Forecasting tropical cyclone-induced rainfall in coastal Australia: implications for effective flood management

K.K. Sahaa, M.M. Hasanb, Ali QUAZI

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3 Citations (Scopus)

Abstract

This article is designed to predict the amount of rainfall resulting from tropical cyclones (TCs) in Australia’s coastal regions and contributes to predicting the likelihood of extreme rainfall events. For this purpose, a Poisson–Gamma generalised linear model is fitted to the TC-induced rainfall with distance of the rainfall station from the TC track and translational speed (TS) of TC as predictors. Both variables have significant negative impact on rainfall. For the lowest TC TS, the 99th percentiles of rainfall for the furthest and closest station distances from the TC track were estimated as 132.5 mm and 236.9 mm, respectively. When the TC track is the closest to the rainfall station and the TS is the lowest, the 99.9th percentile of the estimated rainfall is 366.3 mm. The ability of the model to capture extremely high rainfall amounts may prove useful in forecasting floods. Improved flood forecasting and management will reduce loss of life and property, thereby contributing to the social and economic well-being of Australia’s coastal population.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalAustralasian Journal of Environmental Management
Volume00
DOIs
Publication statusPublished - 2015

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tropical cyclone
natural disaster
rainfall
management
coastal region
linear model
flood forecasting
well-being
event
ability
economics

Cite this

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abstract = "This article is designed to predict the amount of rainfall resulting from tropical cyclones (TCs) in Australia’s coastal regions and contributes to predicting the likelihood of extreme rainfall events. For this purpose, a Poisson–Gamma generalised linear model is fitted to the TC-induced rainfall with distance of the rainfall station from the TC track and translational speed (TS) of TC as predictors. Both variables have significant negative impact on rainfall. For the lowest TC TS, the 99th percentiles of rainfall for the furthest and closest station distances from the TC track were estimated as 132.5 mm and 236.9 mm, respectively. When the TC track is the closest to the rainfall station and the TS is the lowest, the 99.9th percentile of the estimated rainfall is 366.3 mm. The ability of the model to capture extremely high rainfall amounts may prove useful in forecasting floods. Improved flood forecasting and management will reduce loss of life and property, thereby contributing to the social and economic well-being of Australia’s coastal population.",
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AU - Sahaa, K.K.

AU - Hasanb, M.M.

AU - QUAZI, Ali

PY - 2015

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N2 - This article is designed to predict the amount of rainfall resulting from tropical cyclones (TCs) in Australia’s coastal regions and contributes to predicting the likelihood of extreme rainfall events. For this purpose, a Poisson–Gamma generalised linear model is fitted to the TC-induced rainfall with distance of the rainfall station from the TC track and translational speed (TS) of TC as predictors. Both variables have significant negative impact on rainfall. For the lowest TC TS, the 99th percentiles of rainfall for the furthest and closest station distances from the TC track were estimated as 132.5 mm and 236.9 mm, respectively. When the TC track is the closest to the rainfall station and the TS is the lowest, the 99.9th percentile of the estimated rainfall is 366.3 mm. The ability of the model to capture extremely high rainfall amounts may prove useful in forecasting floods. Improved flood forecasting and management will reduce loss of life and property, thereby contributing to the social and economic well-being of Australia’s coastal population.

AB - This article is designed to predict the amount of rainfall resulting from tropical cyclones (TCs) in Australia’s coastal regions and contributes to predicting the likelihood of extreme rainfall events. For this purpose, a Poisson–Gamma generalised linear model is fitted to the TC-induced rainfall with distance of the rainfall station from the TC track and translational speed (TS) of TC as predictors. Both variables have significant negative impact on rainfall. For the lowest TC TS, the 99th percentiles of rainfall for the furthest and closest station distances from the TC track were estimated as 132.5 mm and 236.9 mm, respectively. When the TC track is the closest to the rainfall station and the TS is the lowest, the 99.9th percentile of the estimated rainfall is 366.3 mm. The ability of the model to capture extremely high rainfall amounts may prove useful in forecasting floods. Improved flood forecasting and management will reduce loss of life and property, thereby contributing to the social and economic well-being of Australia’s coastal population.

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KW - tropical cyclone

KW - rainfall

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KW - coastal regions

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