Spatial analysis of flash flood and Drought impact from Climate Change in Phongsaly District, Phogsaly Province, by using Geo-Informatics Technology and Modelling

Journal
Global Sustainability Research
Publication Date
DOI
10.56556/gssr.v2i3.515
Language
EN
License
Copyright (c) 2023 Global Sustainability Research

Keywords

  • drought
  • flood
  • flash flood
  • model
  • climate change
  • IPCC

Abstract

A method for predicting the water resource in the region in the future to be used as a basis for mitigating the consequences is to study how climate change affects hydrology. The purpose of this study is to i). choose a global climate model that is suitable for the area, ii). rainfall run-off modelling, iii). drought and flood hazard index map. The SSP-126, SSP-245, and SSP-585 scenarios were chosen as the most appropriate global climate model among the four institutes, with efficiency criteria using the coefficient of Nash-Sutcliffe and Kling-Gupta and then calibrate the data with the Bias Correction Linear Scaling method which divides the analysis period into 2 periods for Near-Future and Far-Future from analyzing Rainfall Run-off Modeling from Rainfall Concentration 1-hours, 3-hours and 6-hours. It was found that the SSP-585 scenario in the Rainfall Concentration 1-hours model has the most dangerous area for very high risk until the end of the 21st century. For the analysis of drought indices SPI_1, SPI_3 and SPI_6 in Near-Future, it was found that the frequency of droughts is increasing according to the worst scenario, the scenario with the most drought is SSP-585 and in the Far-Future, the frequency of drought is decreasing according to the worst scenario, the scenario with the most drought is SSP-126.

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Cite This Article

Boutsamaly, S., Sonemanivong, C., Kannitha, S., siharath, p., Vilaychaleun, S., Thammathevo, K., Oudomdeth, A., & Kittiphone, T. (2023). Spatial analysis of flash flood and Drought impact from Climate Change in Phongsaly District, Phogsaly Province, by using Geo-Informatics Technology and Modelling. Global Sustainability Research. https://doi.org/10.56556/gssr.v2i3.515