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A collaborated framework to improve hydrologic ecosystem services management with sparse data in a semi-arid basin
Author(s) -
Yifan Wu,
Yang Xu,
Guodong Yin,
Xuan Zhang,
Chong Li,
Liyu Wu,
Wang Xiao,
Qiuhong Hu,
Fanghua Hao
Publication year - 2021
Publication title -
hydrology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 48
eISSN - 2224-7955
pISSN - 1998-9563
DOI - 10.2166/nh.2021.146
Subject(s) - soil and water assessment tool , ecosystem services , surface runoff , environmental science , swat model , hydrological modelling , arid , valuation (finance) , hydrology (agriculture) , water resources , infiltration (hvac) , environmental resource management , computer science , water resource management , ecosystem , drainage basin , streamflow , business , ecology , geography , engineering , cartography , climatology , meteorology , geotechnical engineering , finance , biology , geology
Applying various models to assess hydrologic ecosystem services (HESs) management has the potential to encourage efficient water resources allocation. However, can a single model designed on these principles be practical to carry out hydrologic ecosystem services management for all purposes? We address this question by fully discussing the advantages of the variable infiltration capacity (VIC) model, the soil and water assessment tool (SWAT), and the integrated valuation of ecosystem services and tradeoffs (InVEST) model. The analysis is carried both qualitatively and quantitatively at the Yixunhe River basin, China, with a semi-arid climate. After integrating the advantages of each model, a collaborated framework and model selection method have been proposed and validated for optimizing the HESs management at the data sparse scenario. Our study also reveals that the VIC and SWAT model presents the better runoff reproducing ability of the hydrological cycle. Though the InVEST model has less accuracy in runoff simulation, the interannual change rate is similar to the other two models. Furthermore, the InVEST model (1.08 billion m3) has larger simulation result than the SWAT model (0.86 billion m3) for the water yield, while both models have close results for assessment of sediment losses.

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