Publication

IMPORTANCE OF RAINFALL MEASUREMENTS FOR THE FLOOD FORECASTING OF THE MEKONG RIVER BASIN


Publication Date : 2007-01-01
Author : Hapuarachchi, H. A. P.TAKEUCHI, K.FUKAMI, K.INOMATA, H.ZHOU, M.
Countries :
Disaster Management Theme :
Disaster Type : Flood
Document Type : Research Paper
Languange : en
Link : https://www.researchgate.net/profile/Prasantha_Hapuarachchi/publication/242074594_IMPORTANCE_OF_RAINFALL_MEASUREMENTS_FOR_THE_FLOOD_FORECASTING_OF_THE_MEKONG_RIVER_BASIN/links/02e7e53586be1954d9000000.pdf

Abstact :

This paper presents the results of an application of a grid based distributed hydrological model, BTOPMC (Block-wise use of TOPMODEL with Muskingum-Cunge method) to the Mekong River basin. The BTOPMC model was particularly developed for modelling large river basins based on the extended TOPMODEL concepts. The model has been tested in various regions of the world and proven to be robust for hydrological modelling and flood forecasting. Most of the model parameters are physically based; hence the number of parameters to be calibrated is few. Therefore the model is also suitable for modelling and analyzing the long term effects on the hydrology of large river basins due to human impacts and climatic variations. The model employs latest publicly available GIS/RS data as input and it is possible to obtain the output results at any location of the basin which is very important for integrated water resources management. In this study most of the input data to the model such as elevation data, land cover, soil map and texture, NDVI (normalized difference vegetation index), radiation, could cover, sunshine duration, diurnal temperature range, mean temperature, vapour pressure, wind speed etc. are obtained from publicly available data sets. The model results are verified and the performance is evaluated using observed data at different locations. Model results are compared with gauged precipitation data and satellite based precipitation (3B42 V6) data as input. The model capability for forecasting flood events at different locations is checked and found to be acceptable. However it was observed that the lack of gauged precipitation data in Cambodia, Laos and Vietnam tends to hinder the model performance. Nevertheless the model performance can be improved significantly with proper precipitation input. The overall results justify the physical soundness of the model; hence the BTOPMC model can be successfully applied for hydrologic modelling and river flow forecasting of the Mekong River basin.