. E-mail addresses: [email protected] (A. Tedeschi), [email protected] (M. Menenti). 1 Tel.: ‡31-317-474596; fax: ‡31-317-419000.

0378-3774/02/$ ± see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 3 7 7 4 ( 0 1 ) 0 0 1 4 0 - 8

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3.0 pF. Signi®cant differences were observed between the mean values (for each treatment) of most of van Genuchten's parameters, particularly between the (0% 2 day) and (1% 2 day) treatments. Prior to the evaluation of irrigation schedules the SWAP model was calibrated and validated against the data available in the 1993 (eggplant crop). Irrigation schedules were compared on the basis of a performance indicator (Sc), which measures the relative change in the amount of adsorbed and dissolved salt over an entire irrigation season. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Salinity; Model; Simulation

1. Introduction In southern and eastern Mediterranean areas renewable water resources are very scarce. Indeed, their per capita availability is the lowest worldwide. A large fraction (53%) of the population experience long periods of water shortage, and 18% of the population suffer periodical lack of water (World Bank, 1992). This scenario may worsen given that global water consumption has increased five-fold since 1940 (Falkenmark and Biswas, 1995). Water consumption has increased because: (1) agriculture and industry have become more intensive; (2) the population and numbers of new settlements have increased; and (3) the living standard has improved. With the current trend (Postel, 1986) also the demand of water for agriculture will increase in contrast with increasing scarcity due to: (a) overdraft of groundwater; (b) exploitation of surface water courses reaching the limit of sustainability; and (c) rapid increase in the demand for drinking water and industrial water. This inter-sectoral competition tends to restrict water availability in agriculture, which is the largest and least efficient user. These trends have led research to be carried out into the use of lower quality water in agriculture, in addition to renewing efforts achieve water conservation. Both saline and wastewater may be used for irrigation, but then the chemical, physical and biological properties of water have to be analyzed as a function of its intended use. According to Chhabra (1996) under certain situations, such as in coastal areas or where shallow groundwater is used for irrigation, water can be a source of salts and lead to development of soil salinity. In southern Italy large coastal areas of intensive agriculture are progressively becoming salt affected, mainly because of irrigation with saline ground water (Tedeschi, 1999). Accumulation of soluble salts in the soil is directly related with the salt content of the irrigation water (Somani, 1991). A salinity problem related to water quality occurs if the total quantity of the salts in the irrigation water is such that salts accumulate in the root-zone. Moreover, according to Manchanda et al. (1993) in areas where annual rainfall is less than 250 mm, saline waters (EC > 4 dS m 1) will cause salt toxicity in most crops. In areas where annual rainfall exceeds 500 mm, water up to an EC ˆ 16 dS m 1 can be utilized for some crops. Several classifications of water quality have been proposed (Wilcox, 1948; USSL Staff, 1954; Ayers and Westcot, 1985). In general, the assessment of water quality and the permitted level of some toxic elements are based on two related aspects, i.e. the possible effects on the physical and chemical properties of the soil and the impact on crop yield. The Wilcox classification comprises four classes of salinity, four classes of sodicity and several combinations that will consider the quantity (ECw) and quality (SAR) of dissolved

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salts. The sodium adsorption ratio (SAR) is defined as the quantity of Na‡ compared to Ca2‡ and Mg2‡. The suitability or unsuitability of irrigation water should also be evaluated on the basis of local conditions in conjunction with the prevailing climate, soil and plant growth. The effect of salts on crop growth is believed to be largely of an osmotic nature. If excessive quantities of soluble salts accumulate in the root-zone, the crop has extra difficulty in extracting enough water from the saline solution, thereby affecting the yield adversely (Somani, 1991). The use of saline waters has adverse effects on the soil rather than on the crop. The supply of soluble salts from irrigation water is responsible for the origin of saline soils (secondary salinization) in combination with boundary conditions such as insufficient drainage and rainfall in arid or semi-arid zones. When saline or sodic water is used, the best irrigation management and use of appropriate agronomic techniques are necessary. The best irrigation management may vary according to whether the objective is to maximize production or to minimize the adverse effects on soil. Traditionally, crop yield has been the most important goal, with the risk that the soil fertility decreases because of the accumulation of salts. Preservation of the soil quality should be given higher priority to guarantee the sustainability of irrigation. The conventional way to evaluate irrigation strategies is to carry out several years of experimental trials to evaluate a limited range of irrigation schedules. Numerical simulation models of solute and water flow in soils may help extract additional information from field trials. Once these simulation models are validated, they can be used to evaluate the consequences of changes in plant and soil properties or in irrigation strategies, and thus provide a more concrete basis to assist agronomists, breeders, and supporting services (Ragab et al., 1990). Several computer models simulating actual crop growth in the presence of water stress or a shortage in nutrient supply have been developed (van Keulen, 1975, 1982; Penning de Vries and van Laar, 1982; van Keulen and Wolf, 1986). Some published models are very detailed and demand an exhaustive amount of input data, which are not always available. Other models are simplified versions of the latter but yet give satisfactory results. This paper describes a study of the long-term effect of the use of saline irrigation water. The impact of the observed differences in soil physical properties is illustrated by a simulated study of water and solute transport. The study was carried out in a high-value agricultural area in the Sele valley. In this area, because of sea-water intrusion, the water table, from which water for irrigation is normally extracted, is becoming progressively salt affected, thus increasing the risk of soil salinization. 1.1. Background 1.1.1. Irrigation strategies This section gives a short review of irrigation strategies to prevent harmful accumulations of salt in the root-zone when saline or sodic water is available. The application of a particular irrigation strategy depends on the local conditions, such as climate, soil, plants, and no less important water price, water availability and traditional irrigation management.

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There are several strategies, but three main categories may be considered. The first is the direct use of saline water throughout the crop season. In this case proper timing can help to avoid low levels of soil water that cause salts in the soil solution to become highly concentrated. Therefore more frequent irrigation, keeping the soil at higher moisture contents, prevents high salt concentrations in the soil solution and leads to minimizing the harmful effects of a given level of salinity (Somani, 1991; Tanji, 1990). Results in such directions are reported in Sharma et al. (1977); they studied the effect of irrigating wheat with saline water (EC ˆ 11 dS m 1; SAR ˆ 26:9) using irrigation intervals of 10, 15, 20, and 25 days but keeping the total water application the same. Their results show that accumulation of salts was higher in the soil irrigated at 10 day intervals, but the moisture content in the root-zone was greater throughout the cropping season. The result was that the effective salt concentration was much less than in the soil irrigated at intervals of 15, 20 and 25 days. Minhas (1994) used a saline water of EC ˆ 12 dS m 1 on soil already salinized and concluded that when saline water is used on such soil very frequent water application can be beneficial. Shainberg and Shalhevet (1984) studied the effect of the frequency of saline water irrigation on yield, and concluded that higher frequencies lead to higher yields. The second method is to develop an irrigation plan for the entire crop growth season based on crop tolerance to salinity, salt sensitivity in a particular growth stage, and salinity of the irrigation water. Usually non-saline water is used in the early, sensitive growth stages and on non-tolerant crops. Later when the tolerant growth stage is reached, saline water is applied. After harvest, non-saline water s applied to reclaim the soil profile's upper portion and to prepare the soil for the next cropping season. This cyclic use of high quality and saline water can be repeated again and again, provided that certain physical properties of the soil related to permeability and water transmission can be maintained. Pasternak et al. (1986) studied three levels of water salinity, equivalent to EC of 1.2, 4.5 and 7.5 dS m 1. At the two higher salinity levels, irrigation of a tomato crop was started immediately after sowing; at two crop stages identified by the author as the four-leaf-stage or at the eleven-leaf-stage. The results showed that the ECe throughout the season was low relative to the ECe that is usually obtained with water at these levels of salinity. Moreover, the crops that received the saline water at a later growth stage gave a higher yield than those which received saline water earlier. Manchanda (1995) studied the possibility of alternating canal water with higher salinity waters (EC ˆ 6 and 18 dS m 1). The combination of canal water in the pre-sowing stage and saline water later on was an effective strategy. The third and last strategy is to mix waters of different quality to obtain water suitable for irrigation. This strategy is often proposed as a way to increase the water supply. Dinar et al. (1986) added saline water to non-saline water, the saline water had an EC ˆ 4, 6 and 11 dS m 1. The increase in water supply by combining non-saline and saline water is not always technically or economically feasible, and depends on specific crop and water pricing. Agarwal and Roest (1986) described the reuse of drainage water to irrigate an eggplant crop by different irrigation strategies. These were: canal water with salinity of 0.3 dS m 1, pure drainage water with salinity varying from 2.5 to 6.3 dS m 1, alternate use of both and mixed in equal proportion. Eggplant production was reduced by 54% when only the drainage saline water was used. The alternate use of drainage and canal water gave a better crop yield.

