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- W4386820132 abstract "AbstractIn recent years, the incidence of noticeably heavy rainfall events and associated flash floods have encouraged us to investigate long-term trends in extreme rainfall and flash flood vulnerability mapping. Thus, in this study, a hybrid model was designed by integrating Weight of Evidence and Naïve Bayes to identify areas prone to flash floods for Uttarakhand and its ability compared with AdaBoost. Furthermore, the significance of long-term rainfall trends was evaluated using Mann–Kendall, Modified Mann-Kendall, and Innovative Trend Analysis, and extreme rainfall events were also examined for 51 years (1970-2020). The result showed that the WOE-NB and AdaBoost had the acceptable goodness-of-fit (AUC = 0.969 & AUC = 0.973, respectively). Moreover, ITA can identify some important patterns based on on-trend results that other tests cannot. The return period revealed that about 97.54% of the flash floods were caused by normal rainfall, with 2.45% being caused by severely abnormal rainfall.Keywords: flash flood susceptibility mappingbivariate statistical modelmultivariate statistical modelrainfall trendextreme rainfallDisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also." @default.
- W4386820132 created "2023-09-19" @default.
- W4386820132 creator A5014929507 @default.
- W4386820132 creator A5021829777 @default.
- W4386820132 date "2023-09-18" @default.
- W4386820132 modified "2023-09-26" @default.
- W4386820132 title "Flash-flood susceptibility modelling in data-scarce region using a novel hybrid approach and trend analysis of precipitation" @default.
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- W4386820132 doi "https://doi.org/10.1080/02626667.2023.2259887" @default.
- W4386820132 hasPublicationYear "2023" @default.
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