Zihang Fang

Effective evaluations of the future urban expansion impacts (UEI) on surface runoff in alpine basins are full of challenges due to the lack of reliable methods. Our objective was to provide a new approach by coupling the Land Use Scenario Dynamics-urban (LUSD-urban) and Soil Conservation Service-Curve Number (SCS-CN) models to estimate the future UEI on surface runoff. Taking the Qinghaihu-Huangshui basin (QHB) in the Tibetan Plateau, China, as an example, we first applied the SCS-CN model to quantify the surface runoff in 2000 and 2018 and analyzed the changes in surface runoff. Next, we applied the LUSD-urban model to simulate urban expansion under five localized shared socioeconomic pathways (SSPs) from 2018 to 2050. Finally, we assessed the UEI on surface runoff in the QHB from 2018 to 2050. We found that coupling the LUSD-urban and SCS-CN models could effectually evaluate the future UEI on surface runoff. Compared with the combination of the Future Land Use Simulation (FLUS) and SCS-CN models, our method reduced the absolute evaluation errors from 3.40% and 11.78% to 0.18% and 4.23%, respectively. In addition, the results showed that future urban expansion will have severe impacts on surface runoff in the valley region. For example, as a result of urban expansion, the surface runoff in the Huangzhong, Xining, and Datong catchments will increase by 4.90–9.01%, 4.25–7.36%, and 2.33–3.95%, respectively. Therefore, we believe that the coupled model can be utilized to evaluate the future UEI on surface runoff in alpine basins. In addition, the local government should pay attention to flood risk prevention, especially in the valley region, and adopt reasonable urban planning with soft and hard adaptation measures to promote the sustainable development of alpine basins under rapid urban expansion.

Assessing the climate change impact (CCI) on weather conditions is important for addressing climate change and promoting sustainable development. This study used a weather preference index (WPI) as an indicator to evaluate the CCI on weather conditions in China under different scenarios from 2025 to 2100. First, we analyzed the change in the WPI in China from 1971 to 2013. Then, we estimated the trends in the WPI in China from 2025 to 2100 under different representative concentration pathways (RCPs) based on global climate models. We found that China’s weather conditions improved from 1971 to 2013, as the national average WPI increased from 1.34 to 1.59 with a change rate of 0.03 per decade (0.03/10 a). Under all climate change scenarios, the weather conditions in China will deteriorate. The change rates of the WPI will be −0.19/10 a ∼ − 0.01/10 a. The number of people experiencing deteriorated weather conditions will be 0.71 billion ∼ 1.22 billion, accounting for 53.28% ∼ 91.58% of the total population in China. We also found that the area of the regions with deteriorated weather conditions under all three climate change scenarios will be 2.34 million km², accounting for 24.31% of China’s total land area. At the same time, as the emissions concentrations increase from RCP2.6 to RCP8.5, the area of the regions with severely deteriorated weather conditions in China will increase from 0 to 3.27 million km². Therefore, we suggest that China needs to implement effective measures to address climate change in the future and focus on the mitigation of and adaptation to climate change in regions with deteriorated weather conditions.