Examining the Relationship between Rainfall, Runoff, and Turbidity during the Rainy Season in Western Japan

Mohamad Basel Al Sawaf, K. Kawanisi, M. Bahreinimotlagh
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Abstract

Given the changing climate, understanding the recent variability in large-scale rainfall patterns is a crucial task in order to better understand the underlying hydrological processes that occur within a watershed. This study aims to investigate how rainfall events in western Japan have changed due to climate change and how these changes have affected runoff–turbidity dynamics during the rainy season. To address the research objectives, we analyzed two decades of precipitation records in the Gōno River watershed and examined the associated runoff–turbidity dynamics during floods using turbidity–discharge (T-Q) loops, quantified using an enhanced hysteresis index. Our findings revealed a kind of intense rainfall event occurring every 3 to 4 years. Additionally, spatial pentad analysis showed varying intensities of accumulated precipitation, indicating that extreme rainfall is not confined to a specific spatial zone. Regarding turbidity–discharge behavior, we found that clockwise hysteresis patterns were caused by sediment sources from near-channel areas, while anticlockwise patterns were caused by soil erosion from nearby areas. Another notable finding was that turbidity peaks during floods may represent the earlier (or later) arrival of turbid water from distant upstream sources due to intense precipitation. One of the key challenges in quantifying hysteresis patterns is that there is no agreed-upon definition for how to determine the start and end of a flood event. This can lead to bias in the quantification of these patterns.
研究西日本雨季降雨、径流和浊度之间的关系
鉴于气候不断变化,为了更好地了解流域内发生的基本水文过程,了解近期大尺度降雨模式的变化是一项至关重要的任务。本研究旨在调查气候变化如何改变了日本西部的降雨事件,以及这些变化如何影响了雨季的径流-湍流动态。为实现研究目标,我们分析了岗野川流域二十年的降水记录,并利用浊度-排量(T-Q)环分析了洪水期间相关的径流-湍流动态,使用增强滞后指数进行量化。我们的研究结果表明,每 3 到 4 年就会发生一次强降雨。此外,空间五边形分析表明累积降水的强度各不相同,这表明极端降雨并不局限于特定的空间区域。在浊度-排水行为方面,我们发现顺时针方向的滞后模式是由河道附近地区的泥沙源造成的,而逆时针方向的滞后模式则是由附近地区的水土流失造成的。另一个值得注意的发现是,洪水期间的浊度峰值可能是由于强降水导致上游远处的浊水提前(或推迟)到达。对滞后模式进行量化的主要挑战之一是,对于如何确定洪水事件的起点和终点,目前还没有统一的定义。这可能导致这些模式的量化出现偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.60
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