JOURNAL ARTICLE

Model calibration and uncertainty analysis for runoff in the Chao River Basin using sequential uncertainty fitting

Fenghua TangHuashan XuZhixing Xu

Year: 2012 Journal:   Procedia Environmental Sciences Vol: 13 Pages: 1760-1770   Publisher: Elsevier BV

Abstract

The Chao River is one of the most important surface water sources for drinking water in Beijing. Due to the impacts of human activities and climate change, the Chao River basin is facing water scarcity. Therefore, it is very important to effectively manage water resources, while the distributed watershed model is the useful and effective tool. Soil and Water Assessment Tool (SWAT) was selected to set up hydrological model in the Chao River basin. Model calibration and uncertainty analysis were performed with Sequential Uncertainty Fitting (SUFI-2), which is one of the programs integrated with SWAT in the package SWAT-CUP (SWAT Calibration and Uncertainty Programs). Results showed that the p-factor was 0.85 and the r-factor was 1.12 in calibration period (1995-1999) while the p-factor was 0.83 and the r-factor was 2.15 in validation period (2000-2002). When values of p-factor and r-factor are accepted, further goodness of fit can be quantified by the coefficient of determination (R2) and Nash–Sutcliffe coefficient (NS) between the observed and the final best simulated data. The results indicated that R2 was 0.90 and NS was 0.88 in calibration period, while R2 was 0.77 and NS was 0.74 in validation period. The results of calibration and uncertainty analysis were satisfactory.

Keywords:
SWAT model Environmental science Calibration Hydrology (agriculture) Watershed Surface runoff Drainage basin Soil and Water Assessment Tool Water resources Statistics Mathematics Geology Geography Streamflow Computer science Ecology

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36
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1.45
FWCI (Field Weighted Citation Impact)
22
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0.84
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Citation History

Topics

Hydrology and Watershed Management Studies
Physical Sciences →  Environmental Science →  Water Science and Technology
Hydrology and Drought Analysis
Physical Sciences →  Environmental Science →  Global and Planetary Change
Soil Moisture and Remote Sensing
Physical Sciences →  Environmental Science →  Environmental Engineering

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