Abstract:Cascade hydropower stations are effective in water resource utilization, regional water allocation, and flood risk management. Under changing climate conditions, water resources would experience complex temporal and spatial changes, which may lead to various issues relating to flood control and water resource management, and challenge the existing optimal scheduling of cascade hydropower stations. It is thus important to conduct a study on cascade hydropower station scheduling under changing climate conditions. In this study, the Jinsha River rainfall-discharge statistical model is developed based on the statistical relationship between meteorological and runoff indicators. Validation results indicate that the developed model is capable of generating satisfactory simulation results and thus can be used for future Jinsha River runoff projection under climate change. Meanwhile, the Providing Regional Climates for Impacts Studies (PRECIS) is run to project future rainfall in the Jinsha River basin under two General Circulation Models (ECHAM5 and HadAM3P), two scenarios (A1B and B2), and four periods (1961-1990, 1991-2020, 2021-2050, and 2051-2099). The regional climate modeling data are analyzed and then fed into the Jinsha hydrological model to analyze the trends of future discharge at Xiangjiaba Hydro Station. Adaptive scheduling strategies for cascade hydropower stations are discussed based on the future inflow trend analysis and current flood scheduling mode. It is suggested that cascade hydropower stations could be operated at flood limited water level (FLWL) during 2021-2099. In addition, the impoundment of cascade hydropower stations should be properly delayed during the post-flood season in response to the possible occurrence of increased and extended inflow in wet seasons.

Many studies found that land use change (LUC) had great impacts on regional precipitation, due to thermodynamic and dynamic responses. However, the relative contributions of these two factors to changes in precipitation due to LUC are rarely investigated. This study quantifies the relative contributions of

The Tibetan Plateau (TP) is often called the “Water Tower of Asia,” which contains the largest amount of snow and glaciers outside the polar regions. As an important and variable feature of the land surface, snow coverage on the TP has great impacts on regional climate. However, the commonly used ERA5 reanalysis in dynamical downscaling largely overestimates the snow depth for the TP. To improve the representation of snow cover in ERA5, a new ERA5‐driven downscaling data set (High Asia Refined analysis version 2, HAR v2) was generated by the Weather Research and Forecasting (WRF) model with the bias‐corrected snow depth. This study aims to identify and better understand the impact of bias‐corrected initial snow conditions on simulated regional climate, by comparing the HAR v2 with a 5‐year ERA5 forced WRF simulation without bias correction of initial snow depth (referred to as WRF_ERA5). The results show that the bias correction significantly improves the simulation of 2 m air temperature (T2), with regional mean cold bias reduced by 0.2°C–2.4°C, but no significant improvement in precipitation simulation is found. Further comparative analysis reveals that higher snow depth in WRF_ERA5 leads to T2, mean daily precipitation, summer extreme precipitation, and contributions of convective precipitation to summer mean daily precipitation decrease by 0°C–4°C, 0%–60%, 0%–40%, and 0%–10%, respectively, in most areas of the TP. In addition, the bias‐corrected initial snow depth also has impacts on simulated diurnal cycles of precipitation and T2 and leads to peak hours one hour earlier. Overall, this study confirms the importance of snow cover for the climate in the TP.

Abstract. Land use and cover have been significantly changed all around the world during the last decade. In particular, the Grain for Green (GG) program has resulted in significant changes in regional land use and cover, especially in China. Land use and cover change (LULCC) may lead to changes in regional climate. In this study, we take the Yangtze River basin as a case study and analyze the impacts of LULCC and reforestation on summer rainfall amounts and extremes based on the Weather Research and Forecasting model. Firstly, two observed land use and cover scenarios (1990 and 2010) were chosen to investigate the impacts of LULCC on summer rainfall during the last decade. Secondly, two hypothetical reforestation scenarios (i.e., scenarios of 20 % and 50 % cropland changed to forest) were taken based on the control year of 2010 to test the sensitivity of summer rainfall (amounts and extremes) to reforestation. The results showed that average summer rainfall and extreme summer daily rainfall decreased in the Yangtze River basin between 1990 and 2010 due to LULCC. Reforestation could increase summer rainfall amount and extremes, and the effects were more pronounced in populated areas than over the whole basin. Moreover, the effects of reforestation were influenced by the reforestation proportion. In addition, the summer rainfall increased less conversely, with the transform proportion of cropland to forest increased from 20 % to 50 %. By analyzing the changes in water vapor mixing ratio, upward moisture flux, and 10 m wind, it is suggested that this result might be caused by the horizontal transportation processes of moisture. Although a comprehensive assessment of the impacts of LULCC on summer rainfall amounts and extremes was conducted, further studies are needed to investigate the uncertainty better.

Abstract. Land use and cover has been significantly changed all around the world during the last decade. In particular, the Returning Farmland to Forest Program (RFFP) have resulted in significant changes in regional land use and cover, especially in China. The land use and cover change (LUCC) may lead to the change in regional climate. In this study, we take the Yangtze river basin as a case study and analyze the impacts of LUCC and reforestation on summer rainfall amount and extremes based on the Weather Research and Forecasting model. Firstly, two observed land use and cover scenarios (1990 and 2010) were chosen to investigate the impacts of LUCC on the summer rainfall during the last decade. Secondly, two hypothetical reforestation scenarios (i.e., scenarios of 20 % and 50 % cropland changed to be forest) were taken based on the control year of 2010 to test the sensitivity of summer rainfall (amount and extremes) to reforestation. The results showed that LUCC between 1990 and 2010 decreased average summer rainfall, while increased extreme summer daily rainfall in the Yangtze River basin. The extreme summer daily rainfall increased up to 50 mm, which was mainly observed in the midstream and downstream. Reforestation could increase summer rainfall amount and extremes, and the effects were more pronounced at the local scale where suffered reforestation than at the whole basin. Moreover, the effects of reforestation were influenced by the reforestation proportion. In this study, the average summer rainfall increased more for the scenario of 20 % croplands changed to forests than that for the scenario of 50 %, while the high-intensity short-duration rainfall increased more for the scenario of 50 % croplands changed to forests than that for the scenario of 20 %. Although a comprehensive assessment of the impacts of LUCC on summer rainfall amount and extremes was conducted, further studies are needed to better investigate the uncertainty.