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|Title:||Flood Hazard Mapping and Risk Assessment for Chindwin River Basin, Myanmar |
Flood Hazard Mapping and Risk Assessment for Chindwin River Basin, Myanmar
|Authors:||Chit myo Lwin|
CHIT MYO LWIN
Burapha University. Faculty of Geoinformatics
|Keywords:||Flood GIS Hydrologic model Hydraulic model Google Earth Engine Flood inundation Flood risk Flood exposure Flood vulnerability Flood hazard|
|Abstract:||Myanmar is a country exposed to natural disasters such as floods, cyclones, earthquakes, forest fires, landslides, etc. Among them, the flood is one of the natural disasters and mainly occurred in the Ayeyarwaddy River basin and my study area, Chindwin River is the biggest tributary of it. Such a flood disaster is threatening to the exposures and vulnerabilities in the Chindwin River Basin, and this study aims to prevent and manage the flood risk for disaster management
In this study, the GIS-based modelling of the flood inundation maps was developed using the hydrologic model (HEC-HMS) and hydraulic model (HEC-RAS) for two flood events. Also, it estimated the different return periods (2, 5, 10, 50 & 100 years) floods in the river basin. Moreover, the flood extent and depth of the flood were validated with the flood map calculated from the remotely sensed techniques in the google earth engine (GEE) and the flood river bed, respectively. To prevent and manage the flood disaster, the flood risk assessment in the village tract level is carried out by exploring the factors of the flood hazard, flood exposures, and flood vulnerability.
Firstly, in the development of the hydrologic model, the land use/land cover map, soil layer, etc. were prepared in GIS platform as a pre-processing step. Moreover, the automatic delineation of stream network, watershed boundary and the terrain analysis was carried out using the 12.5 m spatial resolution of the Digital Elevation Model (ALOS/PALSAR) in the HEC-GeoHMS which is an extension of GIS program. All of the processing datasets were exported into HEC-HMS for the further hydrologic model by mainly using the precipitation and water discharge. The selected flood events (2015 and 2017) were utilized to estimate the rainfall-runoff simulation using the hydrologic model with calibrated and validated approaches. The model performance of the coefficient of correlation (R), the coefficient of determination (R2 ), and the Nash-Sutcliffe model efficiency (EFF) have resulted in a range of 0.93 – 0.98, 0.8649 – 0.9532, and 0.804 -0.944 respectively. According to the results, the relationships of the 2015 and 2017 storm events indicated an appropriate and closed relationship between the computed and observed flows.
Moreover, in the development of the hydrodynamic model, the Triangulated Irregular Network (TIN) was generated with the 30 m contour intervals computed from the Digital Elevation Model (DEM) in the GIS environment. Besides, the geometric data such as cross-section, flow path, streamline and bank lines were generated in the HEC-Geo-RAS, which is a plug-in of the GIS software and then exported into HEC-RAS for the hydraulic modelling. The cross-sectionsare very important and which can be validated with the field observation data in the editing option. The required Manning number “n” values were calculated for each cross-section of both sides of the river. The hydraulic model was used to perform the unsteady-flow simulations of the predicted flood hydrographs. The observed water level data were used for the calibration and validation of the HEC-RAS model performance. Validation of the results for the 2015 and 2017 flood events was compared with the flood maps derived from the Sentinel 1 radar satellite data in google earth engine (GEE). In the comparison of the flood inundation area of the simulated result and the flood area from remote sensing, the overlapping area is 71.5% and 72.1% for 2015 and 2017 flood events respectively. And it is a closed validated checking for the flood area. The total flood inundation area of the 2015 flood event is about 4133.9 km2, with a 13.8-meter maximum depth of the flood and extended into low land terrain and flood plain areas especially, in the Homalin, Kalay, and Monywa townships due to the low land topography. The flow conditions of 2, 5, 10, 20, 50, and 100 year return periods were also produced in the hydrologic model, and the flood extent and the surface water level are gradually increasing in the river basin.
Finally, to manage and prepare the risk in the study area, the flood risk assessment was analyzed by accounting the three main factors, namely, flood hazard map, which was the 50 year return period developed by hydrologic and hydraulic models. The conceptual equation of this risk assessment is FR = FH x FE x FV. The flood exposure was included the layers of the population, crop, schools, hospital and road network, and flood vulnerabilities calculated from the parameters of age composition (< 14 and > 65 years old), literacy, and urban area. According to the result, 23.64 % of village tracts in the total 1341 village tracts will be affected. Flood risk area was described as the low, medium, high, and very high magnitude with 11.3%, 3.9%, 5.1%, and 3.3% in the village tract level, respectively. The higher flood risk area has mainly occurred in Homalin, where are the junction of upstream Chindwin river and U Yu tributary, Kalay low terrain at Kalay tributary, and downstream area, Monywa township. |
|Description:||Master Degree of Science (M.Sc.)|
|Appears in Collections:||Faculty of Geoinformatics|
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