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Distributed agro-hydrological modeling with SWAP to improve water and salt management of the Voshmgir Irrigation and Drainage Network in Northern Iran
Abstract
The agro-hydrological model SWAP was used in a distributed manner to quantify irrigation water management effects on the water and salt balances of the Voshmgir Network of North Iran during the agricultural year 2006-2007. Field experiments, satellite images and geographical data were processed into input data for 10 uniform simulation areas. As simulated mean annual drainage water (312 mm) of the entire area was only 14% smaller than measured (356 mm), its distribution over the drainage units was well reproduced, and simulated and measured groundwater levels agreed well. Currently, water management leads to excessive irrigation (621-1436 mm year-1), and leaching as well as high salinity of shallow groundwater are responsible for large amounts of drainage water (25-59%) and salts (44-752 mg cm-2). Focused water management can decrease mean drainage water (22-48%) and salts (30-49%), compared with current water management without adverse effects on relative transpiration and root zone salinity.
... Recently, distributed integrated crop and hydrological models have been widely used to simulate the complex agro-hydrological processes coupled with salt dynamics and crop production (Aghdam et al., 2013;Noory et al., 2011;Van Dam et al., 2008;Vanuytrecht et al., 2014). Taking advantage of geographic information systems (GIS), distributed integrated crop and hydrological models provide precise simulations of regional hydrological processes and crop growth by incorporating the heterogeneity of soil moisture, salinity, and texture, the groundwater table depth and salinity, and cropping patterns (Amor et al., 2002;Bastiaanssen et al., 2003a;Jiang et al., 2015;Nazarifar et al., 2012;Xue et al., 2017). ...
... Recently, distributed integrated crop and hydrological models have been widely used to simulate the complex agro-hydrological processes coupled with salt dynamics and crop production (Aghdam et al., 2013;Noory et al., 2011;Van Dam et al., 2008;Vanuytrecht et al., 2014). Taking advantage of geographic information systems (GIS), distributed integrated crop and hydrological models provide precise simulations of regional hydrological processes and crop growth by incorporating the heterogeneity of soil moisture, salinity, and texture, the groundwater table depth and salinity, and cropping patterns (Amor et al., 2002;Bastiaanssen et al., 2003a;Jiang et al., 2015;Nazarifar et al., 2012;Xue et al., 2017). ...
The temporal and spatial distributions of regional irrigation water
productivity (RIWP) are crucial for making decisions related to agriculture,
especially in arid irrigated areas with complex cropping patterns. Thus, in this study, we
developed a new RIWP model for an irrigated agricultural area with complex
cropping patterns. The model couples the irrigation- and drainage-driven soil water and salinity dynamics and shallow groundwater movement in order to quantify the temporal and spatial distributions of the target hydrological and biophysical variables. We divided the study area into 1 km × 1 km hydrological response units (HRUs). In each HRU, we considered four land use types: sunflower fields, wheat fields, maize fields, and uncultivated lands (bare soil). We coupled the regional soil hydrological processes and groundwater flow by taking a weighted average of the water exchange between unsaturated soil and groundwater under different land use types. The RIWP model was calibrated and validated using 8 years of hydrological variables obtained from regional observation sites in a typical arid irrigation area in North China, the Hetao Irrigation District. The model simulated soil moisture and salinity reasonably well as well as groundwater table depths and salinity. However, overestimations of groundwater discharge were detected in both the calibration and validation due to the assumption of well-operated drainage ditch conditions; regional evapotranspiration (ET) was reasonably estimated, whereas ET in the uncultivated area was slightly underestimated in the RIWP model. A sensitivity analysis indicated that the soil evaporation coefficient and the specific yield were the key parameters for the RIWP simulation. The results showed that the RIWP decreased from maize to sunflower to wheat from 2006 to 2013. It was also found that the maximum RIWP was reached when the groundwater table depth was between 2 and 4 m, regardless of the irrigation water depth applied. This implies the importance of groundwater table control on the RIWP. Overall, our distributed RIWP model can effectively simulate the temporal and spatial distribution of the RIWP and provide critical water allocation suggestions for decision-makers.
... The estimated yield is the most fundamental and important indicator with which to evaluate the performance of a crop model. At a regional scale, remote sensing is often coupled with crop models to estimate spatially accurate yields [24][25][26][27][28][29]. For example, Zhou et al. [28] incorporated MODIS-retrieved phenological information into the WOFOST model to improve rice leaf area index (LAI) simulation accuracy in the Dongting Lake region, Hunan province, China. ...
... Remote sensing data can provide more heterogeneous spatial and temporal information for crop model inputs, and have been widely used for calibration of canopy state variables [24,45,46], soil properties [25,47,48], and phenological information [28,42,49] in modeling processes. In the present research, the Global LAnd Surface Satellite LAI (GLASS LAI; [50]) product was used as ancillary remote sensing data to calibrate MCWLA-Rice over a large area; this product is superior in temporal integrity and spatial continuity than other available LAI products [50]. ...
Few studies have focused on the potential impacts of topography on regional crop simulation, which might constrain the development of crop models and lead to inaccurate estimations for food security. In this study, we used remote sensing data to calibrate a regional crop model (MCWLA-Rice) for yield simulation in a double-rice crop rotation system in counties of Hunan province dominated by three landforms (plain, hill, and mountain). The calibration scheme with coarse remote sensing data (Global LAnd Surface Satellite, GLASS) greatly improved model accuracy for the double-rice system and is a promising method for yield estimation in large areas. The average improvement in relative root mean square error (RRMSE) was at most 48.00% for early rice and 41.25% for late rice. The average improvement in coefficient of determination (R2) value was at most 0.54 for early rice and 0.19 for late rice. Estimation of yield in counties dominated by different landform types indicated that: (1) MCWLA-Rice tended to be unstable in areas of complex topography and resulted in unbalanced proportions of overestimations and underestimations. (2) Differences in yield simulation between early rice and late rice varied among counties; yield estimates were highest in predominantly hilly counties, followed by counties dominated by plains, and lowest in predominantly mountainous counties. The results indicated that the topography might harm the accuracy of crop model simulations. Integration of topographic factors into crop models may enable yield estimation with enhanced accuracy to promote social development.
... SWAP is an agro-hydrologic model that can simulate water and TDS transfer in soil layers and crop production. It has been widely used in groundwater level simulation in agricultural areas, irrigation scheduling, drainage system planning, and return flow simulations (Droogers et al. 2001;Singh 2004;Mostafazadeh-Fard et al. 2008;Noory et al. 2011;Bennett et al. 2013;Shafiei et al. 2014;Kumar et al. 2015;Hassanli et al. 2016;Tavakoli et al. 2015). Considering its wide application and short runtimes, SWAP has been selected to simulate the quantity and quality of agricultural return flows in the current paper. ...
... Based on the results of previous studies, as well as trial and error, inputs and parameters of the SWAP model that have more impact on the optimization results have been identified as initial groundwater levels, initial salinity of soil layers, hydraulic conductivity variables (Ks, Kh, LEXP), shape parameters of main wetting (n) and drying curves (α), residual (θ r ) and saturated (θ s ) water content of soil layers, and depth and salinity of irrigation water. Ranges of variations of the selected parameters are obtained from previous studies (i.e., Sarwar and Feddes 2000;Droogers et al. 2001;Noory et al. 2011;Samipour et al. 2010;Bennett et al. 2013;Shafiei et al. 2014;Tavakoli et al. 2014;Kumar et al. 2015;Soltani et al. 2016) and recommendations provided in SWAP documents. ...
A new methodology is proposed for sizing the required infrastructures for water and waste load allocation in river systems receiving return flow from agricultural networks. A nonlinear optimization model with a constraint based on Conditional Value at Risk (CVaR) is developed to provide water and waste load allocation policies. The CVaR-based constraint limits the probabilistic losses due to existing uncertainties in available surface water. The deep uncertainties of return flow simulation model parameters, which have significant impacts on the simulated quantity and quality of agricultural return flows, are handled by using the Info-Gap theory. Total Dissolved Solid (TDS) is selected as water quality indicator and diverting a fraction of return flows to evaporation ponds is considered to control the TDS load of agricultural waste load dischargers. Quantity and TDS load of agricultural return flows over a one-year cultivation period are simulated by using a calibrated SWAP agro-hydrological model. The results of many runs of SWAP model for different combinations of important uncertain parameters in their ranges of variations, provide some response (impact) matrixes which are used in optimization model. The applicability of the proposed methodology is illustrated by applying it to the PayePol region in the Karkheh River catchment, southwest Iran. The selected strategy for water and waste load allocation in the study area is expected to provide total annual benefit of 48.64 million US Dollars, while 7.84 million m3 of total return flow should be diverted to evaporation ponds. The results support the effectiveness of the methodology in incorporating existing deep uncertainties associated with agricultural water and waste load allocation problems.
... Their study focused on improving crop yields and WPs by improving crop husbandry, reducing seepage losses, and reallocating canal water. Noory et al. (2011) used a distributed SWAP-WOFOST model to evaluate current irrigation water management with regard to the amount of drainage water and its salinity in the Voshmgir Network of North Iran during 2006-2007. Their study aimed to improve the regional environment by changing irrigation water management at a regional scale. ...
... The results showed that the sum of simulated field drainage by the distributed SWAP-WOFOST model and the estimated amount of drainage from the canal seepage was 3.82 × 10 8 m 3 , close to the amount of water discharged annually into Wuliangsuhai (3.89 × 10 8 m 3 ). The NRMSE, MRE, and NSE of drainage amount were, respectively, 18.95%, 0.31%, and −0.43, close to the model performance as reported by Noory et al. (2011). In summary, the calibrated and validated model has the potential to help in future decision making for irrigation management in the HID. ...
The Hetao Irrigation District (HID) is an important food production area, where irrigation is essential for agriculture. Because of water shortages, it is crucial to optimize the irrigation schedule and cropping structure to preserve the water resource and maintain sustainable crop production. In this study, a distributed Soil-Water-Atmosphere-Plant WOrld FOod STudies model was calibrated and validated, and then used to simulate yield and water productivity (WP) during 2000–2010 in the HID. Then, the suggested irrigation schedules and the cropping structure were analyzed by comparisons of yield and WP. The results showed that, compared with the basic scenario, the annual average yields of spring wheat, spring maize, and sunflower were improved by 17.3, 1.2 and 10.5%, respectively, and the crop WPs were increased by 9.5, 3.7 and 16.5%, respectively, after division in the suggested irrigation scenario. The corresponding multiyear (2000–2010) average field irrigation amount (irrigation amount × cultivated areas) that would be saved was 4.89 × 108 m3. Although the capillary rise of groundwater was larger, the groundwater depth could not sustainably decline during 2000–2010. Therefore, the irrigation schedules and the cropping structure suggested in this study could contribute to more sustainable food production and reduced irrigation water usage in the HID.
... Nevertheless, these models do not specifically consider secondary salinity processes (such as agricultural activities). Noory et al. (2011) used the SWAP model for quantifying water management effects on drainage water amount and its salinity at the regional scale. Bailey et al. (2019) also applied a SWATbased model to an irrigated area. ...
Salinity is a major environmental phenomenon that affects watersheds and irrigated areas worldwide. The watershed-scale salinity modeling requires a watershed-scale model like the Soil and Water Assessment Tool (SWAT) that simulates hydrologic processes throughout a watershed. The Richards equation can assist in addressing very complex processes that affect water flow in the unsaturated root zone influenced by gravity and capillarity at a field scale. The SWAT model does not use the Richards equation for modeling flows in the root zone, resulting in less accuracy in simulating hydrologic processes related to agriculture. This study presents an integrated framework for the watershed-scale salinity modeling by modifying the water-salt balance (SWAT-S) model linked to the Soil Water Atmosphere Plant (SWAP) model. The integrated framework was applied to the Mond River Basin of Iran. The model was calibrated and validated with historical records of the river discharge and salt concentration using the SUFI-2 optimization algorithm to evaluate the model's strength and to verify the accuracy of simulations. The model performance was satisfactory in calibration and validation periods with the coefficient of determination (R²), Nash–Sutcliffe efficiency (NSE), Percent bias (|PBIAS|), and RMSE-observations standard deviation ratio (RSR) ranging from 0.56 to 0.87, 0.52 to 0.87, 0.2 to 22.2, and 0.37 to 0.69, respectively. Also, P‐factor values were more than 0.65, while R‐factor values were less than 1.40.
