Spatial calibration and uncertainty reduction of the SWAT model using multiple remotely sensed data

文献类型： 外文期刊

第一作者： Lee, Sangchul

作者： Lee, Sangchul;Lee, Sangchul;Kim, Dongho;McCarty, Gregory W.;Anderson, Martha;Gao, Feng;Lei, Fangni;Zhang, Xuesong;Crow, Wade;Moglen, Glenn E.;Yen, Haw;Qi, Junyu;Yeo, In -Young;Sun, Liang

作者机构：

关键词： Remotely sensed products; Additional constraints; Parameter uncertainty; Soil and water assessment tool (SWAT)

期刊名称：HELIYON （ 影响因子：4.0； 五年影响因子：4.1 ）

ISSN：

年卷期： 2024 年 10 卷 10 期

页码：

收录情况： SCI

摘要： Remotely sensed products are often used in watershed modeling as additional constraints to improve model predictions and reduce model uncertainty. Remotely sensed products also enabled the spatial evaluation of model simulations due to their spatial and temporal coverage. However, their usability is not extensively explored in various regions. This study evaluates the effectiveness of incorporating remotely sensed evapotranspiration (RS-ET) and leaf area index (RS-LAI) products to enhance watershed modeling predictions. The objectives include reducing parameter uncertainty at the watershed scale and refining the model's capability to predict the spatial distribution of ET and LAI at sub-watershed scale. Using the Soil and Water Assessment Tool (SWAT) model, a systematic calibration procedure was applied. Initially, solely streamflow data was employed as a constraint, gradually incorporating RS-ET and RS-LAI thereafter. The results showed that while 14 parameter sets exhibit satisfactory performance for streamflow and RS-ET, this number diminishes to six with the inclusion of RS-LAI as an additional constraint. Furthermore, among these six sets, only three effectively captured the spatial patterns of ET and LAI at the sub-watershed level. Our findings showed that leveraging multiple remotely sensed products has the potential to diminish parameter uncertainty and increase the credibility of intrawatershed process simulations. These results contributed to broadening the applicability of remotely sensed products in watershed modeling, enhancing their usefulness in this field.

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