4.7 Article

Comparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time steps

期刊

HYDROLOGY AND EARTH SYSTEM SCIENCES
卷 24, 期 5, 页码 2711-2729

出版社

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/hess-24-2711-2020

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资金

  1. Mississippi River Geomorphology and Potamology (MRGP) Program [470711]
  2. U.S. Army Engineer Research and Development Center Military Engineering (Austere Entry)
  3. U.S. Army Engineer Research and Development Center Geospatial Research and Engineering (Climate Adaptive Mission Planning (CAMP))
  4. U.S. Army Engineer Research and Development Center Environmental Quality and Installations (Climate Adaptive Mission Planning (CAMP))

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Large-scale hydrologic forecasts should account for attenuation through lakes and reservoirs when flow regulation is present. Globally generalized methods for approximating outflow are required but must contend with operational complexity and a dearth of information on dam characteristics at global spatial scales. There is currently no consensus on the best approach for approximating reservoir release rates in large spatial scale hydrologic forecasting, particularly at diurnal time steps. This research compares two parsimonious reservoir routing methods at daily steps: Doll et al. (2003) and Hanasaki et al. (2006). These reservoir routing methods have been previously implemented in large-scale hydrologic modeling applications and have been typically evaluated seasonally. These routing methods are compared across 60 reservoirs operated by the U.S. Army Corps of Engineers. The authors vary empirical coefficients for both reservoir routing methods as part of a sensitivity analysis. The method proposed by Doll et al. (2003) outperformed that presented by Hanasaki et al. (2006) at a daily time step and improved model skill over most run-of-the-river conditions. The temporal resolution of the model influences model performances. The optimal model coefficients varied across the reservoirs in this study and model performance fluctuates between wet years and dry years, and for different configurations such as dams in series. Overall, the method proposed by Doll et al. (2003) could enhance large-scale hydrologic forecasting, but can be subject to instability under certain conditions.

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