Impacts of Climate Change and Land Use/Cover Change on Runoff in the Huangfuchuan River Basin DOI Creative Commons
Xin Huang, Lin Qiu

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2048 - 2048

Published: Nov. 29, 2024

Studying the response of runoff to climate change and land use/cover has guiding significance for watershed planning, water resource ecological environment protection. Especially in Yellow River Basin, which a variable fragile ecology, such research is more important. This article takes Huangfuchuan Basin (HFCRB) middle reaches as area, analyzes impact scenarios on by constructing SWAT model. Using CMIP6 GCMs obtain future data CA–Markov model predict use data, two are coupled estimate process HFCRB, uncertainty estimated decomposed quantified. The results were follows: ① good adaptability HFCRB. During calibrated period validation period, R2 ≥ 0.84, NSE 0.8, |PBIAS| ≤ 17.5%, all meet evaluation criteria. ② There negative correlation between temperature runoff, positive precipitation runoff. Runoff sensitive rise increase. ③ types order cultivated > grassland forest land. ④ variation range under combined effects LUCC that single or scenarios. increase SSP126, SSP245, SSP585 10.57%, 25.55%, 31.28%, respectively. Precipitation main factor affecting changes Model source prediction.

Language: Английский

Characterizing and predicting carbon emissions from an emerging land use perspective: A comprehensive review DOI
Haizhi Luo, Zhengguang Liu, Yingyue Li

et al.

Urban Climate, Journal Year: 2024, Volume and Issue: 58, P. 102141 - 102141

Published: Nov. 1, 2024

Language: Английский

Citations

5
Study on landscape pattern changes and their correlation with ecosystem services in intensely human-disrupted basins: evidence from China’s Maotiao River DOI
Huiqing Han, Ying-jia Zhang,

Yuanju Jian

et al.

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(5)

Published: April 25, 2025

Language: Английский

Citations

0
Trends in Emissions from Road Traffic in Rapidly Urbanizing Areas DOI Open Access

Yinuo Xu,

Dawei Weng,

Shuo Wang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7400 - 7400

Published: Aug. 28, 2024

The process of urbanization has facilitated the exponential growth in demand for road traffic, consequently leading to substantial emissions CO2 and pollutants. However, with development expansion network, distribution emission characteristics pollutant are still unclear. In this study, a bottom-up approach was initially employed develop high-resolution inventories (NOx, CO, HC) from primary, secondary, trunk, tertiary roads rapidly urbanizing regions China based on localized factor data. Subsequently, standard length method utilized analyze spatiotemporal across different networks while exploring their heterogeneity. Finally, influence elevation surface vegetation cover traffic-related taken into consideration. results indicated that CO2, HC, NOx increased significantly 2020 compared those 2017 trunk roads, Fuzhou uneven; 2017, areas high were predominantly concentrated central low coverage levels topography but expanded 2020. This study enhances our comprehension variations carbon resulting regional network expansion, offering valuable insights case studies worldwide undergoing similar infrastructure development.

Language: Английский

Citations

1
Impacts of Climate Change and Land Use/Cover Change on Runoff in the Huangfuchuan River Basin DOI Creative Commons
Xin Huang, Lin Qiu

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2048 - 2048

Published: Nov. 29, 2024

Studying the response of runoff to climate change and land use/cover has guiding significance for watershed planning, water resource ecological environment protection. Especially in Yellow River Basin, which a variable fragile ecology, such research is more important. This article takes Huangfuchuan Basin (HFCRB) middle reaches as area, analyzes impact scenarios on by constructing SWAT model. Using CMIP6 GCMs obtain future data CA–Markov model predict use data, two are coupled estimate process HFCRB, uncertainty estimated decomposed quantified. The results were follows: ① good adaptability HFCRB. During calibrated period validation period, R2 ≥ 0.84, NSE 0.8, |PBIAS| ≤ 17.5%, all meet evaluation criteria. ② There negative correlation between temperature runoff, positive precipitation runoff. Runoff sensitive rise increase. ③ types order cultivated > grassland forest land. ④ variation range under combined effects LUCC that single or scenarios. increase SSP126, SSP245, SSP585 10.57%, 25.55%, 31.28%, respectively. Precipitation main factor affecting changes Model source prediction.

Language: Английский

Citations

0