Runoff response to multiple land-use changes and climate perturbations

Runoff response to multiple land-use changes and climate perturbations is distinct, and the main influencing factors vary significantly in different regions. However, few have simultaneously considered the effects of multiple land use changes (vegetation cover changes, terraces and check-dams construction, and urban expansion) and climatic perturbations (precipitation, potential evapotranspiration, and temperature) on runoff and constructed separate expressions for distinct study areas. This article attempted to determine the main influencing factors of runoff according to the fitting function in the eight subregions of the middle Yellow River (MYR), construct the expressions between the controlling parameter in the Budyko framework and the main factors, and quantify the contribution of climate factors and land use changes to runoff by combining the elasticity coefficient in each subregion. The results indicated that climate factors and land use changes could significantly impact controlling parameters, and there were differences between regions. Climate change promoted an increase in runoff, while land use change promoted its reduction, and the reduction value outweighed its increase. In terms of land use changes, increasing vegetation coverage could suppress runoff reduction, while constructing terraces and check-dams could promote its reduction. The urban expansion benefited runoff collection and, therefore, could suppress runoff reduction. Its absolute contribution rate exceeded 200% in apparent urban expansion areas. In addition, the contribution rates of land use to runoff changes in the northern arid and semi-arid regions were significantly higher than those in the southern, and they were more sensitive to land use changes. The research results can provide a reference for analysing the runoff response to different land-use changes and can further advance people's understanding of the water cycle.     

Using a groundwater quality negotiation support system to change land-use management near a drinking-water abstraction in the Netherlands

A negotiation support system (NSS) was developed to solve groundwater conflicts that arose during land-use management. It was set up in cooperation with the stakeholders involved to provide information on the impact of land use, e.g., agriculture, nature (forested areas), recreation, and urban areas, on the quality of both infiltrating and abstracted groundwater. This NSS combined simulation programs that calculate (1) the concentrations of nitrate in shallow groundwater for each land-use area and (2) the transport of nitrate in the groundwater-saturated zone. The user interface of the NSS enabled scenario analyses. The NSS was validated at a drinking-water abstraction near Holten (the Netherlands) using a spatial planning process aimed at sustainable land-use and groundwater-resource management. Two land-use scenarios were considered: a base scenario reflecting the autonomous development and an adapted land-use scenario. The calculated results for shallow groundwater provided an explicit spatial overview of the impact of historical land use and N application on the quality of abstracted groundwater as well as insight into the impact of changes in land use and N application. Visualization of the conflicting interests of agriculture and the drinking-water abstraction helped all stakeholders accept the necessary changes in land use identified by the adapted land-use scenario of the NSS. These changes were included in the preferred land-use management option in the regional planning process, which has since been formalized. The NSS provided system insight, scoping analyses, and education, in addition to generating quantitative information on the impact of land-use functions on groundwater quality.     

Numerically modelling groundwater in an arid area with ANN‐generated dynamic boundary conditions

Groundwater is sensitive to the climate change and agricultural activities in arid and semi‐arid areas. Over the past several decades, human activities, such as groundwater extraction for irrigation, have resulted in aquifer overdraft and disrupted the natural equilibrium in these areas. Regional groundwater simulation is important to determine appropriate groundwater management policies, and numerical simulation has become the most popular method. However, most groundwater models were developed with static boundary conditions. In this research, the Minqin oasis, an arid region located in northwest China, was selected as the study area. An artificial neural network (ANN) was developed to simulate effects of weather conditions, agricultural activities and surface water on groundwater level in a dynamic boundary of the domain. Subsequently, a groundwater numerical model, named ANN‐FEFLOW model, was developed, with a dynamic boundary condition defined by the ANN model. The verifying results showed that the model has higher precision, with a root mean square error (RMSE) of 0·71 m, relative error (RE) of 17·96% and R² of 0·84 relative to the great groundwater change. Furthermore, the groundwater model has higher precision than the conventional groundwater model with static boundary condition, particularly in the area near the dynamic boundary. This study demonstrated that dynamic boundaries can improve the precision of the regional groundwater model in an arid area and that ANN can provide higher accuracy prediction capability for groundwater levels with dynamic boundary. Copyright © 2010 John Wiley & Sons, Ltd.     

