Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia

The forecasting of future streamflow aids researchers and policymakers to understand how changes in climate affect hydrological systems. However, traditional computational approaches demand intensive data specifically for the basin, and it is costly. The shift towards more contemporary and data-driv...

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Main Authors: Mohd Nasir, Muhammad Adib, Zainuddin, Zaitul Marlizawati, Harun, Sobri, Kamal, Md Rowshon, Ismail, Habibu
Format: Article
Published: Springer Science and Business Media Deutschland GmbH 2024
Online Access:http://psasir.upm.edu.my/id/eprint/106168/
https://www.springerprofessional.de/en/streamflow-projection-under-cmip6-climate-scenarios-using-a-supp/26712142
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.1061682024-10-15T07:46:12Z http://psasir.upm.edu.my/id/eprint/106168/ Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia Mohd Nasir, Muhammad Adib Zainuddin, Zaitul Marlizawati Harun, Sobri Kamal, Md Rowshon Ismail, Habibu The forecasting of future streamflow aids researchers and policymakers to understand how changes in climate affect hydrological systems. However, traditional computational approaches demand intensive data specifically for the basin, and it is costly. The shift towards more contemporary and data-driven approaches known as support vector regression (SVR) in hydrological modeling utilizing only the hydro-climate data from Coupled Model Intercomparison Project Phase 6 (CMIP6) provides rapid input–output data processing with accurate future projection. CMIP6 is an updated and improved Global Climate Models (GCMs) for the exploration of the specific impacts of changing streamflow patterns for improved water management in agricultural areas. The delta change factor method was used to generate climate sequences, fed into the SVR model to project streamflow from 2021 to 2080. The SVR model fitted reasonably well, demonstrated by several statistical indicators, including Kling-Gupta Efficiency (KGE), Nash–Sutcliffe Efficiency (NSE), Percent Bias (PBias), and Root Mean Squared Error (RMSE), with the training phase performance surpassing the testing phase. Future projections indicated increased rainfall during the dry season for most months, excluding April to June. The rise in precipitation was particularly pronounced during the wet season. Maximum and minimum temperature projections increased for all SSPs, with SSP5-8.5 predicted a substantial increase. The projection revealed that seasonal streamflow changes would range between – 19.1 to – 1.2 and – 7.5 to – 3.1 in the dry and wet seasons, respectively. A considerable streamflow reduction is anticipated for all SSPs in April and May due to increased temperatures, with the most pronounced impact in the SSP5-8.5. Assessing the effects of climate variations on water resource availability is crucial for identifying effective adaptation strategies to address the anticipated rise in irrigation demands due to global warming. The projected streamflow changes due to potential climate impacts are significant for Bukit Merah Reservoir, aiding the formulation of appropriate operational strategies for irrigation releases. Springer Science and Business Media Deutschland GmbH 2024 Article PeerReviewed Mohd Nasir, Muhammad Adib and Zainuddin, Zaitul Marlizawati and Harun, Sobri and Kamal, Md Rowshon and Ismail, Habibu (2024) Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia. Environmental Earth Sciences, 83 (4). ISSN 1866-6299 https://www.springerprofessional.de/en/streamflow-projection-under-cmip6-climate-scenarios-using-a-supp/26712142
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description The forecasting of future streamflow aids researchers and policymakers to understand how changes in climate affect hydrological systems. However, traditional computational approaches demand intensive data specifically for the basin, and it is costly. The shift towards more contemporary and data-driven approaches known as support vector regression (SVR) in hydrological modeling utilizing only the hydro-climate data from Coupled Model Intercomparison Project Phase 6 (CMIP6) provides rapid input–output data processing with accurate future projection. CMIP6 is an updated and improved Global Climate Models (GCMs) for the exploration of the specific impacts of changing streamflow patterns for improved water management in agricultural areas. The delta change factor method was used to generate climate sequences, fed into the SVR model to project streamflow from 2021 to 2080. The SVR model fitted reasonably well, demonstrated by several statistical indicators, including Kling-Gupta Efficiency (KGE), Nash–Sutcliffe Efficiency (NSE), Percent Bias (PBias), and Root Mean Squared Error (RMSE), with the training phase performance surpassing the testing phase. Future projections indicated increased rainfall during the dry season for most months, excluding April to June. The rise in precipitation was particularly pronounced during the wet season. Maximum and minimum temperature projections increased for all SSPs, with SSP5-8.5 predicted a substantial increase. The projection revealed that seasonal streamflow changes would range between – 19.1 to – 1.2 and – 7.5 to – 3.1 in the dry and wet seasons, respectively. A considerable streamflow reduction is anticipated for all SSPs in April and May due to increased temperatures, with the most pronounced impact in the SSP5-8.5. Assessing the effects of climate variations on water resource availability is crucial for identifying effective adaptation strategies to address the anticipated rise in irrigation demands due to global warming. The projected streamflow changes due to potential climate impacts are significant for Bukit Merah Reservoir, aiding the formulation of appropriate operational strategies for irrigation releases.
format Article
author Mohd Nasir, Muhammad Adib
Zainuddin, Zaitul Marlizawati
Harun, Sobri
Kamal, Md Rowshon
Ismail, Habibu
spellingShingle Mohd Nasir, Muhammad Adib
Zainuddin, Zaitul Marlizawati
Harun, Sobri
Kamal, Md Rowshon
Ismail, Habibu
Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
author_facet Mohd Nasir, Muhammad Adib
Zainuddin, Zaitul Marlizawati
Harun, Sobri
Kamal, Md Rowshon
Ismail, Habibu
author_sort Mohd Nasir, Muhammad Adib
title Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
title_short Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
title_full Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
title_fullStr Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
title_full_unstemmed Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
title_sort streamflow projection under cmip6 climate scenarios using a support vector regression: a case study of the kurau river basin of northern malaysia
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/106168/
https://www.springerprofessional.de/en/streamflow-projection-under-cmip6-climate-scenarios-using-a-supp/26712142
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