Application of Remote Sensing and Hydrological Modelling in Flood Prediction Studies

Remote sensing techniques have been used in various applications including agriculture, forestry, oceanography and environmental studies. This study was carried out using remote sensing techniques and hydrological modeling for flood prediction in the Klang Valley. The remote sensing satellite data t...

Full description

Saved in:
Bibliographic Details
Main Authors: Seeni Mohd , Mohd Ibrahim, Mansor , Mohd Adli
Format: Article
Language:English
Published: 2000
Subjects:
Online Access:http://eprints.utm.my/id/eprint/2039/1/Application_of_RS_and_hydro.pdf
http://eprints.utm.my/id/eprint/2039/
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Remote sensing techniques have been used in various applications including agriculture, forestry, oceanography and environmental studies. This study was carried out using remote sensing techniques and hydrological modeling for flood prediction in the Klang Valley. The remote sensing satellite data that were used is the Landsat-5 Thematic Mapper (TM) data whilst the flood prediction is based on the U.S. Soil Conservation Service Technical Release 55 (SCS TR-55) model. This model involves the calculation of runoff from Curve Number (CN) that relate to landuse, soil type, hydrological conditions and soil moisture. In the determination of runoff, landuse information were derived from the Landsat-5 TM data and landuse maps. The runoff values were used in the calculation of concentration time, peak discharge and bankfull discharge. The peak discharge was calculated by the graphical method of SCS TR-55 model whilst the bankfull discharge was derived from the slope area method. Flood occurrence was determine by comparing the peak discharge values with bankfull discharge values. Flooding occurs if the peak discharge exceeds the bankfull discharge. In this study, watershed areas were generated and the area that would be flooded for specific amount of rainfall were determined using remote sensing techniques and the SCS TR-55 model. The results that were obtained are encouraging and indicate the potential of using remote sensing techniques with hydrological modeling for flood prediction.