LAUSR

Flood-prone areas are associated with hydrological time series data such as rainfall, water level and river flow. The possibility to predict flood is to relate all the three data involved. However, in order to develop a multivariable prediction model based on chaos approach, each datum needs to identify chaotic dynamics. As such, the Sungai Galas, Dabong in Kelantan, Malaysia which is a flood disaster area has been selected for the analysis. Rainfall, water level and river flow data in this area were collected to be analysed using the Cao method to identify the presence of chaotic dynamics. The hydrological data is uncertain, which is difficult to predict because the data involved is located in the area of flood disaster. The analysis showed the presence of chaotic dynamics on rainfall, water level and river flow data in the Sungai Galas which involved uncertain data located in flood affected areas by using Cao method. Therefore, a multivariable flood prediction model can be implemented using a chaos approach.