• Energy Research

AbstractIncreasing 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.

AbstractIncreasing 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.

AbstractThe impacts of climate‐induced changes in discharge and base level in three tributaries of the Saint‐Lawrence River, Québec, Canada, are modelled for the period 2010–2099 using a one‐dimensional morphodynamic model. Changes in channel stability and bed‐material delivery to the Saint‐Lawrence River over this period are simulated for all combinations of seven tributary hydrological regimes (present‐day and those predicted using three global climate models and two greenhouse gas emission scenarios) and three scenarios of how the base level provided by the Saint‐Lawrence River will alter (no change, gradual fall, step fall). Even with no change in base level the projected discharge scenarios lead to an increase in average bed material delivery for most combinations of river and global climate model, although the magnitude of simulated change depends on the choice of global climate model and the trend over time seems related to whether the river is currently aggrading, degrading or in equilibrium. The choice of greenhouse gas emission scenario makes much less difference than the choice of global climate model. As expected, a fall in base level leads to degradation in the rivers currently aggrading or in equilibrium, and amplifies the effects of climate change on sediment delivery to the Saint‐Lawrence River. These differences highlight the importance of investigating several rivers using several climate models in order to determine trends in climate change impacts. Copyright © 2010 John Wiley & Sons, Ltd.

AbstractThe impacts of climate‐induced changes in discharge and base level in three tributaries of the Saint‐Lawrence River, Québec, Canada, are modelled for the period 2010–2099 using a one‐dimensional morphodynamic model. Changes in channel stability and bed‐material delivery to the Saint‐Lawrence River over this period are simulated for all combinations of seven tributary hydrological regimes (present‐day and those predicted using three global climate models and two greenhouse gas emission scenarios) and three scenarios of how the base level provided by the Saint‐Lawrence River will alter (no change, gradual fall, step fall). Even with no change in base level the projected discharge scenarios lead to an increase in average bed material delivery for most combinations of river and global climate model, although the magnitude of simulated change depends on the choice of global climate model and the trend over time seems related to whether the river is currently aggrading, degrading or in equilibrium. The choice of greenhouse gas emission scenario makes much less difference than the choice of global climate model. As expected, a fall in base level leads to degradation in the rivers currently aggrading or in equilibrium, and amplifies the effects of climate change on sediment delivery to the Saint‐Lawrence River. These differences highlight the importance of investigating several rivers using several climate models in order to determine trends in climate change impacts. Copyright © 2010 John Wiley & Sons, Ltd.