Rain, Rain, Go Away: Stochastic Model In Predicting The Future Rainfall

This study explores the Markov Chain (MC) method for forecasting future precipitation in Tanah Merah, Kelantan. This study also defined the state space and time set in discrete where the data is being observed daily. The rainfall is categorized into 5 states, which are . The transition probability matrix (TPM) was then determined for each month. On top of the TPM for each month, risk matrices were also established for each state. These risk matrices are constructed by calculating the limiting distribution of the TPMs. This risk matrix shows the likelihood of future floods warning given the current state of rainfall.

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Publication Details

Journal
ASM Science Journal
Published
2025-08-18
DOI
https://doi.org/10.32802/asmscj.2025.1581
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
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article

Rain, Rain, Go Away: Stochastic Model In Predicting The Future Rainfall

S. Samsuddin
ASM Science Journal
Hydrology and Drought Analysis
article

Rain, Rain, Go Away: Stochastic Model In Predicting The Future Rainfall

S. Samsuddin
article en

Abstract

This study explores the Markov Chain (MC) method for forecasting future precipitation in Tanah Merah, Kelantan. This study also defined the state space and time set in discrete where the data is being observed daily. The rainfall is categorized into 5 states, which are . The transition probability matrix (TPM) was then determined for each month. On top of the TPM for each month, risk matrices were also established for each state. These risk matrices are constructed by calculating the limiting distribution of the TPMs. This risk matrix shows the likelihood of future floods warning given the current state of rainfall.

ASM Science JournalVol. 20(2)
Universiti Teknologi MARA (MY)
Openalex Percentile: Top 80%
Hydrology and Drought Analysis
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