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将连通性理论整合到流域模型中 第二部分:结构和功能连通性的应用和评估。

Integrating connectivity theory within watershed modelling part II: Application and evaluating structural and functional connectivity.

机构信息

Dept. of Civil Engineering, University of Kentucky, United States of America.

Dept. of Civil Engineering, University of Kentucky, United States of America.

出版信息

Sci Total Environ. 2020 Oct 20;740:140386. doi: 10.1016/j.scitotenv.2020.140386. Epub 2020 Jun 20.

Abstract

Integrating connectivity theory within watershed modelling is one solution to overcome spatial and temporal shortcomings of sediment transport prediction, and Part I and II of these companion papers advance this overall goal. In Part II of these companion papers, we investigate sediment flux via connectivity formula discretized over many catchments and then integrated via sediment routing; and we advance model evaluation technology by using hysteresis of sensor data. Model evaluation with hysteresis indices provides nearly a 100% increase in model statistics. Hysteresis loop evaluation shows a shift from near linear behavior at low to moderate events and then clock-wise loops for larger events indicating the importance of proximal sediment sources. Catchment-scale sediment flux varies as function of the probability of timing and extent of connectivity of an individual catchment. Watershed-scale sediment flux shows self-similarity for the main stem of the river channel as the 181 catchments are integrated moving down gradient. Sediment flux varies from event-to-event as a function of the most sensitive connected pathways, including ephemeral gullies and roadside ditches in this basin. These sensitive pathways contribute disproportionately large amounts to overall sediment yield regardless of the total rainfall depth. Prediction requires the connectivity formula, erosion formula and sediment routing formula; and the probability of connectivity alone was a poor predictor for sediment transport. The result highlights the importance of coupling connectivity simulations with sediment transport formula, and our method provides one such approach.

摘要

将连通性理论集成到流域模型中是克服泥沙输移预测时空局限性的一种解决方案,本系列论文的第一部分和第二部分都致力于实现这一总体目标。在本系列论文的第二部分中,我们通过将连通性公式离散化到多个流域并通过泥沙输移进行积分来研究泥沙通量;我们还通过使用传感器数据的滞后现象来推进模型评估技术。使用滞后指数进行模型评估可使模型统计数据增加近 100%。滞后环评估表明,在低到中等事件下,近线性行为发生转变,然后在较大事件下出现顺时针环,表明近端泥沙源的重要性。流域尺度的泥沙通量随单个流域连通时间和程度的概率而变化。在将 181 个流域向下游整合时,河道干流的流域尺度泥沙通量表现出自相似性。泥沙通量随事件而变化,这是由于最敏感的连通路径,包括该流域的短暂冲沟和路边沟渠。这些敏感路径对总泥沙产量的贡献不成比例地大,而与总降雨量无关。预测需要连通性公式、侵蚀公式和泥沙输移公式;而连通性的概率本身就是泥沙输移的一个较差预测因子。研究结果强调了将连通性模拟与泥沙输移公式相结合的重要性,而我们的方法提供了这样一种方法。

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