Abstract
Abstract. How will the combined impacts of land use change, climate change, and hydrologic modeling influence changes in urban flood frequency and what is the main uncertainty source of the results? Will such changes differ by catchment with different degrees of current and future urban development? We attempt to answer these questions in two catchments with different degrees of urbanization, the Fanno catchment with 84% urban land use and the Johnson catchment with 36% urban land use, both located in the Pacific Northwest of the US. Five uncertainty sources – general circulation model (GCM) structures, future greenhouse gas (GHG) emission scenarios, land use change scenarios, natural variability, and hydrologic model parameters – are considered to compare the relative source of uncertainty in flood frequency projections. Two land use change scenarios, conservation and development, representing possible future land use changes are used for analysis. Results show the highest increase in flood frequency under the combination of medium high GHG emission (A1B) and development scenarios, and the lowest increase under the combination of low GHG emission (B1) and conservation scenarios. Although the combined impact is more significant to flood frequency change than individual scenarios, it does not linearly increase flood frequency. Changes in flood frequency are more sensitive to climate change than land use change in the two catchments for 2050s (2040–2069). Shorter term flood frequency change, 2 and 5 year floods, is highly affected by GCM structure, while longer term flood frequency change above 25 year floods is dominated by natural variability. Projected flood frequency changes more significantly in Johnson creek than Fanno creek. This result indicates that, under expected climate change conditions, adaptive urban planning based on the conservation scenario could be more effective in less developed Johnson catchment than in the already developed Fanno catchment.
Highlights
Human-induced land cover change and climate change are important factors in urban flooding
The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) (Randall et al, 2007) projects that heavy precipitation events will be more frequent during the 21st century over most of the Pacific Northwest of USA based on simulations using Atmosphere-Ocean General Circulation Models (GCMs)
To determine the effect of GCM simulations (GCM structures), we first calculate the differences in flood frequency changes that are derived by different GCM simulations while holding the other data such as land use changes, emission scenarios, hydrologic model parameters, and natural variability constant
Summary
Human-induced land cover change and climate change are important factors in urban flooding. For mitigation of and protection from potential flood risk in urban areas, we need to improve our understanding of the possible impacts of the ubiquitous uncertainty of urban flood projection This uncertainty stems from several sources; internal variability of the climate system, future GHG and aerosol emissions, the translation of these emissions into climate change by GCMs, spatial and temporal downscaling, and hydrological modeling (Bates et al, 2008). To quantify uncertainty in flood frequency change, this study considers five uncertainty sources; GCM structures, future GHG emission scenarios, future land use scenarios, hydrologic model parameters, and natural variability of the climate system. Further details of the data and methods used in this study are given
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