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1.1.2. Crop yield Dissolved salts have general and specific effects on plants that directly influence crop growth and yield. As the salt concentration increases above a threshold level, both the growth rate and the ultimate size of most plant species progressively decrease. Chloride, sodium and boron may exert specific toxic effects such as osmotic and ionic equilibrium (Na‡/K‡ and Na‡/Ca2‡) on susceptible crops (Greenway and Munns, 1980). The excess of Na‡ can be compensated by the increase in Ca2‡ concentrations in stems, leaves and roots. The toxic effect is due to the inhibition or reduction of enzymatic activity. The variations in sensitivity are due to differences in genetic characteristics. The plant can isolate the toxic element (normally in the old leaves for the non-halophyte plants or in the vacuole for the halophyte) to reduce the damage. Osmotic processes are of a more general nature. They reduce the available water and so decrease the cellular turgor of the leaves and roots (Kafkafi, 1991). As a consequence, transpiration is hampered, a phenomenon sometimes referred to as ``physiological drought''. It leads to a decrease in plant growth, that seems to be more related to the availability of assimilates than to turgor alone. According to LaÈuchli and Epstein (1990), Kriedmann (1986), Papp et al. (1983) and Curtis and LaÈuchli (1987), leaf area development is affected by salinity conditions. Indeed, as the salinity concentration in the solution increases the leaf area decreases linearly. The reduction in leaf area is due to the decrease in cell stretching and division. 1.1.3. Soil properties Somani (1991) reported that the use of sodic water (high SAR) reduces the infiltration rate. The infiltration rate of soils irrigated by sodic water is known to decrease with increasing sodium on the exchangeable complex. When low electrolyte or sodic water is used for irrigation or leaching, most of the salts in the surface layer are pushed downward resulting in a reduced infiltration rate. To understand how the poor physical properties of sodic soils develop, one must look at the binding mechanism involving the negatively charged colloidal clays and organic matter of the soil (Tanji, 1990; Rhoades et al., 1992; Tanji and Yaron, 1994). More specifically, the envelope of electrostatically adsorbed cations around the colloids, and the means by which exchangeable sodium, electrolyte concentration and pH affect this envelope, must be considered. The DDL (diffuse double layer) model describes electrochemical phenomena at the charged soil±liquid interface. Many physical properties of soils can be modeled as an interaction between the DDL and soil clay particles. Soils with high clay fractions are more readily affected by the presence of salt; the clay fraction has the greatest specific surface area and is therefore most active in physicochemical processes such as swelling and dispersion (Shainberg and Levy, 1992). Dispersion is very important in the context of irrigation with saline and sodic water since it is the process causing a reduction in permeability. The difference between swelling and dispersion processes is important. Swelling of reference clays (Shainberg et al., 1981a,b) and soils (Emerson and Bakker, 1973) is not greatly affected by low exchangeable sodium percentage (ESP) values but increases significantly as ESP increases above 15. Instead, the dispersion of clay is very sensitive to low levels of sodicity and increases markedly in the low ESP range (Shainberg and Levy, 1992).

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Rowell et al. (1969) found that at the same electrolyte concentration and with an increase in ESP, the permeability decreases as a result of the increased clay swelling. Varallyay and Szabolcs (1974) and Varallyay (1977a) have noted that the alkalization of soils, particularly of heavy-textured, high swelling clay soils, causes increased hydration, swelling, dispersion of soil colloids, aggregate and structure destruction, and clogging of macropores. Frenkel et al. (1978) demonstrated that clay dispersion and clogging of pores within a soil column reduce hydraulic conductivity. They stated that dispersion and swelling of clays within the soil matrix are interrelated phenomena, and that both can reduce soil hydraulic conductivity. The exact levels of exchangeable sodium and electrolyte concentration at which hydraulic conductivity is appreciably reduced vary with mineralogy, clay content and soil bulk density (Frenkel et al., 1978). Shainberg et al. (1981a,b) concluded that when high-quality water is used, an ESP of 5 can be detrimental to the physical properties of the soil and that when waters of higher salinity are used, an ESP of 15 is required to damage soil physical properties of soil. Somani (1991) found that these changes were clearly reflected by changes in a water retention curve. The curve indicated a close relationship between the degree of Na saturation and the water retention of the soil, especially in the range 2.0±3.0 pF. A similar tendency was also observed even when swelling was limited. Water retention increased over the entire range of soil water content. By contrast, gravitational pore space decreased. The same author found that the available moisture content increased with ESP, which conflicts with the classical explanation of the water supply of plants in alkali soils and confirmed the findings of Varallyay (1977b). 1.1.4. Objective of the study The case study presented in this paper relates to an experiment carried out from 1988 to 1993, with irrigation treatments repeated consistently on the same plots throughout the experiment. The aim of the paper is to evaluate different irrigation schedules alternating sodic and fresh water. The evaluation was performed by using a numerical simulation model and taking into account the impact of sodic water on soil physical properties. Measurements taken during field trials were used to calibrate and validate the numerical simulation model and to illustrate the consequences on salt and water balance of the irrigation schedules considered in the study. The numerical simulation model used in the study was SWAP (van Dam et al., 1997) and the field trials were carried out from 1988 to 1993. 2. Theory of SWAP SWAP is a deterministic model describing water and solute transport as shown schematically in Scheme 1 in the form of flow chart. The model describes water uptake by the roots using a volumetric sink term that is added to the continuity equation for soil water flow. The model also describes the transport of salts, pesticides and other solutes, that are described with relatively simple kinetics. Solute transport is not detailed with the description of each ionic species.

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Scheme 1.

The transport equation applied in SWAP describes, one-dimensional, convective± dispersive mass transport, including non-linear adsorption, linear decay and proportional root uptake in unsaturated±saturated soil (Nielsen et al., 1986; Boesten and van der Linden, 1991):   @…yc ‡ rb Q† @qc @ @c ˆ ‡ y…Ddif ‡ Ddis † (1) m…yc ‡ rb Q† Kr Sc @t @z @z @z where c is the solute concentration in the mobile soil water (g cm 3), y the volumetric water content (cm3 cm 3), t the time (s), rb the dry soil bulk density (g cm 3), z the gravitational head (cm), Ddif the diffusion coef®cient (cm2 per day), Ddis dispersion (cm 2 per day), m ®rst-order rate coef®cient for decomposition (per day), Kr root uptake preference factor and S is the root water extraction rate (per day). The total pressure head h is the sum of the matrix and osmotic pressure head, i.e. h ˆ hm ‡ ho . The amount adsorbed Q is given by the equation below. The solute may be dissolved in the soil water and/or may be adsorbed to organic matter or clay minerals: X ˆ yc ‡ rb Q

(2) 3

where X is the total concentration in the system (g cm ) and Q is the amount adsorbed (g g 1). The adsorption isotherm describes the amount of solutes adsorbed in equilibrium with the solute concentration. In SWAP an instantaneous equilibrium is assumed between

