| نویسندگان | Mostafa Yaghoobzadeh,Davood Akbari,Farhad Azarmi-Atajan |
| نشریه | water harvesting research |
| شماره صفحات | 109-121 |
| شماره سریال | 6 |
| شماره مجلد | 1 |
| نوع مقاله | Full Paper |
| تاریخ انتشار | 2023 |
| نوع نشریه | الکترونیکی |
| کشور محل چاپ | ایران |
| نمایه نشریه | isc |
چکیده مقاله
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.
لینک ثابت مقاله