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M. A Malek
The Institute of Energy, Policy and Research, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43009, Kajang, Selangor
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Mathematics

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Forecsting of Hydrological Time Series Data with Lag-one Markov Chain Model M. A Malek; A.M Baki
ASEAN Journal on Science and Technology for Development Vol. 31 No. 1 (2014): ASEAN Journal on Science and Technology for Development (AJSTD)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (459.943 KB) | DOI: 10.29037/ajstd.26

Abstract

Planning and operation are important elements in water resource management. Rainfall forecasting is one of the conducts commonly used to extend the lead-time for catchments with short response time. However, it is difficult to obtain a high degree of accuracy in rainfall forecasting using deterministic models. Therefore, a probability-based rainfall forecasting model, based on Markov Chain provided a better alternative due to its ability to preserve the basic statistical properties ofthe original series. This method was especially useful in the absence of long-term recorded data, a rampant phenomenon in Malaysia. Comparison of statistics in the generated synthetic rainfall data against those of the observed data revealed that reasonable levels of acceptability were achieved.
Co-Authors A.M Baki