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c and Q, and the non-linear Freundlich equation is used to calculate Q. The Freudlich adsorption isotherm can be written as   C Nf (3) Q ˆ Kf Cref Cref where Kf is the Freudlich coef®cient (cm3 g 1), Nf the Freudlich exponent and Cref is a reference value of the solute concentration (g cm 3) which is used to make Nf dimensionless. Details on the theory of SWAP are reported in van Dam et al. (1997). For uptake of soil water by plant roots, a simple and practical sink term was used, as proposed by Feddes et al. (1978) and modi®ed later by Hoogland et al. (1981). This sink term (S) depends on the total pressure head (h) and the maximum extraction rate (Smax). To account for the effect of soil temperature, soil aeration, and rooting intensity, Hoogland et al. (1981) proposed that Smax should decrease linearly with soil depth. The total water uptake from the entire root-zone cannot exceed potential transpiration. The potential transpiration can be calculated as the difference between the potential evapotranspiration (ETp) and potential evaporation (Ep). The ETp was calculated according to Priestley and Taylor (1972). The potential soil evaporation was calculated according to Belmans et al. (1983). SWAP can be applied to analyze the effect of saline water on crop yield. The actual transpiration (Tact) is an important model output for evaluating the moisture available for crop production. The Tact/Tpot ratio is often used as a measure of moisture availability. Hanks (1974) stated that reduction in crop yield Yact/Ypot, when moisture is the only limiting factor, can be obtained as Yact Tact ˆ Ypot Tpot

(4)

This concept was based on De Wit (1958), who found a linear relationship between total dry matter and seasonal transpiration for a number of ®eld experiments. van Hoorn et al. (1993) and Katerji et al. (1996, 1998) showed that this relation describes the response of crop yield to salinity. We will use this ratio to estimate to what extent water salinity affects crop production compared with the yield observed in the plot irrigated by normal water. 3. Materials and methods Research began in 1988 at the Torre Lama experimental farm of the University of Naples (province of Salerno), in a Mediterranean environment (annual temperature ˆ 15:5 8C and total rainfall ˆ 908 mm). The soil is a clay loam (around 30% clay) classified as Argiustolls in an alluvional environment. It has a mollic epipedon over an A horizon and a clayey B horizon (USDA, 1994). The sand fraction is dominated by volcanic minerals. In Table 1 the soil characteristics and the clay composition (by X-ray diffraction) are reported. The samples were collected in February 1993. From 1988, the effects of drip irrigation with sodic water on soil and vegetable crops grown in successive spring±summer and autumn±winter cycles were studied (Barbieri

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Table 1 Soil characteristics and clay composition (by X-ray diffraction) in February 1993 NaCl (%)

Coarse sand (2±0.2 mm) (%) Fine sand (0.2±0.02 mm) (%) Silt (0.02±0.002 mm) (%) Clay (<0.002) (%) Lime (%) pH Organic matter (%) Total N (%) Assimilable P2O5 (ppm) Exchangeable K2O (ppm) Illite Vermiculite Illite±Montmorillonite Kaolinite

0

1

20.0 28.0 26.5 25.5 Traces 7.12 1.44 0.104 96 570 Prevalent Few Traces Traces

19.5 29.0 26.3 25.2 Traces 7.94 1.14 0.085 42 442

et al., 1990; Caruso and Postiglione, 1993). The experiment entailed the factorial comparison between three irrigation frequencies (2, 5 and 10 days ˆ T2 , T5, T10) and five concentrations of irrigation water. The five saline concentrations of water were obtained by adding commercial NaCl to the normal water (later indicated as 0%) as reported: concentrations of NaCl 1.25, 2.5, 5 and 10 g l 1 (that we will indicate as 0, 0.125, 0.25, 0.5 and 1%). Table 2 shows the water composition used on the control 0% and on the treatments to which salt was added. The irrigation volumes (Table 3) were equivalent to the evaporation from a class A pan recorded between one watering and the next, minus total rainfall. The class A pan coefficient was taken equal to 1, as well as the crop coefficient throughout the crop season so that the leaching applied was determined by the difference between the assumed crop coefficient and the correct value, i.e. as estimated according to Allen et al. (1998). The procedure applied to determine water gift is explained by the numerical example (June 1993) in Table 4. Table 4 reports the Kc values related to crop season length Table 2 Characteristics of fresh irrigation water pH EC at 25 8C (dS m 1) SAR (mg l 1) Ca2‡ (mg l 1) Mg2‡ (mg l 1) Na‡ (mg l 1) K‡ (mg l 1) Cl (mg l 1) SO42 (mg l 1) HCO3 (mg l 1) CO32 (mg l 1)

7.52 0.50 5.33 79 178 375 6 21 200 340 Absent

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Table 3 Crops, seasonal irrigation volumes and amounts (t ha 1) of salts given by saline irrigation Tomato

Snapbean

1988

1989 3

3670 m ha Treatments (%) 0 ± 1 36.7 t ha

1

1

Eggplant

1990 3

3340 m ha ± 33.0 t ha

1

1

1991 3

3760 m ha ± 37.6 t ha

1

1

1992 3

2670 m ha ± 26.7 t ha

1

1

1993 3

3880 m ha ± 38.8 t ha

1

1

5420 m3 ha ± 54.2 t ha

1

1

according to Allen et al. (1998). They assumed a length of the crop season growth season in the Mediterranean environment (plant date May/June) of 140 days. The length of the crop in our case is 133 days (planted on DOY 123, and harvested on DOY 256). Comparing the Kc values estimated from the literature with the applied Kc (i.e. 1), it is clear that for the central period of the crop season no leaching was applied (mid Kc ˆ 1:05, applied Kc ˆ 1). In the initial stage (initial Kc ˆ 0:60; applied Kc ˆ 1) and the final stage (Kc ˆ 0:90; applied Kc ˆ 1) of the crop season an amount of water was available for salt leaching. Saline irrigation usually started after the crop had overcome transplant stress. In 1993, for the crop of eggplant cf. ``Mirabelle'', such differentiation occurred 5 weeks after transplant. Trickle irrigation was applied by means of drippers placed every 20 cm along rows spaced 90 cm apart. To evaluate the effects of salt accumulation, treatments were replicated every year in the same plot. The trial was conducted with three replications. On a monthly basis, in the plots irrigated with 0 and 1% levels and frequencies of 2, 5 and 10 days, soil samples were taken in the 0±30, 30±60 and 60±90 cm layers. The electrical conductivity of the saturated extract of soil paste (ECe in dS m 1 at 25 8C) was measured by a conductimeter. To evaluate the possible change in soil physical properties due to salt accumulation through the years, undisturbed soil samples were taken on the plots at 0 and 1% salt level and frequencies of 2, 5 and 10 days. The samples were taken during the summer 1993 in the 0±10 and 20±30 cm layers in duplo. The samples were transported to the laboratory to be saturated and the water retention curves were obtained by the instantaneous profile Table 4 Example given to determine the water applied and evaluation of leaching (applied), on the eggplant crop for June 1993 Kc according to FAO Initial Kc ˆ 0.60 Kc applied throughout the season Leaching applied Rainfall (6.0 mm) Evaporation (212.90 mm) Evaporation and rainfall water gift (206.9 mm)

