Flood estimation using radar-based quantitative precipitation considering impact of urban growth / Salwa Ramly
Flooding problems also had been exacerbated by the increased growth and rapid development especially in the Klang Valley. The urban growth has resulted in the need of more commercial spaces and housing demands. Radar-based QPE offer high temporal and spatial distribution of rainfall data over the wa...
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| Format: | Thesis |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/82272/1/82272.pdf https://ir.uitm.edu.my/id/eprint/82272/ |
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| Summary: | Flooding problems also had been exacerbated by the increased growth and rapid development especially in the Klang Valley. The urban growth has resulted in the need of more commercial spaces and housing demands. Radar-based QPE offer high temporal and spatial distribution of rainfall data over the watershed. Therefore, with the advantage of weather radar data in spatial and temporal scales, flood estimation could be enhanced by integrating the radar-based QPE with the flood estimation model. The purpose of the study is to estimate flood using radar-based quantitative precipitation considering impact of urban growth. RAINRATE AUTO V2 was developed to extract radar-based QPE data for specific catchment areas. The system simplify the tedious works of raw weather radar data processing and QPE derivation. From the analysis, correlation of radar-rainfall data and gauge-rain data gives R2 value of 0.7738. It is thus concluded that the radar-rainfall data can be used for radar-based QPE. A flood estimation model is developed by integrating the use of GIS and HEC-HMS in a novel HEC-GeoHMS model for Upper Klang Ampang catchment. ArcGIS software was used to process the GIS data and develop the basin model and extract the hydrologic parameters of the river basin to be used in the rainfall-runoff model. Using the radar-based QPE as input the flood estimation for significant heavy rainfall event on 27th April 2015 was carried out. The rainfall-runoff model successful computed the flood estimation with Nash-Sutcliffe of 0.655 with peak discharge of 139.3m3/s. This computed peak discharge is relatively low compare to observed peak flow 210.4m3/s. However, the result is in line with others findings which acknowledged the lower value of peak discharge for radar-based QPE input rainfall data. An urban growth model is developed using SLEUTH model which uses historical satellite images data as input data for urban growth analysis. The model considers increased urbanization from year 2020 to 2050 but with decreasing growth rate. Integration of the rainfall-runoff model and urban growth model is proposed as a decision making tools to estimate and simulate future flood risks for design and development planning purposes. |
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