The change of import and export trade of Chinese enterprises actually reflects the appreciation and depreciation of RMB, which are closely related to the total volume of import and export trade of Chinese enterprises and the formulation of corresponding foreign exchange measures.Generally speaking, the rise of the RMB exchange rate means the appreciation of the RMB is conducive to imports, while the decline of the RMB exchange rate means the depreciation of the RMB and the decline of the price of export commodities, so it has a greater price advantage and is conducive to exports. Chinese enterprises should correctly grasp the rise and fall of RMB exchange rate and carry out import and export trade reasonably when developing abroad.
Adverse impacts and increasing economic losses from tropical cyclones (TCs) are a major focus in respect to the potential global warming of 1.5 °C or even 2.0 °C. Based on observed meteorological data and county‐scale loss records, loss‐inducing rainfall and wind speed thresholds are identified using the regional climate model CCLM to project future TC events in China. An established damage function is combined with future gross domestic product predictions under five shared socio‐economic pathways. At the 1.5 °C warming level, normalized TC losses will be four times higher than in the reference period (1986–2005). At the 2.0 °C warming level, a sevenfold increase is projected. Relative to the 1.5 °C warming level, TCs will become more frequent under the 2.0 °C scenario, especially along the southeast coast of China. Nearly 0.2–0.5% of the increase in gross domestic product might be offset by TC losses between the 1.5 °C and 2.0 °C warming levels, and the single highest TC loss at 2.0 °C may double that at 1.5 °C, with a larger affected area and more severe rainstorms and wind speeds. Rainfall is attributed more often to TC losses than wind speed. Limiting global warming at 1.5 °C would avoid an estimated increase in TC losses of more than 120 billion CNY annually.
Abstract. Hydrological simulations are a main method of quantifying the contribution rate (CR) of climate change (CC) and human activities (HAs) to watershed streamflow changes. However, the uncertainty of hydrological simulations is rarely considered in current research. To fill this research gap, based on the Soil and Water Assessment Tool (SWAT) model, in this study, we propose a new framework to quantify the CR of CC and HAs based on the posterior histogram distribution of hydrological simulations. In our new quantitative framework, the uncertainty of hydrological simulations is first considered to quantify the impact of “equifinality for different parameters”, which is common in hydrological simulations. The Lancang River (LR) basin in China, which has been greatly affected by HAs in the past 2 decades, is then selected as the study area. The global gridded monthly sectoral water use data set (GMSWU), coupled with the dead capacity data of the large reservoirs within the LR basin and the Budyko hypothesis framework, is used to compare the calculation result of the novel framework. The results show that (1) the annual streamflow at Yunjinghong station in the Lancang River basin changed abruptly in 2005, which was mainly due to the construction of the Xiaowan hydropower station that started in October 2004. The annual streamflow and annual mean temperature time series from 1961 to 2015 in the LR basin showed significant decreasing and increasing trends at the α= 0.01 significance level, respectively. The annual precipitation showed an insignificant decreasing trend. (2) The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was 42.6 % due to CC, and the remaining 57.4 % was due to HAs, such as the construction of hydropower stations within the study area. (3) The comparison with the other two methods showed that the CR of CC calculated by the Budyko framework and the GMSWU data was 37.2 % and 42.5 %, respectively, and the errors of the calculations of the new framework proposed in this study were within 5 %. Therefore, the newly proposed framework, which considers the uncertainty of hydrological simulations, can accurately quantify the CR of CC and HAs to streamflow changes. (4) The quantitative results calculated by using the simulation results with the largest Nash–Sutcliffe efficiency coefficient (NSE) indicated that CC was the dominant factor in streamflow reduction, which was in opposition to the calculation results of our new framework. In other words, our novel framework could effectively solve the calculation errors caused by the “equifinality for different parameters” of hydrological simulations. (5) The results of this case study also showed that the reduction in the streamflow in June and November was mainly caused by decreased precipitation and increased evapotranspiration, while the changes in the streamflow in other months were mainly due to HAs such as the regulation of the constructed reservoirs. In general, the novel quantitative framework that considers the uncertainty of hydrological simulations presented in this study has validated an efficient alternative for quantifying the CR of CC and HAs to streamflow changes.
