Abstract
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.
Highlights
This study is to identify the presence of chaotic dynamics of hydrological data located in flood prone areas for the purpose of constructing multivariable flood prediction model based on a chaos approach
There are several methods that can help in identifying the presence of chaotic dynamics i.e.; phase space plot method [1], Cao method [2] and exponent Lyapunov [3]
This is because the Cao method has successfully identified the presence of chaotic dynamics for hydrological data [5], [6]
Summary
This study is to identify the presence of chaotic dynamics of hydrological data located in flood prone areas for the purpose of constructing multivariable flood prediction model based on a chaos approach. The hydrological data involved are rainfall time series data, water level time series data and river flow time series data at Sungai Galas, Dabong in Kelantan, Malaysia. This area is a region where flood happens that causes uncertain hydrological data. For the study, the only chaotic dynamically identifiable data will be used in further studies to develop a multivariable prediction model based on a gradual approach The construction of this multivariable prediction model is to predict flood in area of Sungai Galas. Water level and river flow time series that are hydrological data from Sungai Galas are used in the analysis. It can be noted here that the hydrological data involved looked like random but analysis was needed to identify the presence of chaotic dynamics on the hydrological data involved
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