4.3 Article

Evaluation of hydrological response to extreme climate variability using SWAT model: application to the Fuhe basin of Poyang Lake watershed, China

期刊

HYDROLOGY RESEARCH
卷 48, 期 6, 页码 1730-1744

出版社

IWA PUBLISHING
DOI: 10.2166/nh.2016.115

关键词

extreme climate; Fuhe basin; hydrological response; parameter calibration; Poyang Lake; SWAT model

资金

  1. National Natural Science Foundation of China [41331174]
  2. Natural Science Foundation of Hubei Province of China [2015CFB331]
  3. Special Fund by Surveying & Mapping and Geoinformation Research in the Public Interest [201512026]
  4. Collaborative Innovation Center for Major Ecological Security Issues of Jiangxi Province and Monitoring Implementation [JXS-EW-08]
  5. LIESMARS Special Research Funding

向作者/读者索取更多资源

Differences between simulated and observed data often occur when the watershed model is applied under extreme climate. It is necessary to assess the stability of hydrological models in a wide range of climate variation. A case study was conducted in Fuhe basin of Poyang Lake, China using the Soil and Water Assessment Tool (SWAT) model, which was calibrated under different climates in average years, dry and wet years, high and low temperature years, respectively. The model was first calibrated with dataset in average years, and the validation in the whole period showed results agreed well with the observed stream flow. The well-parameterized model calibrated under extreme climate was used to simulate hydrological responses in different climate years. All simulations generated results closely matching observed data with R-2 and ENS greater than 0.88, although the model was likely to slightly overestimate stream flow in average and dry years, and underestimate in wet years and high temperature years. In addition, each simulation was independent to other simulations with different parameters calibrated in different climate periods tested by Student's T-test. Therefore, the model has the potential probability to accommodate a large range of climate variation to predict hydrological responses to climate change.

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