Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on artificial multi-segmented rating curves at the confluence of two rivers

Environmental Research Communications Pub Date : 2024-02-08 DOI:10.1088/2515-7620/ad277c

Hansol Kang, Yeonsu Kim, Hyunuk An, J. Byun, Joonwo Noh

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Abstract

To mitigate flood damages led by recent climate changes, reliable flow discharge data are essential for successful open-channel management during the extreme floods. Generally, flow discharge is computed using the rating curve (RC) established from the relation of flowrate and water level stage. Determination of the parameters of the rating curves are subject to the uncertainties related with difficulties and limitation of the flow monitoring to cover the wide ranges of flow variation. Especially at the river confluences, the uncertainties pronounces when flood occurs due to several factors such as roughness change, backwaters, and levee overflow. The Seomjin River basin in Korea suffered from flood inundation occurred at the tributary confluence during the extreme flood in 2020. In identifying the reliable flow rate of the main stream and tributary, this study proposed an indirect flow assessment scheme using a 1D hydrodynamic simulation model to find the best-simulated water level in an iterative manner based on the Monte Carlo (MC) simulation. With a large number of discharge data generated from the random number combination, it is possible to find the best results automatically by specifying the reliability limitation considering the uncertainty of the pre-determined RC parameters associated with the roughness coefficient. Nash Sutcliff-efficiency (NSE) was incorporated to evaluate the reproduced water level to meet the threshold specified for NSE ≥ 0.75. The simulated flowrates computed from the revised RC and roughness coefficients revealed error ranges of 8% ~ 36.6% compared with the design flood. The approach proposed in this study is applicable to determine the valid parameters necessary to create a revised RC at the existing water level gauge station where the uncertainties of the RC are pronounced especially in the vicinity of the channel confluence

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利用蒙特卡罗模拟和基于两条河流汇合处人工多段等级曲线的一维水力模型估算河流排放量

为减轻近期气候变化导致的洪水损失，在特大洪水期间，可靠的流量排泄数据对成功进行明渠管理至关重要。一般情况下，根据流量和水位阶段的关系建立的额定流量曲线（RC）可以计算流量排泄量。额定曲线参数的确定具有不确定性，这与流量监测难以覆盖较大的流量变化范围有关。特别是在河流汇合处，由于粗糙度变化、回水和堤坝溢流等多种因素，在发生洪水时会出现不确定性。在 2020 年的特大洪水中，韩国宣津江流域的支流汇合处遭受了洪水淹没。为确定干流和支流的可靠流量，本研究提出了一种间接流量评估方案，利用一维水动力模拟模型，以蒙特卡罗（MC）模拟为基础，通过迭代方式找到最佳模拟水位。在随机数组合生成大量排水数据的情况下，考虑到与粗糙度系数相关的预定 RC 参数的不确定性，通过指定可靠性限制，可以自动找到最佳结果。Nash Sutcliff-efficiency（NSE）用于评估再现水位，以满足 NSE ≥ 0.75 的阈值要求。根据修订后的 RC 和粗糙度系数计算出的模拟流量显示，与设计洪水相比，误差范围为 8% ~ 36.6%。本研究提出的方法适用于确定必要的有效参数，以便在现有水位测量站建立修正的 RC，因为 RC 的不确定性非常明显，尤其是在河道汇合点附近。

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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Environmental Research Communications

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