My SETDS methodology should work fine with any datetime stamped data. So here is an attempt to apply some similar technique for "Flood Risk Pattern Recognition" in Malaysia:
[PDF] Flood Risk Pattern Recognition Using Chemometric Technique: A Case Study in Muda River Basin (Computational Water, Energy, and Environmental Engineering) by Ahmad Shakir Mohd Saudi and others
[7] Trubin, I.A. (2008) Exception Based Modelling and Forecasting. Proceedings of the Computer Measurement Group, Nevada, 7-12 December 2008, 353-364..."
[PDF] Flood Risk Pattern Recognition Using Chemometric Technique: A Case Study in Muda River Basin (Computational Water, Energy, and Environmental Engineering) by Ahmad Shakir Mohd Saudi and others
..."Time Series Analysis
is essential for the prediction of water level in the study area, where this
method enables
an efficient
evaluation of the process from the performance by analyzing data. The method
produces three important
data (e.g., Upper
Control Limit (UCL), Average Value (AVG) and Lower Control Limit (LCL)) for the
trend and prediction
of future hydrological modelling, where the Sigma is within a range value of a
set of data.Control Chart can
detect some trends and patterns with actual data deviations from historical
baseline, be able to capture unusual
resource usage, can determine the dynamic threshold, and also can become the
best base lining to examine the actual
data deviation from the historical baseline (Igor Trubin, 2008) [7].
The equation implementedin this analysis was:
Moving Range = Plot : MRt for t = 2, 3,, m. ...[7] Trubin, I.A. (2008) Exception Based Modelling and Forecasting. Proceedings of the Computer Measurement Group, Nevada, 7-12 December 2008, 353-364..."
