Abstract
Remote sensing techniques have been used in various applications including agriculture, forestry, oceanography and environmental studies. This paper reports on a study that has been carried out using remote sensing techniques and hydrological modelling for flood prediction in the Klang Valley. The remote sensing satellite data that have been 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 Numbers (CN) that relate to land use, soil type, hydrological condition and soil moisture. In the determination of runoff, land use information are derived from the Landsat-5 TM data and land use 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 determined by comparing the peak discharge values with bankfull discharge values. Flooding occurs if the peak discharge exceeds the bankfull discharge. In the 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 modelling for flood prediction. (Keywords : Remote sensing, hydrological modelling, floods)

Introduction
Flood is a major problem especially for people who live in low lying areas. Floods can cause death and at the same time bring damage to properties such as houses, buildings, plantation, livestock, etc. Studies of floods using remote sensing techniques usually involve delineating flooding areas. For example, Philipson et al. (1980) used Landsat Thematic Mapper (TM) data to map the flood boundary for Black River in the U.S.A. This study used visual interpretation techniques of band 7 (0.8 - 1.1 µ m) Landsat TM data. Other studies in flood delineation can be found in Sollers et al. (1978) and Kalensky et al. (1979). Remote sensing techniques are also used to monitor lake and swamp areas. Barret et al. (1982) used remote sensing techniques to monitor large lake and swamp such as Lake Chat and Okowango swamp in South Africa. In this study they used the visible and infrared bands of the Meteosat data.

Generally, flood is an important subject of study in hydrology and hydrologists are able to predict floods by using hydrological modelling. The data that are needed in flood prediction are rainfall, land use, topography information etc. These data are generally derived from field observations which are costly and time consuming. The use of remote sensing techniques can decrease the cost of data acquisition. Remote sensing can also provide up-to-date data or information for large areas in a short time compared to traditional methods (Philipson et al. 1980, U.S. Department of Agriculture, 1986). The U.S. Department of Agriculture uses remote sensing techniques in determining watershed geometry, drainage network, soil moisture data and land use information. Various studies have also been done in determining runoff coefficient using remote sensing data (Bondelid et al. 1981, Engman and Sing 1981 and Hill et al. 1987). Engman and Sing (1981) reported that remote sensing is rapidly becoming an important source of data and information for hydrological modelling. Ochi et al.(1989), have used remote sensing data in flood damage forecasting based on flood flow modelling. Normalized vegetation index (NVI) from remote sensing data and slope gradient were used to calculate runoff ratio. The flood flow modelling was later used in simulation study for flood movements in various types of vegetation.

This paper reports on the use of the Landsat-5 Thematic Mapper (TM) data and the U.S. Soil Conservation Service Technical Release 55 (SCS TR-55) hydrological model in the prediction of floods in the Klang Valley and its surrounding areas.

Study Area
The Klang Valley and its surrounding areas have been selected for the study. The area falls within the coordinates 366 000mE, 360 000mN and 444 000mE, 330 000mN (refer figure 1). This area is chosen since it is in a valley surrounded by hills with some major rivers flowing through the area. Many locations in the area are also prone to flooding during heavy rainfall.


FIGURE 1. Study area of Klang Valley and its surrounding areas.
Remote Sensing Data and Other Ancillary Data
The remote sensing data that was used is the Landsat-5 TM satellite data (see figure 2). The satellite data is relatively cloud free and excellent for deriving various information required in the study. Other data that were collected are rainfall data, soil type data and information on hydrological condition.


FIGURE 2. Landsat-5 TM image of study area.