Soil moisture(SM)is a critical variable in terrestrial ecosystems,especially in arid and semi-arid areas where water sources are limited.Despite its importance,understanding the spatiotemporal variations and influenci...Soil moisture(SM)is a critical variable in terrestrial ecosystems,especially in arid and semi-arid areas where water sources are limited.Despite its importance,understanding the spatiotemporal variations and influencing factors of SM in these areas remains insufficient.This study investigated the spatiotemporal variations and influencing factors of SM in arid and semi-arid areas of China by utilizing the extended triple collation(ETC),Mann-Kendall test,Theil-Sen estimator,ridge regression analysis,and other relevant methods.The following findings were obtained:(1)at the pixel scale,the long-term monthly SM data from the European Space Agency Climate Change Initiative(ESA CCI)exhibited the highest correlation coefficient of 0.794 and the lowest root mean square error(RMSE)of 0.014 m^(3)/m^(3);(2)from 2000 to 2022,the study area experienced significant increase in annual average SM,with a rate of 0.408×10^(-3)m^(3)/(m^(3)•a).Moreover,higher altitudes showed a notable upward trend,with SM increasing rates at 0.210×10^(-3)m^(3)/(m^(3)•a)between 1000 and 2000 m,0.530×10^(-3)m^(3)/(m^(3)•a)between 2000 and 4000 m,and 0.760×10^(-3)m^(3)/(m^(3)•a)at altitudes above 4000 m;(3)land surface temperature(LST),root zone soil moisture(RSM)(10-40 cm depth),and normalized difference vegetation index(NDVI)were identified as the primary factors influencing annual average SM,which accounted for 34.37%,24.16%,and 22.64%relative contributions,respectively;and(4)absolute contribution of LST was more significant in subareas at higher altitudes,with average absolute contributions of 0.800×10^(-3)m^(3)/(m^(3)•a)between 2000 and 4000 m and 0.500×10^(-2) m^(3)/(m^(3)•a)above 4000 m.This study reveals the spatiotemporal variations and main influencing factors of SM in Chinese arid and semi-arid areas,highlighting the more pronounced absolute contribution of LST to SM in high-altitude areas,providing valuable insights for ecological research and water resource management in these areas.展开更多
Clean-energy substitution technology for existing residential buildings in cities is an inevitable choice for sustainable development and low-carbon ecological city construction.In this paper,the current status of ene...Clean-energy substitution technology for existing residential buildings in cities is an inevitable choice for sustainable development and low-carbon ecological city construction.In this paper,the current status of energy-saving renovation and renewable-energy applications for existing residential buildings in various cities in China was summarized by using statistical methods.The geographical distribution of clean-energy power generation in primary energy production in China was explored in depth.According to different climatic divisions for existing urban residences,clean-energy production and consumption were analyzed and predicted based on the STIRPAT model.The results show that the energy consumption of urban residential buildings in 2016 increased by 43.6%compared with 2009,and the percentage of clean energy also increased from 7.9%to 13.4%.Different climatic regions have different advantages regarding clean energy:nuclear power generation leads in the region that experiences hot summers and warm winters,whereas wind and solar power generation lead in the cold and severely cold regions.The present results provide basic data support for the planning and implementation of clean-energy upgrading and transformation systems in existing urban residences in China.展开更多
基金supported by the Natural Science Foundation of Henan Province(252300421290)the National Natural Science Foundation of China(41771438)+1 种基金the Program for Innovative Research Team(in Science and Technology)of Henan University(22IRTSTHN010)the Postgraduate Education Reform and Quality Improvement Project of Henan Province(HNYJS2020JD14).
文摘Soil moisture(SM)is a critical variable in terrestrial ecosystems,especially in arid and semi-arid areas where water sources are limited.Despite its importance,understanding the spatiotemporal variations and influencing factors of SM in these areas remains insufficient.This study investigated the spatiotemporal variations and influencing factors of SM in arid and semi-arid areas of China by utilizing the extended triple collation(ETC),Mann-Kendall test,Theil-Sen estimator,ridge regression analysis,and other relevant methods.The following findings were obtained:(1)at the pixel scale,the long-term monthly SM data from the European Space Agency Climate Change Initiative(ESA CCI)exhibited the highest correlation coefficient of 0.794 and the lowest root mean square error(RMSE)of 0.014 m^(3)/m^(3);(2)from 2000 to 2022,the study area experienced significant increase in annual average SM,with a rate of 0.408×10^(-3)m^(3)/(m^(3)•a).Moreover,higher altitudes showed a notable upward trend,with SM increasing rates at 0.210×10^(-3)m^(3)/(m^(3)•a)between 1000 and 2000 m,0.530×10^(-3)m^(3)/(m^(3)•a)between 2000 and 4000 m,and 0.760×10^(-3)m^(3)/(m^(3)•a)at altitudes above 4000 m;(3)land surface temperature(LST),root zone soil moisture(RSM)(10-40 cm depth),and normalized difference vegetation index(NDVI)were identified as the primary factors influencing annual average SM,which accounted for 34.37%,24.16%,and 22.64%relative contributions,respectively;and(4)absolute contribution of LST was more significant in subareas at higher altitudes,with average absolute contributions of 0.800×10^(-3)m^(3)/(m^(3)•a)between 2000 and 4000 m and 0.500×10^(-2) m^(3)/(m^(3)•a)above 4000 m.This study reveals the spatiotemporal variations and main influencing factors of SM in Chinese arid and semi-arid areas,highlighting the more pronounced absolute contribution of LST to SM in high-altitude areas,providing valuable insights for ecological research and water resource management in these areas.
基金This research was funded by the National Key Research and Development Plan(2018YFC0704800).
文摘Clean-energy substitution technology for existing residential buildings in cities is an inevitable choice for sustainable development and low-carbon ecological city construction.In this paper,the current status of energy-saving renovation and renewable-energy applications for existing residential buildings in various cities in China was summarized by using statistical methods.The geographical distribution of clean-energy power generation in primary energy production in China was explored in depth.According to different climatic divisions for existing urban residences,clean-energy production and consumption were analyzed and predicted based on the STIRPAT model.The results show that the energy consumption of urban residential buildings in 2016 increased by 43.6%compared with 2009,and the percentage of clean energy also increased from 7.9%to 13.4%.Different climatic regions have different advantages regarding clean energy:nuclear power generation leads in the region that experiences hot summers and warm winters,whereas wind and solar power generation lead in the cold and severely cold regions.The present results provide basic data support for the planning and implementation of clean-energy upgrading and transformation systems in existing urban residences in China.
