Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | 100388 |
Fachzeitschrift | Climate Services |
Jahrgang | 30 |
Publikationsstatus | Veröffentlicht - Apr. 2023 |
Abstract
Climate change is one of the most important factors impacting hydrological regimes. In this paper, climate change impact on streamflow of Loukkos basin (northwestern Morocco) is evaluated using SWAT model for three future periods: near (2021–2040), mid (2041–2070), and far (2071–2100), compared to baseline 1981–2020. A set of bias-corrected climate models was used: five regional climate models (EURO-CORDEX), four global climate models (CMIP6) and their ensemble mean, under two representative concentration pathways respectively (RCP 4.5; RCP 8.5) and (SSP2-4.5; SSP5-8.5). Furthermore, SUFI-2 algorithm in SWAT-CUP was performed to calibrate (1981–1997), validate (1998–2015), and analyze uncertainty for each dataset at ten hydrological stations. In most stations, statistical performance indicated a good simulation, with a Nash–Sutcliffe efficiency (NSE) greater than 0.77 and percent bias (PBIAS) within ±10% on a monthly basis. Overall, 82% of models indicated that future climate could decline streamflow. The largest decrease would be for 2071–2100 and under RCP 8.5/SSP5-8.5. Our findings could help planners and policymakers in developing reasonable water management policies and climate change adaptation measures.
ASJC Scopus Sachgebiete
- Umweltwissenschaften (insg.)
- Globaler Wandel
- Erdkunde und Planetologie (insg.)
- Atmosphärenwissenschaften
Ziele für nachhaltige Entwicklung
Zitieren
- Standard
- Harvard
- Apa
- Vancouver
- BibTex
- RIS
in: Climate Services, Jahrgang 30, 100388, 04.2023.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Hydrological modeling of spatial and temporal variations in streamflow due to multiple climate change scenarios in northwestern Morocco
AU - Acharki, Siham
AU - Taia, Soufiane
AU - Arjdal, Youssef
AU - Hack, Jochen
N1 - Funding Information: The publication of this article was funded by the Open Access Publishing Fund of Leibniz University Hannover. The authors would like to express their deepest gratitude to Dr. Daniela Jacob (Editor-in-Chief) and the reviewers for their valuable comments on the manuscript. We thank also Abdeslam Acharki for accompanying us on field trips. Thank you to Loukkos Hydraulic Basin Agency and Loukkos Regional Agricultural Development Office for providing us with meteorological and hydrological data-sets. We also acknowledge the Earth System Grid Federation (ESGF) and its sponsors for storing and giving total access to Euro-CORDEX and CMIP6 outputs. Funding Information: The publication of this article was funded by the Open Access Publishing Fund of Leibniz University Hannover. The authors would like to express their deepest gratitude to Dr. Daniela Jacob (Editor-in-Chief) and the reviewers for their valuable comments on the manuscript. We thank also Abdeslam Acharki for accompanying us on field trips. Thank you to Loukkos Hydraulic Basin Agency and Loukkos Regional Agricultural Development Office for providing us with meteorological and hydrological data-sets. We also acknowledge the Earth System Grid Federation (ESGF) and its sponsors for storing and giving total access to Euro-CORDEX and CMIP6 outputs.
PY - 2023/4
Y1 - 2023/4
N2 - Climate change is one of the most important factors impacting hydrological regimes. In this paper, climate change impact on streamflow of Loukkos basin (northwestern Morocco) is evaluated using SWAT model for three future periods: near (2021–2040), mid (2041–2070), and far (2071–2100), compared to baseline 1981–2020. A set of bias-corrected climate models was used: five regional climate models (EURO-CORDEX), four global climate models (CMIP6) and their ensemble mean, under two representative concentration pathways respectively (RCP 4.5; RCP 8.5) and (SSP2-4.5; SSP5-8.5). Furthermore, SUFI-2 algorithm in SWAT-CUP was performed to calibrate (1981–1997), validate (1998–2015), and analyze uncertainty for each dataset at ten hydrological stations. In most stations, statistical performance indicated a good simulation, with a Nash–Sutcliffe efficiency (NSE) greater than 0.77 and percent bias (PBIAS) within ±10% on a monthly basis. Overall, 82% of models indicated that future climate could decline streamflow. The largest decrease would be for 2071–2100 and under RCP 8.5/SSP5-8.5. Our findings could help planners and policymakers in developing reasonable water management policies and climate change adaptation measures.
AB - Climate change is one of the most important factors impacting hydrological regimes. In this paper, climate change impact on streamflow of Loukkos basin (northwestern Morocco) is evaluated using SWAT model for three future periods: near (2021–2040), mid (2041–2070), and far (2071–2100), compared to baseline 1981–2020. A set of bias-corrected climate models was used: five regional climate models (EURO-CORDEX), four global climate models (CMIP6) and their ensemble mean, under two representative concentration pathways respectively (RCP 4.5; RCP 8.5) and (SSP2-4.5; SSP5-8.5). Furthermore, SUFI-2 algorithm in SWAT-CUP was performed to calibrate (1981–1997), validate (1998–2015), and analyze uncertainty for each dataset at ten hydrological stations. In most stations, statistical performance indicated a good simulation, with a Nash–Sutcliffe efficiency (NSE) greater than 0.77 and percent bias (PBIAS) within ±10% on a monthly basis. Overall, 82% of models indicated that future climate could decline streamflow. The largest decrease would be for 2071–2100 and under RCP 8.5/SSP5-8.5. Our findings could help planners and policymakers in developing reasonable water management policies and climate change adaptation measures.
KW - Climate change
KW - CMIP6
KW - Sentinel-2
KW - Streamflow
KW - SWAT model
UR - http://www.scopus.com/inward/record.url?scp=85159604927&partnerID=8YFLogxK
U2 - 10.1016/j.cliser.2023.100388
DO - 10.1016/j.cliser.2023.100388
M3 - Article
AN - SCOPUS:85159604927
VL - 30
JO - Climate Services
JF - Climate Services
M1 - 100388
ER -