Optimal water resources allocation and crop planning for Mandla district of Madhya Pradesh

Abstract

In India, it is essential to improve the net profit by optimized agriculture. The continuous decline on water resources indicates to adopt the sustainable utilization of resources in tribal area of Mandla district, Madhya Pradesh. To arrive at the optimal crop planning, linear programming (LP) optimization techniques were used to formulate an efficient cropping pattern for maximizing net profit for the Mandla district of Madhya Pradesh. The allocation of water to the agriculture is heavily influenced by cropped area that guarantees food requirement, therefore, land constraint is required. The optimized results shows that the area of major crops like rice, wheat, gram, vegetables, mustard and soybean crop increases against the reduction in area of crops like maize, black gram, moong, and arhar. Existing cropping intensity of the district is 110%. The net income is expected to increase by ` 5.92 Cr, when compared to existing income. In Mandla district, it is observed that, Nainpur blocks has highest net seasonal return for both the season followed by Bichhiya block. To achieve the maximum profit per unit of land, cropping intensity should be more than 180% for the district, therefore an extensive measures were taken to fix out the water demand supply gap for agriculture. In this analysis a user-friendly Linear programing software, TORA 2.0 was used for optimal allocation of water and land resources under multi-crop condition for Mandla district. The net annual profit is increased by 5.1% under optimal allocation conditions, which is also reflected into cropping intensity i.e. 195%. The sensitivity analysis of model parameter shows that the better price of crop is the most sensitive parameter followed by the crop area. The optimized model can be applied as a reliable decision tool for adopting the farm and regional level decisions of optimal land and water resources allocation. The outcome of the study can assist the policy-makers in taking decisions to develop a sustainable plan of land and water resources for the available area.