عنوان مقاله [English]
Background and objective: Iran with the average of annual precipitation about 230 mm is one of the countries in the world which is located in the semi-arid and arid regions. Improper spatial and temporal distribution of rainfall regarding to the time of required water for agriculture is another problem for agricultural sector. Using crop growth simulation models is a strategy which can be used to assess water balance, to simulate the growth process and to study different managerial scenarios.
In this regard, the combination of crop growth simulation models with geographic information system (GIS) and optimization models is also necessary. Calibration of crop parameters is one of the limiting factors of the use of crop growth simulation models. Results of previous researches have shown that the use of simulation models out of range, often leading to disappointing results. Some of these parameters are crop (variety) specific, so to use of these models, they must first be calibrated according to the local varieties. In the past decades several models have been developed for agricultural land use planning in different scales. The aim of the present study was to determine the cropping area of major agricultural crops based on the combined results of the Crop growth simulation model and is linear programming in the Mahidasht plain, Kermanshah province. In this study, WOFOST model is used to simulate crop growth and GAMS software is used for linear programming.
Material and methods: Field experiments was carried out in the cropping year 2010-2011 for calibration and validation of crop parameters of WOFOST model for major crops (wheat, barley and maize) under deficit irrigation managements. Experiments were implemented as randomized complete block design with three irrigation regimes (Full irrigation, 20 and 40 percent deficit irrigation) and four replications. Agricultural lands in the plain were classified into 440 equal units according to soil characteristics and administrative divisions. Maximization of farmers' income was considered as the objective function in the linear programming model. The constraints of monthly water, seasonal water, labor, land and agricultural machinery were considered at the study area. Considering the available water in the study area the best cropping pattern in 8 studied scenarios of water supply and irrigation system were determined using developed model.
Results: The value of most sensitive parameters of WOFOST model for major crops in the Mahidasht plain was determined by model calibration. Yield and water requirement of mentioned crops in the potential and water-limited situations were estimated in the region regarding to long-term average climatic parameters. Analysis of the scenarios showed that the scenario 6 (doubled water price and sprinkler irrigation system) with the total farmers' income of 140 billion IRR has the highest income among studied scenarios. The area under cultivation in this scenario would be 75,262 hectares which shows increasing compared to the base scenario.
Conclusion: The combination of crop growth simulation models and linear programming can be used for determination of the appropriate cropping patterns under different conditions of water resources.
The maximum farmers' income in this study would be occurred in the scenario 6 which water price will be doubled and irrigation system is sprinkler.