Evaluation of simulation effect and uncertainty analysis of SWAT model driven by CMADS and traditional meteorological station data in the Lancang River Basin, China

Jiantao Lu; Guibing Hou; Baohua Wang; Yongqi Liu; Hui Qin

doi:10.1117/12.2684936

24 October 2023 Evaluation of simulation effect and uncertainty analysis of SWAT model driven by CMADS and traditional meteorological station data in the Lancang River Basin, China

Jiantao Lu, Guibing Hou, Baohua Wang, Yongqi Liu, Hui Qin

Author Affiliations +

Proceedings Volume 12804, Second International Conference on Sustainable Technology and Management (ICSTM 2023); 128040E (2023) https://doi.org/10.1117/12.2684936
Event: 2nd International Conference on Sustainable Technology and Management (ICSTM2023), 2023, Dongguan, China

Abstract

In recent years, the China Meteorological Assimilation Driving Datasets (CMADS) have been widely used to drive various hydrological models due to their accuracy and effectiveness. In order to explore the effect of the Soil and Water Assessment Tool (SWAT) model driven by CMADS and Traditional Meteorological Stations Data (TMSD) in the runoff simulation of the southwest river where meteorological data is insufficient, the SWAT model of Lancang River Basin is driven by the datasets mentioned above, and the model is calibrated with the measured monthly runoff data from the hydrological station. At the same time, the accuracy and effectiveness of the CMADS-driven SWAT model are evaluated, and the Sequential Uncertainty Fitting (SUFI2) is used to analyze the parameter uncertainty of the model. The results show that the models supported by CMADS and TMSD perform well in the rate periodic and verification period, the NSE coefficient and other evaluation indexes of the SWAT model driven by CMADS are obviously superior to the model driven by TMSD at each hydrological station. It indicates that for the whole Lancang River Basin with a large area, SWAT model driven by CMADS can have better simulation effect and simulation accuracy is higher than that of TMSD. It also shows that CMADS can reduce the uncertainty of results caused by the uncertainty of meteorological input data and parameters effectively in SWAT model.

Citation Download Citation

Jiantao Lu, Guibing Hou, Baohua Wang, Yongqi Liu, and Hui Qin "Evaluation of simulation effect and uncertainty analysis of SWAT model driven by CMADS and traditional meteorological station data in the Lancang River Basin, China", Proc. SPIE 12804, Second International Conference on Sustainable Technology and Management (ICSTM 2023), 128040E (24 October 2023); https://doi.org/10.1117/12.2684936

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KEYWORDS

Data modeling

Atmospheric modeling

Meteorology

Calibration

Uncertainty analysis

Databases

Computer simulations

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