Scholarlink

<p>Riverine floods are severe natural disasters that cause massive socioeconomic and human losses, especially in densely populated regions of India. Accurate and trustworthy hydrological data are required to effectively mitigate these recurring catastrophes and for water resource management. The aim of this study is to identify the most suitable distribution model for the Gomati River, a tributary of the Ganga River system, based on the Lucknow-based gauging station. The annual peak discharge data from 1969 to 2011 were obtained from the Central Water Commission. The Mann-Kendall test shows a decrease in the magnitude of annual peak flood for the gauging station. In this analysis, the Log-Pearson type III, Gumbel Max, Lognormal, and Normal probability distribution models are used to estimate flood magnitudes for 2, 5, 10, 25, 50, 100, and 200-year return periods. Based on the Goodness-of-Fit tests, the Nash-Sutcliffe efficiency test and the root mean square error-observations standard deviation Ratio test, the Log-Pearson type III was found to be the best fit model. Estimated flood magnitudes for 2-, 5-, 10-, 25-, 50-, 100-, and 200-year return periods are 433.7, 805.6, 1147.9, 1715.1, 2253.3, 2907.0 and 3699.1&#xa0;m³/s, respectively. These values are useful for designing safe hydraulic structures- such as dams and major bridges with a 100-year return period, and culverts or infrastructure with a 50-year return period- as well as for planning embankments, mapping flood hazard zones, and preserving riverine ecosystems in Lucknow.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Flood frequency analysis of Gomati River at Lucknow, Ganga Alluvial Plain, India

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月5日

查看全文
  • Shashwat Verma,
  • Sonu Kumar,
  • Priyanka Singh,
  • Satyendra Singh,
  • Ratan Kar,
  • Munendra Singh

摘要

Riverine floods are severe natural disasters that cause massive socioeconomic and human losses, especially in densely populated regions of India. Accurate and trustworthy hydrological data are required to effectively mitigate these recurring catastrophes and for water resource management. The aim of this study is to identify the most suitable distribution model for the Gomati River, a tributary of the Ganga River system, based on the Lucknow-based gauging station. The annual peak discharge data from 1969 to 2011 were obtained from the Central Water Commission. The Mann-Kendall test shows a decrease in the magnitude of annual peak flood for the gauging station. In this analysis, the Log-Pearson type III, Gumbel Max, Lognormal, and Normal probability distribution models are used to estimate flood magnitudes for 2, 5, 10, 25, 50, 100, and 200-year return periods. Based on the Goodness-of-Fit tests, the Nash-Sutcliffe efficiency test and the root mean square error-observations standard deviation Ratio test, the Log-Pearson type III was found to be the best fit model. Estimated flood magnitudes for 2-, 5-, 10-, 25-, 50-, 100-, and 200-year return periods are 433.7, 805.6, 1147.9, 1715.1, 2253.3, 2907.0 and 3699.1 m³/s, respectively. These values are useful for designing safe hydraulic structures- such as dams and major bridges with a 100-year return period, and culverts or infrastructure with a 50-year return period- as well as for planning embankments, mapping flood hazard zones, and preserving riverine ecosystems in Lucknow.