Flood events and flood risk assessment in relation to climate and land-use changes: Saint-François River,southern Québec,Canada

Abstract

In the current context of climatic variability, it is important to quantify the impact on the environment. This study deals with an analysis of climatic data and land-use changes in terms of the impacts on flood recurrence based on multisource data. The study area covers the mouth of the Saint-François River (southern Québec, Canada), where spring floods and ice jams are a recurring problem. The flood frequency analysis shows an increase in flooding over recent decades, attributable to an increase in winter temperatures that has the effect of causing ice jams earlier in the year. Regarding land-use changes, a small decrease in agricultural surface areas is observed, from 53% to 39%, along with increases in forest and urban surface areas from 27% to 38% (forest) and 3% to 5% (urban) between 1928 and 2005. In a context of continuing climate warming, more pronounced inter-annual variations are to be expected along with a higher incidence of flooding.

Editor Z.W. Kundzewicz

Citation Ouellet, C., Saint-Laurent, D. and Normand, F., 2012. Flood events and flood risk assessment in relation to climate and land-use changes: Saint-François River, southern Québec, Canada. Hydrological Sciences Journal, 57 (2), 313–325.     

Development and application of a stochastic optimization model for groundwater management: crop pattern and conjunctive use consideration

The need for irrigation water in arid and semi-arid regions is mostly supplied by groundwater. Furthermore, the agricultural development in these areas is not generally based on a comprehensive plan, which can cause aquifers depletion. On the other hand, to properly manage an aquifer and to have an optimal crop plan, the stochastic nature of the different parameters of a groundwater system such as groundwater recharge and water demands should be taken into consideration. In this paper, we develop an explicit stochastic optimization model for Firouzabad aquifer in Iran. This formulation is based on the first and second moment analysis for groundwater head which has been initially proposed for surface water resources management by Fletcher and Ponnambalam. We extend the model to create a new random withdrawal policy for conjunctive use setting in which the randomness in available precipitation is taken into account. The interesting point is that the model provides the respective probabilities of shortage and surplus without imposing the extra decision variables into the optimization model. A genetic-based algorithm is used to solve the stochastic nonlinear and non-convex formulation. The outcome results indicate that the current crop pattern should be changed, that is, the allocated areas of some crops have to be meaningfully reduced. Finally, to validate our model efficiency, we demonstrate that how much close the statistical characteristics obtained from the optimization model are to those estimated from the Monte Carlo simulation. Furthermore, the optimal benefits obtained using the proposed optimization model are as suitable as the benefits achieved using the corresponding Monte Carlo-based optimization model.     

Quantitative analysis of the driving factors for groundwater resource changes in arid irrigated areas

How to quantify the impact of climate change and human activities on groundwater is not only a hot topic of current research but also a key point of water resource management in arid irrigated areas. Therefore, this paper analyzes the changes in the trends of land use, climate, and groundwater extraction in the Yanqi Basin in recent years and uses the distributed hydrological model MIKE-SHE to quantitatively analyze the impacts of these three factors on groundwater resources. The results show that: 1. The Nash coefficients of the simulated and observed groundwater levels during the verification period are 0.84, 0.79 and 0.76; the correlation coefficient between the simulated and observed soil moisture is 0.86. Although there are some uncertainties in the simulation, the results prove that the model can be used to simulate arid irrigated areas. 2. The effects of these three factors on groundwater levels are 5, 12.5 and 82.5%, respectively, and have caused the regional average groundwater level to decrease by a maximum of 0.07, 0.23 and 1.79 m, respectively. The effects of these three factors on the interactions between surface water and groundwater were 7.04, 3.63 and 89.33%. Groundwater extraction has become the main influencing factor of regional groundwater resources changes due to its more direct influence. 3. The influence of groundwater extraction has a strong spatial distribution characteristic and 10% of the study area has been greatly impacted by the groundwater extraction. Base on the above results, integrating multidisciplinary knowledge to establish the relationship between ecological environment and groundwater changes can provide strategies for the sustainable development of groundwater.     

