TY - JOUR
T1 - Large-scale flood risk assessment under different development strategies
T2 - the Luanhe River Basin in China
AU - Zhao, J.
AU - Chen, H.
AU - Liang, Q.
AU - Xia, X.
AU - Xu, J.
AU - Hoey, T.
AU - Barrett, B.
AU - Renaud, F.G.
AU - Bosher, L.
AU - Zhou, X.
PY - 2021/10/11
Y1 - 2021/10/11
N2 - Increasing resilience to natural hazards and climate change is critical for achieving many Sustainable Development Goals (SDGs). In recent decades, China has experienced rapid economic development and became the second-largest economy in the world. This rapid economic expansion has led to large-scale changes in terrestrial (e.g., land use and land cover changes), aquatic (e.g., construction of reservoirs and artificial wetlands) and marine (e.g., land reclamation) environments across the country. Together with climate change, these changes may significantly influence flood risk and, in turn, compromise SDG achievements. The Luanhe River Basin (LRB) is one of the most afforested basins in North China and has undergone significant urbanisation and land use change since the 1950s. However, basin-wide flood risk assessment under different development scenarios has not been considered, although this is critically important to inform policy-making to manage the synergies and trade-offs between the SDGs and support long-term sustainable development. Using mainly open data, this paper introduces a new framework for systematically assessing flood risk under different social and economic development scenarios. A series of model simulations are performed to investigate the flood risk under different land use change scenarios projected to 2030 to reflect different development strategies. The results are systematically analysed and compared with the baseline simulation based on the current land use and climate conditions. Further investigations are also provided to consider the impact of climate change and the construction of dams and reservoirs. The results potentially provide important guidance to inform future development strategies to maximise the synergies and minimise the trade-offs between various SDGs in LRB.
AB - Increasing resilience to natural hazards and climate change is critical for achieving many Sustainable Development Goals (SDGs). In recent decades, China has experienced rapid economic development and became the second-largest economy in the world. This rapid economic expansion has led to large-scale changes in terrestrial (e.g., land use and land cover changes), aquatic (e.g., construction of reservoirs and artificial wetlands) and marine (e.g., land reclamation) environments across the country. Together with climate change, these changes may significantly influence flood risk and, in turn, compromise SDG achievements. The Luanhe River Basin (LRB) is one of the most afforested basins in North China and has undergone significant urbanisation and land use change since the 1950s. However, basin-wide flood risk assessment under different development scenarios has not been considered, although this is critically important to inform policy-making to manage the synergies and trade-offs between the SDGs and support long-term sustainable development. Using mainly open data, this paper introduces a new framework for systematically assessing flood risk under different social and economic development scenarios. A series of model simulations are performed to investigate the flood risk under different land use change scenarios projected to 2030 to reflect different development strategies. The results are systematically analysed and compared with the baseline simulation based on the current land use and climate conditions. Further investigations are also provided to consider the impact of climate change and the construction of dams and reservoirs. The results potentially provide important guidance to inform future development strategies to maximise the synergies and minimise the trade-offs between various SDGs in LRB.
KW - Sustainable Development Goals
KW - Flood risk
KW - Climate change
KW - Land use change
KW - Hydrodynamic flood modelling
KW - Open data
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85116898977&partnerID=MN8TOARS
U2 - 10.1007/s11625-021-01034-6
DO - 10.1007/s11625-021-01034-6
M3 - Article
SN - 1862-4065
JO - Sustainability Science
JF - Sustainability Science
ER -