Global warming has increased the probability of extreme climate events, with compound extreme events having more severe impacts on socioeconomics and the environment than individual extremes. Utilizing the Coupled Model Intercomparison Project Phase 6 (CMIP6), we predicted the spatiotemporal variations of compound extreme precipitation-high temperature events in China under three Shared Socioeconomic Pathways (SSPs) across two future periods, and analyzed the changes in exposed populations and identified influencing factors. From the result, we can see that, the CMIP6 effectively reproduces precipitation patterns but exhibits biases. The frequency of compound event rises across SSPs, especially under high radiative forcing, with a stronger long-term upward trend. Furthermore, the economically developed areas, notably China’s southeastern coast and North China Plain, will be hotspots for frequent and intense compound extreme events, while other regions will see reduced exposure. Finally, in the long-term future (2070–2100), there is a noteworthy shift in population exposure to compound events, emphasizing the increasing influence of population factors over climate factors. This highlights the growing importance of interactions between population and climate in shaping exposure patterns.
River islands are sandbars formed by scouring and silting. Their evolution is affected by several factors, among which are runoff and sediment discharge. The spatial-temporal evolution of seven river islands in the Nanjing Section of the Yangtze River of China was examined using TM (Thematic Mapper) and ETM (Enhanced Thematic Mapper)+ images from 1985 to 2015 at five year intervals. The following approaches were applied in this study: the threshold value method, binarization model, image registration, image cropping, convolution and cluster analysis. Annual runoff and sediment discharge data as measured at the Datong hydrological station upstream of Nanjing section were also used to determine the roles and impacts of various factors. The results indicated that: (1) TM/ETM+ images met the criteria of information extraction of river islands; (2) generally, the total area of these islands in this section and their changing rate decreased over time; (3) sediment and river discharge were the most significant factors in island evolution. They directly affect river islands through silting or erosion. Additionally, anthropocentric influences could play increasingly important roles.
Fluvial islands are vital from both morphological and ecological perspectives and consequently have been hotspots of morphodynamic research in large rivers around the world. This study selected 14 representative fluvial islands in the lower reaches of the Yangtze River and explored their spatial-temporal evolution, including their shape and area dynamics during 1945–2016, by interpreting remote sensing images and analyzing the hydrological data. Results indicated that the total area of the 14 fluvial islands showed a growing trend at an average rate of 0.30 km 2 yr −1 during the 72 years. The island Fenghuangzhou experienced the largest change in area, while Xiaohuangzhou (XHZ) had the smallest change in area. Sediment discharge and flooding were assumed to be the primary natural factors controlling the island dynamics. Furthermore, dam construction and bank reinforcement also played a critical role in preventing shoreline collapse, improving channel conditions, and promoting the stability of fluvial islands. From 1976 to 2016, the maximum erosion occurred on the left XHZ, while the maximum accretion was found on the Qingjiezhou island. Almost the entire river section experienced an accretion process on the right bank, which was assumed to be caused by the construction of erosion control structures. Besides, the dynamics of the fluvial islands along the lower Yangtze River appears to follow the erosion processes of the river bank. Our findings can provide an important reference for sustainable utilization and management of fluvial islands.
The development of rural communication improves the socialization of young people in rural areas,but in the same time the insufficient rural communication also restricts the development of rural youth socialization.Rural youth is an important force in the construction of new countryside.Therefore,developing rural communication scientifically plays a significant and realistic role in the constant improvement of the socialization level of rural youth and training them into builders of spiritual civilization,creators of a well-off life,practitioner and beneficiary of democratic politics and the major force in the construction of new countryside.
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