Assessment of reference evapotranspiration across an arid urban environment having poor data monitoring system

Estimation of reference evapotranspiration (ET₀) in urban areas is challenging but essential in arid urban climates. To evaluate ET₀ in an urban environment and non-urban areas, air temperature and relative humidity were measured at five different sites across the arid city of Isfahan, Iran, over 4 years. Wind speed and sunshine hours were obtained from an urban surrounding weather station over the same period and used to estimate ET₀. Calculated ET₀ was compared with satellite-based ET₀ retrieved from the MOD16A2 PET product. Although MODIS PET was strongly correlated with the Valiantzas equation, it overestimated ET₀ and showed average accuracy (r = 0.93–0.94, RMSE = 1.18–1.28 mm/day, MBE = 0.73–0.84 mm/day). The highest ET₀ differences between an urban green space and a non-urban area were 1.1 and 0.87 mm/day, which were estimated by ground measurements and MODIS PET, respectively. The sensitivity of ET₀ to wind speed and sunshine hours indicated a significant effect on cumulative ET₀ at urban sites compared to the non-urban site, which has a considerable impact on the amount of irrigation required in those areas. Although MODIS PET requires improvement to accurately reflect field level microclimate conditions affecting ET₀, it is beneficial to hydrological applications and water resource managers especially in areas where data is limited. In addition, our results indicated that using limited data methods or meteorological data from regional weather stations, leads to incorrect estimation of ET₀ in urban areas. Therefore, decision-makers and urban planners should consider the importance of precisely estimating ET₀ to optimize management of urban green space irrigation, especially in arid and semi-arid climates such as the city of Isfahan.     

SOM-DRASTIC: using self-organizing map for evaluating groundwater potential to pollution

Groundwater is considered as the most important water resource, especially in arid and semi-arid regions, so it is crucial to impede this source of water to be contaminated. One of the most common methods to assess groundwater vulnerability is DRASTIC method. However, the subjectivity existing in defining DRASTIC weights and ratings as well as inadaptability of the parameters involved in this method with special geology, hydrogeology, land use and climatic conditions have urged researchers to modify this method. In this paper, a new method combining a special type of the neural networks called Self-Organizing Map (SOM) and the traditional DRASTIC model resulting in the hybrid SOM-DRASTIC model is applied to modify and improve DRASTIC Model. The traditional DRASTIC method holds a summation among all negative effects of different factors contributing to vulnerability, while the proposed hybrid method is able of classifying the groundwater vulnerability and deriving the real relation existing between the DRASTIC parameters as the inputs and the vulnerability class as the output of the method. The vulnerability assessment process was performed on the Zayandeh-Rud river basin aquifers in Iran. The SOM-DRASTIC identified the northern parts of the study area as the most vulnerable areas with a drastically fractured structure, while the traditional DRASTIC ranked the western parts as the most vulnerable regions with a high rate of net recharge. The results demonstrate that the proposed method can be used by managers and decision-makers as an alternative robust tool for vulnerability-based classification and land use planning.     

Geomorphological changes in an arid transgressive coastal dune field due to natural processes and human impacts

Geomorphological changes in recent decades in an arid transgressive coastal dune system (Maspalomas, Gran Canaria, Canary Islands) are analyzed. The methodology used is based on the generation of two geomorphological maps (1961 and 2003) by interpretation of digital orthophotos. The overlay of both maps in a geographic information system (GIS) enabled the spatial and surface changes of the landforms to be determined, and the processes that generated these changes. Twelve cultural and geomorphological processes were identified from highest to lowest importance, namely: anthropization by urban occupation (114 ha changed), stabilization (92.5 ha), barchanization (37 ha), salinization/halophytication (15 ha), anthropization (12.4 ha), deflation (11.8 ha), dune loss/beach gain (11.3 ha), dune formation (9.6 ha), progradation (8 ha), retrogradation (7.7 ha), destabilization (2.7 ha) and flooding (0.7 ha). Geomorphological changes are associated with a combination of five main factors, three of anthropogenic origin and two natural ones. The natural factors are: (1) the arid climate, which favors changes occurring at high speed; (2) the existence of a progressive sedimentary deficit. Anthropogenic factors are: (3) construction of tourist urbanizations, infrastructures and facilities; (4) installation of equipment or infrastructure on the beaches; (5) the activities carried out by users. These human factors have altered the aeolian dynamics and reduced the area occupied by vegetation in some areas, causing changes in aeolian sedimentary processes. The geomorphological processes identified can be used as indicators of environmental change, allowing us to synthesize the changes in landforms detected, and group all combinations derived from the analysis by GIS and analyze them spatially. Thus, the environmental changes in the transgressive coastal dune systems could be interpreted more effectively. Copyright © 2018 John Wiley & Sons, Ltd.     

