Climate change impacts on extreme precipitation of water supply area in Istanbul: use of ensemble climate modelling and geo-statistical downscaling

Abstract

Numerous statistical downscaling models have been applied to impact studies, but none clearly recommended the most appropriate one for a particular application. This study uses the geographically weighted regression (GWR) method, based on local implications from physical geographical variables, to downscale climate change impacts to a small-scale catchment. The ensembles of daily precipitation time series from 15 different regional climate models (RCMs) driven by five different general circulation models (GCMs), obtained through the European Union (EU)-ENSEMBLES project for reference and future (2071-2100) scenarios are generated for the Omerli catchment, in the east of Istanbul city, Turkey, under scenario A1B climate change projections. Special focus is given to changes in extreme precipitation, since such information is needed to assess the changes in the frequency and intensity of flooding for future climate. The mean daily precipitation from all RCMs is under-represented in the summer, autumn and early winter, but it is overestimated in late winter and spring. The results point to an increase in extreme precipitation in winter, spring and summer, and a decrease in autumn in the future, compared to the current period. The GWR method provides significant modifications (up to 35%) to these changes and agrees on the direction of change from RCMs. The GWR method improves the representation of mean and extreme precipitation compared to RCM outputs and this is more significant, particularly for extreme cases of each season. The return period of extreme events decreases in the future, resulting in higher precipitation depths for a given return period from most of the RCMs. This feature is more significant with downscaling. According to the analysis presented, a new adaption for regulating excessive water under climate change in the Omerli basin may be recommended. ARTICLE HISTORY

Analyzing Effects of Two Different Land Use Datasets on Hydrological Simulations by Using SWAT Model

“…In the recent years, Kara and Yucel (2015) investigated the changes in extreme flows under predicted future climatic conditions by using Hydrologiska Byråns Vattenbalansavdelning (HBV) model. Another work assessed these changes by using 15 different regional climate models using predicted scenarios based on various frequency and intensity of flooding (Kara et al, 2016). Moreover, developed a modeling framework by using SWAT and WEAP models for the entire Istanbul Metropolis, and modeled the water potential of Istanbul, that also covered Omerli Basin, by using global datasets.…”

Water resources availability in southern Europe at the basin scale in response to climate change scenarios

“…To avoid excessive smoothing of the precipitation series, which is critical for a hydrological simulation, the median year will be considered, and the climate change scenarios will be built on it. This proposed method has been successfully employed to simulate precipitation scenarios by other authors [43,64]. This effect is not as strong for the rest of the parameters.…”

Investigation of The Effect of Climate Change on Extreme Precipitation: Tekirdağ Case

“…al., 2020). Therefore, regional climate models (RCMs) is one of the methods that is used for regional assessment however GCM&RCM coupling outputs cannot be used directly at a local scale for the impact studies since RCMs keep coupled GCM biases, particularly for extreme events (Kara et al, 2016). Furthermore, complexity of rainfall processes also produces larger bias between observations and model results (Dai, 2006).…”