Abstract
Amongst the impacts of climate change, those arising from extreme hydrological events are expected to cause the greatest impacts. To assess the changes in temperature and precipitation and their impacts on the discharge in the upper Yangtze Basin from pre-industrial to the end of 21st century, four hydrological models were integrated with four global climate models. Results indicated that mean discharge was simulated to increase slightly for all hydrological models forced by all global climate models during 1771–1800 and 1871–1900 relative to the 1971–2000 reference period, whereas the change directions in mean discharge were not consistent among the four global climate models during 2070–2099, with increases from HadGEM2-ES and MIROC5, and decreases from GFDL-ESM2M and IPSL-CM5A-LR. Additionally, our results indicated that decreases in precipitation may always result in the decrease in mean discharge, but increases in precipitation did not always lead to increases in discharge due to high temperature rise. The changes in extreme flood events with different return intervals were also explored. These extreme events were projected to become more intense and frequent in the future, which could have potential devastating impacts on the society and ecosystem in this region.
Highlights
Every year, extreme hydrological events cause enormous suffering, economic, and often catastrophic environmental damage throughout the world
In addition to the impact assessment of climate change on the discharge over the upper Yangtze River Basin (UYRB) during the period of 2070–2099 under the RCP2.6, RCP4.5, and RCP8.5 scenarios, we assess the impacts during the period of 1771–1800 under a pre-industrial control scenario, and during the period of 1871–1900 and the period of 1971–2000 under a historical scenario with historical CO2 concentration
The performance of the model can be judged as satisfactory if R2 value is > 0.6, as suggested by Benaman et al (2005). According to these criteria used in previous studies, the model efficiency statistics for the four hydrological models (HMs) in this study indicate the good performance of calibration and validation with Nash–Sutcliffe efficiency (NSE) value > 0.71, ±18.82% ≤ PBIAS ≤ ±25.10%, and
Summary
Extreme hydrological events cause enormous suffering, economic, and often catastrophic environmental damage throughout the world. For example, cause famine and wildfires in Australia and North America, whilst in Asia, summer flooding frequently ruins millions of dollars of agricultural investment and displaces large numbers of humans. Floods are identified as the most destructive hazards in the world [1,2,3,4]. The Emergency Events Database has recorded 3062 severe floods, which alone accounts for 47% of all weather-related disasters worldwide during 1995–2015 [5]. These floods have affected 2.3 billion people and caused 157,000 deaths. In July 2020, for example, flooding has caused an estimated
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