Evaluation of Negative Economic-Environmental Externalities of Overextraction of Groundwater

In recent decades, increased extraction of groundwater for human and agriculture consumption has led to a substantial drop in groundwater level in large areas of across the world. Declining groundwater levels is a serious problem in itself and has multiple economic, social, cultural, political, security-related, and environmental externalities. The negative economic-environmental externalities of overextraction of groundwater in the Orzouiyeh plain in the Kerman Province, Iran, were evaluated using methods such as replacement cost, production function, market prices, shadow price, and the value of the input marginal product. After evaluating externalities, the Positive Mathematical Programming method was used to evaluate different water policies to reduce the consumption of groundwater. The total economic losses due to the externalities were calculated to equal 2.8 U.S. million dollars. The damages caused by environmental externalities were calculated to equal 436.1 U.S. million dollars. The results related to the positive planning model show that the best policy among different options, such as deficit irrigation policy or combined policies, involves implementation of pressurized irrigation systems.     

Groundwater Governance in the United States: Common Priorities and Challenges

Groundwater is a critical component of the water supply for agriculture, urban areas, industry, and ecosystems, but managing it is a challenge because groundwater is difficult to map, quantify, and evaluate. Until recently, study and assessment of governance of this water resource has been largely neglected. A survey was developed to query state agency officials about the extent and scope of groundwater use, groundwater laws and regulations, and groundwater tools and strategies. Survey responses revealed key findings: states' legal frameworks for groundwater differ widely in recognizing the hydrologic connection between surface water and groundwater, the needs of groundwater‐dependent ecosystems, and the protection of groundwater quality; states reported a range in capacity to enforce groundwater responsibilities; and states have also experienced substantial changes in groundwater governance in the past few decades. Overall, groundwater governance across the United States is fragmented. States nevertheless identified three common priorities for groundwater governance: water quality and contamination, conflicts between users, and declining groundwater levels. This survey represents an initial step in a broader, continuing effort to characterize groundwater governance practices in the United States.     

Influence of Seasonal Pumping on Groundwater Sources and Flow System,Nagaoka Plain,Japan

Intensive groundwater development in the urban area of the Nagaoka Plain, Japan, has induced changes in the pH and saturation index of calcite in groundwater. To account for these chemical changes, it is important to determine seasonal variations of recharge and the groundwater flow system in the aquifer. This study identified the sources and flow system of groundwater in this urban area by a comprehensive method using stable isotope data and a numerical groundwater model of the Nagaoka Plain. Stable isotope evidence shows that the groundwater is recharged by meteoric water originating from low‐elevation areas rather than the mountains surrounding the plain. The water table in the study area is drawn down during the winter and recovers in the other seasons. Numerical modeling shows that discharge occurs primarily along the Shinano River during the recovery period, whereas discharge is centered in urbanized areas during the drawdown period, when a conical depression of the water table stimulates recharge from the immediate area. These results are indications of a local groundwater flow system, with its recharge area between the Shinano River and the urban areas, which is governed by intensive seasonal groundwater extraction.     

Using bromide data tracer and HYDRUS-1D to estimate groundwater recharge and evapotranspiration under film-mulched drip irrigation in an arid Inland Basin,Northwest China

Accurate estimation of groundwater recharge (GR) and evapotranspiration (ET) are essential for sustainable management of groundwater resources, especially in arid and semi-arid regions. In the Manas River Basin (MRB), water shortage is the main factor restricting sustainable development of irrigated agriculture, which relies heavily on groundwater. Film-mulched drip irrigation significantly changes the pattern and dominant processes of water flow in the unsaturated zone, which increases the difficulty of GR and ET estimation. To better estimate GR and ET under film-mulched drip irrigation in the MRB, bromide tracer tests and soil lithologic investigation were conducted at 12 representative sites. A one-dimensional variably saturated flow model (HYDRUS-1D) was calibrated at each site using soil evaporation data inferred from the bromide tracer tests. The results showed that average annual soil evaporation in uncultivated lands calculated from bromide trace tests was 25.55 mm. The annual GR ranged from 5.5 to 37.0 mm under film-mulched drip irrigation. The annual ET ranged from 507.0 to 747.1 mm, with soil evaporation between 35.7 and 117.0 mm and transpiration between 460.9 and 642.3 mm. Soil evaporation represented 7% to 16% of the total ET and more than 70% of precipitation and irrigation water was used by cotton plants. Spatial variations of soil lithology, water table depth and initial soil water content led to the spatial differences of GR and ET in the MRB. Our study indicated that bromide tracer tests are useful for inferring ET in the arid and semi-arid oases. The combination of bromide tracer tests and HYDRUS-1D enhances reliability for estimation of GR and ET under film-mulched drip irrigation in the MRB and shows promise for other similar arid inland basins around the world.     

