Evaluation of SMDI Drought Index Changes Using Data and Scenarios of Climate Change Model

Abstract

Drought begins with a lack of rainfall and depending on its duration and severity, Drought can affect parameters such as soil moisture, volume of surface and subsurface water, and human and ecosystem activities. For this purpose, in this research, by using the estimated soil moisture data by the SWAP model and the data of the fifth climate change report, agricultural drought was determined by using of the soil moisture deficit index for the future period (2020-2039) and then they compared with the base period (1992-2011). The results showed that the climatic parameters such as minimum temperature, maximum temperature and precipitation have increased in the future period compared to the base period. The RCP8.5 scenario has estimated the temperature is higher and the precipitation is lower compared to the RCP4.5 scenario. Moisture changes at a soil depth (30 cm) showed that the percentage of soil moisture increases slightly for each scenario in the future period (2020-2039) compared to the base period (1992-2011). The presence of error values of R2=0.81, NS=0.79 and RMSE=0.02 showed that there is a high correlation between the measured and observed results of soil moisture obtained from calibration and validation of the SWAP model. The results show that calculated SMDI drought index values in the future period (2020-2039) for RCP4.5 scenario has higher than the RCP8.5 scenario, and the predicted SMDI value for the future period is higher than the base period. The results of SMDI drought index uncertainty under RCP4.5 and RCP8.5 scenarios showed that CanEsm2 model has the most certainty and IPSL models have the least certainty compared to other models. The results of this research determined that drought can be estimated in the future by using the vegetation model.