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Consistency assessment of rating curve data in various locations using Bidirectional Reach (BReach)

机译:使用双向范围(漏洞)各个位置中评级曲线数据的一致性评估

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When estimating discharges through rating curves, temporal data consistency is a critical issue. In this research, consistency in stage-discharge data is investigated using a methodology called Bidirectional Reach (BReach), which departs from a (in operational hydrology) commonly used definition of consistency. A period is considered to be consistent if no consecutive and systematic deviations from a current situation occur that exceed observational uncertainty. Therefore, the capability of a rating curve model to describe a subset of the (chronologically sorted) data is assessed in each observation by indicating the outermost data points for which the rating curve model behaves satisfactorily. These points are called the maximum left or right reach, depending on the direction of the investigation. This temporal reach should not be confused with a spatial reach (indicating a part of a river). Changes in these reaches throughout the data series indicate possible changes in data consistency and if not resolved could introduce additional errors and biases. In this research, various measurement stations in the UK, New Zealand and Belgium are selected based on their significant historical ratings information and their specific characteristics related to data consistency. For each country, regional information is maximally used to estimate observational uncertainty. Based on this uncertainty, a BReach analysis is performed and, subsequently, results are validated against available knowledge about the history and behavior of the site. For all investigated cases, the methodology provides results that appear to be consistent with this knowledge of historical changes and thus facilitates a reliable assessment of (in) consistent periods in stage-discharge measurements. This assessment is not only useful for the analysis and determination of discharge time series, but also to enhance applications based on these data (e.g., by informing hydrological and hydraulic model evaluation design about consistent time periods to analyze).
机译:通过评级曲线估计放电时,时间数据一致性是一个关键问题。在该研究中,使用称为双向覆盖范围(漏洞)的方法研究了阶段 - 放电数据的一致性,该方法从A(在操作水文中)常用的一致性定义。如果没有与当前情况的连续和系统的偏差发生超过的观察性不确定性,则视为一致。因此,通过指示额定曲线模型表现令人满意的最外面的数据点,评估曲线模型的额定曲线模型的能力在每次观察中进行评估。这些点被称为最大左或右到达,这取决于调查的方向。这个时间达不应该与空间范围混淆(表明河流的一部分)。在整个数据序列中,这些到达的变化表示数据一致性的可能变化,如果没有解决可能会引入额外的错误和偏差。在本研究中,基于其重要的历史评级信息和与数据一致性相关的特定特征来选择英国,新西兰和比利时的各种测量站。对于每个国家,区域信息最大限度地用于估计观察性不确定性。基于这种不确定性,进行违规分析,随后,验证了结果的可用知识,了解了网站的历史和行为。对于所有调查的病例,该方法提供了似乎与历史变化的知识一致的结果,从而促进了对阶段放电测量中一致期间的可靠评估。该评估不仅可用于分析和确定放电时间序列,还可以基于这些数据来增强应用程序(例如,通过通知水文和液压模型评估设计对分析的一致时间段)。

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