... According to previous studies, 19 crop parameters and 7 soil hydraulic parameters (Khan and Abbas, 2007;Noory et al., 2011;Qian et al., 2021) were selected for parameter sensitivity analysis ( Table 2). The results showed that LAI and yield were more sensitive to the change in crop parameters, while plant height was only sensitive to TSUMEA and TSUMAM. ...
Drip irrigation under film mulch (DIUFM) and subsurface pipe drainage (SPD) are important measures to cope with water shortages and soil salinization in arid areas of northwest China. To investigate the coordinated operation mode of DIUFM and SPD, a new H2DSWAP model was developed based on coupling the HYDRUS-2D with a Soil–Water–Atmosphere–Plant model (SWAP). In the H2DSWAP model, real-time evapotranspiration, simple root growth, and the interaction between crops and soil water and salt are considered to improve the simulation accuracy. The model was calibrated and validated using parameter estimation and uncertainty analysis software (PEST) using field experiment datasets in 2019 and 2020 respectively. Compared with the original HYDRUS-2D model, the simulation accuracy of the H2DSWAP for soil water (root mean square error (RMSE) = 0.011 cm³·cm⁻³; mean absolute error (MAE) = 0.008 cm³·cm⁻³; determinant coefficient (R²) = 0.869) and soil salt (RMSE = 0.296 g·kg⁻¹; MAE = 0.231 g·kg⁻¹; R² = 0.959) contents has been greatly improved. In addition, the simulation of the leaf area index (LAI) and yield also fitted well with field observations. The calibrated model was used to predict salt transport at depths of 0–100 cm and the change in maize yield under DIUFM. The results indicated that maize yield decreased yearly, and soil salinity increased yearly under DIUFM without SPD. Based on the obtained results, the management strategies of winter irrigation (WIR) under different drip irrigation water amounts, namely 600 mm (S1), 540 mm (S2), 480 mm (S3), and 420 mm (S4), were further investigated. Water productivity (WP) and yield were used as evaluation indices. The WIR was carried out every 4–5 years when the drip irrigation amount of the maize field was S1 and S2 was recommended. However, it was recommended to carry out WIR every 2 and 3 years under S3 and S4, respectively. Overall, the H2DSWAP model can be used as a useful tool to guide the operation mode of drip irrigation under mulch and subsurface pipe drainage in saline soils.
... However, it is difficult to quantitatively study the cycle and utilization of water and N in the field, due to the time-consuming and high cost of field experiments (Hao et al., 2014). Moreover, some water and N balance observations are difficult to measure directly (Noory et al., 2011). Therefore, simulation models are important alternatives for evaluating long-term water and N dynamics in the field (Rath et al., 2021). ...
Water shortage and poor soil fertility are the main factors restricting the sustainable development of peanut production in semi-arid areas of Northeast China. It is thus essential to have a deep understanding of the soil water-nitrogen dynamics and crop water/nitrogen use for developing water and nutrient strategies. Three levels of irrigation treatment (W 65 , 65% of field capacity; W 55 , 55% of field capacity; W 45 , 45% of field capacity) and a rain-fed treatment (CK) were implemented in field experiments conducted for peanut during the growing seasons of 2016 and 2017 in Liaoning, Northeast China. The AHC (Agro-Hydrological & chemical and Crop systems simulator) model was calibrated and validated, and then applied to assess peanut yield, water productivity (WP) and nitrogen use efficiency (NUE) for the present situation and future irrigation scenarios. The results indicated that the AHC model was capable of simulating soil water and nitrogen status and peanut growth. Simulations of soil water/nitrogen contents and crop growth indicators (Leaf area index, aboveground biomass, plant height and yield) fitted well with field observations. Simulated dynamics showed that 9-21% of the total water input and 14-27% of the total N input were leached out the root zone (0-60 cm). Rainfall was the main cause of water percolation and nitrogen leaching. The highest average yield (5701 kg ha-1) and NUE (26.77 kg kg-1) were obtained in the W 55 treatment. The WP was not obviously decreased under the W 55 treatment, and was only 4.1% lower than that of the CK treatment, in which the WP was highest. Based on scenario analysis with the consideration of crop yield, WP and NUE, the optimal irrigation amount of 80-97 mm is recommended for peanut cultivation in this region. We demonstrated that the AHC model could be used to develop water management strategies for peanuts in Northeast China to conserve water while sustaining agriculture.
... Related crop models include DSSAT (Jones et al., 2003), WOFOST (Van Diepen et al., 1989), and HERMES (Hlavinka et al., 2014). The other method uses the Richards equation to determine the spatial and temporal SWM (Ma et al., 2011;Noory et al., 2011;Zhou et al., 2012). In principle, the Richards equation is processbased and more accurate in identifying and representing SWM. ...
Sensitivity analysis is important for determining the parameters in the model calibration process. In our study, a variance-based global sensitivity analysis (extended Fourier amplitude sensitivity test, EFAST) was applied to an agro-hydrological model (the SWAP (Soil-Water-Atmosphere-Plant model) model). The sensitivities of 20 parameters belonging to 4 categories (soil hydraulics, solute transport, root water uptake, and environmental stresses) for the simulated accumulated transpiration, dry matter (DM), and yield of sunflowers were analyzed under three nitrogen application rates (N1, N2, and N3), four salinity levels (S1, S2, S3, and S4), and three root distributions (R1, R2, and R3). The results indicated that for predominantly loamy soils, the high-impact parameters for accumulated transpiration, DM, and yield were the soil hydraulic parameters (α and n), critical stress index for compensatory root water uptake (ωc), the salt level at which salt stress starts (Pi), the decline of root water uptake above Pi (SSF), residual water content (θr), saturated water content (θs), and relative uptake of solutes by roots (TSCF). We also found that nitrogen application did not change the order of the parameter impacts on accumulated transpiration, DM, and yield. However, TSCF replaced α as the highest-impact parameter for the accumulated transpiration, DM, and yield at high salinity levels (S2 and S3). Furthermore, α was also the highest-impact parameter for DM and yield under different root distributions, but the highest-impact parameters for transpiration were ωc, α, and θs under R1, R2, and R3, respectively. Nitrogen application could be neglected when considering the interactive effects of nitrogen application, salinity level, and root distribution on the transpiration, DM, and yield. Additionally, the mean values and uncertainties of the transpiration, DM, and yield were similar in all scenarios, except S3, which showed a sharp decrease in the mean values. We suggest determining the above eight parameters (α, n, ωc, Pi, SSF, θr, θs, and TSCF) and the saturated vertical hydraulic conductivity (Ks) based on rigorous calibrations with direct or indirect local measurements using economical methods (e.g., a literature review), with limited observations for other parameters when using the SWAP model and other similar agro-hydrological models. S. 2021. Sensitivity analysis of the SWAP (Soil-Water-Atmosphere-Plant) model under different nitrogen applications and root distributions in saline soils. Pedosphere. 31(5): 807
... However, these methods tend to be subjective in parameter quantization and are difficult to verify. In recent decades, the intelligent optimization algorithm has achieved continuous development, including ant colony optimization engine (Nguyen et al., 2016), the artificial neural network (Nguyen et al., 2019), the differential evolution algorithm (Adeyemo and Otieno., 2010;Vafashoar and Meybodi, 2020), the genetic algorithm (Ines et al., 2006;Arunkumar et al., 2017;Aghelpour et al., 2020), the particle swarm optimization algorithm (Noory et al., 2011), which has provided a great chance for the optimized calculation of crop water consumption. Compared with traditional optimization methods, these methods are more efficient in dealing with complex problems. ...
The finite water resources are the main factors limiting agricultural sustainable development in arid and semiarid zones. In these water-scarce areas, optimizing limited water resources is an important way to reduce water consumption, increase crop yields and improve regional economic benefits. In this study, a CA-Jensen optimization model integrating cellular automata method and crop water production function into multi-objective dynamic optimization was developed and applied to the middle reaches of the Heihe River basin in the Northwest China to adjust the spatial distribution of cropland and the spatiotemporal allocation of crop water consumption. The net economic benefits of unit water, the crop water productivity and the value of the terrestrial ecosystem services represented the economic, social and ecological benefits in the objective function of the optimization model respectively. Adaptive cellular genetic algorithm was utilized to search and solve the optimization model. The obtained optimization results of the base year (2015) showed that the net benefits of unit water increased by 4.5% and the crop water productivity increased by 28.6%. In addition, for the target year (2030), although the reduction of agricultural water and cultivated land by 12.95% and 18.63% respectively led to a decrease of total economic benefits by 15.72%, the net benefits of unit water and social benefits got increased by 15.71% and 20.52%, respectively. Therefore, the optimization model can provide decision makers with guidance on the rational allocation of regional agricultural water resources in the future.
... Excessive irrigation and induced secondary salinization have been common issues faced by many arid irrigated watersheds with shallow groundwater (e.g. in Northwest China, Pakistan and Northwest India, South Australia, and Northern Iran) (Doble et al., 2006;Kahlown et al., 2005;Noory et al., 2011;Qureshi et al., 2008;Ren et al., 2016;Singh et al., 2010). Water-saving practices (WSPs) are thus necessary for regulating the agroecosystem processes and improving the soil-water-salt environments in such watersheds (Khan et al., 2009;Pereira et al., 2007). ...
Scenario analysis is the basis of developing rational water management practices (WMPs) for watersheds. How to predict future hydrological responses on a regional-scale is still a challenge for modeling work in irrigated watersheds with shallow groundwater environments. Therefore, this paper presents an efficient realization of predicting regional agroecosystem responses and searching for appropriate WMPs, through using a water balance-based, semi-distributed hydrological model (SWAT-AG). The scenario case study is carried out in the Jiyuan Irrigation System located in the Hetao of upper Yellow River basin, based on the calibrated and validated modeling work in our previous companion paper. Eight scenarios of water-saving practices (WSPs) are proposed, with consideration for reducing irrigation depth and controlling initial groundwater depth. Then the coupled responses of agroecosystem processes to various WSPs are predicted for the case study region in 2012 and 2013, mainly related to the groundwater depth, root zone soil water and salinity, and crop yield/natural vegetation biomass. Based on the analysis for proposed scenarios, the 100% of present irrigation depth combined with increasing initial GWD by 50 cm are recommended as appropriate WSPs for dry years, and the 80% of present irrigation depth combined with increasing initial GWD by 100 cm are recommended for wet years, in order to maintain good environmental conditions for both crops and natural vegetation. In addition, results show that SWAT-AG could overcome the scale/function limitations of traditional soil/crop models and also avoid computational issues of numerical models. We further point out that the scenarios in reality will be more complicated and comprehensive in time and space, and thus the predictions should be updated accordingly. Overall, this case study fully presents the feasibility and practicality of using the SWAT-AG model to realize the scenario response analysis and water management decision-making on a region scale for irrigated watersheds with shallow groundwater environments.
... The PBREOP model is a two-level optimization model with combined use of an agro-hydrological model (SWAP-EPIC). An agro-hydrological model, Soil-Water-Atmosphere-Plant (SWAP) was applied to assess the effects of management of irrigation water on water and salt balances [19]. The study authors found that the adopted water management in the area leads to excessive irrigation and leaching, as well as elevated groundwater salinity. ...
Agro-hydrological water management frameworks help to integrate expected planned management and expedite regulation of water allocation for agricultural production. Low production is not only due to the variability of available water during crop growing seasons, but also poor water management decisions. The Tanjung Karang Rice Irrigation Scheme in Malaysia has yet to model agro-hydrological systems for effective water distribution under climate change impacts. A climate-smart agro-hydrological model was developed using Excel-based Visual Basic for Applications (VBA) for adaptive irrigation and wise water resource management towards water security under new climate change realities. Daily climate variables for baseline (1976-2005) and future (2010-2099) periods were extracted from 10 global climate models (GCMs) under three Representative Concentration Pathway scenarios (RCP4.5, RCP6.0, and RCP8.5). The projected available water for supply to the scheme would noticeably decrease during the dry season. The water demand in the scheme will differ greatly during the months in future dry seasons, and the increase in effective rainfall during the wet season will compensate for the high dry season water demand. No irrigation will therefore be needed in the months of May and June. In order to improve water distribution, simulated flows from the model could be incorporated with appropriate cropping patterns.