1 0.40

Mid Kc ˆ 1.05 1 0.05

End Kc ˆ 0.90 1 0.10

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method (Wind, 1968). The RETC program was used to fit the parametric model of van Genuchten et al. (1992) to the observations. In 1993, the sixth year of the trial, after the winter rains (April) and in summer (August) soil samples were taken at depths of 0±30, 30±60, 60±90 and 90±120 cm on the 0 and 1% treatments. The water stability index (WSI) of the aggregates was determined according to the Malquori method (Malquori and Cecconi, 1962): WSI ˆ 100…1 A=B†, where WSI is the water aggregate stability of the soil (%), A the quantity of aggregates dispersed in water after 50 and B is the quantity of aggregates dispersed in water after 600 . Infiltration tests were also carried out with normal water, at constant pressure head with a double-cylinder infiltrometer. Cumulated infiltration data were fitted by the equation I…t† ˆ st1=2 ‡ K t , where I is the cumulated infiltration (mm), t the time (h), s the sorptivity and Kt is the hydraulic conductivity of the transmission zone. The infiltration rate was obtained by the first derivative of the above equation: i…t† ˆ 1=2 st 1=2 ‡ K t , where i is the infiltration rate (mm h 1), with s, t and Kt defined as above (Phillip, 1957, 1969). To estimate the water content throughout the irrigation season soil samples were taken after an irrigation event on each plot, at depths of 0±30, 30±60 and 60±90 cm. The soil moisture was obtained by the gravimetric method. 3.1. Model materials and methods A simulation study was performed using the soil and irrigation data described above. The SWAP model (van Dam et al., 1997) was used. Soil water actual transport extended (SWAP) is a one-dimensional, deterministic model based on Richard's equation. It was developed by Feddes et al. (1978) and later modified by Belmans et al. (1983). It was used successfully in different arid and semi-arid environments (Feddes and van Dam, 1996). The simulations were focused on eggplant, drip irrigated by saline water at 0 and 1% concentrations of NaCl. To solve the differential equation describing water and solute flow, either boundary conditions at both the top and bottom of the system or one initial condition (e.g. water content) and one boundary condition (e.g. at the bottom) have to be specified. Therefore from the available data at the beginning of the crop season, the water content through the soil profile was used to describe the initial boundary condition. At the bottom of the domain, the groundwater table was set at the depth of 1 m. This depth was estimated because usual soil tillage at this depth, produces a discontinuity in the soil profile that has an effect on soil permeability. Above this depth soil has a higher permeability, so that irrigation tends to saturate the soil below the tillage depth. Initial solute concentration was estimated from the ECe data. The obtained van Genuchten parameters were used to characterize the soil physical properties. Through the irrigation calendar, frequency, quantity and salt concentration of each irrigation, it was possible to reproduce the experimental conditions. The meteorological station available in the experimental field gave daily observations of precipitation, temperature, relative humidity, net radiation and wind speed. The weekly values of leaf area index (LAI) were measured to calculate Ep, and root depth was also measured.

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The following numerical experiments were carried out. 1. Considering the physical properties of the 0 and 1%, plots the effects of two different irrigation frequencies (2 and 10 days) with saline water for 4 years were simulated on the eggplant crop. Thus the long-term effects of saline irrigation were evaluated. 2. Using the soil physical properties of plot 1%, the effect of two different irrigation frequencies (every 2 and 10 days) with fresh water for 4 years were simulated. The simulation of irrigation with normal water on saline soil provides a prediction of its recovery. The results of the simulations are expressed by the values of the indicator Sc. To carry out these numerical experiments three steps were needed. (a) Model calibration: this was performed for the plot irrigated with normal water (0%) every 5 days (treatment 0% T5) where measurements of soil water content were available throughout the soil profile and at different times. At every calibration attempt the sum of squared deviations was calculated between measured soil moisture data and simulated data. (b) Model validation: SWAP was validated against measurements of soil water content for the plot irrigated every 5 days with sodic water (treatments 1% T5). Calculated crop production was also compared with observed crop production from the plot irrigated with normal water every 2 and 10 days (treatments 0% T2, 0% T10) and with saline water every 2 and 10 days (treatments 1% T2, 1% T10). (c) Model sensitivity: analysis of model sensitivity was performed to assess the impact of model calculation, of the observed difference in soil physical properties between the control, 0% T2, and the saline treatment, 1% T10 were carried out. Therefore, on the snapbean crop (planted DOY 154, harvested DOY 212) simulations in which the variables changed were the soil physical properties were carried out. 3. Long-term scenarios (4 years) were performed for the experiment (1% T10) to evaluate the sustainability of irrigation management options. On the basis of irrigation schedules frequently applied in the geographical area of our study and of irrigation strategies reported in the literature, ``cycling fresh/saline waters on salinized soil'' was simulated. An irrigation frequency of 2 and 10 days was applied and the quality of the irrigation water was alternated at each application between fresh and sodic water with 10 g l 1 of NaCl. 3.1.1. Numerical experiments The specific data used in each numerical experiment are listed in Table 5. The effect of different irrigation strategies was evaluated on the extreme treatments 0 and 1%. Therefore on the 0 and 1% plots two irrigation frequencies (2 and 10 days) and sodic water (10 g l 1 of NaCl) were considered. These simulations provide indications of longterm effects of saline irrigation. On the saline plot (1% T2 and T10) two irrigation frequencies of 2 and 10 days and fresh water were considered. These simulations provide a prediction of the recovery of saline soil. The results of the simulation are expressed by the following indicator Sc: Sc ˆ

‰…Sa ‡ Sd †Šf ‰…Sa ‡ Sd †Ši ‰…Sa ‡ Sd †Ši

(5)

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Table 5 Schematization of the model simulation carried out to evaluate the long-term effects of saline irrigation Physical properties used 0% 0% 1% 1% 1% 1%

Water quality 1

T2 T10 T2 T10 T2 T10

Saline (10 g l NaCl) Saline (10 g l 1 NaCl) Saline (10 g l 1 NaCl) Saline (10 g l 1 NaCl) Fresh (0 g l 1 NaCl) Fresh (0 g l 1 NaCl)

Frequency

Run time

Crop

2-day ˆ T2 10-day ˆ T10 T2 T10 T2 T10

1990±1993 1990±1993 1990±1993 1990±1993 1990±1993 1990±1993

Eggplant Eggplant Eggplant Eggplant Eggplant Eggplant

where Sa is the total adsorbed salts in the soil pro®le (mg cm 2), Sd the total dissolved salts in the soil pro®le (mg cm 2), f ®nal and i for initial. The initial and ®nal values refer to the beginning and the end of the observation period. Table 6 reports the data used for model sensitivity. Model sensitivity was tested with the soil physical properties observed for the 0% T2 treatment. The water was fresh water, the frequency was 2 days, applied on snapbean crop for the period 90±93 and the initial water and salt content were those reported in Table 6. The simulation now mentioned is identified by (code A). To ascertain whether the model was able to respond to the changed soil physical properties, the only parameters that were modified in the AA simulation are the soil physical properties, belonging to the 1% T10, while the irrigation frequency, water quality, crop, run time, and the water and salt content are the same as those of the A simulation. The same consideration was made for simulation B in which the soil physical parameters and all the data reported in Table 6 were those referring to 1% T10. Model sensitivity was evaluated by changing the soil physical parameters from 1% T10 to 0% T2 (BB simulation). Instead all the other data refer to the 1% T10 treatments. Therefore simulation A against AA, and also simulation B against BB, allowed us to evaluate model sensitivity, since, if different results are obtained between them, they can be attributed to the changed soil physical properties, and more importantly to the ability of the model (sensitivity) to express such small changes in different results. Table 6 Overview of the numerical experiments carried out to assess model sensitivity to observed soil hydrological propertiesa Identification Soil code hydrological properties

Water quality

A AA BB B

Fresh (0 g l 1 NaCl) 2 Fresh (0 g l 1 NaCl) 2 Saline (10 g l 1 NaCl) 10 Saline (10 g l 1 NaCl) 10

0% 1% 1% 0%

T2 T10 T10 T2

Frequency Run time (days)

1990±1993 1990±1993 1990±1993 1990±1993

Crop

Initial mean water content (cm3 cm 3)

Initial mean salt content (mg cm 2)

Snapbean Snapbean Snapbean Snapbean

0.26 0.26 0.28 0.28

1.5 1.5 4.5 4.5

a In each paired experiment (A and AA, B and BB) the soil hydrological properties were used as observed for the irrigation treatments listed in the table. Initial conditions were specified using observed vertical profiles of soil water content and salt concentration. Here the mean values only are given.

