Abstract
Several whole-farm agro-economic optimization models have been developed to deal with lumped planning issues in the agriculture sector. However, these models cannot be used to devise appropriate management strategies at land parcel level, because of the differences between farm characteristics, and the increased complexity of the hydrological processes. Based on Spatial Farm Database (SFD) which is consisted of a number of farm-level spatial data, including location, paddock properties, owner specifications and budgets, it is possible to provide the farm manager with some suggestions regarding the optimal choice of crops and the area to be allocated for each one. To this end, genetic algorithm is used in order to cope with model nonlinearity and a large number of decision variables. In order to test the proposed model, the Mobarakabad district is modeled with 126 agriculture fields, and the optimization model is run for this area. Results showed that the optimization procedure can find more realistic farm-level optimal solutions due to its advantage in adequate modeling of field characteristics, common groundwater resources, and the associated constraints. The results of lumped optimizations could also be used as benchmarks for the purposes of comparison and interpretation.
Highlights
Cropping pattern is one of the most important designs and performance parameters in irrigation management which is in direct relationship with water-use efficiency and optimal allocation of soil and water resources [1]
A number of approaches including benefit-cost, functional, programming, and simulation aim at improving the irrigation process by timely allocation of water to crops which are used in order to determine the best cropping pattern and the land area which should be allocated for cultivation of each crop [2]-[5]
The results of the present study showed that the suggested procedure can be effectively employed for proposing distributed cropping pattern decisions with respect to conjunctive utilization of surface and groundwater resources
Summary
Cropping pattern is one of the most important designs and performance parameters in irrigation management which is in direct relationship with water-use efficiency and optimal allocation of soil and water resources [1]. A number of approaches including benefit-cost, functional, programming, and simulation aim at improving the irrigation process by timely allocation of water to crops which are used in order to determine the best cropping pattern and the land area which should be allocated for cultivation of each crop [2]-[5]. The costs and benefits approach is widely used for cropping pattern optimization, where the available area of land should be divided between different crops with the aim of achieving maximum net benefits [8]
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