Optimal Allocation of Land and Water Resources in a Canal Command Area in the Deterministic and Stochastic Regimes

Abstract

Water logging is a universal problem of irrigated agriculture and it is a serious threat to the sustainability of irrigated agriculture in many arid and semiarid regions. Limbasi branch canal command area of Mahi Right Bank Canal (MRBC) project, Gujarat, India is also found to be affected by water logging conditions. Present study deals with the formulation of the Deterministic Linear Programming (DLP) and Chance Constrained Linear Programming (CCLP) models which maximizes net return from a canal command area while simultaneously mitigating water logging conditions. The developed models are applied to the Limbasi branch canal command area. The objective function is to maximize net annual return and decision variables are the seasonal cropping pattern and seasonal water supply. Analysis shows that under optimal conditions in the DLP model, there was a 40% deviation of crop area from existing cropping pattern and Net Irrigation Requirement (NIR) of crops was satisfied by conjunctive use of 41% of canal water and 59% of groundwater (annually). There was 91.1% increase in ground water exploitation which consecutively moderated rising water table issues. Net annual return was found to increase by 46.6%. In the CCLP model, NIR of crops was considered as a stochastic variable and normal distribution was found as the best fit. The CCLP model was run from 2 to 40% risk levels and cropping pattern under 10% risk level was considered as optimal at which NIR was satisfied by conjunctive use of 53.8% of canal water and 46.2% of ground water (annually). There was 86% increase in ground water exploitation. The outcome of the study can be used to assist the water resources planners and managers in taking appropriate decisions to develop a sustainable management plan of land and water resources for an overall balance of the system.