Abstract
The impacts of climate change on the discharge regimes in New Brunswick (Canada) were analyzed, using artificial neural network models. Future climate data were extracted from the Canadian Coupled General Climate Model (CGCM3.1) under the greenhouse gas emission scenarios B1 and A2 defined by the Intergovernmental Panel on Climate Change (IPCC). The climate change fields (temperatures and precipitation) were downscaled using the delta change approach. Using the artificial neural network, future river discharge was predicted for selected hydrometric stations. Then, a frequency analysis was carried out using the Generalized Extreme Value (GEV) distribution function, where the parameters of the distribution were estimated using L-moments method. Depending on the scenario and the time slice used, the increase in low return floods was about 30% and about 15% for higher return floods. Low flows showed increases of about 10% for low return droughts and about 20% for higher return droughts. An important part of the design process using frequency analysis is the estimation of future change in floods or droughts under climate scenarios at a given site and for specific return periods. This was carried out through the development of Regional Climate Index (RCI), linking future floods and droughts to their frequencies under climate scenarios B1 and A2.
Highlights
There is currently a broad scientific consensus that the global climate is changing in ways that are likely to have a profound impact on human society and the natural environment over the coming decades
Future climate data were extracted from the Canadian Coupled General Climate Model (CGCM3.1) under the greenhouse gas emission scenarios by 5% - 12% (B1) and A2 defined by the Intergovernmental Panel on Climate Change (IPCC)
Future climate data were extracted from the Canadian Coupled General Climate Model (CGCM) under different greenhouse gas emission scenarios defined by the Intergovernmental Panel on Climate Change [12]
Summary
There is currently a broad scientific consensus that the global climate is changing in ways that are likely to have a profound impact on human society and the natural environment over the coming decades. Anticipating specific climatic impacts is as much of a challenge in assessing risks and uncertainties than predicting future changes As such, it is important: 1) to improve our ability to manage extreme climatic risks, 2) to assess the consequences of extreme events over the decades, and 3) to develop new tools and design criteria to more accurately assess the impact of extreme events on water resources and river discharge (e.g., floods and droughts). Following the single station analysis, a regression analysis was carried out in order to estimate low flows on a regional basis and for ungauged basins Missing from these previous studies were the projections of future floods and low flows conditions under climate change. This aspect will be addressed within the present study
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