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Table 7 Overview of numerical experiments performed to evaluate irrigation sustainability of cycling fresh and saline water Physical properties used

Frequency

Water quality (alternated application) Fresh

1% T10 1% T10

T2 T10

0gl 0gl

Run time

Crop

Identification code

1990±1993 1990±1993

Snapbean Snapbean

C D

Saline 1 1

NaCl NaCl

10 g l 10 g l

1 1

NaCl NaCl

By contrast, comparing simulation A against B, the evaluation of different soil physical properties, irrigation scheduling, water quality and initial soil conditions are estimated. Moreover the differences observed between simulation AA and BB refer to the changed soil physical properties, to irrigation scheduling, water quality and the changed initial soil content. The sustainability of selected irrigation strategies was evaluated as reported in Table 7. Using the soil physical properties observed for treatment 1% T10, two irrigation frequencies of 2 and 10 days were tested. At each day of irrigation the water quality changed. The first irrigation was with normal water and alternated saline±fresh water followed. The evaluation of irrigation strategies was carried out over a period of 4 years. These simulations were performed under the same crop conditions. The crop conditions considered were those relative to non-saline soil. In saline condition the crop requirement is affected by salt stress. Therefore the crop responds to it with a decrease in crop requirement. 3.2. Data analysis 3.2.1. Soil hydrological properties RETC is a computer program to describe the unsaturated soil hydraulic properties for monotonic drying or wetting in homogeneous soils. Soil water retention data are described with the equations of Brooks and Corey (1964), whereas the pore-size distribution models of Burdine and Mualem are used to describe the h(y) and K(h) characteristics in a parametric form (van Genuchten et al., 1992). We used this model to analyze the data from the experimental field of Torre Lama. The model of Mualem (1976a) for predicting the relative hydraulic conductivity, K, uses the Se (relative saturation) variable: y yr (6) ys yr where Se is the effective degree of saturation, also called the reduced water content (0  Se  1), ys the soil water content at saturation and yr is the residual water content. Another function that aptly describes the hydraulic properties is the van Genuchten (1980) equation: Se ˆ

1 (7) ‰1 ‡ …ah†n Šm where a, n and m are empirical constants affecting the shape of the retention curve. Se ˆ

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From different studies it was concluded (van Genuchten et al., 1992) that the equation gives an excellent fit to the observed data for most soils. As a function of pressure head, K(h) is expressed as K…h† ˆ

Ksat f1

…ah†mn ‰1 ‡ …h†n Š

m 2

g

n ml

‰1 ‡ …ah† Š

(8)

where m ˆ 1 l/n. Some of the constants have a physical meaning. Inspection of Eqs. (6) and (8) shows that the soil water retention curve, y(h), contains ®ve parameters. The residual water content, yr, refers to the water content where the gradient dy/dh becomes zero. In practice yr is the water content at some large negative value of the water pressure head. The dimensionless parameter n determines the rate at which the S-shape retention curve turns toward the ordinate for large negative values of h, thus reflecting the steepness of the curve. The a (cm 1) parameter equals approximately the inverse of the pressure head at the inflection point where dy/dh has its maximum value (Wosten and van Genuchten, 1988). The predictive equation for K introduces two additional unknown factors: (1) the pore connectivity parameter, l and (2) Ksat, the saturated hydraulic conductivity. The RETC code may be used to fit anyone, several, or all of these parameters simultaneously to observed data. RETC uses a non-linear least-squares optimization approach to estimate the unknown model parameters from observed retention and/or conductivity or diffusivity data. The approach is based on the partitioning of the total sum of squares of the observed values into a part described by the fitted equation and a residual part of observed values around those predicted with the model. The aim of the curve fitting process is to find an equation that maximizes the sum of squares associated with the model, while minimizing the residual sum of squares. The residual sum of squares reflects the degree of bias and the contribution of random errors. 4. Results 4.1. Field conditions prior to the experiment Soil salinity was monitored throughout the 6 years of the experiment. In 1988, when the experiment was begun, all plots had the same ECe (Fig. 1). Over the years there is clear evidence that no significant change in ECe was observed in the plots irrigated with fresh water (0% T2 and 0% T10). By contrast, ECe increased linearly with time for the treatments with sodic water (1% T2 and 1% T10). The latter implies accumulation of salts over the years. Treatment 1% T2 had higher ECe values through the years than 1% T10. The higher accumulation of salts with an irrigation frequency of 2 days is explained by the larger water gifts in the 10-day treatments. In the control (0% treatment) and in the 1% treatment irrigated with saline water, cyclical seasonal fluctuations may be observed (Fig. 2) with higher values occurring during the dry season and lower values after the autumn±winter rains (Fig. 2).

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Fig. 1. ECe time course from the beginning of research, and rainfall from April 1988±September 1993.

4.2. Effects of sodic water on soil physical properties The Mualem±van Genuchten parameters were estimated for the 0±30 cm soil layer and for each treatment. This soil layer is constructed by combining two samples taken at depths of 0±10 cm and two samples at a 20±30 cm depth. For each parameter the average and the standard deviation of the four samples is given (Table 8). The yr value was much higher in the 0% treatment than in the 1% treatment. The n and m values are much lower for the 1% than for the 0% treatment. The Ksat was not measured but is obtained by fitting

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Fig. 2. Monthly ECe values (layer 0±30 cm) for 2- and 10-day irrigation frequencies.

data in the unsaturated range of the pressure head. The measurements to obtain h(y) and K(h) did not extend through the range of pressure head necessary to obtain a reliable K(h) curve, so evaluation was focused on the h(y) curve. In the latter case the fit obtained was rather good (Figs. 3 and 4). The h(y) curve for both treatments has a somewhat anomalous behavior, since the inflection point is not so evident. Nevertheless, the h(y) curve of the 0% treatment has a clearer inflection point. At equal pressure head, the (y) values for the 1% treatment are

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Fig. 3. Water retention (characteristics) of treatments 0 and 1% with 2-day frequencies in layers 0±10 and 20± 30 cm.

lower than for the 0% treatment in the range of pressure head between 100 and 500 cm. The latter is clearly seen by plotting the h(y) curves in the 100±500 cm range only (Fig. 5). To assess whether the differences in the van Genuchten parameters between treatments are significant, Student's t-test was applied (Table 9). This test does not indicate the cause

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Fig. 4. Water retention (characteristics) of treatments 0 and 1% with 10-day frequencies in layers 0±10 and 20± 30 cm.

of the difference (i.e. use of sodic water). It simply indicates whether the observed differences are significantly larger than the random experimental errors. To estimate the random errors, the four samples were grouped together and the standard deviation and the mean value calculated.

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Table 8 Average values of the Mualem±van Genuchten parameters of the soil samples and their standard deviations Parameters

Treatments 0% T2

3

3

ys (cm cm ) yr (cm3 cm 3) n m

40.6 24.3 1.98 0.495

   

0% T10 5.02 4.41 0.11 0.11

34.0 21.0 1.64 0.388

   

1% T2 7.83 9.05 0.09 0.035

35.4 6.9 1.23 0.178

   

1% T10 6.2 7.91 0.13 0.084

35.4 0.0 1.11 0.103

   

6.13 0.0 0.01 0.01

Student's t-test was calculated at the 95% confidence interval with three degrees of freedom (four samples in each group only) obtaining a critical value for t of 2.35. 4.3. Intra-seasonal variability of soil physical properties Although the differences in Ksat were not significant, field measurements of cumulated infiltration (Fig. 6) prove that the permeability of the 1% treatments was much lower than the permeability of the 0% treatments. The impact of Na on pore space is further confirmed by the seasonal fluctuation in cumulated infiltration for the 1% treatment, while changes were small for the 0% treatment. Further evidence for the impact of NaCl-enriched irrigation water is provided by our measurements of infiltration rates (Fig. 7). Compared with an infiltration rate of 12 (in Table 9 Significance of the difference of the yr, n and m parameters in the van Genuchten equation Parameters

yr

n

m

Treatments 0% T2

0% T10

1% T2

1% T10

0% 0% 1% 1%

T2 T10 T2 T10

±

nsa ±

hsb ns ±

hs hs hs ±

0% 0% 1% 1%

T2 T10 T2 T10

±

hs ±

hs hs ±

hs hs hs ±

0% 0% 1% 1%

T2 T10 T2 T10

±

hs ±

hs hs ±

hs hs hs ±

a b

Non-significant. Highly significant.

