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Urban hydrologic trend analysis based on rainfall and runoff data analysis and conceptual model calibration

机译：基于降雨和径流数据分析及概念模型标定的城市水文趋势分析

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摘要

Urban stormwater is a major cause of urban flooding and natural water pollution. It is therefore important to assess any hydrologic trends in urban catchments for stormwater management and planning. This study addresses urban hydrological trend analysis by examining trends in variables that characterize hydrological processes. The original and modified Mann-Kendall methods are applied to trend detection in two French catchments, that is, Chassieu and La Lechere, based on approximately 1decade of data from local monitoring programs. In both catchments, no trend is found in the major hydrological process driver (i.e., rainfall variables), whereas increasing trends are detected in runoff flow rates. As a consequence, the runoff coefficients tend to increase during the study period, probably due to growing imperviousness with the local urbanization process. In addition, conceptual urban rainfall-runoff model parameters, which are identified via model calibration with an event based approach, are examined. Trend detection results indicate that there is no trend in the time of concentration in Chassieu, whereas a decreasing trend is present in La Lechere, which, however, needs to be validated with additional data. Sensitivity analysis indicates that the original Mann-Kendall method is not sensitive to a few noisy values in the data series.
机译：城市雨水是造成城市洪水和自然水污染的主要原因。因此，重要的是要评估城市流域的任何水文趋势，以进行雨水管理和规划。这项研究通过检查表征水文过程的变量趋势来解决城市水文趋势分析问题。最初的和改进的Mann-Kendall方法基于来自本地监测程序的大约1/10的数据，被应用于两个法国流域Chassieu和La Lechere的趋势检测。在两个流域中，主要水文过程的驱动因素（即降雨变量）均未发现趋势，而径流量中发现了趋势的增加。结果，径流系数在研究期间趋于增加，这可能是由于当地城市化进程的不渗透性增加所致。此外，还研究了概念性城市降雨径流模型参数，这些参数是通过基于事件的模型校准来确定的。趋势检测结果表明，在Chassieu中，集中时间没有趋势，而在La Lechere中，呈下降趋势，但是，这需要其他数据进行验证。敏感性分析表明，原始的Mann-Kendall方法对数据序列中的一些嘈杂值不敏感。

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