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Assessing the contribution of different uncertainty sources in streamflow projections

Hydrological models are commonly used to quantify the hydrological impacts of climate change using general circulation model (GCM) simulations as input. However, application of the model results with respect to future changes in streamflow scenarios remains limited by the large uncertainties stemmin...

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Main Authors: Kamal, Md. Rowshon, Galavi, Hadi, Mirzaei, Majid, Ebrahimian, Mahboubeh
Format: Article
Language:English
Published: Springer 2019
Online Access:http://psasir.upm.edu.my/id/eprint/80731/1/HYDRO.pdf
http://psasir.upm.edu.my/id/eprint/80731/
https://umexpert.um.edu.my/public_view.php?type=publication&row=ODA5MzQ%3D
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spelling my.upm.eprints.807312021-01-23T21:08:35Z http://psasir.upm.edu.my/id/eprint/80731/ Assessing the contribution of different uncertainty sources in streamflow projections Kamal, Md. Rowshon Galavi, Hadi Mirzaei, Majid Ebrahimian, Mahboubeh Hydrological models are commonly used to quantify the hydrological impacts of climate change using general circulation model (GCM) simulations as input. However, application of the model results with respect to future changes in streamflow scenarios remains limited by the large uncertainties stemming from various sources. Therefore, this study aimed to explore uncertainties involved in climate change impact assessment in Hulu Langat Basin, Malaysia, and define the contribution of uncertainty sources to the final uncertainty level. Hydrological model parameters, GCMs, and emission scenario uncertainties were considered the main uncertainty contributors in local-scale impact studies. The equidistant quantile matching method is used to bias-correct simulations of 19 GCMs under two emission scenarios of RCP4.5 and RCP8.5. The Soil and Water Assessment Tool (SWAT) hydrological model is next run by the bias-corrected GCM data to generate a wide spectrum of future streamflow scenarios. Projected monthly streamflow pattern under RCP8.5 showed a different temporal pattern from the observed one. Hydrological model parameter uncertainty was proven to be a larger uncertainty contributor than emission scenario during baseline climate. GCM and emission scenario uncertainties escalated as progressed in time and GCM uncertainty showed larger increments. The monthly pattern of effect of each uncertainty source varied when comparing the two periods of 2030s and 2080s. Therefore, for a superior management of water resources, a study of climate change impacts and uncertainty sources on a smaller scale than the decadal or annual scales can be more informative to the decision makers. Springer 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/80731/1/HYDRO.pdf Kamal, Md. Rowshon and Galavi, Hadi and Mirzaei, Majid and Ebrahimian, Mahboubeh (2019) Assessing the contribution of different uncertainty sources in streamflow projections. Theoretical and Applied Climatology, 137. pp. 1-15. ISSN 1434-4483; ESSN: 0177-798X https://umexpert.um.edu.my/public_view.php?type=publication&row=ODA5MzQ%3D 10.1007/s00704-018-2669-0
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/
language English
description Hydrological models are commonly used to quantify the hydrological impacts of climate change using general circulation model (GCM) simulations as input. However, application of the model results with respect to future changes in streamflow scenarios remains limited by the large uncertainties stemming from various sources. Therefore, this study aimed to explore uncertainties involved in climate change impact assessment in Hulu Langat Basin, Malaysia, and define the contribution of uncertainty sources to the final uncertainty level. Hydrological model parameters, GCMs, and emission scenario uncertainties were considered the main uncertainty contributors in local-scale impact studies. The equidistant quantile matching method is used to bias-correct simulations of 19 GCMs under two emission scenarios of RCP4.5 and RCP8.5. The Soil and Water Assessment Tool (SWAT) hydrological model is next run by the bias-corrected GCM data to generate a wide spectrum of future streamflow scenarios. Projected monthly streamflow pattern under RCP8.5 showed a different temporal pattern from the observed one. Hydrological model parameter uncertainty was proven to be a larger uncertainty contributor than emission scenario during baseline climate. GCM and emission scenario uncertainties escalated as progressed in time and GCM uncertainty showed larger increments. The monthly pattern of effect of each uncertainty source varied when comparing the two periods of 2030s and 2080s. Therefore, for a superior management of water resources, a study of climate change impacts and uncertainty sources on a smaller scale than the decadal or annual scales can be more informative to the decision makers.
format Article
author Kamal, Md. Rowshon
Galavi, Hadi
Mirzaei, Majid
Ebrahimian, Mahboubeh
spellingShingle Kamal, Md. Rowshon
Galavi, Hadi
Mirzaei, Majid
Ebrahimian, Mahboubeh
Assessing the contribution of different uncertainty sources in streamflow projections
author_facet Kamal, Md. Rowshon
Galavi, Hadi
Mirzaei, Majid
Ebrahimian, Mahboubeh
author_sort Kamal, Md. Rowshon
title Assessing the contribution of different uncertainty sources in streamflow projections
title_short Assessing the contribution of different uncertainty sources in streamflow projections
title_full Assessing the contribution of different uncertainty sources in streamflow projections
title_fullStr Assessing the contribution of different uncertainty sources in streamflow projections
title_full_unstemmed Assessing the contribution of different uncertainty sources in streamflow projections
title_sort assessing the contribution of different uncertainty sources in streamflow projections
publisher Springer
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/80731/1/HYDRO.pdf
http://psasir.upm.edu.my/id/eprint/80731/
https://umexpert.um.edu.my/public_view.php?type=publication&row=ODA5MzQ%3D
_version_ 1690372568650874880
score 13.211869

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