Assessment on future rainfall variability for adaptive water resource management in Sabah

Climate is changing at an unprecedented rate, and the increasing demands of the growing population will place further pressures on the climate and environment. Water infrastructures such as water treatment plants often face increased stress during extreme weather events such as heavy rainfall or prolonged drought, disrupting societal needs and prompt urgent upgrades to adapt to the changing climate. The use of climate model projections is increasingly adopted in engineering practices for assessing climate risks and impacts to inform adaptive design and strategy of new infrastructures or upgrades. Using a bias-corrected ensemble member of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) tailored for applications in the water sector, we assessed the variability of projected rainfall from 2021 to 2050 under the moderate warming scenario (RCP 4.5). The findings from this study aim to inform adaptive strategies for upgrading 22 water treatment plants across 18 sites in Sabah, Malaysia, where these plants have experienced numerous disruptions due to high turbidity resulting from heavy rainfall in recent years. The average annual rainfall amount ranges from 1630 mm to 4415 mm, with average total monthly rainfall peaks (>460 mm) in June and August at most sites. The observed shift in June and August is a deviation from historical patterns and is also reflected in the maximum consecutive 1- to 5-day rainfall, ranging from 22 mm to 760 mm across all sites, particularly in the interior and west coast districts. This highlights the need for resilient infrastructure upgrade strategy and adaptive water resource management, such as the introduction of off-site river storage to accommodate the anticipated future rainfall.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-10-15
DOI
https://doi.org/10.1051/bioconf/202413105012/pdf
Primary Topic
Climate Change and Sustainable Development
Type
article
Field-Weighted Citation Impact
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article

Assessment on future rainfall variability for adaptive water resource management in Sabah

Springer Link (Chiba Institute of Technology)
Climate Change and Sustainable Development
article

Assessment on future rainfall variability for adaptive water resource management in Sabah

article en

Abstract

Climate is changing at an unprecedented rate, and the increasing demands of the growing population will place further pressures on the climate and environment. Water infrastructures such as water treatment plants often face increased stress during extreme weather events such as heavy rainfall or prolonged drought, disrupting societal needs and prompt urgent upgrades to adapt to the changing climate. The use of climate model projections is increasingly adopted in engineering practices for assessing climate risks and impacts to inform adaptive design and strategy of new infrastructures or upgrades. Using a bias-corrected ensemble member of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) tailored for applications in the water sector, we assessed the variability of projected rainfall from 2021 to 2050 under the moderate warming scenario (RCP 4.5). The findings from this study aim to inform adaptive strategies for upgrading 22 water treatment plants across 18 sites in Sabah, Malaysia, where these plants have experienced numerous disruptions due to high turbidity resulting from heavy rainfall in recent years. The average annual rainfall amount ranges from 1630 mm to 4415 mm, with average total monthly rainfall peaks (>460 mm) in June and August at most sites. The observed shift in June and August is a deviation from historical patterns and is also reflected in the maximum consecutive 1- to 5-day rainfall, ranging from 22 mm to 760 mm across all sites, particularly in the interior and west coast districts. This highlights the need for resilient infrastructure upgrade strategy and adaptive water resource management, such as the introduction of off-site river storage to accommodate the anticipated future rainfall.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 71%
Climate Change and Sustainable Development
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