| description abstract | The success of irrigation system operation and planning depends on the quantification of supply and demand and equitable distribution of supply to meet the demand if possible, or to minimize the gap between the supply and demand. Most of the irrigation literature mainly focuses on the demand and distribution aspects only. In addition, irrigation projects that receive water from a reservoir can be challenging to manage as annual fluctuations in runoff from the reservoir’s catchment can have considerable impact on the irrigation management strategy. This study focuses on the development of an integrated reservoir-based canal irrigation model (IRCIM) that includes catchment hydrologic modeling, reservoir water balance, command hydrologic modeling, and a rotational canal irrigation management system. The front end of the IRCIM is developed in Visual Basic 6.0, whereas the back-end coding is done in C language. The graphical user interface is the most important feature of the model, as it provides a better interaction between the model and its user. The IRCIM has a modular structure that consists of three modules, viz., catchment module, reservoir module, and crop water demand module. The catchment module predicts daily runoff from the catchment that inflows to the reservoir. Depending on the data availability, this module is provided with the flexibility of choosing between the Soil Conservation Service’s curve number method combined with the Muskingum routing technique, and an artificial neural network technique using the Levenberg–Marquardt algorithm. The reservoir module is based on conservation of mass approach, and results in daily reservoir storage. The crop water demand module is comprised of water-balance models for both paddy and field crops. The irrigation management system serves as the program flow controller for the model and runs the required module when needed. For postseason evaluation of the irrigation system, performance indicators such as adequacy, efficiency, equity, and dependability are used. In a companion paper, the model is applied for Kangsabati Irrigation Project, West Bengal, India. | |
