Hydrological Modelling of canal command using Remote Sensing and GIS
P. K. Gupta, T. Das, N. S. Raghuwanshi, R. Singh
Agricultural and Food Engg. Department,
Indian Institute of Technology, Kharagpur,
West Bengal, 721302, India
S. Dutta, S. Panigrahy
Space Applications Centre, Ahmedabad,
Gujrat - India
Introduction
The major irrigation projects in India and South Asia are reported to perform at a low overall efficiency of 30-35% (Sanmugnathan and Bolton, 1988). Total irrigated area in the country presently accounts for 92 M ha, with canal irrigation projects accounting for about 17.4 M ha of irrigated area (Ministry of Water Resources, 1997). Ensuring reliable canal releases and balancing them with the demands for water has proved difficult, with the results that crops do not receive the right quantities of water at the proper time. In the Damodar Valley Corporation (DVC) command, there is significant amount of canal water wastage due to untimely release, lack of regulatory measure at the outlet and free flooding.
Distributed Hydrological Models (DHM), (Rogers et al., 1985), provide a means of studying the interrelationships of upstream and downstream hydrological regime and of managing water and land resources. MIKE SHE (Refsgaard and Storm, 1995), is a comprehensive, distributed, and physically based modelling system capable of simulating all major hydrological processes in the land phase of hydrological cycle. A major problem in the hydrology is the inadequate field measured data to describe the hydrologic processes. Remote Sensing (RS) has been identified as a tool to produce information in spatial and temporal domain, instead of point measurement, in digital form, with high resolution. Further, RS techniques are extremely relevant as a means of estimating a number of key variables specifically in situation where DHM are required. Remote sensing techniques can produce high spatial coverage of important terms in water balance for large area, but at the cost of a rather sparse temporal resolution. Hydrological model can produce all the terms of water balance at a high temporal, but low spatial resolution (Droogers and Bastiaanssen, 2002). The use of RS data, in combination with DHM, provides new possibilities for deriving spatially distributed time series of input variables, as well as new means for calibration and validation of the hydrological model (Bastiaanssen et al., 2000, Fortin et al., 2001). The use of RS technology involves large amount of spatial data management and requires an efficient system to handle such data. Hence, Geographic Information System makes it possible to store, analyze, retrieve and manipulate data for large and complex problems.
The uniqueness of the research is perceived in the fact that work focuses on large scale hydrological modelling, where the RS data is considered to be essential for an improved understanding of the functioning of large command areas. In the present study, MIKE SHE is applied to the 6 main canal command of the DVC irrigation project for simulating the hydrological water balance taking into account remote sensing data and canal release data. The research focuses on the feasibility of integrating RS data with DHM and its subsequent impact on studies related to the hydrological regime of the command areas. The advantages of integrating RS data with DHM are depicted and discussed.
Model Description
The MIKE SHE is a comprehensive deterministic, distributed and physically based hydrologic modelling system, capable of describing the entire land phase of the hydrological cycle in a given command. The model area is discredited by two analogous horizontal-grid square networks for surface and ground water flow components. These are linked by vertical column of nodes at each grid representing the unsaturated zone. A finite difference solution of the partial differential equations, describing the processes of overland and channel flow (Saint-Venant equations), unsaturated flow (Richards' equation) and saturated flow (Boussinesq equation for confined aquifer), is used for water movement modelling. Interception process is modelled by Jensen model (Jensen, 1983) and actual evapotranspiration is calculated by Kristensen and Jensen model (Kristensen and Jensen, 1975).