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Comparison of SWAT and DLBRM for Hydrological Modeling of a Mountainous Watershed in Arid Northwest China
A distributed physically based model, soil and water assessment tool (SWAT), and a distributed conceptual model, distributed large basin runoff model (DLBRM), were selected to compare their applicability and performance in simulating daily runoff in the Heihe River watershed, the second-largest inland river (terminal lake) with a peak elevation of 5,584 m above sea level (asl) in arid northwest China. Both models have been calibrated against the observed daily runoff at the watershed outlet (Yingluoxia Hydrological Station) for the period of 1995–2004 and validated for the period of 2005–2009. Results show that both SWAT and DLBRM produced reasonable results in this study, and DLBRM performed better than SWAT. The difference in performance is mainly due to data constraints, different interpolation schemes, and spatial representations of landscape variations in the models. The tank storage-output principle used in DLBRM seems more suitable than the Soil Conservation Service curve number (SCS-CN) method used in SWAT to simulate daily flow in an arid area. Both models performed worse in simulating low flows mostly occurring in spring and winter, because of a lack of detailed representation of the impacts of snow-melting processes and frozen soils. The authors’ analysis indicates that consideration of the impacts of snow melting and frozen soils on the hydrological process is key to improving performance of hydrological models in mountainous areas. Because of their simpler operations, lower data requirements, fewer input parameters, and better performances, distributed conceptual models such as DLBRM seem more suitable for hydrological modeling in data-deficient, high elevation, and topographically complex mountainous watersheds in arid regions.
Comparison of SWAT and DLBRM for Hydrological Modeling of a Mountainous Watershed in Arid Northwest China
A distributed physically based model, soil and water assessment tool (SWAT), and a distributed conceptual model, distributed large basin runoff model (DLBRM), were selected to compare their applicability and performance in simulating daily runoff in the Heihe River watershed, the second-largest inland river (terminal lake) with a peak elevation of 5,584 m above sea level (asl) in arid northwest China. Both models have been calibrated against the observed daily runoff at the watershed outlet (Yingluoxia Hydrological Station) for the period of 1995–2004 and validated for the period of 2005–2009. Results show that both SWAT and DLBRM produced reasonable results in this study, and DLBRM performed better than SWAT. The difference in performance is mainly due to data constraints, different interpolation schemes, and spatial representations of landscape variations in the models. The tank storage-output principle used in DLBRM seems more suitable than the Soil Conservation Service curve number (SCS-CN) method used in SWAT to simulate daily flow in an arid area. Both models performed worse in simulating low flows mostly occurring in spring and winter, because of a lack of detailed representation of the impacts of snow-melting processes and frozen soils. The authors’ analysis indicates that consideration of the impacts of snow melting and frozen soils on the hydrological process is key to improving performance of hydrological models in mountainous areas. Because of their simpler operations, lower data requirements, fewer input parameters, and better performances, distributed conceptual models such as DLBRM seem more suitable for hydrological modeling in data-deficient, high elevation, and topographically complex mountainous watersheds in arid regions.
Comparison of SWAT and DLBRM for Hydrological Modeling of a Mountainous Watershed in Arid Northwest China
Zhang, Lanhui (author) / Jin, Xin (author) / He, Chansheng (author) / Zhang, Baoqing (author) / Zhang, Xifeng (author) / Li, Jinlin (author) / Zhao, Chen (author) / Tian, Jie (author) / DeMarchi, Carlo (author)
2016-02-17
Article (Journal)
Electronic Resource
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