... Additionally, the rapid development of remote sensing technology has blossomed data that have been widely used as reference data for calibrating crop model parameters, which could reflect the spatial and temporal heterogeneity of canopy state variables (Maas, 1993;Doraiswamy et al., 2004;Dente et al., 2008;Curnel et al., 2011), soil properties (Moulin et al., 2002;Noory et al., 2011;Ines et al., 2013), and phenology information Chen et al., 2018) at regional scales. Therefore, with the help of remote sensing data, the objective of this study is to evaluate the performance of SMC Scheme across a large region. ...
... An alternative approach for nutrient management, which commonly is much more demanding in terms of computer CPU demands, is the extension of agrohydrological modeling toward nutrients. Agrohydrological models are nowadays strongly focused on understanding water availability to crops and used to schedule irrigation requirements, to anticipate drought yield reductions, and to appreciate salinity stress by crops (Kuhlmann et al., 2012;Noory et al., 2011). This approach, for water availability, usually solves the unsaturated water flow equation (the well-known Richards equation) for a one-dimensional (vertical) water column. ...
... Other studies focus on the water balance and its dynamics at the watershed scale. For the latter, crop models are combined with other models (e.g., hydrological) and applied to quantitative water management and irrigation issues (Noory et al., 2011;Robert et al., 2018;Therond et al., 2014). ...
Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia (˜34 083 km²), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 × 1 km to 100 × 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (< 10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale.
... To understand and improve subsurface drainage systems and minimize their adverse effects, various simulation models have been applied as they can compare different strategies, suggest solutions, and predict consequences in the medium to long term with much less cost than lysimetric experiments Skaggs et al. 2012). One such drainage simulation model is SWAP which has been successfully used to assess the Fourth Drainage Project of Pakistan (Sarwar et al. 2000), predict the drainage flux as a function of rainfallevapotranspiration (El-Sadek et al. 2001), simulate the crop growth and salinity profile for cyclic irrigation with saline water (Verma et al. 2010), evaluate the salt management of an irrigation and drainage network in Iran (Noory et al. 2011), and simulate a subsurface drainage system in arid areas of Iraq (Qureshi et al. 2013). ...
Due to the time and spatial limitations of subsurface drainage pilots, simulation models have been extensively applied for evaluating these systems. Since the accuracy of simulation models depends enormously on the accuracy of model parameters, this study aims to develop an inverse modeling approach for estimating most influential soil hydraulic and solute transport parameters in a subsurface drainage system in an arid and semi-arid region. The SWAP model in conjunction with a genetic algorithm and PEST optimization tool was used to find optimum parameters by minimizing the differences between observed and simulated values of drainage discharge, watertable depth, and drainage salinity. Results revealed that the best simulation of drainage outputs was obtained by parameters which were estimated minimizing an objective function that included all three datasets via a genetic algorithm. Although assuming the soil as a homogeneous and heterogeneous medium had quite similar results from objective functions with one or two datasets, homogeneous assumption worked better in the objective function with three datasets. The inverse modelling approach with GA resulted in a better performance as compared to the PEST optimization tool, particularly in objective functions with two or three datasets.
... In irrigated agro-ecosystems with shallow groundwater depth, the movement of soil water and groundwater, nutrients, salts and vegetation growth are also highly affected by lateral groundwater exchange among different fields (Ren et al., 2016;Konukcu et al., 2006). Previous studies using distributed simulation were mainly focused on evapotranspiration, percolation or lateral drainage (Singh et al., 2006;Noory et al., 2011;Hao et al., 2015;Jiang et al., 2015). The hydrological connections of different land cover types through lateral groundwater exchange have not been studied in detail. ...
Hydrological effects caused by fragmented land cover types in human-dominated agro-ecosystems are poorly understood. In this study, based on visual interpreted high-resolution land cover map, an agro-hydrological model (HYDRUS-dualKc) was used in a distributed manner to investigate the hydrological complexities caused by fragmented land cover types and shallow groundwater. An irrigation system located in the upper Yellow River basin was chosen as a case study area, where field observations were conducted in 2012 and 2013. Combined effects of vegetation, soil, irrigation and groundwater were considered. Simulations of soil moisture and soil salinity fitted well with field observations; evapotranspiration (ET a) was also comparable with remote sensing data. Results showed that the growing season ET a varied from 162 to 567 mm among the different vegetation covers with the values for crop fields usually higher than those for natural lands. The soil evaporation was obviously larger in natural land and the natural vegetation growth was seriously stressed. Through lateral groundwater exchange, the cropland functioned as a stable groundwater recharge zone while the natural land functioned as a discharge zone during the growing season. As a result, 21% of the total water diverted to Jiyuan migrated to natural lands through groundwater due to field percolation and canal seepage, along with 50-75% of the total salt introduced. The fragmented land covers and complex hydrological processes bring many challenges to remote sensing and model simulation. Future land planning and water resources management should consider the hydrological effects caused by the fragmented land cover types and the associated management strategies.
... Using such local studies, it is difficult to assess the large scale heterogeneity of the terrestrial water cycle, due to the vast climate and topographic condition of the country (see, e.g., Section 2 and Modarres, 2006). Other studies that looked at the large-scale water variations of Iran were restricted to the use of hydrological models (e.g., Abbaspour, Faramarzi, Seyed Ghasemi, & Yang, 2009;Noory, van der Zee, Liaghat, Parsinejad, & van Dam, 2011). ...
The arid Middle East is experiencing water scarcity due to shortages in rainfall, ongoing drought, overexploitation of surface water and groundwater, and economic development. Evaluating long-term trends of water resources and the interaction with climate forcing and human intervention is crucial for future water resource management. In this context, we integrated data from the Gravity Recovery and Climate Experiment (GRACE) satellites, altimetry, global land surface and hydrological models, and in-situ observations to assess trends in total water storage (TWS), surface water (SWS) and groundwater (GWS) from 2003 to 2017, over the transboundary aquifer and at the country scale.
Results show that the Middle East experienced negative or positive trends for the TWS and GWS before 2007. However, after 2007, declining trends became more significant in all regions, except eastern Turkey. The most affected regions include Iran, Iraq, and northern Saudi Arabia. The drought resulted in significant decline in groundwater resources. The total loss in groundwater storage (2007 – 2017) is about 827 km3. We developed a drought index based on the total water storage deficit in the region. GRACE-derived groundwater storage declines compare favorably with results from in-situ monitoring (~570 wells) and regional groundwater models in Iran and northern Saudi Arabia (R2 > 0.78). The results highlight current groundwater depletion in the Middle East attributed to drought and over-exploitation and underscores the need to expand the portfolio of water sources to meet increasing water demands.
... The accuracy of SWAP simulations is highly sensitive to the accuracy of input data. Therefore, in case of accurate input data, crop yield would be estimated more reliably (Noory et al., 2011). Input data of the SWAP model is divided into four sections including crop, soil, meteorology, and upper and lower boundary conditions. ...
Precise crop yield forecast at regional scales would increase global food security, especially in strategic crops such as wheat and barley. Soil Water Atmosphere Plant (SWAP) is an agro-hydrological model based on a crop growth detailed module that could properly estimate crop yield using satellite observations as input data. In this study, in order to reduce crop yield estimation errors in wheat and barley, MODIS-based leaf area index (LAI) was assimilated using a sequential update algorithm into SWAP, and GLDAS/Noah-derived surface incoming solar radiation (SISR) was used as an alternative to measured SISR. The assimilation of remotely sensed LAI and using SISR as input was examined in nine different cases. Results showed that soil adjusted vegetation index (SAVI) was the best VI for LAI estimation with coefficient of determination (R²) of 0.72 and root mean square error (RMSE) of 0.87 m² m⁻². Also noise equivalent variations indicated an appropriate sensitivity of SAVI along the entire range of LAI variability. GLDAS/Noah-derived SISR showed good agreement with measured SISR; therefore LAI and SISR were jointly used in the model. Simulation results showed that the lowest percent absolute error (PAE) for aboveground dry biomass and grain yield was obtained in case 7 (the assimilation of the peak LAI in addition to ten days after and before the peak LAI is reached) with 1.59% and case 5 (the daily assimilation of LAI until twenty days after the peak LAI is reached) with 6.06%, respectively. Crop yield estimates were improved by 26.25 and 14.4% compared with no LAI assimilation case. Overall, LAI assimilation into SWAP associated with the most efficient cases in this study would result in an accurate crop yield forecast in wheat and barley.
... The SWAP model has already been applied and tested for various agricultural water management studies throughout the world and has been proven to produce reliable and accurate results Droogers et al., 2010;Van Lier et al., 2015;Xu et al., 2016). It has been shown that the SWAP model could be successfully applied in subsurface drainage studies El-Sadek et al., 2001;Noory et al., 2011;Qureshi et al., 2013). Sarwar and Feddes (2000) and successfully applied the SWAP model to evaluate drainage design parameters for the Fourth Drainage Project, Pakistan. ...
The aim of this study is to present an inverse modelling approach with a genetic algorithm for estimating soil hydraulic and solute transport parameters in two subsurface drainage systems in Iran. In this study, measured data were obtained from Amirkabir and Shoaybiyeh sugarcane fields equipped with subsurface drainage systems. The SWAP model was used for simulating the outputs of subsurface drainage systems. The accuracy of different objective functions which were based on the discrepancies between measured and simulated values of drainage discharge, groundwater depth and drainage water salinity was evaluated in the inverse modelling approach. Based on sensitivity analysis of the SWAP model in studied areas, n shape parameter, lateral hydraulic conductivity, depth to impermeable layer, saturated water content and α shape parameter were selected in the inverse modelling approach. By applying the objective function which is based on drainage discharge and salinity in the Amirkabir study area, the Nash–Sutcliffe Efficiency (NSE) values for predicting drainage discharge and salinity were 0.63 and 0.79, respectively. In the Shoaybiyeh study area, the objective function which includes drainage discharge, groundwater depth and drainage water salinity resulted in NSE values of 0.83, 0.95 and 0.89 for predicting drainage discharge, groundwater depth and drainage water salinity, respectively. Copyright © 2017 John Wiley & Sons, Ltd.
... There are a few previous studies of spatial simulation modeling, which are related to different issues, e.g., agrohydrological process, irrigation water optimization, crop water productivity analysis, distributed ecosystem simulation (Ines et al. 2006;Noory et al. 2011;Singh et al. 2006;Van der Knijff et al. 2010). However, field experiments are usually site-specific, expensive, time consuming and several components of the water and salt balances can not readily be measured. ...
Rice production is one of the largest consumer of water in agriculture. In general, the irrigation water productivity (WPI) is low in paddy fields. In order to improve WPI, a field experiment was conducted in central of Iran during 2009–2010. The experiment was consisted of three irrigation managements and eight advanced rice cultivars (Gerdeh (V1), Zayande-roud (V2), Sazandegi (V3), Hasani (V4), 67–97 (V5), 67–113 (V6), 67–47 (V7), and 67–72 (V8)) in a split plot design with three replications. The irrigation treatments were I1 and I2: permanent flooding under 3.5 and 2.2 cm water depth, respectively, and I3: 0–1.5 cm alternative wetting and drying. To explore deficit irrigation for improved WPI, SWAP model was calibrated using intensive measured data for the foregoing years. The average normalized root-mean-square deviation of yield during calibration was 0.03% and during validation was 4.94% indicating acceptable calibration and validation of the model. WPI for all cultivars were enhanced up to 61% by applying 50% deficit irrigation. On this irrigation regime, V2 and V6 provided the highest WPI (0.84 and 0.79 kg m⁻³, respectively) whereas V4 and V8 yielded the lowest (0.50 and 0.57 kg m⁻³, respectively). The results indicated that rice cultivars (V2 and V6) are the best option with the highest WPI in the irrigation district and calibrated model was able to effectively simulate the crop growth under water deficit conditions.
... Several models have been developed to simulate the field soil salt balance. For example, the SWAP (Soil-Water-Atmosphere-Plant) model was used to simulate soil salt and water transport based on different field cropping patterns, irrigation modes and management modes (Su et al. 2005;Jiang et al. 2011;Noory et al. 2011). Several simulations of water and solute transport were also implemented in the HYDRUS model (Cote et al. 2003;Raine et al. 2005;Singh et al. 2006;Šimu nek et al. 2008;Mubarak et al. 2009). ...
