A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations.
A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations.
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DOI：
10.1002/2014wr016532
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发表时间：
2015-07
影响因子：
5.4
通讯作者：
Smith PJ
中科院分区：
文献类型：
--
作者：
Coxon G;Freer J;Westerberg IK;Wagener T;Woods R;Smith PJ
对河川流量资料的品质进行基准化，并了解其水文分析的资讯内容，是水文科学的重要任务。有各种各样的技术来评估排放的不确定性。然而，很少有研究已经开发出通用的方法来量化排放的不确定性。这项研究提出了一个通用的框架，估计流量的不确定性在许多计量站与不同的误差在水位流量关系。该方法在一个新的框架内利用非参数LOWESS回归，该框架考虑了阶段放电测量的不确定性，阶段放电数据和多段额定曲线的分散性。该框架被应用到500个计量站在英格兰和威尔士，我们评估了流量不确定性的大小在低，平均和高流量点的额定曲线。该框架被证明是强大的，通用的，并能够捕捉特定地点的不确定性，为一些不同的例子。我们的研究揭示了广泛的流量不确定性（10-397%的流量不确定性区间宽度），但大多数测量站（超过80%）的平均和高流量不确定性区间小于40%。我们确定了水位-流量关系的一些区域差异，但结果表明，当地条件在确定计量站流量不确定性的大小方面占主导地位。这突出了在水文分析中使用这些数据之前估计每个测量站的流量不确定性的重要性。提出了一个用于流量不确定性估计的通用框架，允许估计许多集水区的特定地点流量不确定性，当地条件在确定流量不确定性大小方面占主导地位
Benchmarking the quality of river discharge data and understanding its information content for hydrological analyses is an important task for hydrologic science. There is a wide variety of techniques to assess discharge uncertainty. However, few studies have developed generalized approaches to quantify discharge uncertainty. This study presents a generalized framework for estimating discharge uncertainty at many gauging stations with different errors in the stage‐discharge relationship. The methodology utilizes a nonparametric LOWESS regression within a novel framework that accounts for uncertainty in the stage‐discharge measurements, scatter in the stage‐discharge data and multisection rating curves. The framework was applied to 500 gauging stations in England and Wales and we evaluated the magnitude of discharge uncertainty at low, mean and high flow points on the rating curve. The framework was shown to be robust, versatile and able to capture place‐specific uncertainties for a number of different examples. Our study revealed a wide range of discharge uncertainties (10–397% discharge uncertainty interval widths), but the majority of the gauging stations (over 80%) had mean and high flow uncertainty intervals of less than 40%. We identified some regional differences in the stage‐discharge relationships, however the results show that local conditions dominated in determining the magnitude of discharge uncertainty at a gauging station. This highlights the importance of estimating discharge uncertainty for each gauging station prior to using those data in hydrological analyses. A generalized framework for discharge uncertainty estimation is presented Allows estimation of place‐specific discharge uncertainties for many catchments Local conditions dominate in determining discharge uncertainty magnitudes