AbstractsGeography &GIS

The use of geostationary satellite based rainfall estimation and rainfall-runoff modelling for regional flash flood assessment

by Dwi Prabowo Yuga Suseno




Institution: Hokkaido University
Department: 工学
Degree: 博士(工学)
Year: 2013
Record ID: 1236019
Full text PDF: http://hdl.handle.net/2115/53880


Abstract

The availability of rainfall triggered hazard information such as flash flood is crucial in the flood disaster management and mitigation. However, providing that information is mainly hampered by the shortage of data because of the sparse, uneven or absence the hydrological or meteorological observation. Remote sensing techniques that make frequent observations with continuous spatial coverage provide useful information for detecting the hydrometeorological phenomena such as rainfall and floods. This study aims to develop and evaluate geostationary satellite based rainfall estimation by considering cloud types and atmospheric environmental conditions. Furthermore, the satellite rainfall estimation is coupled with rainfall-runoff model for regional flash flood assessment. First, a simple rainfall estimation method using geostationary satellite i.e. Multifunctional Transport Satellite (MTSAT) blended with Tropical Rainfall Measuring Mission (TRMM) 2A12 is performed for Java Island, Indonesia and its surrounding area. The blending process is conducted by developing statistical relationship between cloud top temperature from MTSAT 10.8μm channel (TIR1) which is collocated with rainfall rate (RR) acquired by TRMM 2A12. Inter comparison with TRMM Multi Precipitation Analysis (TMPA) data product is conducted. Temporal validation result shows that TMPA demonstrated better statistical performance than TIR1 and RR statistical relationship model. However for the spatial correlation, TIR1 and RR statistical relationship model shows reasonably better performance than TMPA. Second, the rainfall estimation method basically uses an assumption the lower cloud top temperature is associated with heavier rainfall, particularly for convective cloud type. To fulfill such assumption, the statistical relationship is developed mainly for cumulonimbus (Cb) cloud type. A new two-dimensional threshold diagram (2D-THR) has been developed based on maximum likelihood cloud classification results, which can readily be applied for MTSAT split window datasets. The study area is Japan and its surrounding area. By integrating the cloud type classification especially by separating Cb cloud type from other cloud types can improve the TIR1 and RR statistical relationship, which is indicated by increasing correlation coefficient and the gradient of regression line. Therefore, underestimating rainfall intensity can be avoided by applying rainfall rate and cloud top temperature relationship that uses Cb cloud type only rather than using all cloud types. A good agreement between estimated and measured storm rainfall also has been demonstrated when use this approach. The geostationary satellite based rainfall estimation then applied for characterizing the storm severity. The Hosking-Wallis Regional Frequency Analysis (HW-RFA) method is used to define the frequency distribution of long-term hourly maximum rainfall over Hokkaido Island. HW-RFA indicates that Generalized Normal/Log Normal three parameters (GNO/LN3) is suitable to describe the frequency…