An inverse-modelling approach to assess the impacts of climate change in the Seyhan River basin, Turkey

One of file most significant anticipated consequences of global climate change is the change in Frequency of hydrological extremes. Predictions of climate change impacts oil the regime of hydrological extremes have traditionally been conducted by a top-down approach that involves a high degree of uncertainty associated with the temporal and spatial characteristics of general circulation model (GCM) Outputs and the choice of downscaling technique. This Study uses the inverse approach to model hydrological risk and Vulnerability to changing climate conditions in the Seyhan River basin, Turkey. With close collaboration with the end users, the approach first identifies critical hydrological exposures that may lead to local failures in the Seyhan River basin. The Hydro-BEAM hydrological model is used to inversely transform the main hydrological exposures, such as floods and droughts, into corresponding meteorological conditions. The frequency of critical meteorological conditions is investigated under present and future climate scenarios by means of a weather generator based oil the improved K-nearest neighbour algorithm, The weather generator, linked with the Output of GCMS in the last step of the proposed methodology, allows for the creation of all ensemble of scenarios and easy Updating when improved GCM Outputs become available. Two main conclusions were drawn from the application of the inverse approach to the Seyhan River basin. First, floods of 100-, 200- and 300-year return periods under present conditions will have 102-, 293- and 1370-year return periods under the future conditions; that is, critical flood events will occur much less frequently under the changing climate conditions. Second, the drought return period will change from 5.3 years under present conditions to 2.0 years tinder the future conditions that is, critical drought events will occur Much more frequently under the changing climate conditions.