Computational dam safety analysis based on predicted probable maximum flood discharge from statistical downscaling taking into consideration different general circulation models

One of the main reasons of dam failures is insufficient spillway capacity. Spillway is designed based on the Inflow Design Flood (IDF) determined from historical data using Probable Maximum Flood (PMF) or Flood Frequency Analysis (FFA). Changes in the hydrological cycle are observed due to the climate changes; therefore, forecasters need re-calculated scenarios in many situations. Downscaling, which is a reduction of time and space dimensions in climate models, will probably be the future of climate change research. Attempts done in this study to: develop a new approach to predict IDF from statistical downscaling using Linear Genetic Programming (LGP); search the impacts of climate change on the new IDF; computational dam safety analysis for the case study dam using FLOW-3D. Reasonable results were achieved in downscaling the peak monthly discharges directly from daily and monthly weather variables (NCEP and CGCM3) without involving rainfall-runoff models. FFA based on historical data, both observed and statistically downscaled, are used to get the IDF values. Analysis of the future projections of FFA reveals a general tendency towards changes in the IDF. It was observed that the results of the proposed methodology are comparable to the existing PMF method based on observed historical data. Comparison results of the new and the existing methods will help the design engineers to make judgment on IDFs of proposed dams. Commercial CFD software, FLOW-3D, is used to investigate the dam safety based on the design flood. In some cases, structural retrofitting or an early warning system can be carried out for dams in risk. It is also necessary that all possible climate scenarios are to be analyzed during the selection of IDF for proposed dams.