Estimating minimum streamflow from measurements at ungauged sites in regions with streamflow-gauging networks

被引:5
|
作者
Konrad, Christopher [1 ]
Rumsey, Christine [2 ]
机构
[1] US Geol Survey, Washington Water Sci Ctr, 934 Broadway, Tacoma, WA 98402 USA
[2] US Geol Survey, Utah Water Sci Ctr, West Valley City, UT USA
基金
美国海洋和大气管理局;
关键词
low flow; streamflow; ungauged basins; LOW-FLOW REGIONALIZATION; BASEFLOW RECESSION; RIVER; WATER; UNCERTAINTY; MODEL; BASIN; RECHARGE; IMPACT;
D O I
10.1002/hyp.13452
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Estimation of low flows in rivers continues to be a vexing problem despite advances in statistical and process-based hydrological models. We develop a method to estimate minimum streamflow at seasonal to annual timescales from measured streamflow based on regional similarity in the deviations of daily streamflow from minimum streamflow for a period of interest. The method is applied to 1,019 gauged sites in the Western United States for June to December 2015. The gauges were clustered into six regions with distinct timing and magnitude of low flows. A gamma distribution was fit each day to the deviations in specific discharge (daily streamflow divided by drainage area) from minimum specific discharge for gauges in each region. The Kolmogorov-Smirnov test identified days when the gamma distribution was adequate to represent the distribution of deviations in a region. The performance of the gamma distribution was evaluated at gauges by comparing daily estimates of minimum streamflow with estimates from area-based regression relations for minimum streamflow. Each region had at least 8 days during the period when streamflow measurements would provide better estimates than the regional regression equation, but the number of such days varied by region depending on aridity and homogeneity of streamflow within the region. Synoptic streamflow measurements at ungauged sites have value for estimating minimum streamflow and improving the spatial resolution of hydrological model in regions with streamflow-gauging networks.
引用
收藏
页码:2057 / 2067
页数:11
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