Determination of rainfed wheat agriculture potential through assimilation of remote sensing data with SWAT model case study: ZarrinehRoud Basin, Iran

Abstract

Considering the importance of rainfed agriculture in adaptation to nature and long-term sustainability in the human food supply and livelihood of farmers, the main purpose of this study is to investigate the potential of rainfed agriculture in the Zarrinehroud basin as this basin is one of the most important sub-basins of Lake Urmia. For this study, the remote sensing data of surface soil moisture and evapotranspiration were combined with the SWAT model using the Data Assimilation method, Ensemble Kalman Filter (EnKF). Calibration of runoff flow rate in the SWAT model showed the correlation coefficient ranging between 0.69 and 0.84 in the calibration period (2000–2009) and between 0.64 and 0.86 for the validation period (2010–2014). The assimilation of the remote sensing data with the calibrated SWAT model showed that the model simulations for both the variables of surface soil moisture and actual evapotranspiration improved by at least 25% in both 2010 and 2014. It has been determined that 10.5 and 25.4% of the region's lands have a Very Appropriate and Appropriate potential for rainfed wheat agriculture, respectively. Areas with Moderate and Inappropriate potential occupy 64.1% of the lands in the region. HIGHLIGHTS The efficiency of the SWAT model in predicting the yield of rainfed wheat was evaluated in improvement with remote sensing data.; Assimilation of remote sensing data significantly improved the simulation results of the calibrated SWAT model.; The results of this study could be an efficient tool in order to cope with water scarcity in the region for agricultural and water resources decision makers.;

Keywords

• data assimilation
• enkf
• evapotranspiration
• soil moisture
• urmia lake