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Fig. 5. Average of the water retention curve for the 0 and 1% treatments, in the pressure range between 100 and 500 cm.

143

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summer) and 19 mm h 1 (in winter) of the control irrigated with normal water, the 1% treatment gave a rate of 0.6 mm h 1 in summer, whereas in winter there was no infiltration for 6 h. 4.4. Model calibration Three variables were used for model calibration: (a) the lower boundary condition; (b) the attenuation coefficient for net radiation; and (c) the function describing root water uptake. As described in Section 3, water tends to accumulate at the interface between the upper and lower soil layers. We took this feature into account by specifying the lower boundary condition as pressure head being zero at this interface, i.e. at a depth of 1 m. This considerably improved agreement between simulated and observed soil water content. The attenuation coefficient describes absorption of net radiation within the canopy (Belmans et al., 1983) as Rn(z† ˆ Rn (top of canopy) exp( coefficient LAI), where LAI is the leaf area index. We increased the value of this coefficient from 0.6 to 0.9. This increases absorbed net radiation and therefore potential transpiration. Finally we used the function given by Prasad (1988) instead of that originally given by Feddes et al. (1988). These modifications were applied step by step. Finally as shown in Table 10, the RMS error for the 0% T5 plot was equal to 3.9%. Table 10 shows, for the top layer, that the simulated data are close to the measured data, except for some days of the simulation (such as days 194 and 208) where the differences are significant. For the 30±60 cm layer the simulated values are higher than the measured data. This possibly depends on a discontinuity in the soil profile that is more evident in the 0% plot compared with the 1% plot where the simulated data of this layer are closer to the measured data. Such discontinuity in the soil profile was documented by the values of the WSI (Fig. 8). In the 60±90 cm layer the simulated data are almost constant and again close to those observed (Table 10). 4.5. Model validation SWAP was validated against independent measurements of soil water content performed on the 1% T5 treatment. The simulation was made in the same way as for the calibration but this time the soil physical properties were those obtained for 1% treatments. The observations are reproduced very well by SWAP (Table 11), and the RMS error was 3.5%, even lower than the value obtained in the calibration experiments. In some instances deviations of simulated from observed soil water content are slightly larger. A better agreement was obtained for the 30±60 cm layer compared with the calibration case. The calculated relative yields obtained by Eq. (4) for all treatments are given in Table 12. Yact is the actual observed yield, while the actual transpiration (Tact) was estimated with SWAP. For these treatments simulated crop yield was calculated with Eq. (4). Observed relative yields were obtained by taking the value for the 0% T2 as Ypot (46 t ha 1). For the 0% T2 treatment the actual relative yield was 1 against the calculated value ˆ 0:93, a rather good agreement.

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Fig. 6. Infiltration cumulated in summer 1993 and winter 1994, for treatments 0 and 1%.

4.6. Evaluation of model sensitivity We evaluated model sensitivity to changes in soil hydrological properties as described in Section 3 (see Table 6 for an overview of the sensitivity experiments). As indicated by the differences in Sc values (Table 13), changes in soil hydrological properties lead to significant changes in the pattern of salt accumulation and leaching. For example, the Sc value is 0.86 for the AA simulation against 0.73 for the control A simulation. A

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Fig. 7. Infiltration rate of the 0 and 1% treatments measured in summer 1993 and winter 1994.

greater difference in the Sc value is observed between the B simulation ( 0.01) against the BB simulation that gave a Sc of 0.24. In a more general sense, the results of the numerical experiments with fresh and saline water are similar: using the soil hydrological properties observed for the saline treatments leads to larger values of calculated leaching. 4.7. Evaluation of irrigation strategies The irrigation strategies listed in the leftmost column of Table 14 were evaluated using SWAP by comparing values of the Sc indicator. The latter provides a straightforward comparison of salt accumulation throughout the years for all the scenarios irrigated by saline water (SW) and leaching for the normal water (NW) scenarios. Over the entire

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Table 10 Value of the soil moisture (%) measured (Me) and simulated (Si) at different depths (cm) during the crop season and the RMS error (RMS) for the treatment irrigated with normal water every 5 days (0% T5)a Day number

164 173 183 194 208 215 222 237 251 a

0% T5 Me

Si

Me

Si

Me

Si

0±30 (cm) (%)

0±30 (cm) (%)

30±60 (cm) (%)

30±60 (cm) (%)

60±90 (cm) (%)

60±90 (cm) (%)

18.46 24.70 20.15 21.94 19.04 19.18 16.69 18.35 21.92

16.62 24.80 18.18 28.19 25.47 18.36 17.71 25.15 23.48

24.19 28.08 28.37 22.89 22.03 25.34 24.91 25.02 30.53

33.16 33.32 33.32 33.75 33.78 33.12 32.95 34.25 34.25

38.35 43.43 40.65 38.65 41.43 35.57 31.57 30.03 42.97

35.25 35.22 35.25 35.20 35.25 35.22 35.20 35.30 35.30

RMS ˆ 3:9%.

Fig. 8. Changes in the water index stability of the soil structure in relation to soil depth during 1993.

period considered in the numerical experiments, the differences between irrigation scenarios are somewhat self-evident, such as the large increase in solute accumulation when using sodic water on the fresh water treatment. Of greater interest are differences between scenarios observed for individual years. The effect of changing irrigation frequency, for example, is highly dependent on the amount and distribution of rainfall. In 1991 and 1993 even the use of sodic water on the fresh water treatment did not lead to large solute accumulation.

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Table 11 Value of the soil moisture (%) measured (Me) and simulated (Si) at different depths (cm) during the crop season and the RMS error (RMS) for the treatment irrigated with saline water every 5 days (1% T5)a Day number

164 173 183 194 208 215 222 237 251 a

1% T5 Me

Si

Me

Si

Me

Si

0±30 (cm) (%)

0±30 (cm) (%)

30±60 (cm) (%)

30±60 (cm) (%)

60±90 (cm) (%)

60±90 (cm) (%)

24.12 32.56 29.45 28.42 29.75 23.53 24.57 31.67 29.16

23.58 29.18 23.44 29.49 28.84 22.80 22.80 27.16 24.81

31.52 37.79 38.10 30.14 26.77 32.74 35.04 33.51 38.10

33.48 34.52 33.11 35.25 33.70 32.48 32.65 33.97 33.36

37.70 43.95 39.04 39.93 40.53 34.86 32.04 34.57 44.55

35.50 35.56 35.44 36.06 35.36 35.25 35.30 35.53 35.43

RMS ˆ 3:5%.

Table 12 Actual yield, observed relative yield and calculated relative yield obtained with numerical experiments described in the texta Treatments

Actual crop production (t ha 1)

Observed relative yield (t ha 1)

Transpiration (cm)

Calculated relative yield

0% 0% 1% 1%

46.0 41.8 14.8 23.0

1.00 0.90 0.32 0.50

34.6 26.3 18.3 14.2

1.00 > Yr > 0.93 0.90 > Yr > 0.70 0.32 > Yr > 0.49 0.50 > Yr > 0.38

T2 T10 T2 T10 a

Relative yield Yr calculated as T act =T pot ˆ Y act =Y max .

