Purpose Cambodia is considered one of the countries that are most vulnerable to adverse effects of climate change, particularly floods and droughts. Kampong Speu Province is a frequent site of calamitous flash floods. Reliable sources of flash flood information and analysis are critical in efforts to minimize the impact of flooding. Unfortunately, Cambodia does not yet have a comprehensive program for flash flood hazard mapping, with many places such as Kampong Speu Province having no such information resources available. The purpose of this paper is, therefore, to determine flash flood hazard levels across all of Kampong Speu Province using analytical hierarchy process (AHP) and geographical information system (GIS) with satellite information. Design/methodology/approach The integrated AHP–GIS analysis in this study encompasses ten parameters in the assessment of flash flood hazard levels across the province: rainfall, geology, soil, elevation, slope, stream order, flow direction, distance from drainage, drainage density and land use. The study uses a 10 × 10 pairwise matrix in AHP to compare the relative importance of each parameter and find each parameter’s weight. Finally, a flash flood hazard map is developed displaying all areas of Kampong Speu Province classified into five levels, with Level 5 being the most hazardous. Findings This study reveals that high and very high flash flood hazard levels are identified in the northwest part of Kampong Speu Province, particularly in Aoral, Phnum Srouch and Thpong districts and along Prek Thnot River and streams. Originality/value The flash flood hazard map developed here provides a wealth of information that can be invaluable for implementing effective disaster mitigation, improving disaster preparedness and optimizing land use.
Rainfall is one of the important parameters for evaluating flood hazard risk. Cambodia is a vulnerable country to extreme rainfall where the number of rain gauges over the country is limited. Therefore, the possibilities of applying rainfall products from satellite observation and rainfall forecasting models are crucial for the country. The purpose of this research is to evaluate the detecting accuracy of the rainfall-based Weather Research Forecasting (WRF) model and TRMM rainfall products by comparing with observed rainfall during heavy rainfall for different topography over Cambodia. The categorical statistic is used to calibrate the rainfall from the WRF model with observed rainfall from 23 stations over Cambodia on selected heavy rainfall dates of 15, 17, and 19 September 2019. Cambodia experienced floods along the Tonle Sap River and the Mekong Basin by the triggered heavy rainfall. The results show that the detecting accuracy of days 15, 17, and 19 from TRMM rainfall matched with observed rainfall are 55%, 71%, and 63%, respectively. The average detecting accuracy of mountainous is 65% whereas plains are 63.33%. The average detecting accuracy of coastal and Tonle Sap is 53.66% and 63%, respectively. Moreover, the detecting accuracy of days 15, 17, and 19 forecasts from the WRF model compared with observed rainfall are 41%, 69%, and 63%, respectively. The average detecting accuracy of mountainous, plains, coastal, and Tonle Sap are 52%, 55.66%, 52.33%, and 65.66%, individually. The forecast rainfall from the WRF model and TRMM could detect the rainfall. They are therefore should be used in the areas that lack rainfall stations in Cambodia.
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