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首页> 外文期刊>Journal of hydrologic engineering >Hydrologic Modeling of the Blue River Basin Using NEXRAD Precipitation Data with a Semidistributed and a Fully Distributed Model
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Hydrologic Modeling of the Blue River Basin Using NEXRAD Precipitation Data with a Semidistributed and a Fully Distributed Model

机译:使用NEXRAD降水数据的半分布式和全分布式模型对蓝河流域进行水文建模

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摘要

A semidistributed (DPHMRS) and a fully distributed (MISBA) physically based hydrologic models were applied to the Blue River Basin (BRB) of Oklahoma in a multiyear mode using next-generation radar (NEXRAD) precipitation data. DPHMRS generally over-simulated low flows of BRB during the validation stage partly because rainfall events based on radar precipitation data are likely too high. However, by adjusting the NEXRAD data based on Mesonet gauge measurements, the Nash-Sutcliffe efficiency (Ef) in the validation run is significantly improved from -0.16 to 0.46. The model performance of DPHMRS also depends on the subbasin resolution, and it was found that DPHMRS can optimally model BRB with seven subbasins. Goodness-of-fit statistics of streamflow simulated by both models demonstrate better performance of MISBA compared to DPHMRS in calibration (E_f improved from 0.53 to 0.82) and validation (E_f improved from 0.46 to 0.83) stages. This difference is partly due to spatially distributed information of soil, land use, and precipitation data for BRB that are partially averaged out in the subbasin framework of DPHMRS, while such information are better retained in the fully distributed framework of MISBA. It seems a fully distributed hydrologic model can more fully take advantage of the spatially distributed information of input data for BRB than a semidistributed model if such detailed data are available. However, this may not be necessarily true for river basins where either data are limited, or where river basins have fairly uniform land use and nonmountainous terrain characteristics.
机译:使用下一代雷达(NEXRAD)降水数据,在多年模式下将基于半分布式(DPHMRS)和完全分布式(MISBA)的物理水文模型应用于俄克拉荷马州的蓝河流域(BRB)。在验证阶段,DPHMRS通常会过度模拟BRB的低流量,部分原因是基于雷达降水数据的降雨事件可能太高。但是,通过基于Mesonet量规测量调整NEXRAD数据,验证运行中的Nash-Sutcliffe效率(Ef)从-0.16显着提高到0.46。 DPHMRS的模型性能还取决于子盆地的分辨率,并且发现DPHMRS可以最佳地建模具有七个子盆地的BRB。两种模型模拟的流量拟合优度统计数据表明,与DPHMRS相比,MISBA在校准(E_f从0.53改进到0.82)和验证(E_f从0.46改进到0.83)阶段具有更好的性能。这种差异部分是由于在BRHMRS的子盆地框架中对BRB的土壤,土地利用和降水数据的空间分布信息进行了部分平均,而在MISBA的完全分布式框架中则更好地保留了这些信息。如果有这样的详细数据,似乎完全分布式的水文模型可以比半分布式模型更充分地利用BRB输入数据的空间分布信息。但是,对于数据有限或流域土地使用相当统一且地形不山区的流域,不一定是正确的。

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  • 来源
    《Journal of hydrologic engineering 》 |2015年第10期| 04015015.1-04015015.9| 共9页
  • 作者

    Zahidul Islam; Thian Yew Gan;

  • 作者单位

    Water Policy Branch, Alberta Environment and Sustainable Resource Development, 7th Floor Oxbridge Place, 9820 106 St NW, Edmonton, AB, Canada T5K 2J6 Civil and Environmental Engineering, Univ. of Alberta, Edmonton, AB, Canada T6G 2W2;

    Dept. of Civil and Environmental Engineering, NREF 3-033, Univ. of Alberta, Edmonton, AB, Canada T6G 2W2;

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