Key concepts for the analysis of climate change impacts for river basin management in the River Danube

River Systems ◽  
2012 ◽  
Vol 20 (1) ◽  
pp. 7-21 ◽  
Author(s):  
Bastian Klein ◽  
Imke Lingemann ◽  
Enno Nilson ◽  
Peter Krahe ◽  
Thomas Maurer ◽  
...  
2016 ◽  
Vol 543 ◽  
pp. 828-845 ◽  
Author(s):  
Helmut Habersack ◽  
Thomas Hein ◽  
Adrian Stanica ◽  
Igor Liska ◽  
Raimund Mair ◽  
...  

2012 ◽  
Vol 3 (3) ◽  
pp. 171-184 ◽  
Author(s):  
Avi Ostfeld ◽  
Stefano Barchiesi ◽  
Matthijs Bonte ◽  
Carol R. Collier ◽  
Katharine Cross ◽  
...  

Despite uncertainty pertaining to methods, assumptions and input data of climate change models, most models point towards a trend of an increasing frequency of flooding and drought events. How these changes reflect water management decisions and what can be done to minimize climate change impacts remains unclear. This paper summarizes and extends the workshop outcomes on ‘Climate Change Impacts on Watershed Management: Challenges and Emerging Solutions’ held at the IWA World Water Congress and Exhibition, Montréal, 2010, hosted by the IWA Watershed and River Basin Management Specialist Group. The paper discusses climate change impacts on water management of freshwater ecosystems and river basins, and illustrates these with three case studies. It is demonstrated through the case studies that engagement of relevant stakeholders is needed early in the process of building environmental flows and climate change decision-making tools, to result in greater buy-in to decisions made, create new partnerships, and help build stronger water management institutions. New alliances are then created between water managers, policy makers, community members, and scientists. This has been highlighted by the demonstration of the Pangani integrated environmental flow assessment, through the Okavango River Basin case study, and in the more participatory governance approach proposed for the Delaware River Basin.


2016 ◽  
Vol 55 ◽  
pp. 141-150 ◽  
Author(s):  
Bjarke Stoltze Kaspersen ◽  
Torsten Vammen Jacobsen ◽  
Michael Brian Butts ◽  
Eva Boegh ◽  
Henrik Gioertz Müller ◽  
...  

Author(s):  
Patricia Ann JARANILLA-SANCHEZ ◽  
Lei WANG ◽  
Katsunori TAMAGAWA ◽  
Izumi HASEGAWA ◽  
Hiroki YAMAMOTO ◽  
...  

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Kodai Yamamoto ◽  
Takahiro Sayama ◽  
Apip

AbstractClimate change will have a significant impact on the water cycle and will lead to severe environmental problems and disasters in humid tropical river basins. Examples include river basins in Sumatra Island, Indonesia, where the coastal lowland areas are mostly composed of peatland that is a wetland environment initially sustained by flooding from rivers. Climate change may alter the frequency and magnitude of flood inundation in these lowland areas, disturbing the peatland environment and its carbon dynamics and damaging agricultural plantations. Consequently, projecting the extent of inundation due to future flooding events is considered important for river basin management. Using dynamically downscaled climate data obtained by the Non-Hydrostatic Regional Climate Model (NHRCM), the Rainfall-Runoff-Inundation (RRI) model was applied to the Batanghari River Basin (42,960 km2) in Sumatra Island, Indonesia, to project the extent of flood inundation in the latter part of the twenty-first century. In order to obtain reasonable estimates of the extent of future flood inundation, this study compared two bias correction methods: a Quantile Mapping (QM) method and a combination of QM and Variance Scaling (VS) methods. The results showed that the bias correction obtained by the QM method improved the simulated flow duration curve (FDC) obtained from the RRI model, which facilitated comparison with the simulated FDC using reference rainfall data. However, the high spatial variability observed in daily and 15-day rainfall data remained as the spatial variation bias, and this could not be resolved by simple QM bias correction alone. Consequently, the simulated extreme variables, such as annual maximum flood inundation volume, were overestimated compared to the reference data. By introducing QM-VS bias correction, the cumulative density functions of annual maximum discharge and inundation volumes were improved. The findings also showed that flooding will increase in this region; for example, the flood inundation volume corresponding to a 20-year return period will increase by 3.3 times. River basin management measures, such as land use regulations for plantations and wetland conservation, should therefore consider increases in flood depth and area, the extents of which under a future climate scenario are presented in this study.


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