Performance Assessment of SWAT Model for Estimating Soil Moisture (Case Study: Nomal Watershed)

Document Type : review paper

Authors

• Fatemeh Valinejad ¹
• Khalil Ghorbani ²
• Mahdi Zakerinia ²
• Amirahmad Dehghani ³
• Behnam Ababaee ⁴

¹ MSc student of Irrigation and Drainage- Agriculture and Natural Resources Faculty of Gorgan University, Iran.

² Assistant Professor, Water Engineering Department, Gorgan University, Iran.

³ Associate Professor, Water Engineering Department, Gorgan University, Iran.

⁴ PhD of Irrigation and Drainage, Iran.

10.22067/jwsd.v1i1.34600

Abstract

Soil moisture is a key variable in understanding hydrological processes and energy fluxes in the ground. Therefore, accurate simulation of soil moisture is useful in irrigation planning and crop management, flood and drought prediction, water quality management, climate change and weather forecast. But despite the importance of this hydrological variable, field measurement method is not appropriate considering huge spatial-temporal changes in soil properties as well as its high cost. Accordingly, the use of physical models as an approach to solve the problem has been addressed by researchers. In this study SWAT conceptual model is used to stimulate soil moisture in a Nomal watershed. SUFI2 algorithm was used in SWAT-CUP software pack for calibrating SWAT model, the amount of soil moisture measurements, and analysis of model uncertainty in the watershed. Uncertainty analysis was done by calculating P-factor and R-factor. According to results, R-factor in most sub-watersheds was less than 1, while in the whole watershed it was 1/01. P-factor in sub-watersheds was between 50-99 percent and the whole watershed 90 percent. These values ​​indicated good calibration for moisture parameter in the watershed as well as large uncertainty predictions. bR2 index was 58 percent showing acceptable accuracy in watershed model calibration. Moreover, important information on soil moisture both in terms of spatial as well as temporal (daily scale) distribution (sub-watershed) was obtained with an estimated uncertainty band of predictions.

Keywords

• Moisture estimation
• SWAT model
• Nomal watershed
• Uncertainty analysis

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