4.8. Sustainability of irrigation with sodic water The cycling of fresh and sodic water (1% treatment) was evaluated by numerical experiments. Two irrigation frequencies were considered (Table 15): 2 (schedule C) and 10 days (schedule D). In both cases the salt is leached, but the amount leached is slightly higher with a frequency of 10 days. This is explained by the larger water gifts in schedule D. Cycling of Table 13 Values of the indicator Sc calculated for the numerical experiments performed to assess model sensitivity Identification code A AA BB B

1990 0.25 0.52 0.22 0.02

1991 0.25 0.45 0.05 0.06

1992 0.41 0.36 0.05 0.11

1993 0.19 0.19 0.02 0.03

1990±1993 0.73 0.86 0.24 0.01

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Table 14 Values of the indicator Sc calculated for all the scenarios simulated Scenarios 0% 0% 1% 1% 1% 1%

T2 ‡ SW T10 ‡ SW T2 ‡ SW T10 ‡ SW T2 ‡ NW T10 ‡ NW

1990 1.16 1.27 0.15 0.17 0.49 0.58

1991

1992

0.13 0.07 0.08 0.03 0.42 0.52

1993

0.26 0.37 0.06 0.12 0.37 0.32

1990±1993

0.10 0.04 0.09 0.19 0.26 0.27

2.37 2.22 0.19 0.09 0.86 0.89

Table 15 Values of the Sc indicator calculated for the irrigation strategies simulateda Identification code

1990

1991

1992

1993

1990±1993

C Water content (cm3 cm 3) Number of days in which y < 0.33

0.46 0.34 13

0.11 0.35 3

0.04 0.35 6

0.00 0.34 15

0.53

D Water content (cm3 cm 3) Number of days in which y < 0.33

0.45 0.33 27

0.15 0.34 22

0.04 0.34 12

0.01 0.32 35

0.57

a

Water content (y) of the soil profile 0±90 cm, number of days in which the water content of the soil profile is below the water content at field capacity (y ˆ 0:33 cm3 cm 3).

fresh and sodic water increases leaching significantly, as shown by the value of Sc obtained for schedule D in comparison with schedule B (Table 13). The amount of salt leached with schedule D (Sc ˆ 0:57) is twice the amount leached with schedule B (Sc ˆ 0:24). 5. Discussion of results 5.1. Field conditions prior to the experiment The evolution of soil salinity from the start of the experiment indicates that all plots were originally in the same condition, such that observed impacts of irrigation treatments on soil properties and crop yield are due to the applied irrigation water, its frequency and solute concentration. The pattern of observed seasonal fluctuations in soil salinity is explained by the rising of salts normally contained in the soil and by the amount of NaCl added through irrigation in the spring±summer period when evapotranspiration prevails, and by leaching of the salts in the autumn±winter period, when percolation prevails. Such cyclical oscillations are very limited in the 0% plot but considerable for the 1% treatment, with very marked differences from the control, in summer when irrigation water enriched with NaCl is applied.

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5.2. Effects of sodic water on soil physical properties The different behavior of the soil water retention curve for the 1% compared to the curve for the 0% treatment may be explained by clay swelling. The latter occurs when a large amount of Na is present on the exchangeable complex and may result in blocking or partial blocking of the conducting pores (Quirk and Schofield, 1955). According to several authors (Frenkel et al., 1978; Shainberg et al., 1981a,b; Quirk, 1986) sodium causes the deterioration and deflocculation of the clay colloids with a reduction in porosity and extremely unfavorable consequences with regard to permeability. Somani (1991) concluded that all these changes are clearly reflected by water retention curves. In fact our curves indicate a close relationship between the degree of Na saturation and the water retention of the soil, particularly in the range 2.0±3.0 pF. The values of available soil water content obtained for our experiment (see Figs. 4 and 5) were rather low. To evaluate these results we took an other series of samples in 1999 on the 0 and 0.5% treatments for the 0±30 cm soil layer. The soil water content at field capacity (h ˆ 330 cm) was rather close to our previous results and the resulting available soil water content was again rather low. We obtained (1999 soil sample) 0.10 cm3 cm 3 on the 0% treatment and 0.15 cm3 cm 3 on the 0.5% treatment. Since these samples were analyzed in a different laboratory using different methods we conclude that our low values of available soil water are reliable. This result might be the consequence of occlusion of small pores due to the deposition of salts. We note that our fresh water has a rather high Na content. The differences in the van Genuchten n and m parameters among the extreme treatments of 0% T2, 1% T2, and 0% T10, 1% T10 are highly significant (Table 9). The differences in the estimated Ksat were not significant as expected on the basis of the poor accuracy of estimates. Differences in yr were significant between the 1 and 0% treatments. There was an exception though the difference between the 1% T2 and 0% T10 was not significant. It should be recalled (Table 2) that a significant amount of Na is present in the water used in the 0% treatments. Because of the lower frequency of irrigation (i.e. 10 days), solute deposition and degradation of clay colloids may occur in the 0% T10 treatment as indicated by the seasonal fluctuations in ECe (Fig. 2). Moreover, solute deposition tends to be less in the 1% T2 treatment than in the 1% T10 treatment because of the higher frequency of irrigation which keeps the soil wetter. The combination of the two factors tends to reduce the difference in the impact of Na on the soil water retention curve. 5.3. Intra-seasonal variability of soil physical properties The cumulated infiltration rate related to the 1% treatment in winter is plotted with a hatched line to indicate our best guess of what the infiltration trend could have been. This very great reduction in the infiltration rate may be explained by the presence of exchangeable Na and by the formation of a surface crust due to the high sodium content. The latter causes dispersion of the clays with the consequent formation of fine pores. A further consequence is high bulk density as well as the decrease in hydraulic conductivity of the bulk of the underlying soil (Frenkel et al., 1978; Kazman et al., 1983; Shainberg

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and Letey, 1983). The abundant rains occurring in the period immediately before the measurements may also have contributed to the lack of infiltration in winter. The anomalous trend of the infiltration in the 1% treatment in summer must also be attributed to the presence of a surface crust. Initially the superficial crust prevented infiltration, while later on the softening and/or fissuring of the crust led to a higher infiltration rate. Even later during the infiltration test, the infiltration rate stabilized around the above mentioned value of 0.6 mm h 1. Such deterioration was greater in the two layers closer to the surface, where the largest accumulation of salts was observed. Furthermore, in the control treatment, an unexpected degradation of the structure was observed in the 30±60 cm layer, which indicates a discontinuity of the profile in this layer. As no similar discontinuity was found in the texture, the explanation of such behavior may be sought in the presence of a plough pan at around 35±40 cm. Above this the soil would appear to remain moister, creating an environment which does not promote good decomposition of organic matter and leads to deterioration of structure stability (Cavazza et al., 1986). 5.4. Model calibration The greatest improvement in model accuracy on soil water content was obtained by specifying pressure head h ˆ 0 at z ˆ 1 m (bottom boundary condition). This is the approximate depth up to which soil structure is modified by deep tillage done regularly (prior to the experiment) at the location of the experiment. Visual inspection of the soil profile (Scheme 1) shows a clear boundary between an upper and lower soil layer at this depth. Soil tillage does lead to relatively higher permeability in clay soils, so we concluded that a sharp decrease in soil permeability is likely to occur at an approximate depth of 1 m and this leads to accumulation of water during irrigation. We reproduced this situation with our bottom boundary condition. The higher value of the attenuation coefficient accounts for differences in canopy architecture and leaf absorptions between our crops and those considered by Belmans et al. (1983). 5.5. Model validation The lower irrigation frequency on the 0% T10 treatment determined a decrease in the actual transpiration equal to 70% of the potential (Tact/T pot ˆ 0:70), while the actual relative yield was 90% (0.90) against the reference value of (1.00), i.e. a reduction of only 10%. In the 1% T2 treatment, where irrigation with saline water is given every 2 days, saline stress reduced the actual transpiration to about half of the potential (0.49) while the effect on yield was stronger, i.e. 32% of potential. In the 1% T10 treatment, a marked reduction in the actual transpiration (38% of potential) and yield (50% of potential) was observed. The higher yield (50%) of the 1% T10 treatment compared with the 1% T2 treatment (32%) can be explained by the irrigation frequency. With an irrigation frequency of 10 days (1% T10), each water gift is five times bigger than a water gift in 1% T2. So the wetted profile is larger and more layers are involved. Hence, some of the salts are