In recent years, Xinjiang Oasis has faced a major challenge of increasing risk of secondary salinization caused by drip irrigation under plastic mulch. Predicting the salt balance is therefore essential for understanding how to sustain the use of salinized land in this arid area. This research validated the SWAGMAN (Salt, Water And Groundwater MANagement) Destiny model to simulate and forecast the movement of salt in different soil textures based on field experiments. The results were verified with extensive field work in Shihutan, Xinjiang, China. They show that soil salinity decreases in the upper layers and increases in the bottom layers of the investigated soil profile. The desalinization rate in sand, which shows an overall steady trend throughout the soil profile, is generally higher than that in loam and clay. The depth of 60cm is critical for loam and clay; soil salinity decreases above it but increases below it. Model sensitivity analysis reveals the variation of soil salinity is independent of the initial electrical conductivity setting of SWAGMAN Destiny simulations. This study indicates that numerical modelling is a useful approach for efficiently estimating the salt balance under drip irrigation. The result provides a scientific basis for making adaptive strategies to manage salinised farmlands in arid zones.
... Many models were developed to predict the effects of water deficit and salinity on crop growth, for example, SWAP (Soil-Water-Atmosphere-Plant, Noory et al., 2011) and SALTMED (Salt-Mediterranean, Ragab (2001); Silva et al., 2013;Rameshwaran et al., 2013) that are either complex or need many input data that are not readily available. ...
Salinization of soil is primarily caused by capillary rise from saline shallow groundwater or application of saline irrigation water. In this investigation, the transient state analytical model was modified to predict water uptake from saline shallow groundwater, actual crop evapotranspiration, soil water content, dry matter, seed yield and soil salinity under different saline groundwater depths, irrigation water salinities and deficit irrigation for quinoa. Considering the effect of salinity on soil saturated hydraulic conductivity and maximum root depth in presence of shallow saline groundwater, the model resulted in good agreement between the measured and predicted saline groundwater uptake, soil salinity increase at different groundwater depths (300-800 mm) and water salinity (10-40 dS m-1). Therefore, the modified model is applicable for quinoa yield and soil salinity prediction and it could be a valuable tool for soil salinity management in presence of shallow saline groundwater. Furthermore, prediction of quinoa yield by the modified model can be used for better irrigation water salinity management under different saline groundwater depths, irrigation water salinities and deficit irrigation. © 2016, Gorgan Univ Agricultural Sciences and Natural Resources. All rights reserved.
... A modeling approach can aid in such assessments (Adamowski et al., 2010; Nalley et al., 2012; Nalley et al., 2013; Valipour, 2014a Valipour, , 2015 Yaeger et al., 2014; Butler and Adamowski, 2015; Inam et al., 2015). Successfully employed to predict the expected responses of hydrological systems to proposed water resource policies (Tuppad et al., 2010; Noory et al., 2011; Park and Roesner, 2012; Haidary et al., 2013; Rathinasamy et al., 2013; Belayneh et al., 2014), hydrological models have proven effective in physically interpreting natural phenomena. However, traditional hydrological models do not consider anthropogenic impacts on water cycle dynamics (Wagener et al., 2010), thereby limiting their ability to fully mimic the response of hydrological systems to evolving circumstances . ...
The purpose of this study was to develop and verify a socio-hydrological model using system dynamics (SD), thereby combining a deterministic conceptual hydrological model and a social model incorporating population, land use, economics, technology, and policy dimensions. Applied to a central South Korean watershed where wastewater is reused for paddy irrigation, the present model was verified in terms of structure and behavior. Structural validity was confirmed when expected simulation sensitivity and consistency criteria were met during behavior sensitivity and extreme conditions tests. The model's behavioral validity in predicting hydrological processes including evapotranspiration, stream flow, and groundwater level, was also confirmed as the calibrated model performance during the validation period showed good agreement with those of the Soil and Water Assessment Tool (SWAT) model, validated for the study watershed, as well as observed groundwater levels. The values of Nash-Sutcliffe efficiency (ENS), percent bias (PBIAS), and R2 which compared model results with those of the SWAT model were 0.77, 3.0%, and 0.79, respectively, for the evapotranspiration, and 0.69, 1.4%, and 0.75, respectively, for the stream flow, while the generated and observed groundwater levels exhibited a linear relationship with an R2 value of 0.70. The validated model indicated that urbanization within the study watershed could lead to increased stream flow and greater wastewater reuse. Instream flow regulation led to a decrease in stream flow tied to a lower base flow, and a decrease in social benefits associated with a decline in wastewater reuse. An assessment was made of the SD-based socio-hydrological model's usefulness when acting as an element of an integrated framework in providing a better understanding of small-scale socio-hydrological systems' interactions and the underlying causes of general trends and problems. SD-based socio-hydrological modeling was deemed a suitable decision-support framework for designing water resource policies contributing to successful integrated water resources management practice.
... Similarly, Mandare et al. (2008) used SWAP to evaluate the effect of varying shares of canal water and saline groundwater in the water used for irrigation on wheat crop yield, and suggested a more frequent irrigation and a precise leveling of the grounds to improve the crop yields. Noory et al. (2011) developed a distributed SWAP model to simulate irrigation management strategies devised for controlling return flow salinity in Voshmgir irrigation-drainage network, Iran. They found the lower irrigation volumes to be effective on decreasing both the return flow quantity and the total salt drained from the network. ...
... Similarly, Mandare et al. (2008) used SWAP to evaluate the effect of varying shares of canal water and saline groundwater in the water used for irrigation on wheat crop yield, and suggested a more frequent irrigation and a precise leveling of the grounds to improve the crop yields. Noory et al. (2011) developed a distributed SWAP model to simulate irrigation management strategies devised for controlling return flow salinity in Voshmgir irrigation-drainage network, Iran. They found the lower irrigation volumes to be effective on decreasing both the return flow quantity and the total salt drained from the network. ...
In this study, a new methodology is presented for simultaneous agricultural water and return flow (waste load) allocation in rivers. In this methodology, an objective function based on Conditional Value at Risk (CVaR) and a Nonlinear Interval Number Programming (NINP) technique are utilized. The CVaR can handle uncertainties in the form of probability distributions, while NINP incorporates uncertain inputs which are only available as intervals. This CVaR-NINP framework is used for agricultural water and return flow allocation planning under uncertainty. In this paper, to reduce the amount of saline return flow discharged into the river, a part of return flow of each agricultural network is diverted to an evaporation pond. Some meta-models based on Artificial Neural Network (ANN) are trained and validated using the results of Soil, Water, Atmosphere and Plant (SWAP) simulation model to reliably approximate the quantity and Total Dissolved Solids (TDS) load of agricultural return flows in a critical 7-day period. The effectiveness of the proposed methodology is examined through applying it to a part of Karkheh River catchment in the southwestern part of Iran. The results confirm the applicability of the model in incorporating the main uncertainties and generating water and waste load allocation policies in the form of interval numbers.
... Recently, the concept of distributed modeling becomes dominant when based on geographic information systems (GIS), and can be used for simulation of agro-ecosystems on regional scale. There are a few previous studies of spatial simulation modeling , which are related to different issues, e.g., agro-hydrological process, irrigation water optimization, crop water productivity analysis, distributed ecosystem simulation (Singh et al., 2006; Ines et al., 2006; van der Knijff et al., 2010; Noory et al., 2011). Distributed hydrological models like SWAT (Arnold et al., 1993) and AGNPS (Young et al., 1989) have also been widely used at watershed and basin scale. ...
Due to the spatial variability of soil hydraulic properties and hydrological factors, field scale models with one-dimensional structure were not applicable to the regional scale modeling. A distributed model, which is named as GSWAP, was developed for simulating soil water flow and salt transport on a regional scale by closely coupling the Soil-Water-Atmosphere-Plant (SWAP) model and ArcInfo. The data of GSWAP can be efficiently pre/post processed based on the strong capabilities of spatial data analysis and processing in ArcInfo. The study area was divided into subunits through the combination of soil type, land use, climate and water table depth conditions. Each subunit was supposed to be an equivalent homogenous system with a set of effective soil hydraulic parameters, which were obtained by using the Genetic Algorithms coupled with SWAP model. Finally，the GSWAP model was applied to the Yonglian Irrigation System, Hetao Irrigation District of Inner Mongolia as a case study. Results showed that the GSWAP model could be efficiently used to simulate the soil water and solute dynamics on a regional scale.
... 。但田间试验相对耗时、耗 资且具有一定的方案特定性，难以考虑多种农业用 水管理措施的情景组合。同时，试验中部分水盐均 衡项是难于直接测量的 [4] 。而借助于数学模拟模型 并结合田间试验成果，则可开展多种用水情景下的 土壤水盐动态与作物生长预测分析。该方法可有机 整合系统中各种影响因素，并能获取丰富的水盐动 态信息，以辅助于决策和制定优化的灌溉措施 [5][6][7] 。 目前，研究者已开发了诸多水盐动态模拟模型(如 SWAP [8] (soil water atmosphere plant) 和 HYDRUS [9] 等)，但由于模型开发目的不同及其区域针对性， 已建模型并不具有普适性，在特定区域应用时往往 需要对模型进行适当改进。 本研究将以 SWAP 模型为基础，对 SWAP 模型 进行如下改进：1)引入变活动节点法，以实现对寒 区土壤融化期水盐运移过程的合理描述；2)引入 S 形土壤水分胁迫函数 [10] ，以及考虑盐分容限值的 S 形盐分胁迫函数 [11] ，并基于土壤水溶质势水头进行 计算，以提高干旱盐渍化条件下的根系吸水模拟准 确性。进一步将参数与输入数据较少且可以模拟作 物 生 长 过 程 及 实 际 产 量 的 EPIC ( environmental policy integrated calculator)作物生长模型 [12] ...
The quantitative description of soil water flow, solute transport and crop growth processes at field scale is significant for the decision-making of appropriate water use practices in arid irrigation districts. In this study, a modified agro-hydrological model (SWAP-EPIC) for coupled simulation of soil water flow, solute transport and crop growth was developed based on SWAP (soil water atmosphere plant) model and EPIC (environmental policy integrated calculator) crop growth model. The variable active-node method was adopted into the original SWAP model for reasonably simulating the soil water and solute transport processes during soil thawing period. Additionally, the S-shaped osmotic head-dependent functions for describing water and salt stress were also introduced. Further, the EPIC crop growth model, which could simulate the crop growth process and actual crop yield with moderate data input and parameters, was coupled into the SWAP model. Then the field applicability of SWAP-EPIC model was respectively tested using the field experiment data of spring wheat and spring maize at Huinong experimental site in Ningxia. The simulated and observed soil moisture, salinity concentration, and crop growth indicator (leaf area index and dry above-ground biomass) were compared for spring wheat and spring maize. The results showed that the soil moisture was matched very well, with MRE (mean relative error) and RMSE (root mean square error) close to zero and NSE (NSE and Sutcliffe model efficiency) approached to one. The simulated and observed salinity concentration showed an agreement with some slight discrepancy. The simulated LAI and above-ground biomass both matched well with observed ones. Meanwhile, the simulated crop yield was also close to the observations, with relative errors of 4.9% for spring wheat, and 3.3% for spring maize. The results indicated that the modified model (SWAP-EPIC) could be efficiently used to simulate the soil water and salt dynamics, crop growth, and their relationships at field scale.
... SWAP model has been extensively employed for soil water simulation (Crescimanno and Garofalo, 2005;Eitzinger et al., 2004;Gusev and Nasonova, 2003;Bonfante et al., 2010;Marinov et al., 2005;Van Dam et al., 2008), water management (Noory et al., 2011;Ma et al., 2011), and saline water application (Verma et al., 2012;Su et al., 2005;Jiang et al., 2011;Droogers, 2000). It has also been popular in studies on groundwater (Anuraga et al., 2006;Xu et al., 2012) and ET (Droogers, 2000;Utset et al., 2004). ...
