Flood Risk Index (FRI) is the multi-criteria linked with the factors of vulnerability; exposure, susceptibility, and resilience. In order to establish local FRI, crucial local information have to be accumulated. However, under the limitation of land-use data, particular techniques were applied in this study. CA Markov model was used to analyze the past missing land-use data and, also forecast the future land-use of Pakpanang river basin under conditions of plan and without plan. The ratio changes of forest, agriculture, wetland and water, and urban areas were considered. Then, the result of LULC spatial-temporal changes was then applied to Hec-HMS and Hec-Ras , with Arc GIS extension of Hec-GeoHMS and Hec-GeoRas software, in order to evaluate the flood hydrographs and flood severity in three municipalities corresponding to 100-year return period rainfall. Afterward, the FRI of Pakpanang, Chianyai, and Hua-sai, which ranges from 0 to 1, were evaluated by using the modified FRI equations. It was found that sensitivity analysis in the area of forest on flood depth and inundation areas is incoherent. Nevertheless, without land-use planning, the changes in these three cities cause higher flood risk, where Chianyai is the riskiest as the FRIE is 0.58. Further consideration of FRIE and FRIP proportion that reveals the FRI deviation indicates that to reduce flood risk, Chianyai would need the most resources and highest effort comparison to Pakpanang and Hua-sai.
Time Series Analysis of Rainfall Variability at North Jordan: A Case Study at Yarmouk River Basin
