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One-day offset in daily hydrologic modeling: An exploration of the issue in automatic model calibration

机译:每日水文建模中的一日偏移:自动模型校准中的问题探索

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Hydrologic modeling literature illustrates that daily simulation models are incapable of accurately representing hydrograph timing due to relationships between precipitation and watershed hydrologic response that happen with a sub-daily time step in the real world. For watersheds with a time of concentration less than 24 h and a late day precipitation event, the observed hydrographic response frequently occurs one day after the precipitation peak while the model simulates a same day event. The analysis of sub-daily precipitation and runoff in this study suggests that, this one-day offset is inevitable in daily analysis of the precipitation-runoff relationship when the same 24-h time interval, e.g. the calendar day, is used to prepare daily precipitation and runoff datasets. Under these conditions, daily simulation models will fail to emulate this one-day offset issue (1dOI) and result in significant daily residuals between simulated and measured hydrographs. Results of this study show that the automatic calibration of such daily models will be misled by model performance metrics that are based on the aggregation of daily residuals to a solution that systematically underestimate the peak flow rates while trying to emulate the one-day lags. In this study, a novel algorithm called Shifting Hydrograph In order to Fix Timing (SHIFT) is developed to reduce the impact of this one-day offset issue (1dOI) on the parameter estimation of daily simulation models. Results show that with SHIFT the aforementioned automatic calibration finds a solution that accurately estimates the magnitude of daily peak flow rates and the shape of the rising and falling limbs of the daily hydrograph. Moreover, it is shown that this daily calibrated model performs quite well with an alternative daily precipitation dataset that has a minimal number of 1dOIs, concluding that SHIFT can minimize the impact of 1dOI on parameter estimation of daily simulation models. (C) 2016 Elsevier B.V. All rights reserved.
机译:水文模拟文献表明,由于降水和流域水文响应之间的关系是在现实世界中每天发生的次日时间步长而产生的,因此日常模拟模型无法准确表示水文图形的时间。对于浓度小于24小时的集水区,并有一个较晚的降水事件,观测到的水文响应经常发生在降水高峰后的一天,而该模型模拟的是同一天的事件。本研究对次日降水量和径流量的分析表明,在相同的24小时时间间隔(例如30分钟)内,每天的降水量与径流量关系的每日分析不可避免会出现这一天的偏移量。日历日用于准备每日降水和径流数据集。在这种情况下,每日模拟模型将无法模拟这一天的偏移量问题(1dOI),并导致模拟水文图和测量水文图之间存在大量的每日残差。这项研究的结果表明,此类日常模型的自动校准将被模型性能指标所误导,该模型性能指标基于每日残差的总和,在试图模拟一天的滞后时,系统地低估了峰值流速。在这项研究中,开发了一种新颖的算法,称为“为了确定时间而移动水位图”(SHIFT),以减少此一日偏移量问题(1dOI)对每日模拟模型的参数估计的影响。结果表明,使用SHIFT,上述自动校准可找到一种解决方案,该解决方案可准确估算每日峰值流量的大小以及每日水位图的上升和下降分支的形状。此外,结果表明,该每日校准模型在具有最少1dOI数量的替代日降水量数据集上的效果非常好,这表明SHIFT可以将1dOI对每日模拟模型参数估计的影响降至最低。 (C)2016 Elsevier B.V.保留所有权利。

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