Fahimeh Razi
Abstract
Long meteorological drought can lead to the onset of hydrological drought. In this research, the lag time between the two types of drought was investigated for determining the hydrologic drought onset after realizing the climatological drought. This is a matter to provide managers with enough time for ...
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Long meteorological drought can lead to the onset of hydrological drought. In this research, the lag time between the two types of drought was investigated for determining the hydrologic drought onset after realizing the climatological drought. This is a matter to provide managers with enough time for decision making before the occurrence of water shortage in the watershed. The SWAT water balance model was used to determine and predict the lag time between the two types of drought for Foomanat (Anzali wetland) watershed in Gilan province Due to the ability to simulate the long-term flow of representative rivers in the basin. The OAT method was employed for the sensitivity analysis of the water balance model. Among the parameters used in SWAT, three parameters including curve number, available water, and the evaporation compensation factor in the soil were recognized as the most effective parameters for the results of the model. Calibration and validation of SWAT were performed using SCH model. The calculated Nash-Sutcliff and correlation coefficient in estimating runoff as well as determining and predicting the lag time between the two types of drought by SWAT were acceptable. The Nash coefficient was obtained as 0.68 and 0.8 for calibration, and 0.65 and 0.79 for validation periods, respectively. Using the calibrated model, one can predict the water balance situation and the lag time between the onset of meteorological drought and the emerging hydrological drought in the watershed for any interested meteorological drought scenarios. Based on the results, the chance of having a one -month lag time, is more than 70 percent, while the chance of a 2-month lag time in the Foomanat watershed Anzali wetland) is more than 23 percent.