Effects of Groundwater Development on Uranium: Central Valley,California, USA

Uranium (U) concentrations in groundwater in several parts of the eastern San Joaquin Valley, California, have exceeded federal and state drinking water standards during the last 20 years. The San Joaquin Valley is located within the Central Valley of California and is one of the most productive agricultural areas in the world. Increased irrigation and pumping associated with agricultural and urban development during the last 100 years have changed the chemistry and magnitude of groundwater recharge, and increased the rate of downward groundwater movement. Strong correlations between U and bicarbonate suggest that U is leached from shallow sediments by high bicarbonate water, consistent with findings of previous work in Modesto, California. Summer irrigation of crops in agricultural areas and, to lesser extent, of landscape plants and grasses in urban areas, has increased Pco₂ concentrations in the soil zone and caused higher temperature and salinity of groundwater recharge. Coupled with groundwater pumping, this process, as evidenced by increasing bicarbonate concentrations in groundwater over the last 100 years, has caused shallow, young groundwater with high U concentrations to migrate to deeper parts of the groundwater system that are tapped by public-supply wells. Continued downward migration of U-affected groundwater and expansion of urban centers into agricultural areas will likely be associated with increased U concentrations in public-supply wells. The results from this study illustrate the potential long-term effects of groundwater development and irrigation-supported agriculture on water quality in arid and semiarid regions around the world.     

Isotopic and hydrochemical insights into the groundwater characteristics along an arid to semi-humid climate gradient in China

In arid to semi-arid regions, groundwater is a critical water resource heavily relied upon, with the recharge sources and patterns being predominantly shaped by climate change and regional disparities. To compare the characteristics of groundwater in the endorheic and exorheic river basins with the climate transition zone of Gansu Province, this study uses isotopic hydrochemical analyses. This study summarizes the differences in regional groundwater recharge and evolutionary patterns. The results shows that the distribution patterns of precipitation isotopes in endorheic and exorheic river basins are opposite to those of groundwater isotopes. Specifically, the precipitation in the endorheic areas is more depleted in heavy isotopes, whereas the groundwater is more enriched. Both endorheic areas and exorheic areas exhibit similar characteristics of groundwater hydrochemical evolution, evolving from low-mineralization Mg²⁺ HC ${\mathrm{O}}_3^{-}$ recharge water to Na⁺ Cl⁻ type water with saline characteristics. The former is primarily replenished by surface water, whereas the latter is primarily replenished by precipitation. Variations in recharge patterns along with the differences in climatic conditions lead to distinct groundwater conditions in the two regions.     

中国干旱和半干旱带的10年际演变特征

利用Thornthwaite的干湿分类函数,对近100年中国干旱和半干旱区界限的10年际变动特征进行了分析.结果发现：近50年,在东北中部和华北北部,干旱和半干旱边界呈波动式东移,有明显向东扩展的趋势;在华北南部和陕西南部,半干旱边界也呈波动式南扩,其中陕西南部半干旱边界向南扩展的范围最大.近100年,10年际的干旱和半干旱边界也呈波动式摆动且存在向东和向南扩展的趋势,但在华北南部与东北中部两个地区以20世纪20年代前后干旱和半干旱的范围最大、最强.干旱和半干旱分界线的位置变化与区域升温和降水减少密切相关.     

Evaluation of efficiency of different estimation methods for missing climatological data

Reliable estimation of missing data is an important task for meteorologists, hydrologists and environment protection workers all over the world. In recent years, artificial intelligence techniques have gained enormous interest of many researchers in estimating of missing values. In the current study, we evaluated 11 artificial intelligence and classical techniques to determine the most suitable model for estimating of climatological data in three different climate conditions of Iran. In this case, 5 years (2001–2005) of observed data at target and neighborhood stations were used to estimate missing data of monthly minimum temperature, maximum temperature, mean air temperature, relative humidity, wind speed and precipitation variables. The comparison includes both visual and parametric approaches using such statistic as mean absolute errors, coefficient of efficiency and skill score. In general, it was found that although the artificial intelligence techniques are more complex and time-consuming models in identifying their best structures for optimum estimation, but they outperform the classical methods in estimating missing data in three distinct climate conditions. Moreover, the in-filling done by artificial neural network rivals that by genetic programming and sometimes becomes more satisfactory, especially for precipitation data. The results also indicated that multiple regression analysis method is the suitable method among the classical methods. The results of this research proved the high importance of choosing the best and most precise method in estimating different climatological data in Iran and other arid and semi-arid regions.     

