Prediction of spatial and temporal variability of soil moisture in marghab watershed using swat

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

The integrated maps of soil moisture having high spatial resolution and appropriate quality are of great importance in land management. Due to the lack of monitoring stations in watersheds, especially in mountainous areas, field monitoring of soil moisture is a time-consuming, costly and error-prone process. SWAT model was used to obtain a suitable method for spatial and temporal simulation of soil moisture in the Marghab watershed of Khuzestan province with an area of 690 km2. The daily meteorological data of Barangard and Izeh synoptic stations, soil and land use maps, and digital elevation model were used as inputs to the model. The SUFI-2 program was used for calibration, sensitivity and uncertainty analysis, and validation of the model using the runoff data of Jologir-Marghab hydrometric station. The model was run from 2003 to 2019 for calibration and from 1995 to 2002 for validation, with a three-year warm-up from 1992-1994. Nash-Sutcliffe efficiency (NSE) and determination coefficient (R2) were used to determine the goodness of fit of the model, and P-Factor and R-Factor indices were used to determine the degree of uncertainty. Based on the simulated and observed monthly runoff hydrographs as well as the statistical criteria, the SWAT performance in simulating monthly runoff was acceptable both in the calibration and validation periods. The NSE, R2, P-Factor, and R-Factor were 0.76, 0.73, 0.68, and 0.62, respectively in the calibration period, and 0.73-0.71-0.60 and 0.65, respectively in the validation period. After model calibration and validation, soil moisture maps were obtained for the 1995-2019 period. The results indicated that SWAT model is a promising tool for simulating soil moisture in the catchment area with appropriate spatial (sub-basin scale and hydrological response units) and temporal (monthly and annual scale) distributions.

Language:
Persian
Published:
Iranian Journal of Soil and Water Research, Volume:53 Issue: 10, 2023
Pages:
2365 to 2382
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