GIS-based decision support system for groundwater assessment in large irrigation project areas

In large canal irrigation project areas, integrated management of surface and groundwater resources can improve water use efficiencies and agricultural productivity and also control water logging. Such integrated management requires an estimation of spatial distribution of recharge and ground water flow in the underlying aquifer. Recharge occurs both as percolation losses from fields and seepage losses from the water distribution network. Percolation losses are influenced by weather, soil properties, land use, and canal water and groundwater use. Seepage losses depend on the conditions of flow in the water distribution system. In large irrigation project areas all the factors influencing the recharge of groundwater vary spatially. In this study, a geographical information systems (GIS) is used to map the spatial distribution of recharge which then serves as input to a regional groundwater flow model for simulating the behavior of the underlying aquifer. The basis is that the project area can be divided into a set of basic simulation units (BSUs) that are homogenous with respect to the conditions that influence the recharge processes. A daily field soil water balance model and a simple canal flow model are used to estimate the percolation and seepage losses, respectively. The combination of models and GIS can be used as an integrated decision support system to assess the groundwater resources and derive strategies for integrated management of canal and groundwater resources in the project area. © 2003 Elsevier B.V. All rights reserved.

[1]  J. C. Ramírez,et al.  Estimation of aquifer parameters under transient and steady-state conditions , 1984 .

[2]  Dennis L. Corwin,et al.  Applications of GIS to the Modeling of NonPoint Source Pollutants in the Vadose Zone: A Conference Overview , 1996 .

[3]  P. Burrough,et al.  Principles of geographical information systems , 1998 .

[4]  F. H. S. Chiew,et al.  Groundwater Recharge from Rainfall and Irrigation in the Campaspe River Basin , 1991 .

[5]  P. Sarma,et al.  Regional Ground Water Modelling Using Finite Element Method - A Case Study , 1996 .

[6]  N. H. Rao,et al.  Field test of a simple soil-water balance model for irrigated areas , 1987 .

[7]  V. Tsihrintzis,et al.  Use of Geographic Information Systems (GIS) in water resources: A review , 1996 .

[8]  Stephen J. Walsh,et al.  GIS implications for hydrologic modeling: Simulation of nonpoint pollution generated as a consequence of watershed development scenarios , 1992 .

[9]  L. A. Swain,et al.  Predicted water-level and water-quality effects of artificial recharge in the Upper Coachella Valley, California, using a finite-element digital model , 1978 .

[10]  G. Gee,et al.  Estimating recharge rates for a groundwater model using a GIS , 1996 .

[11]  T. Narasimhan,et al.  Overview of the Finite Element Method in Groundwater Hydrology , 1982 .

[12]  Joe T. Ritchie,et al.  Model for predicting evaporation from a row crop with incomplete cover , 1972 .

[13]  G. Marsily,et al.  Estimating recharge from ephemeral streams in arid regions: A case study at Kairouan, Tunisia , 1978 .

[14]  N. H. Rao,et al.  Planning intraseasonal water requirements in irrigation projects , 1998 .

[15]  W. G. Gray,et al.  Finite elements in water resources. , 1982 .

[16]  Jasminko Karanjac,et al.  Mathematical Model of Uluova Plain, Turkey A Training and Management Tool , 1977 .

[17]  Subhash Chander,et al.  Optimal multicrop allocation of seasonal and intraseasonal irrigation water , 1990 .

[18]  S. P. Neuman,et al.  Estimation of aquifer parameters under transient and steady-state conditions: 2 , 1986 .

[19]  Subhash Chander,et al.  Irrigation scheduling under a limited water supply , 1988 .

[20]  Chester C. Kisiel,et al.  Worth of additional data to a digital computer model of a groundwater basin , 1974 .

[21]  M. Rosegrant,et al.  Asian food production in the 1990s: Irrigation investment and management policy , 1993 .

[22]  C. C. Kisiel,et al.  Application of the Convolution Relation to Estimating Recharge from an Ephemeral Stream , 1970 .

[23]  Honesto Roaza,et al.  INTEGRATING GEOGRAPHIC INFORMATION SYSTEMS IN GROUND-WATER APPLICATIONS USING NUMERICAL MODELING TECHNIQUES , 1993 .

[24]  John R. Williams,et al.  EPIC-erosion/productivity impact calculator: 1. Model documentation. , 1990 .

[25]  N. H. Rao,et al.  Assessment of groundwater potential for conjunctive water use in a large irrigation project in India , 1989 .

[26]  L. Duckstein,et al.  An event‐based model of recharge from an ephemeral stream , 1980 .

[27]  S. P. Neuman,et al.  Estimation of Aquifer Parameters Under Transient and Steady State Conditions: 1. Maximum Likelihood Method Incorporating Prior Information , 1986 .

[28]  M. N. Bhutta,et al.  GROUNDWATER RECHARGE IN IRRIGATED AGRICULTURE: THE THEORY AND PRACTICE OF INVERSE MODELLING , 1996 .

[29]  Andrew N. Sharpley,et al.  EPIC, Erosion/Productivity Impact Calculator , 1990 .