| 2 | Small water bodies in China:Spatial distribution and influencing factors显示文摘Inland water bodies,including ponds,lakes,reservoirs,and rivers,provide extensive ecosystem services for human beings.Among these,small water bodies(SWBs),such as ponds and small reservoirs,are more common landscape features and important biogeochemical reactors.SWBs can significantly influence biogeochemical processes and hydrologic cycles.However,due to their small size,SWBs(<10 ha)have been largely ignored in natural resource surveys,leading to a limited understanding of their spatial distribution in China.Insufficient geospatial datasets of SWBs limit the accurate assessments of resource utilization and fluxes of biogenic elements in both aquatic and terrestrial ecosystems.To address this,in this study,we applied a convolutional neural network and a visual interpretation approach to extract SWBs from high-resolution satellite images from Google Earth.The spatial distribution of SWBs in China was mapped,and drivers of the spatial pattern of SWBs were also identified.As a result,a total of 5.18 million water bodies with a surface area larger than 0.1 ha,including ponds,lakes,and reservoirs,were identified.These water bodies(>0.1 ha)cover approximately 179300 km^(2),which is approximately 1.8%of the land area in China.In addition,the combined shoreline length of the water bodies was approximately 2157400 km.Of these water bodies,96.85%were SWBs,accounting for 17.85%of the total water area and 76.4% of the total shoreline length.Precipitation,terrain,and human activity cumulatively explained 45% of the variance in SWB distribution,with precipitation being the strongest climatic explanatory factor.Our results provide important data for determining the roles of SWBs in biogeochemical cycles,habitat protection,and hydrological cycles. | Mingquan LV Shengjun WU Maohua MA Ping HUANG Zhaofei WEN Jilong CHEN | 2022 | Science China Earth Sciences2022，65，8： | 1 |
| 3 | Urban water system theory and its model development and application显示文摘The urban water system theory is an extension of the basin water system science on an urban scale, providing a new systematic solution for the unbalanced human-water relationship and severe water challenges, such as waterlogging, black and odorous water, and ecological degradation caused by urbanization. Most existing studies on urban water systems have focused on individual water cycle processes linked with water supply and sewage treatment plants, but mutual feedback between the water cycle and its associated material circulation and water ecology, as well as human processes, still needs further exploration. In this paper, the concept, theory, and technical methodology of the urban water system were developed based on the water cycle and basin water system science. The Urban Water System 5.0(UWS 5.0) model was developed by integrating the Time Variant Gain rainfall-runoff Model with Urban water system(TVGM_Urban) in different underlying surface conditions for analyzing the natural-social water cycle processes and their associated water environmental and ecological processes and the influence of multiscale sponge measures. Herein, five major simulation functions were realized: rainfall-runoff-nonpoint source pollutant load,water and pollutant transportations through the drainage network system, terminal regulation and purification, socioeconomic water cycle, and water system assessment and regulation. The location for the case study used in this paper was Wuhan City. The findings showed that the entire urban water system should consider the built-up area and its associated rivers and lakes as the research object and explore the integrations among the urban natural-social water cycle and river regulations inside and outside of the city as well as the effects of socioeconomic development and sponge measures on the water quantity-quality-ecology processes. The UWS 5.0 model efficiently simulated the urban rainfall-runoff process, total nitrogen(TN) and total phosphorus(TP) concentrations in water bodies, and characteristic indicators of socioeconomic development. For the rainfall-runoff simulations, the correlation coefficient and Nash-Sutcliffe efficiency(NSE) fall under the excellent and good classes, respectively. For the TN and TP concentration simulations, results exhibited good bias and the correlation coefficients exceeded 0.90 for 78.1% of the sampled sites. The simulation of 18 socioeconomic indicators provided excellent bias, correlation coefficient, and NSE values of 100%, 83.3%, and 69.4% to total indicators, respectively. Based on the well-calibrated UWS 5.0 model, the source sponge,artificial enhancement, and source reduction-path interception-terminal treatment measures were optimized, which considerably mitigated waterlogging, black and odorous water, and lake eutrophication, respectively. The mitigation performance revealed that the maximum inundated area for a once-in-10-year rainfall event was reduced by 32.6%, the removal ratio of the black and odorous water area was 65%, the comprehensive trophic state index of water bodies was reduced by 37%, and the green development level of Wuhan City in 2020 increased from 0.56 to 0.67. This study is expected to advance the intersection and development of multidisciplinary fields(e.g., urban hydrology, environmental science, and ecology) and offer an important theoretical and technical basis for solving urban complex water issues and promoting green development of cities. | Jun XIA Yongyong ZHANG Dunxian SHE Shiyan ZHANG Jun YANG Mingquan LV Xiang ZHANG Anqi LUO Shengjun WU Yang LIU | 2024 | Science China Earth Sciences2024，67，3： | 0 |
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