Uncertainty Analysis of Regional Rainfall Frequency Estimates in Northeast India
Auteur(s): |
Nilotpal Debbarma
Parthasarathi Choudhury Parthajit Roy Shivam Agarwal |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Civil Engineering Journal, 1 novembre 2021, n. 11, v. 7 |
Page(s): | 1817-1835 |
DOI: | 10.28991/cej-2021-03091762 |
Abstrait: |
Estimation of rainfall quantile is an important step in regional frequency analysis for planning and design of any water resources project. Related evaluations of accuracy and uncertainty help to further assist in enhancing the reliability of design estimates. In this study, therefore, we investigate the accuracy and uncertainty of regional frequency analysis of extreme rainfall computed from genetic algorithm-based clustering. Uncertainty assessment is explored with prediction of quantiles with a new spatial Information Transfer Index (ITI) and Monte Carlo simulation framework. And, accuracy assessment is done with the comparison of regional growth curves to at-site analysis for each homogenous region. Further, uncertainty assessment with the ITI method is compared with Maximum Likelihood estimation (MLE) optimized by a genetic algorithm (GA) to check the suitability of the method. Results obtained suggest the ITI-based uncertainty assessment for regional estimates outperformed those of at-site estimates. The MLE-GA method based on at-site estimates was found to be better than at-site estimates based on L-moments, suggesting the former as a better alternative to compare with regional frequency estimates. Moreover, minimal bias and least deviation of the regional growth curve were obtained in the rainfall regions. The confidence intervals of regional estimates were seen to be well within the bounds of normality assumptions. |
Copyright: | © 2021 Nilotpal Debbarma, Parthasarathi Choudhury, Parthajit Roy, Shivam Agarwal |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10641226 - Publié(e) le:
29.11.2021 - Modifié(e) le:
02.12.2021