SWAT-based hydrological modelling of tropical land-use scenarios

Abstract

The Hulu Langat basin, a strategic watershed in Malaysia, has in recent decades been exposed to extensive changes in land-use and consequently hydrological conditions. In this work, the impact of Land Use and Cover Change (LUCC) on hydrological conditions (water discharge and sediment load) of the basin were investigated using the Soil and Water Assessment Tool (SWAT). Four land-use scenarios were defined for land-use change impact analysis, i.e. past, present (baseline), future and water conservation planning. The land-use maps, dated 1984, 1990, 1997 and 2002, were defined as the past scenarios for LUCC impact analysis. The present scenario was defined based on the 2006 land-use map. The 2020 land-use map was simulated using a cellular automata-Markov model and defined as the future scenario. Water conservation scenarios were produced based on guidelines published by Malaysia’s Department of Town and Country Planning and Department of Environment. Model calibration and uncertainty analysis was performed using the Sequential Uncertainty Fitting (SUFI-2) algorithm. The model robustness for water discharge simulation for the period 1997–2008 was good. However, due to uncertainties, mainly resulting from intense urban development in the basin, its robustness for sediment load simulation was only acceptable for the calibration period 1997–2004. The optimized model was run using different land-use maps over the periods 1997–2008 and 1997–2004 for water discharge and sediment load estimation, respectively. In comparison to the baseline scenario, SWAT simulation using the past and conservative scenarios showed significant reduction in monthly direct runoff and monthly sediment load, while SWAT simulation based on the future scenario showed significant increase in monthly direct runoff, monthly sediment load and groundwater recharge.

Editor D. Koutsoyiannis; Associate editor C. Perrin     

Groundwater Depth Forecasting Using Configurational Entropy Spectral Analyses with the Optimal Input

Accurate groundwater depth forecasting is particularly important for human life and sustainable groundwater management in arid and semi-arid areas. To improve the groundwater forecasting accuracy, in this paper, a hybrid groundwater depth forecasting model using configurational entropy spectral analyses (CESA) with the optimal input is constructed. An original groundwater depth series is decomposed into subseries of different frequencies using the variational mode decomposition (VMD) method. Cross-correlation analysis and Shannon entropy methods are applied to select the optimal input series for the model. The ultimate forecasted values of the groundwater depth can be obtained from the various forecasted values of the selected series with the CESA model. The applicability of the hybrid model is verified using the groundwater depth data from four monitoring wells in the Xi'an of Northwest China. The forecasting accuracy of the models was evaluated based on the average relative error (RE), root mean square error (RMSE), correlation coefficient (R) and Nash-Sutcliffe coefficient (NSE). The results indicated that comparing with the CESA and autoregressive model, the hybrid model has higher prediction performance.     

Development of a three‐dimensional watershed modelling system for water cycle in the middle part of the Heihe rivershed,in the west of China

A three‐dimensional numerical modelling system is developed to study transformation processes of water resources in alluvial fan and river basin along the middle reaches of the Heihe River Basin, Northwest China, an arid and semi‐arid region. Integrating land utilization, remote sensing and geographic information systems, we have developed a numerical modelling system that can be used to quantify the effects of land use and anthropogenic activities on the groundwater system as well as to investigate the interaction between surface water and groundwater. Various hydraulic measurements are used to identify and calibrate the hydraulic boundary conditions and spatial distributions of hydraulic parameters. In the modelling study, various water exchanges and human effects on the watershed system are considered. These include water exchange between surface water and groundwater, groundwater pumping, lateral water recharges from mountain areas, land utilization, and infiltration and evaporation in the irrigation and non‐irrigation areas. The modelling system provides a quantitative method to describe spatial and temporal distributions and transformations between various water resources, and it has application to other watersheds in arid and semi‐arid areas. Copyright © 2011 John Wiley & Sons, Ltd.