... 内蒙古河套灌区是中国重要的粮经作物生产基地之 一。灌区地处黄河上游的干旱-半干旱内陆地区，由于气 候干旱少雨，良好的土壤水盐状况是保障农业生产的主 导因素。准确评估灌区土壤水盐与作物生长状况，对农 业生产与水资源优化利用具有积极意义。目前，诸多国 内外学者通过开展田间试验进行土壤水盐状况对作物生 长影响的相关研究 [1][2][3] ，试验研究成本较高、耗费时力且 结 果 具 有 特 定 性 。 农 田 水 文 模 型 ( 如 SWAP [4] 、 HYDRUS-1D [5] 等)的出现为模拟和预测农田水盐动态和 作物生长过程提供了便利条件，但受灌溉、土壤质地、 种植作物种类等多种因素空间变异影响，模型难以直接 推广到区域尺度 [6] 。 基于地理信息系统技术的分布式水文 模型可综合考虑上述因素的空间变异特征，受到人们的 重视 [6][7][8] 。 Singh 等 [6] 利用分布式 SWAP 模型评估水盐胁迫 条件下 Sirsa 地区作物耗水和产量；Jiang 等 [7] 研究了黑河 中游地区水管理措施对区域水分生产率的影响，指出通 [9] 开发了与 ArcGIS 紧密结合的 GSWAP 模型，并 进行了永联试验区支渠尺度模拟研究；杨树青等 [10] 基于 土壤水盐空间分布特征将研究区分为 3 个均质小区，开 展了盐渍化土壤环境下微咸水利用模式研究。但已有研 究由于缺乏充分的实测数据进行模型校验，尚未能实现 对灌区农业水文过程的准确刻画与剖析。为此，本研究 拟以河套灌区解放闸灌域为研究区，采用分布式模拟的 方 式 将 耦 合 了 EPIC ( erosion-productivity impact calculator ) 作 物 生 长 模 块 [11] 的 HYDRUS-1D 模 型 (HYDRUS-EPIC [12] )推广至区域尺度应用，并结合区域 土壤水盐、作物生长的综合观测试验进行模型率定与验 证，以定量评估研究区土壤水盐和作物生长的时空状况。 与土壤盐分含量相比，作物根区盐分浓度能更直观 反映出作物生长受盐分胁迫情况。图 6b 给出作物生育 期内根区土壤盐分平均浓度分布状况。研究区的作物根 区盐分浓度在 3.1～13.5 g/L 之间，平均值为 6.4 g/L。鉴 于玉米种植面积占研究区农田面积 30%以上 [19] 且其耐 盐性不如小麦、葵花 [20] ，选取玉米评估区域盐分状况。 尽管不同品种、不同生育阶段玉米耐盐性有所差异，但 现有研究表明 [21][22] ...
Soil moisture and salinity are two key factors for crop production in arid irrigation districts. It is critical to modify soil water-salt dynamics and crop growth on a regional scale for the sustainable agriculture. In this paper, a distributed agro-hydrological model that well considers the spatial variability of soil and hydrological factors was developed to simulate soil water movement, solute transport and crop growth process on the regional scale. Jiefangzha Irrigation System (JIS) of the Hetao Irrigation District was selected as the study area. The JIS was divided into 201 homogeneous simulation units based on the combinations of weather-soil-crop-irrigation. In this way, the one-dimensional agro-hydrological model-HYDRUS-EPIC (HYDRUS-1D coupled with EPIC crop growth module), was used and expanded to the regional scale. Field experiments were conducted in 2012 and 2013. The dataset of soil moisture, soil solute concentration, leaf area index (LAI) and crop yield were collected at 40 monitoring points, and used for model calibration and validation. Simulated soil moisture and salinity concentration in the root zone showed good agreement with the measured values. During the calibration process, root mean square error (RMSE), mean relative error (MRE) and coefficient of determination (R2) for soil moisture were 0.03 cm3/cm3, 0.3% and 0.67, respectively. For salinity concentration, RMSE, MRE and R2 were 2.72 g/L, -13.5% and 0.53.LAI and crop yields were fitted well with the observations. MRE values for the estimated and measured LAI and crop yields were 1.0% and 1.1%, and R2 were both larger than 0.90 for these two items. During the validation process, RMSE, MRE, and R2 were 0.04 cm3/cm3, 2.6%, 0.57 for soil moisture, and 2.62 g/L, -4.5%, 0.51 for salinity concentration, respectively. And MRE and R2 were 9.1%, 0.88 for LAI, and -1.9%, 0.92 for crop yields. These results showed that the distributed agro-hydrological model was able to simulate the soil water flow, salt transport, and crop growth process in JIS with accuracy. The calibrated and validated model was then applied to predict spatial distribution of soil moisture, salinity concentration, crop evaporation and crop yields of the study area in present irrigation water management practices. Effective saturation and salinity concentration in the root zone were chosen to represent soil water and salinity stress on crop growth. Results showed that effective saturation ranged from 0.44 to 0.90 with an average of 0.7 for the JIS. In most areas, soil water could meet crop water consumption needs. In the areas where groundwater depth (GWD) was less than 1.3 m, root water uptake was limited due to waterlogging. The average salinity concentration in the root zone varied from 3.1 g/L in the northwest to 13.5 g/L in the northeast with an average of 6.4 g/L for the whole district. High soil salinity concentration limited crop production seriously. Corresponding to the spatial distribution of salinity concentration in the root zone, crop relative yield (ratio of actual yield and average yield of JIS) ranged from 0.33 to 1.33.The results suggested that for the northeastern part, where GWDs were larger than 2.0 m, more irrigation was needed for leaching salt. It was also better to plant more salt tolerant crops in these areas. In northwestern and southwestern parts, shallow groundwater levels intensified water logging or salinity accumulation problems. The study indicated that it is better to keep the groundwater depth not shallower than 1.3 m for maintaining the crop yields. ©, 2015, Chinese Society of Agricultural Engineering. All right reserved.
... In view of the costs involved in purifying and desalinizing water, the supply of good quality water for agricultural needs is particularly becoming scarce and costly. For this reason, the use of low to marginal quality water for irrigation is increasing [Hamilton et al., 2007;Qadir et al., 2007], most notably in water scarce countries [Rengasamy, 2006;Noory et al., 2011]. ...
[1] In arid and semiarid regions, irrigation water is scarce and often contains high concentrations of salts. To reduce negative effects on crop yields, the irrigated amounts must include water for leaching and therefore exceed evapotranspiration. The leachate (drainage) water returns to water sources such as rivers or groundwater aquifers and increases their level of salinity and the leaching requirement for irrigation water of any sequential user. We develop a conceptual sequential (upstream-downstream) model of irrigation that predicts crop yields and water consumption and tracks the water flow and level of salinity along a river dependent on irrigation management decisions. The model incorporates an agro-physical model of plant response to environmental conditions including feedbacks. For a system with limited water resources, the model examines the impacts of water scarcity, salinity and technically inefficient application on yields for specific crop, soil, and climate conditions. Moving beyond the formulation of a conceptual frame, we apply the model to the irrigation of Capsicum annum on Arava Sandy Loam soil. We show for this case how water application could be distributed between upstream and downstream plots or farms. We identify those situations where it is beneficial to trade water from upstream to downstream farms (assuming that the upstream farm holds the water rights). We find that water trade will improve efficiency except when loss levels are low. We compute the marginal value of water, i.e., the price water would command on a market, for different levels of water scarcity, salinity and levels of water loss.
... Recently, the concept of distributed modeling becomes dominant when based on geographic information systems (GIS), and can be used for simulation of agro-ecosystems on regional scale. There are a few previous studies of spatial simulation modeling, which are related to different issues, e.g., agro-hydrological process, irrigation water optimization, crop water productivity analysis, distributed ecosystem simulation (Singh et al., 2006;Ines et al., 2006;van der Knijff et al., 2010;Noory et al., 2011). Distributed hydrological models like SWAT (Arnold et al., 1993) and AGNPS (Young et al., 1989) have also been widely used at watershed and basin scale. ...
Irrigation is essential for agriculture in the middle Heihe River basin, Northwest China, due to water scarcity and dryness of climate. The diverted river water for agriculture is being gradually reduced which requires an increased water use performance to meet crop water requirements and to maintain crop yields. It is therefore crucial to better know about the present agro-hydrological processes, irrigation performance and water productivity, and to further investigate the potential water saving on a regional scale. In this study, a distributed agro-hydrological model was developed by close coupling of an agro-hydrological model (SWAP-EPIC) and ArcInfo geographic information system. Combined effects of weather, crop, soil and irrigation factors were considered. The Yingke Irrigation District (YID), in the middle Heihe River basin, was chosen as case study, where experiments were conducted at both field and regional scales in 2012–2013. Parameters relative to soils and crops were first calibrated with field observed data and the model was later used in a distributed manner to simulate the agro-hydrological process of YID. Results showed that water productivity was spatially varied and quite small due to excessive irrigation water use. Crop evapotranspiration averaged 589 mm and deep percolation was 125 mm on average, which accounted for 21% of total irrigation. Analysis of the target scenario simulation indicated that the improvement of water conveyance and irrigation scheduling could lead to a 30% reduction of deep percolation, and save 15% of irrigation water without negative effects on crop yields.
... The information generated is helpful for establishing a more sustainable agriculture as well as supporting strategies for the mitigation of pollution, named by Strauch et al. (2013) as the "Best Management Practices". The hydrological model SWAP (Soil, Water, Atmosphere and Plant) is one of the existing algorithms used worldwide for a variety of soils, crops and climatic conditions ( Chirico et al., 2013;Crescimanno et al., 2012;Eitzinger et al., 2004;Kamble et al., 2013;Ma et al., 2011;Noory et al., 2011). The model has shown consistent results when applied to maize crops in sub-tropical climates ( Pinheiro et al., 2013) and to soybeans and common beans in tropical climates (Scorza Junior et al., 2010;Durigon et al., 2012). ...
... In this context, use of modelling techniques to simulate the salt dynamics and crop yield under irrigated saline environment using the data acquired from short term field experiments and prediction for future could be an alternative of such long term experiments. A plethora of models have been developed and used for short and long term simulation of salt and water transport under different climatic, drainage and crop conditions (Martin et al., 1984;Majeed et al., 1994;Singh and Singh, 1996;Lamsal et al., 1999;Bakker et al., 2010;Noory et al., 2011). Models for simulating water, salt and nutrient dynamics in the unsaturated zone of the soil profile are useful for optimising the application of saline irrigation water and fertilizers, which assist in sustainable crop production. ...
Quantitatively assessing the practicality and sustainability of saline groundwater for irrigation at the regional level could provide a valuable reference for macro decision-making and management in terms of alleviating the severe contradiction between freshwater shortages and food production. In this study, the distributed agro-hydrological SWAP-WOFOST (Soil-Water-Atmosphere-Plant-WOrld FOod STudy) model was applied in the east-central North China Plain (NCP). The model was used to simulate the five saline water irrigation scenarios for a 20-year period, and the effects on the spatiotemporal variations in crop yield, water productivity (WP), and soil water and salt balances were analyzed. Furthermore, appropriate saline water irrigation schemes were solved considering crop yield reduction and soil salt accumulation. Finally, spatial matching between the appropriate irrigation schemes and saline groundwater resources from the perspectives of “water quality” and “water quantity” was evaluated. The main results were as follows. (1) The average yield and WP of winter wheat during the simulation period remained stable or increased slightly under saline water (2–6 g L⁻¹) irrigation for winter wheat compared with that under freshwater irrigation, whereas the average yield and WP of the following summer maize decreased to varying degrees. (2) When the sum of seasonal precipitation and irrigation of summer maize was >450 mm, 401–450 mm, 351–400 mm, 200–350 mm and <200 mm, the average soil salt leaching depth was approximately 120 cm, 100 cm, 80 cm, 60 cm and 40 cm, respectively. (3) On the premise that the average salt content of the 2-m soil profile at summer maize harvest during the simulation period was less than 3 g kg⁻¹, if the average crop yield reduction of the rotation system in the range of ≤500 kg hm⁻², ≤1000 kg hm⁻², ≤1500 kg hm⁻² and ≤2000 kg hm⁻² was permitted, the dominant maximum irrigation water salinity in the study area was 3 g L⁻¹, 4 g L⁻¹, 6 g L⁻¹ and 6 g L⁻¹, respectively. (4) The average saline water amount needed for winter wheat irrigation during the simulation period was approximately 22.78 × 10⁸ m³, which was approximately 9% more than the exploitable amount of saline groundwater. The results could support decision-making related to developing and using shallow saline groundwater for irrigation.
