Abstract:
Agriculture sector in India accounts for nearly 80% of fresh water and 30% of energy consumption. In other developing countries also, available water and energy resources are already under considerable stress and there is general realization that traditionally low efficiency of systems can no longer be accepted and needs to be improved. Poor management of irrigation water use is one of the principal reasons for low water and energy use efficiency. Further, a range of environmental problems, such as waterlogging, leaching of agro-chemicals, soil salinization etc. are also linked to inefficient water use. Generally, there are multiple objectives of irrigation water management: maximize net return, minimize irrigation costs, maximize yield, optimally distribute a limited water supply, minimize groundwater pollution etc. After a cropping pattern is adopted in an irrigation command, irrigation requirements depend on the crop and soil characteristics, meteorological conditions, and rainfall. To best allocate the water resources with the available surface water resources (through irrigation canals) and groundwater development in the region, an irrigation manager is required to take decisions in real-time to meet the water demands in a command area. Thus, for a given cropping pattern, canal network and groundwater development, one of the objectives of irrigation water management could be optimization of energy requirement for pumping groundwater. A conceptual spatially distributed model has been developed for the optimization of energy requirement for the operation of an irrigation system. The model computes crop water demands in the command area in real-time and calculates the water demands at the canal system head after accounting for the system characteristics and seepage losses. Based on the availability of water at canal head, the model computes optimum configuration of the canal network operation during each week. This model can be used by the irrigation manager for real-time operation of a canal system. The model results have been tested for a crop season with the data of Lakhaoti branch canal command in UP State, India. The results demonstrate that considerable energy can be saved by rationally operating a canal system in real-time.
