Planning of agricultural inputs in Ur watershed to maximize net benefit under limited resources

Abstract

Two models (CROPWAT and LINGO) were used to optimize the resource allocation and achieving higher efficiency in agricultural productivity. Quantitative evaluation of hydro-meteorology parameters was carried out for crop water and irrigation requirement planning using CROPWAT model. Whereas, LINGO model applied to determine the optimum land and water resources allocation to major crops of kharif and rabi season in the Ur watershed using agriculture data such as net income per ha which was calculated based on various sub factures, viz. cost of fertilizers and pesticides, cost of seeds, yield of crops, daily wages of labour and machine charges, selling base price of commodities. Results revealed that the crop water requirement in kharif season was 593 cm and in rabi season 421 cm, whereas irrigation requirement was 71.16 cm and 294.7 cm respectively. Because, the crop grown during kharif season require less irrigation water. Therefore only supplemental irrigation requirement have to be planned for kharif crops. But in rabi season, more irrigation water is required to bring whole area under cultivation. That’s why the scenarios were considered based on available resources of watershed to fulfill the demand. Output of the CROPWAT model was used as input of the LINGO model for formulation of the linear programming equations under different scenario. There were three scenarios considered in each cropping seasons, viz. in kharif season (i) Existing scenario; (ii) Some need based crop scenario; (iii) Limitation with cash crop scenario; and in rabi season (i) Existing scenario with conventional method of wheat growing; (ii) Scenario under System of Wheat Intensification; (iii) Scenario under increasing 10% irrigation water. It was observed that the combination of both the models is appropriate for finding the optimal land and water resources allocation to the major crops in kharif and rabi season for maximizing net income of the watershed.