Development of web-based hydrograph analysis tool considering seasonality and flow condition

Citations

WEB OF SCIENCE

6
Citations

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4

초록

Baseflow was proven to be the most unpredictable component of streamflow through various research. However, the recent method for estimating baseflow is due to the development of theoretical and computational techniques. This paper attempted to develop a fully automated baseflow separation system based on a recursive digital filter with an optimization algorithm for the single separation. Most of the previous baseflow separation methods use a single set of a parameter and BFImax (the maximum value of baseflow index), which can underestimate or overestimate the baseflow; however, the system developed in this study estimates multiple optimized a parameters using seasonality and flow conditions and uses them for BFImax calculation and baseflow separation. This system derived baseflow results in better understanding of watershed and streamflow tendency characteristics. This study developed a Web-based Hydrograph Analysis Tool 2020 with a user-friendly interface and new separation method regarding the seasonality and flow conditions with a fully automated python module to optimize a parameters and BFImax. The application to the two area show diverse parameter sets and different baseflow according to seasonality and flow conditions representing the flow characteristics. This study could be a fundamental tool for detailed watershed management decisions regarding water security in the dry season or environmental water for aquatic ecosystems.

키워드

baseflowbaseflow separationdigital recursive filterweb based hydrograph analysis toola parameteroptimizationAUTOMATED TECHNIQUESBASEFLOWRECHARGE
제목
Development of web-based hydrograph analysis tool considering seasonality and flow condition
저자
Yang, DongseokLee, SeoroKim, JonggunKim, SeongjoonEngel, BernardLim, Kyoungjae
DOI
10.1111/1752-1688.13178
발행일
2024-04
유형
Article
저널명
Journal of the American Water Resources Association
60
2
페이지
707 ~ 724