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leached. Instead in the 1% T2 treatment, where the irrigation frequency is 2 days and the water gifts are smaller, the wetted profile is small and fewer soil layers are involved, so there is less leaching. In conclusion, calculated relative yields have the same general trend as the observations, but calculated values of relative yield were significantly different from observations. 5.6. Evaluation of the model sensitivity The numerical experiments performed to assess model sensitivity indicate that the differences in the estimated Mualem±van Genuchten parameters do have a significant influence on model results. This implies that these differences must be taken into account when evaluating irrigation schedules with SWAP. The results were also rather consistent: changing the soil properties from those of the ``fresh water: high irrigation frequency'' treatment to those of the ``saline water: low irrigation frequency'' gave a higher value of calculated leaching, independently of the type of water and initial conditions. This is easily explained by the lower permeability of the 1% treatments. These simple experiments confirmed model sensitivity to the irrigation schedule in combination with initial conditions, i.e. A versus B and AA versus BB and to irrigation. 5.7. Evaluation of irrigation strategies The results obtained show significant interannual variability due to variability in rainfall and other climatic factors. Irrigation strategies, therefore, should be evaluated over a long period of time, taking into account both climatic variability and long-term impacts on soil conditions. 5.8. Sustainability of irrigation with sodic water Both schedules C and D have advantages and disadvantages. Higher irrigation frequency is beneficial (see also Sharma et al., 1977; Minhas, 1994) because the moisture content is higher and reduces salt accumulation. Strategies in which the frequency is lower but the amount of water given at each water application is higher, such as D, are also beneficial because at each time the volume of water is high and able to leach salts from the root-zone. In Table 15 the average water content throughout the crop season (length of the crop season 60 days) for each year is reported. The number of days in which the average water content of the soil profile is below the value of the water content at field capacity (y ˆ 0:33 cm3 cm 3) is shown. The C case gives a water content slightly higher than the D case for the years considered. If we define a ``dry day `` as one when the water content of the soil profile is below the water content at field capacity (Table 15), it is clear that the 10-day irrigation frequency leads to more dry days than the 2-day irrigation frequency. Indeed, for 1990 the number of dry days is 13 for the 2-day irrigation frequency against 27 days for the 10-day frequency. For the following years the trend is the same, with more dry days when the irrigation frequency of 10 days is considered.

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Such results confirm that: 1. a higher irrigation frequency determines higher moisture content of the soil pro®le and less salt accumulation; 2. a lower irrigation frequency in which the amount of water given at each water application is higher, causes greater amounts of salts to be leached from the root-zone at every application. The strategies applied by cycling fresh and saline water (C and D simulations) have been proposed by several authors (Dinar et al., 1986; Agarwal and Roest, 1986) to improve water availability. In our case the cycling starts with fresh water and is followed by saline water and an alterance of 1:1 was performed. Initial irrigation with fresh water is necessary, since more crops are most sensitive to salinity in the early growth stage. 6. Summary and conclusions After 6 years of trials, in the plots irrigated with 1% saline water, besides an increase in the ECe values, a considerable increase in ESP (64) was recorded. Furthermore, the soil structure showed deterioration along the whole profile, clearly as a result of the deflocculation of clay colloids induced by the sodium. Such deterioration, which was considerable in the surface layers due to the greater accumulation of salt, caused a severe reduction in soil permeability, thereby leading to a further slowdown in salt leaching which, because of insufficient autumn±winter rainfall, was already at low levels. Significant differences in the h(y) curves for the plots 0% T2, T10 and 1% T2, T10 were observed. The h(y) curve of the 1% treatments and both irrigation frequencies had lower values of y than the 0% treatments at the same pressure head. The water retention curves show a clear relationship between the level of sodium and a reduction in soil retention, especially in the range 2.0±3.0 pF. To assess the impact of different irrigation schedules alternating saline and fresh water a numerical model of soil water and solute flow (SWAP) was applied. SWAP is a deterministic model describing water and solute transport: it describes root water uptake through a sink term dependent on soil pressure head and osmotic pressure head added to the continuity equation of soil water flow. The model was calibrated using data collected on the 0.5% T5 treatment. The RMS error was 3.5%. The crop yield (eggplant) estimated on the basis of simulated crop transpiration compared well with the observed yield. Lower irrigation frequency (10 days) led to a decrease in actual transpiration (70% of the potential) and in actual yield (90% of the potential), salt stress (1% T2) resulted in a decrease in actual transpiration (50% of the potential), and in actual yield (32% of the potential). By contrast, saline stress was combined with lower irrigation frequency but higher volumes, actual transpiration and crop yield decreased to 38 and 50% of the potential, respectively. The better outcome of the latter combination can be explained by the higher water gift of the 10-day irrigation frequency (five times larger than with a 2day frequency), resulting in a deeper wetted profile. The sensitivity of model results to the observed differences in soil hydrological properties between irrigation treatments was confirmed by performing numerical experiments.

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Irrigation strategies, on eggplant crop, were evaluated on the extreme 0 and 1% treatments. On these treatments several scenarios were evaluated to describe the effect of continuing saline irrigation and of using fresh water after termination of the saline treatments. We propose the use of performance indicator, Sc, to evaluate irrigation strategies. The indicator Sc calculated for each year and between the first and last year gives a clear idea of the salt accumulation in the soil and also which irrigation strategies lead to higher salt accumulation. Evaluation of cycling saline and fresh water on an already saline soil, showed that differences in performance between them depend significantly on the evolution of hydrological conditions in different years. Acknowledgements The authors are grateful to Dr. W.H. van der Molen for the detailed and careful comments he kindly provided on the first manuscript. Two reviewers provided many comments, detailed and to the point which improved the manuscript significantly. The authors sincerely appreciated the assistance provided in many ways by Dr. J.J.B. Bronswijk, Dr. W.G.W. Bastiaanssen, Prof. R.A. Feddes, Prof. G. Barbieri and Prof. L. Postiglione. References Agarwal, M.C., Roest, C.J.W., 1986. In: Agarwal, M.C., Roest, C.J.W. (Eds.), Towards Improved Water, Management in Haryana State. Final Report of Indo-Dutch Operational Research Project on Hydrological Studies. Alterra-Wageningen, 80 pp. Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop Evapotranspiration. Guidelines for Computing Crop Water Requirements, Vol. 56. FAO, 110 pp. Ayers, R.S., Westcot, D.W., 1985. Water Quality for Agriculture, Vol. 29. FAO Bulletin. Barbieri, G., Caruso, G., Postiglione, L., 1990. Response of processing tomato to irrigation with saline water. In: Proceedings of the 1st Congress of European Society of Agronomy, Paris, 27 December. Belmans, C., Wesseling, J.G.R.A., Feddes, R.A., 1983. Simulation model of water balance of a cropped soil: SWATRE. J. Hydrol. 63, 271±286. Boesten, J.J.T.I., van der Linden, A.M.A., 1991. Modeling the influence of sorption and transformation on pesticide leaching and persistence. J. Environ. Qual. 20, 425±435. Brooks, R.H., Corey, A.T., 1964. Hydraulic properties of porous media. Hydrology paper No. 3, Colorado State University, Fort Collins, CO, 27 pp. Caruso, G., Postiglione, L., 1993. Effetti dell'irrigazione con acqua a diversa concentrazione salina sul suolo e su cultivar di pomodoro da industria (Lycopersicon lycopersicum L.). Riv. Di. Agron. 3, 211±219. Cavazza, L., Patruno, A., Ardizzoni, E., 1986. Influenza di alcune lavorazioni su alcune proprietaÁ fisiche del suolo. Riv. Di. Agron. 2/3, 184±203. Chhabra, R., 1996. Soil Salinity and Water Quality. Oxford Press, New Delhi, 284 pp. Curtis, P.S., LaÈuchli, A., 1987. The effect of moderate salt stress on leaf anatomy in hibiscus cannabinus (Kenaf) and its relation to leaf area. Am. J. Bot. 74, 538±542. De Wit, C.T., 1958. Transpiration and crop yield. Versl. Landbouwk. Onderz. 64.6, The Hague, The Netherlands, 84 pp. Dinar, A., Letey, J., Vaux Jr., H.J., 1986. Optimal ratios of saline and no-saline irrigation waters for crop production. Soil Sci. Soc. Am. J. 50, 440±443.

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