عنوان مقاله [English]
Arid and semi-arid regions always face the challenges of food security, ecosystem sustainability and, consequently, increased water productivity. Crop water productivity can be used as a suitable indicator to identify areas prone to cultivate a particular crop in these areas. In return, identifying and selecting suitable cultivation areas will help increase productivity. Selecting suitable areas for cultivation is not enough to achieve high crop water productivity. Using appropriate management scenarios to achieve this goal is essential. Deficit irrigation is one of the management strategies to increase water productivity. Investigating the effect of various management scenarios on water productivity in the field studies will be time-consuming and costly. The computer models could be used as tools to simulate the effects of management scenarios on crop yield and water productivity. So far, various crop growth simulation models have been developed and used to investigate the impacts of management scenarios on crop water productivity. In large-scale decision and policy-making, the growing conditions of crops in different farms are not the same. Most of crop growth simulation models are designed for point and field scales, and for large-scale use, the use of auxiliary tools such as GIS is essential. Agricultural activities are the most important means of livelihood for a large number of people in Kermanshah province. According to the Jihad Agricultural Organization, this province is a leading province in terms of the area under cultivation of crops. Soybean is a raw material for the production of many food products and an important source of vegetable oils and proteins which could be a good choice for the farmers of this province.
This study was performed to investigate temporal and spatial variations of soybean water productivity, under different irrigation scenarios, in Gavshan irrigation and drainage network –Razavar river- Kermanshah and Kordestan provinces, as an important indicator to identify areas suitable for the cultivation of this crop. For this purpose, a GIS-based software (for presentation and analyzing spatial data), was used along with a tool called Reference Weather from the Crop Growth Monitoring System (for weather data interpolation) and AquaCrop software plug-in version (for simulating scenarios). The study area was divided into 37 regular grids of 5 by 5 km. Based on the available soil reports, 24 homogeneous soil units were identified in the study area. Then to simulate a model, 94 homogeneous units were delineated by overlaying of grid weathers and soil units. For each grid of weather, daily reference crop evapotranspiration was calculated using the Penman-Monteith equation based on daily weather data (1988-2015). The files required to run the AquaCrop model were prepared based on the available information for each homogeneous unit. Then, soybean growth was simulated under 3 irrigation scenarios (60, 80 and 100% potential irrigation requirement) for all homogeneous units, and for 28 years (1988-2015), using a calibrated model. For these simulations, 7896 projects were prepared and implemented with the AquaCrop plug-in version.
The results showed that grain yield, seasonal evapotranspiration and consequently soybean water productivity are affected by irrigation scenarios. The mean grain yield, seasonal evapotranspiration, and water productivity under 60% irrigation scenario decreased to 56.64, 30.76, and 37.78% relative to the full irrigation scenario, respectively. The results also indicated that these parameters had temporal and spatial variations. These changes increased with increasing water stress intensity (except for temporal changes in seasonal evapotranspiration) in irrigation scenarios. The reason for temporal changes in the studied parameters can be due to annual changes in weather parameters (temperature, precipitation, sundial, etc.). But, spatial changes are due to the simultaneous effect of spatial changes in climatic and soil conditions (water holding capacity, topography, hydraulic conductivity, etc.) and their interactions on each other. With increasing water stress intensity, the annual fluctuations of seasonal evapotranspiration decreased. The reason for this is the dependence of seasonal evapotranspiration on the growth period and air temperature, which does the opposite. In general, the average water productivity of soybean in Mian-Darband plain was higher than in Bile-var plain. According to simulated water productivity, B1 and B4 irrigation zones in the Bile-var plain, and D4 and D9 irrigation zones in Mian-Darband plain were more suitable to soybean cultivation from the point of view of water productivity, which is the key factor in arid and semi-arid climate of Iran.