In order to explore the regional water–salt balance mechanism in Hetao Irrigation District, field experiments were conducted in 2018 and 2019 in the Heji canal study area. The SWAP model was calibrated and validated based on field experiments' observed data. The SWAP model was used to simulate soil water–salt dynamics in saline wasteland after calibration and validation. The results showed that model simulation results of soil water content and soil salt concentration agreed well with the measured values. Soil water content and soil salt concentration changed obviously under the effect of farmland irrigation in the crop growing period. Soil salt was accumulated in saline wasteland. The soil salt accumulation of each soil layer in saline wasteland was 0.164, 0.092, −0.890 and −1.261 mg/cm3, respectively. Soil water content gradually increased and soil salt concentration gradually decreased in the autumn irrigation period. Soil salt was leached in the saline wasteland. The soil salt accumulation of each soil layer in the saline wasteland was −1.011, −1.242, −1.218 and −1.335 mg/cm3, respectively. The saline wasteland became a drainage and salt drainage region for cultivated land. The saline wastelands had an obvious role in adjusting salt balance and maintaining salt dynamic balance in Hetao Irrigation District. HIGHLIGHTS
Soil water–salt transport is concentrated in saline wasteland.;
Soil water content and soil salt concentration changed obviously in crop growing period.;
Soil salt was accumulated in saline wasteland in crop growing period.;
Soil water content gradually increased and soil salt concentration gradually decreased in autumn irrigation period.;
Saline wasteland became a drainage and salt drainage region.;
The agro-hydrological Soil-Water-Atmosphere-Plant-WOrld-FOod-STudy (SWAP-WOFOST) model in a distributed manner represents an important tool for evaluating agro-hydrological cycles and irrigation strategies at different spatiotemporal scales. The reliability of the model simulations and evaluations is dependent on the generation of the distributed simulation units that account for the spatial heterogeneity of various factors, as well as parameter calibration and model validation. In this study, we focused on the most typical overexploited deep groundwater area in the North China Plain (NCP). First, the extended Fourier amplitude sensitivity test (EFAST) was used to conduct global sensitivity analyses for three modules in the SWAP-WOFOST model to identify the parameters that significantly influence the objective variables for calibration at the six experimental stations in the study area. On this basis, the parameters were calibrated and validated in detail using abundant observed data from each station. The normalized root mean square error (NRMSE) values for soil water content, soil salt concentration, winter wheat leaf area index (LAI), winter wheat aboveground biomass, winter wheat yield, summer maize LAI, summer maize aboveground biomass and summer maize yield were 14.93%, 27.20%, 24.60%, 25.27%, 23.12%, 24.55%, 21.33% and 17.94%, respectively, during the calibration period; and the corresponding NRMSE values were 16.26%, 29.36%, 24.20%, 22.75%, 21.77%, 22.03%, 24.38% and 18.62%, respectively, during the validation period. The model provided a good simulation for the soil water contents and summer maize yields and a fair simulation for the other objective variables. Furthermore, a distributed SWAP-WOFOST model was generated by overlaying 12 maps involving meteorology, soil, crops, land use, water resources and administrative divisions, yielding 2809 simulation units. Finally, the simulation accuracy of the distributed model was evaluated under the current irrigation conditions. The results showed that the simulated yields of winter wheat and summer maize were consistent with the statistical values, and the simulated evapotranspiration matched the remote sensing data with acceptable precision. In summary, the distributed SWAP-WOFOST model could be used as an effective tool for simulating crop water productivity in time and space under limited irrigation scenarios and for evaluating the effect of optimized limited irrigation schemes on reducing deep groundwater exploitation in this region.
The east-central North China Plain (NCP) is a globally representative area that presents a sharp contradiction between deep groundwater exploitation and grain production. Evaluating the effects of limited irrigation on crop water productivity (WP) and deep groundwater exploitation reduction in this area is important for developing sustainable agricultural practices. In this study, the 11 limited irrigation scenarios were simulated and analyzed using the distributed Soil-Water-Atmosphere-Plant-WOrld-FOod-STudy (SWAP-WOFOST) model that was established, calibrated and validated in a companion paper; the recommended irrigation timing for maximizing the yield or WP of winter wheat was selected; the irrigation scheme for minimizing evapotranspiration constrained by 14 winter wheat yield reduction thresholds was optimized separately; and further the effects of the optimized irrigation scheme on saving water and reducing deep groundwater exploitation were evaluated. The results showed that the recommended irrigation timing was predominantly in the pre-sowing, booting to anthesis and early grain-filling stages for three irrigations, the pre-sowing and booting to anthesis stages for two irrigations, and the booting to anthesis stage for one irrigation. Adopting the optimized irrigation scheme with the threshold of 60% could achieve the goal of reducing deep groundwater exploitation by 6.05 × 10 ⁸ m ³ but reduced winter wheat yield by approximately 50%. The contribution index of reducing exploitation (CIRE) was defined to identify the contribution of implementing the optimized irrigation scheme to reducing current deep groundwater exploitation. At the related water resource subregional level, the CIRE values showed that this contribution was relatively higher in the related Tuhai and Majia Rivers plain (THMJHP), the related plain of the Zhangwei River basin (ZWHP) and the related plain of the Ziya River basin (ZYHP). Following the framework of simulation-optimization-evaluation, the three results at the manageable county level, namely, the optimized irrigation scheme under the constraint of 14 thresholds, the crop yield variation compared with the current irrigation schedule and the CIRE values, provide decision-making references for implementing limited irrigation for winter wheat under local conditions to achieve the target of deep groundwater exploitation reduction.
The global population is increasing rapidly and expected to touch the 9.5 billion mark by 2050 from the current
7.2 billion. The management of the groundwater resources is a challenging task worldwide against the backdrop
of the growing water demand for industrial, agricultural, and domestic uses and shrinking resources. Moreover,
this task has been hampered significantly due to declining/rising groundwater levels and associated contamination.
A broad range of solutions could be considered to address the aforementioned problems of groundwater
management, but the effectiveness of all the solutions and their combinations cannot be verified with field
experiments. Given their predictive capability, simulation models are often the only viable means of providing
input to management decisions, as they can forecast the likely impacts of a particular water management strategy.
This paper presents a comprehensive review on the simulation modeling applications for the management
of groundwater resources. The past papers on the overview of groundwater simulation models, use of remote
sensing and GIS in groundwater modeling, and application of simulation models in arid and semiarid regions
are described in detail. Conclusions are drawn where gaps exist and more research needs to be focused.
en In the Hetao Irrigation District (HID), reduction of the diverted Yellow River water for agriculture makes partial replacement of fresh water for irrigation by shallow saline groundwater a possible way to alleviate the shortage of freshwater resources. In this study, a SWAP‐WOFOST agro‐hydrological model was calibrated and validated, and then applied in a distributed manner to estimate crop yield, water productivity (WP) of spring wheat, spring maize, and sunflower, and soil salinity with conjunctive use of saline and non‐saline irrigation water during 2000–2010, and a crop zoning was proposed based on simulated crop WP in the HID. Compared with non‐saline water irrigation, the annual average yield of spring wheat, spring maize, and sunflower was changed by −0.2, 5.3, and 8.2%, and the WP was changed by −5.5, 2.6, and 7.6%, respectively, with conjunctive use of saline and non‐saline irrigation water according to the proposed crop zoning. Soil salinity in the rooting zone did not increase with time. The salts remaining in the subsoil were very little, which did not obviously affect the groundwater salinity. Our results demonstrated that partial substitution of fresh water by shallow saline groundwater for irrigation is feasible in the HID. Copyright © 2017 John Wiley & Sons, Ltd.
Résumé
fr Dans le district d'irrigation de Hetao, la réduction d'allocation de l'eau du Fleuve Jaune pour l'agriculture, le remplacement partiel de l'eau douce pour l'irrigation par les eaux salines de nappe phréatique est une manière possible de remédier à la pénurie de ressources en eau douce. Dans cette étude, un modèle agro‐hydrologique SWAP‐WOFOST a été calibré validé et appliqué d'une manière distribuée pour estimer le rendement, l'efficience d'utilisation de l'eau (EUE) sur le blé de printemps, le maïs de printemps, et le tournesol, et la salinité des sols avec l'utilisation conjointe de l'eau saline et non‐salines pour l'irrigation pour la période de 2000 à 2010. Un zonage des cultures a été proposé sur la base du rendement et EUE a été simulée dans le district d'irrigation deHetao. Par rapport à l'irrigation par de l'eau non saline, l'irrigation avec l'utilisation conjointe de l'eau saline et non‐saline selon le zonage proposé a changé le rendement moyen de −0.2 5.3 et 8.2%, et WP de −5.5, 2.6 et 7.6% respectivement pour le blé de printemps, le maïs du printemps et le tournesol. La salinité du sol dans la zone d'enracinement n'a pas augmenté avec le temps. La quantité de sels restant dans le sol était très faible, ce qui n'a pas affecté la salinité des eaux souterraines de manière évidente. Nos résultats ont montré que le remplacement partiel de l'eau d'irrigation par de l'eau saline de la nappe phréatique est envisageable. Copyright © 2017 John Wiley & Sons, Ltd.
Irrigation is essential for agriculture in the Hetao Irrigation District (HID), which is one of the important food production areas in China. Surface irrigation is main irrigation method, and the efficiency of irrigation water usage is very low. With the development of economics and the reduction of the water diversion from the Yellow River for agriculture, it is crucial to improve water productivity (WP) by trying to adopt modern irrigation method, such as sprinkler irrigation. In this study, a SWAP-WOFOST agro-hydrological model was calibrated and validated, and then used to simulate crop yields and WPs in the distributed manner under the scheduled sprinkler and surface irrigation regimes during 2000–2010 in the HID. The cropping pattern was adjusted further by quantitatively comparing the WPs of the three main crops. The results indicated that compared with the surface irrigation scenario, the annual average yields of spring wheat, spring maize, and sunflower were improved by 16.9%, 8.0%, and 11.4%, respectively, and the annual average WPs were increased by 7.9%, 5.0%, and 14.1%, respectively, after zoning in the sprinkler irrigation scenario. The corresponding multiyear (2000–2010) average required field irrigation amount for the whole cultivated lands would reduce about 4.09 × 10⁸ m³ per year. At the same time, the groundwater contribution to crop water consumption became more, which did not cause groundwater depth sustainable decline during 2000–2010. Therefore, the improvement of irrigation method and the adjustment of cropping pattern could contribute to more sustainable food production and saving agricultural water usage in the HID.
The sustainable development of efficient water-saving agricultural irrigation in Loess Plateau requires reasonable and quantitative planning, design, management, and strategies based on crop-water-salt response relationship. In the present paper, data were measured by using the soil-water-salt sensor CS655 to modify the simulation of root uptake in the original Soil Water Atmosphere Plant (SWAP) model. Spring wheat field experiment data in the salinized irrigation district of Fuping County, Shaanxi Province, China were used to test the feasibility of using the SWAP model in irrigation districts of Loess Plateau. The comparison of soil moisture and salt concentration in the root system, along with simulated and measured values of partial above-ground biomass showed the following results: the average relative error and root-square error of soil moisture in the root layer were close to 0; model R2 tended to be 1; simulation accuracy of water module was high; salt concentration in the simulation varied, but the overall simulation consistency was good; crop growth parameters matched well, and simulated yield was close to the actual value with a relative error of 3.6%. The SWAP model can be well applied to simulate soil, water and salt transfer at field scale in salinized districts of Loess Plateau.
The research achievements domestic and abroad in recent years were reviewed from three aspects: risk assessment of waterlogging disaster, technology as well as management of farmland drainage, and the prospects of future development of farmland drainage technology were described. The key research directions in the future was pointed out: the evolution laws of farmland waterlogging disaster under the changing environment should be studied, and the forecast and evaluation technique under artificial-natural complex conditions should be established; the integrated control standard of waterlogging disaster for satisfying the crop production and basic environmental protection demand should be investigated to promote the technical level and management model of conventional farmland drainage control, and the combined system of modern and conventional drainage technology should be discussed; the efficient utilization of farmland drainage resources should be paid attention, and the farmland drainage management model should be studied combining water-saving irrigation with controlled drainage, irrigation and drainage with pond purification, drainage water reuse for irrigation with waterlogging and drought control.
The aim of the program Climate Proof Fresh Water Supply (CPFWS), theme 2 within the Knowledge for Climate (KfC) program, is to develop knowledge about robust and flexible long-term solutions from a local to regional perspective that can contribute to successful strategies to bridge the growing mismatch between demand and supply of fresh water (quantity and salinity) in the changing Dutch Delta.
