Cropping pattern optimization for water resources allocation in Nekuabad irrigation network, Iran

During the last three decades in Iran, a high population growth rate had resulted in an increase in acreage and yield of summer crops with subsequent reduction in the fallow lands. Significant change occurred in the trend of cropping patterns towards crops with lesser water requirements from the limited water resources. Against this background a multi-criteria strategy is needed to improve the productivity of water and solve some major problems in the Nekuabad irrigation network located in the central part of Iran. The main aim of this study was to develop a multi-dimensional model that can optimize a cropping pattern not only to maximize the net benefit, agro-economic water productivity (net return to the volume of water used) and labor employment but also minimizing water consumption and total nitrate leaching.The ET0 calculator software which calculates ET0 using the long term weather data as input to the Penman-Monteith equation was used. Then, net crop water requirements were calculated with the AquaCrop model. The potential of the AquaCrop model in deficit irrigation practice for seven main crops in dry area of Nekuabad irrigation network were studied. A set of second-order, seasonal crop water production functions were developed using the multi-crop simulation model for each crop in the study area. Ultimately, allocations of cropped area and irrigation water were made at seasonal levels through non linear deterministic programming, considering economy, social and environmental aspects. In this way, four critical objective functions subjected to a number of constraints with the use of the general algebra modeling system program were proposed for optimal cropping pattern in dry, wet and normal climatic conditions. These functions were then applied to the predicted optimal cropping pattern and optimal allocated water. In the previous research using linear programming models, for each crop, fixed deficit irrigation ratio alternatives were imposed as input and the models compute optimal water and cropped area. In this study however, for each crop, crop water production functions ranging from 100 to 60% irrigation levels have been applied in the non linear programming model and the model computes the optimum irrigation volume ratio.The calibrated AquaCrop model performed well under full and water stress conditions to predict crop yields, biomass and canopy cover. The coefficient of determination of the regressed crop water production equation showed good correlation between applied water and yield for all the crops. After optimization of the cropping patterns, the highest agro-economic water productivity in the irrigation network was found for potato in the dry year, followed by potato, rice and silage maize. The highest magnitude of global agro-economic water productivity was for the dry season followed by normal season and wet season. The results show that an increase of 116.8 % in net income is attained according to the model for the entire Nekuabad network. A 19.8 % increase in labor employment in wet season was found as compared to the current situation. There was 11% decrease in nitrate leaching for dry season as compared to the current situation. The total optimal amount of applied irrigation water in the study area can be reduced by up to 16.3 % for dry periods. These results demonstrated considerable improvements for the entire Nekuabad compared to the current condition. Cropped area of rice with high water demand decreased as compared to current condition. In contrast, potato and silage maize areas with relatively low water requirement increased. This shows that the multi dimensional model developed in this study has successfully optimized the water allocation in the study area regarding economy, unemployment and pollution aspects