The research scope is limited to ‘Laag-Nederland’ the lower Western parts (mostly below sea level) of the country. This area is strongly influenced by the availability of freshwater from surface water sources and has to deal with saline groundwater sources. Therefore, in this area the main reason for the occurrence of fresh water shortage is a lack of ‘good quality’ or ‘low chlorine’ water sources. Within ‘Laag-Nederland’ the actual research is mainly carried out within three case studies: ‘Zuid-westelijke Delta’ (South-western delta, agriculture on islands, some of them have external fresh water supply some don’t), ‘Haaglanden’ (area between The Hague, Delft and Rotterdam wit a large horticulture sector of major economic importance) and ‘Groene Ruggengraat’(wetland and pasture area of high ecological importance close to main greenports).
Irrigated agriculture is a clear source of non-point pollution by salts and nitrogen species. The impact of such pollution should be quantified according to specific cases. The case of the Malfaras creek basin, a sprinkler irrigation district located in the semiarid Ebro valley in northeast Spain, has been evaluated. The main crops in the district were corn, barley and alfalfa, occupying 93 % of the irrigated area. The fate of water, salts and nutrients was evaluated by a daily water balance developed at a field scale for the natural year 2010. The yearly data of the whole set of 101 irrigated fields plus the non-irrigated area compared to the measured drainage produced a basin water balance with a low degree of error. The basin consumed 90 % of the total water input of which 68 % was used for crop evapotranspiration and the rest was lost due to non-productive uses. 16 % of the incoming water left the irrigation area as drainage water. The irrigated area was responsible for 87 % of the drainage. The average volume of drained water was 152 mm year(-1) for the whole basin area. The irrigated area drained 183 mm year(-1). The basin exported 473 kg of salt per hectare during 2010. This value was the lowest of the sprinkler irrigation areas in the Ebro valley, mainly due to the lower soil salinity. All the crops except barley received a nitrogen surplus of 10-50 % above their needs. The extra nitrogen entered the water cycle increasing the nitrate concentration in the aquifer water (150 mg L-1) and drainage water (98 mg L-1). In 2010 the mass of nitrogen exported by drainage was 49 kg per irrigated hectare. This value is too high for this type of irrigation system and implies that 17 % of nitrogen applied as a fertilizer was lost to drainage water. The key to decreasing the nitrogen leaching and pollution that it causes could be appropriate time-controlled fertigation along with better irrigation scheduling.
In this investigation, a model was developed to predict dry matter, seed yield and other crop parameters of rapeseed under deficit irrigation and salinity by using soil water and salt budget and other simple plant physiological relationships. Two-year experimental data were used. In calibration and validation of the presented model, results indicated that the model was able to estimate evapotranspiration, soil water content, leaf area index, evaporation, crop transpiration, dry matter and seed yield of rapeseed properly. The advantage of this model is its simplicity and easy calibration in other areas and climate conditions and it can be used to estimate yield and other crop parameters with common measurable data in the field. Prediction of crop yield by this model can be used for better management of agronomic systems to reduce administrative costs and in different environmental conditions. Finally, under scarce data, arid and semi-arid environments, this model is proposed to be used by irrigation managers and agricultural advisors.
This article provides theoretical analyses that facilitate the use of the Penman-Monteith equation to make a one-step estimate of crop water requirements. Reluctance to using a one-step estimate results from two outstanding issues, both of which are addressed. First, no method has been yet defined to handle the problem that meteorological variables are commonly available only at 2 m above the ground while, when using the Penman-Monteith equation, they are required at some level above the crop. To resolve this, a blending height is defined in the atmospheric boundary layer (ABL) where meteorological conditions are independent of the underlying crop. Expressions are derived to calculate the aerodynamic resistances to, and the vapor pressure deficit at, the blending height from climate variables at 2 m. Consequently, 2 m climate data can be used in the Penman-Monteith equation, either to estimate transpiration from surface resistance or to calculate surface resistance from measured transpiration. Second, no table of effective values currently exists for the surface resistance of different crops equivalent to that for the crop coefficient. This article calls for field studies to address this need. However, recognizing the need for an interim source of crop-specific surface resistances, a methodology is given for translating the crop coefficient into equivalent surface resistance. To make this translation, it is necessary to specify the relationship between the radiative and aerodynamic energy inputs to evapotranspiration when the crop coefficients were calibrated. Finally, a Penman-Monteith-based, one-step estimation equation is derived that makes proper allowance for the different aerodynamic characteristics of crops in all conditions of atmospheric aridity, and that estimates crop evaporation for any crop of specified height from existing crop coefficients using standard 2 m climate data. © 2006 American Society of Agricultural and Biological Engineers.
Analytical approximations were derived for solute transport of pesticides subject to Freundlich sorption, and first-order degradation restricted to the liquid phase. Solute transport was based on the convection-dispersion equation (CDE) assuming steady flow. The center of mass (first spatial moment) was approximated both for a non-degraded solute pulse and for a pulse degraded in the liquid phase. The remaining mass (zeroth spatial moment) of a linearly sorbing solute degraded in the liquid phase was found to be a function of only the center of mass (first spatial moment) and the Damköhler number (i.e., the product of degradation rate coefficient and dispersivity divided by flow velocity). This relationship between the zeroth and first spatial moments was shown to apply to nonlinearly sorbing pulses as well. The mass fraction leached of a pesticide subject to Freundlich sorption and first-order degradation in the solution phase only was found to be a function of the Damköhler number and of the dispersivity, so independent of sorption. Hence perceptions of the effects of sorption on pesticide leaching should be reconsidered. These conclusions equally hold for other micropollutants that degrade in the solution phase only.
A new and relatively simple equation for the soil-water content-pressure head curve is described. The particular form of the equation enables one to derive closed-form analytical expressions for the relative hydraulic conductivity, when substituted in the predictive conductivity models of N. T. Burdine or Y. Mualem. The resulting expressions contain three independent parameters which may be obtained by fitting the proposed soil-water retention model to experimental data. Results obtained with the closed-form analytical expressions based on the Mualem theory are compared with observed hydraulic conductivity data for five soils with a wide range of hydraulic properties.
Many irrigated areas have shallow water tables creating waterlogging and salinization problems. This has often been controlled by installation of subsurface horizontal pipe drainage; however, these systems export large amounts of salt off farm in the drainage effluent. Improved design and management of subsurface drainage systems to reduce drainage salt loads were tested in a replicated field experiment. Deep, widely spaced drains allowed to flow without control were compared to drains with management to reduce drain flow. These were also compared with shallow, closely spaced drains that protected the root zone only and an undrained control. The deep drains flowed continuously during the two irrigation seasons with an electrical conductivity of around 11 dS/m resulting in a drainage salt load of 5,867 kg/ha. The management measures reduced drainage volume and salinity resulting in a 50% reduction in salt load. The shallow drains only flowed directly after an irrigation or rainfall event with low salinity, around 2 dS/m, resulting in a 95% reduction in salt load. This showed that by management there is great potential for reducing salt mobilization in existing drainage systems, and for new systems shallower drains will minimize sale loads.
This paper gives a review of our current conceptual understanding of the basic processes of water flow and chemical transport in the untsaturated (vadose) zone and of various deterministic mathematical models that are being used to describe these processes. During the past few decades, tremendous effort has been directed toward unravelling the complexities of various interactive physical, chemical, and microbiological mechanisms affecting unsaturated flow and transport, with contributions being made by soil scientists, geochemists, hydrologists, soil microbiologists, and others. Unfortunately, segmented, disciplinary research has contributed to a lack of experimental and theoretical understanding of the vadose zone, which, in turn, has precluded the accurate prediction and management of flow and contaminant transport through it. Thus a more unified and interdisciplinary approach is needed that considers the most pertinent physical, chemical, and biological processes operative in the unsaturated zone. Challenges for both fundamental and applied researchers to reveal the intricacies of the zone and to integrate these with currently known concepts are numerous, as is the urgency for progress inasmuch as our soil and ground water resources are increasingly subjected to the dangers of long-term pollution. Specific research areas in need of future investigation are outlined.
A distributed hydrological model [Wigmosta, M.S., Vail, L.W., Lettenmaier, D.P., 1994. A distributed hydrology-vegetation model for complex terrain. Water Resource Research 30 (6), 1665–1679] is further developed to simulate the detailed spatial and temporal variation patterns of evapotranspiration (ET) around a flux tower site. In addition to meteorological, topographical and soil data, the model utilizes optical remote sensing data (Landsat TM at 30 m resolution) to characterize the distributions of vegetation types and the leaf area index (LAI). The use of LAI allows process-based modeling of major hydrological processes including transpiration, precipitation interception, and evaporation from vegetation and soil. Water flows within and between five strata (overstore, understore, moss/litter, soil unsaturated zone, and soil saturated zone) are modeled on a daily basis. A moving window of nine pixels is used to consider the lateral subsurface flow. The model is applied to a small watershed of dimension of about 16 km×12 km in Saskatchewan, Canada. The temporal variations of simulated ET are compared with eddy-covariance ET measurements over a black spruce stand located within the watershed. The stand was the Old Black Spruce in the Southern Study Area during the Boreal Ecosystem-Atmosphere Study (BOREAS) in 1994. Although the black spruce site is located in a flat area with less than 1.5 m topographical variation within 150 m of the flux tower, there was about 10.5 mm water loss through saturated subsurface flow during the growing season of 1994, accounting for 5.7% of the rainfall in same period. Even though the watershed studied had gentle terrain variations, the topography had considerable influence not only on the water table but also on the soil moisture and saturated water redistribution. This suggests the importance of modeling hydrological processes as influenced by topography in mapping ET.
In situ use of ground water by plants is one option being considered to reduce discharge of subsurface drainage water from irrigated agriculture. Laboratory, lysimeter, and field studies have demonstrated that crops can use significant quantities of water from shallow ground water. However, most studies lack the data needed to include the crop water use into an integrated irrigation and drainage water management system. This paper describes previous studies which demonstrated the potential use of ground water to support plant growth and the associated limitations. Included are results from three field studies which demonstrated some of the management techniques needed to develop an integrated system. The field studies demonstrated that approximately 40 to 45% of the water requirement for cotton can be derived from shallow saline ground water. That regulation of the outflow will result in increasing use. Implementation of integrated management of irrigation and subsurface drainage systems is a viable and sustainable alternative in the management of subsurface drainage water from arid and semi-arid areas only if soil salinity can be managed and if the system is profitable.
In regions where water is more scarce than land, the water productivity concept (e.g. crop yield per unit of water utilized) provides a useful framework to analyse crop production increase or water savings in irrigated agriculture. Generic crop and soil models were applied at field and regional scale, together with geographical and satellite data to analyse water productivity in Sirsa District (India). In this district certain parts show a serious decline in groundwater levels and water shortage, while other parts experience a serious rise of groundwater levels, causing waterlogging and salinization. The regional analysis showed a large spatial variability of water productivity, net groundwater recharge and salinization. Scenario analysis showed that improved crop husbandry, reallocation of canal water from fresh to saline groundwater areas and reduction of seepage losses in saline groundwater areas are effective measures to increase the overall water productivity and to attain sustainable irrigation in Sirsa District.
Mechanisms that determine the rate at which chemicals move through soils include processes such as diffusion/dispersion, adsorption, decay, and intra-aggregate diffusion. Exact analytical solutions can be derived for some of these processes, such as for linear adsorption and linear decay. However, for nonlinear cases, analytical methods cannot be used to obtain the exact solutions of the transport equations, and approximate methods must be employed. The use of numerical techniques helps in modeling the transport of solutes in such cases. Numerical and analytical approaches can and should complement and augment each other. For example, an analytical solution may be used to check the accuracy of a numerical program. On the other hand, a numerical solution may be used to demonstrate the appropriateness (or shortcoming) of a particular assumption necessary in the development of an analytical solution. This chapter discusses some of the transport equations currently used to describe the movement of chemicals in soils and presents solutions based on both numerical and analytical techniques. The chapter discusses the influences of several mechanisms affecting solute transport phenomena, such as nonlinear adsorption, hysteresis in the equilibrium isotherms, and decay.
The traditional approach of installing subsurface drainage systems to solve shallow ground water problems is not feasible along the west side of the San Joaquin Valley of California because of the lack of drain water disposal methods that are economical, technically feasible, and environmentally friendly. Thus, options such as drainage reduction through improved irrigation and drain water reuse are being examined as methods for coping with the subsurface drainage problem. This paper discusses options for reducing subsurface drainage through improved irrigation practices. Options are discussed for improving irrigation system design such as upgrading existing irrigation methods and converting to systems with higher potential irrigation efficiencies. Methods for improving water management are also presented. Case studies on upgrading existing systems or converting to other irrigation methods are presented along with study results of the effect of various policies on reducing subsurface drainage.
The two root water uptake terms tested were: 1) a mechanistic equation based on Darcy's law (type I), and 2) an empirical equation relating soil water potential to relative water uptake (Type II). The Type I term was insensitive to salinity where no reduction in transpiration was shown for increasing irrigation water salinity from 0.0 to 6.0 dS/m and applying water equal to potential transpiration. The Type II term was sensitive to salinity and showed a 35% reduction in water uptake by increasing water salinity from 0.0 to 6.0 dS m-1 and applying water equal to potential transpiration. Predicted reduction in water uptake due to matrix potential was of the same magnitude as that due to salinity. The Type I term resulted in abrupt shifts in water uptake between full and zero transpiration, occasionally resulting in long periods of computed zero transpiration. -from Authors
Drainage reduction through improved irrigation is needed for addressing the problem of drainage water disposal in the San Joaquin Valley in California. Options for improving irrigation include improved management of existing systems (irrigation scheduling, duration of water applications), upgrading traditional surface irrigation systems (reduced field length, increased unit flow rate, surge irrigation, furrow compaction, tailwater recovery), and converting to pressurized irrigation systems (hand-move and linear-move sprinklers, low-energy precision application (LEPA) machines and rip irrigation). The most effective upgrade of surface irrigation systems for reducing subsurface drainage is a reduced field length coupled with reduced irrigation times. Increased furrow flow rates resulted in little change in drainage in some cases. Surge irrigation offers an opportunity of reducing subsurface drainage by only about 1/3. Converting to pressurized irrigation methods can substantially reduce subsurface drainage, but may be uneconomical in some cases. Analyses of large-scale field comparisons of irrigation methods revealed that generalizing about the best irrigation method is difficult. Economic analyses of these comparisons showed a well-managed furrow system to be more profitable than a subsurface drip system in one case, but a subsurface drip system to be more profitable compared to a marginally managed furrow system in another case. The analyses also revealed that disposal costs of subsurface drainage water may need to be much higher than projected costs to economically justify converting from furrow irrigation to irrigation systems with high capital costs.
A simple analytic model is proposed which predicts the unsaturated
hydraulic conductivity curves by using the moisture content-capillary
head curve and the measured value of the hydraulic conductivity at
saturation. It is similar to the Childs and Collis-George (1950) model
but uses a modified assumption concerning the hydraulic conductivity of
the pore sequence in order to take into account the effect of the larger
pore section. A computational method is derived for the determination of
the residual water content and for the extrapolation of the water
content-capillary head curve as measured in a limited range. The
proposed model is compared with the existing practical models of
Averjanov (1950), Wyllie and Gardner (1958), and Millington and Quirk
(1961) on the basis of the measured data of 45 soils. It seems that the
new model is in better agreement with observations.
Borkhar district is located in an arid to semi-arid region in Iran and regularly faces widespread drought. Given current water scarcity, the limited available water should be used as efficient and productive as possible. To explore on-farm strategies which result in higher economic gains and water productivity (WP), a physically based agrohydrological model, Soil Water Atmosphere Plant (SWAP), was calibrated and validated using intensive measured data at eight selected farmer fields (wheat, fodder maize, sunflower and sugar beet) in the Borkhar district, Iran during the agricultural year 2004–2005. The WP values for the main crops were computed using the SWAP simulated water balance components, i.e. transpiration T, evapotranspiration ET, irrigation I, and the marketable yield YM in terms in terms of YMT−1, YM ET−1 and YM I−1.
A clear understanding of all the components of the water balance is essential to analyze possible measures of water savings in irrigated agriculture. However, most components of the water balance are not easily measurable either in terms of the required time interval or the complexity of the processes. For an irrigated area in the Western part of Turkey, the physically based one-dimensional agro-hydrological model SWAP for water transport and crop growth was applied in a distributed manner to reveal all the terms of the water balance. A combination of point data and distributed areal data was used as input for the model. The emphasis was put on the conversion from available data to required data. Simulations were carried out for the period 1985–1996 and detailed analyses were performed for two successive years, a pre-drought year, 1988, and a dry year, 1989. Irrigation deliveries were reduced substantially in 1989, resulting in a modified water balance. Lateral fluxes to drains were reduced, bottom fluxes were changed from groundwater recharge to capillary rise, evapotranspiration was lower, and, most importantly, relative yield was reduced. All these changes were obtained for specific sites by combining existing soil data with cropping patterns. It was concluded that the use of the SWAP model in a distributed way is a useful tool to analyze all the components of the water balance for a whole irrigation system.
This study focuses on the identification of appropriate strategies to improve water management and productivity in an irrigated area of 4270 km2 in India (Sirsa district). The field scale ecohydrological model SWAP in combination with field experiments, remote sensing and GIS has been applied in a distributed manner generating the required hydrological and biophysical variables to evaluate alternative water management scenarios at different spatial and temporal scales.Simulation results for the period 1991–2001 show that the water and salt limited crop production is 1.2–2.0 times higher than the actual recorded crop production. Improved crop husbandry in terms of improved crop varieties, timely sowing, better nutrient supply and more effective weed, pest and disease control, will increase crop yields and water productivity in Sirsa district. The scenario results further showed that reduction of seepage losses to 25–30% of the total canal inflow and reallocation of 15% canal water inflow from the northern to the central canal commands will improve significantly the long term water productivity, halt the rising and declining groundwater levels, and decrease the salinization in Sirsa district.
Soil sodicity development is a process that depends nonlinearly on both salt concentration and composition of soil water. In particular in hot climates, soil water composition is subject to temporal variation due to dry-wet cycles. To investigate the effect of such cycles on soil salinity and sodicity, a simple root zone model is developed that accounts for annual salt accumulation and leaching periods. Cation exchange is simplified to considering only Ca/Na exchange, using the Gapon exchange equation. The resulting salt and Ca/Na-balances are solved for a series of dry/wet cycles with a standard numerical approach. Due to the nonlinearities in the Gapon equation, the fluctuations of soil salinity that may be induced, e.g. by fluctuating soil water content, affect sodicity development. Even for the case that salinity is in a periodic steady state, where salt concentrations do not increase on the long term, sodicity may still grow as a function of time from year to year. For the longer term, sodicity, as quantified by Exchangeable Sodium Percentage (ESP), approaches a maximum value that depends on drought and inflowing water quality, but not on soil cation exchange capacity. Analytical approaches for the salinity and sodicity developing under such fluctuating regimes appear to be in good agreement with numerical approximations and are very useful for checking numerical results and anticipating changes in practical situations.
Iran faces widespread droughts regularly, causing large economical and social damages. The agricultural sector is with 80-90 % by far the largest user of water in Iran and is often the first sector to be affected by drought. Unfortunately, water management in agriculture is also rather poor and hence water productivity of crops WP is far below potential. The growing water scarcity due to drought and the increasing water demands of industries, households and environment, are major threats to sustainable agricultural development in Iran. Therefore, the development of a reliable agricultural drought assessment system would be very beneficial for proper operational decision making on farms, for early warning, for identification of potential vulnerability of areas and for mitigation of drought impacts.
Given the current water scarcity, the limited available amount of water should be used as efficient as possible. To explore on-farm strategies which result in higher WP -values and thus economic gains, the physically based agrohydrological model Soil Water Atmosphere Plant (SWAP), was calibrated and validated using measured data at 8 selected farmer’s fields (wheat, fodder maize, sunflower and sugar beet) in the Borkhar irrigation district in Iran during the agricultural year 2004-05. Using the calibrated SWAP model, on-farm strategies i.e. deficit irrigation scheduling, optimal irrigation intervals and extent of cultivated area, were analyzed based on relations between WP - indicators and water consumption. The results showed a large potential of the improvement of water productivity under limited water supply in the Borkhar irrigation district.
Although agrohydrological models like SWAP offer the possibilities for predicting crop yield, such models may become inaccurate because of uncertainty of input parameters like irrigation scheduling, soil hydraulic parameters and planting dates. This holds especially true when applying distributed modelling at regional scale. Hence to reduce the uncertainty in application of SWAP at regional scales, remotely sensed data of leaf area index and evapotranspiration were used in combination with a geographical information system. The remotely sensed data were inserted into the distributed SWAP model using data assimilation techniques i.e. sequential updating.
Data of LAI were derived from Visible and Near Infrared (VNIR) spectral bands of remote sensing data with moderate to high spatial resolution. However, due to resolution limitations of existing remotely sensed data i.e. thermal bands, these data could not be used directly for routine ET estimation of individual fields. Therefore, a new disaggregation method based on linear disaggregation of ET components within each MODIS pixel, was developed and applied to the simulated MODIS data. The results of the proposed approach were further compared with two other disaggregation approaches being based on weighted ratios, as derived from dividing ET maps of high and low spatial resolution data.
The biggest advantage of the proposed linear disaggregation approach was that the number of high spatial resolution images needed in this method is low, i.e . the approach can even be applied using one land cover map only . As in many regions access to high spatial resolution thermal images is currently not possible, the linear disaggregation method can still be used to assess drought impacts far in advance.
Water balance components as computed by SWAP are quite sensitive to the upper boundary conditions, and hence to irrigation times and application depths. In order to know how much water has been applied, the cumulative actual ET data were therefore used in an automatic calibration mode, i.e. inverse modelling of irrigation scheduling. The ability of inverse modelling to reproduce the initial irrigation times and depth, was first investigated using forward cumulative SWAP simulated ET data based on 5, 15 and 30 days. Thereafter, the cumulative disaggregated remotely sensed ET data based on 5 days were used in the inverse modelling process.
The results showed that the performance of inverse modelling is promising in identifying the irrigation time and depth of irrigation using 5 days based cumulative ET data. However, irrigation amounts, which rewet the soil profile beyond field capacity and thus cause excessive percolation, could not be detected by the applied inverse modelling approach. Also, assimilation of remotely sensed data into a distributed SWAP by automatic calibration needed a large amount of computation time, especially at regional scale.
Hence, to insert the valuable information from remotely sensed land surface data into the SWAP model at regional scale, a simple updating assimilation technique was used. The SWAP model was implemented in a distributed way using the spatial distributed information of soil types, land use and water supply on a raster basis with a grid size of 250 m. In order to link spatial information data with SWAP , a coupling program was written by the author in MATLAB . This program took care of the transfer of in- and output data from one system to the other, as well as to run the model for each pixel.
To have a prediction of crop yield far in advance, the sequential updating process of remotely sensed based data ( LAI and/or relative evapotranspiration ET/ET <sub>p</sub>) was halted at one respectively two months before the end of the wheat growing season. During the sequential updating process known weather data were used, while for the remaining part of the growing season different scenarios were considered based on weather data of a dry, wet and normal year. A value for the optimum gain factor K <sub>g</sub>, that performed best with respect to the observations, was selected
S imulation with assimilation of both LAI and ET/ET <sub>p -</sub> data at both the regional and field scale (bias about %) was very promising in forecasting crop production one month in advance . However, longer term predictions i.e. two months in advance, resulted in a higher bias between the simulated and statistical data. It appeared that in the assimilation process LAI data have a dominant influence. Because of this dominant influence, it is suggested to repeat the assimilation process using the LAI data of the most advanced satellite i.e. IRS-P6 (ResourceSAT1&2) with higher spatial and temporal resolution.
The surface water in the Borkhar irrigation canal network is provided by diversion of the water from the Zayande Rud river. Since this river is mainly fed by the snow melt from January to April, a comprehensive drought assessment system on seasonal basis can be developed by integration of the developed agricultural drought assessment system with the estimates of available surface water being derived from snow pack and snow cover.
The Soil Water Atmosphere Plant (SWAP) model simulates transport of water, solutes, and heat in the vadose zone in interaction with vegetation development. Special features of the model are generic crop growth, versatile top boundary conditions, macroporous flow, and interaction of soil water with groundwater and surface water. We discuss typical model applications that have appeared in recent scientific literature. New model developments are explained with respect to the numerical solution of Richards' equation, macroporous flow, evapotranspiration, and interactions with groundwater and surface water. We describe case studies on agricultural water productivity, regional nutrient management, and groundwater conservation by surface water management. Finally we envision model developments with respect to SWAP for the coming 5 to 10 yr.
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