Effects of Land Use and Land Cover Change on Temperature in Summer over the Yellow River Basin, China

Ru, Xutong; Song, Hongquan; Xia, Haoming; Zhai, Shiyan; Wang, Yaobin; Min, Ruiqi; Zhang, Haopeng; Qiao, Longxin

doi:10.3390/rs14174352

Cited by 7 publications

(3 citation statements)

References 76 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 2 shows the performance statistics for the validation of Mean Bias (MB), Normalized Mean Bias (NMB), Normalized Mean Error (NME), Root Mean Square Error (RMSE), and correlation coefficient (R) in 2020 regarding temperature (T2) and precipitation, which have similarities with the performance in other previous WRF model studies [37][38][39]. The high correlation coefficients between observed and simulated data for temperature (0.77 to 0.93) and precipitation (0.46 to 0.9) indicate that the WRF model configuration can simulate temperature and precipitation in the study area well.…”

Section: Scenario and Model Descriptionmentioning

confidence: 70%

Effects of Land Use/Cover and Meteorological Changes on Regional Climate under Different SSP-RCP Scenarios: A Case Study in Zhengzhou, China

et al. 2023

Self Cite

View full text Add to dashboard Cite

To better understand the possible role of projected land use and cover change (LUCC) in future regional climate projections, we explored the regional climate change response from land use/cover change under different climate scenarios. To do so, we propose a research framework based on different SSP-RCPs to simulate and explore the impacts of future land use/cover changes on the future climate of Zhengzhou City, China, using the Weather Research and Forecasting (WRF) model with land use/cover and meteorological data under different SSP-RCP scenarios based on CMIP6. Two scenarios, SSP2-4.5 and SSP5-8.5, were compared and analyzed by simulating changes in future climate factors of temperature at 2 m height above ground(T2) and precipitation. The results show that T2 is higher for all 4 months by the year 2060 compared to that in the year 2030. Furthermore, a comparison of the abovementioned years showed that the mean temperatures of January and July were higher than those of SSP2-4.5 under the SSP5-8.5 scenario in both years, but in 2030, the mean T2 of April and October were lower than those of SSP2-4.5 under the SSP5-8.5 scenario. In terms of precipitation, both scenarios have no significant precipitation in July in 2030 and 2060, but there is an unusual increase in January and October.

show abstract

Section: Scenario and Model Descriptionmentioning

confidence: 70%

Effects of Land Use/Cover and Meteorological Changes on Regional Climate under Different SSP-RCP Scenarios: A Case Study in Zhengzhou, China

et al. 2023

Self Cite

View full text Add to dashboard Cite

show abstract

“…Due to the limited availability of observational data on surface dust emissions and the high concentration of coarse particulate pollutants during dust weather events, we compared the measurements of coarse PM concentration (PM 10‐2.5 ) with the simulated values to assess the performance of the WRF‐Chem model. To evaluate the meteorological and pollutant simulation results, we employed five statistical metrics: mean bias (MB), normalized mean bias (NMB), normalized mean error (NME), root mean square error (RMSE), and correlation coefficient (R) (Ru et al, 2022; Song et al, 2017; Zhang, Wang, et al, 2022). The calculation method for these statistical metrics can be found in Table 2.…”

Section: Methodsmentioning

confidence: 99%

Impacts of land cover changes on dust emissions in northern China (2000–2020)

Song,

Min,

Song

et al. 2024

Land Degrad Dev

Self Cite

View full text Add to dashboard Cite

Land cover is a key factor affecting dust emissions. Substantial changes in land cover have occurred due to human activities and climate change in northern China. However, the extent to which these changes influence dust emissions is still controversial. Here, we explored the specific impact of land use type transformation on dust emissions between 2000 and 2020 by using the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) from the perspective of land cover changes. Two scenarios were set up and compared to quantify this impact. One scenario was using the land cover data in 2000, and the other scenario was to use the land cover data in 2020. Both scenarios were driven by the initial meteorological conditions in 2020. Results indicated that the land cover changes between 2000 and 2020 reduced dust emissions in northern China, but the weakened intensity showed obvious spatial differences. Different land use conversion types had significant differences in their impact on dust emissions. Transforming bare areas to water bodies can reduce dust emissions by up to −3.62 g m−2 year−1. This is followed by the change from bare areas to sparse vegetation areas, which can decrease dust emissions by −2.9 g m−2 year−1, and then by the conversion from bare areas to cropland, with a reduction of −2.57 g m−2 year−1. These findings can offer methodologies and data support for the quantitative evaluation of the effects of land cover changes on dust emissions. They can also serve as a reference for environmental management when formulating land use policies.

show abstract

“…It provides a large amount of digital land use and ecological change information, so high-resolution satellite remote sensing images are widely used in land use, ecological environment investigations and dynamic monitoring research [8]. The process of land use change has a significant influence on ecosystem services and ecological landscape patterns [9][10][11]. Habitat patches, network structure, rational urban land use, and the development of species are closely related to regional land use structure and spatial layout changes [12].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Sustainability Impacts of the Xiaolangdi Dam: Land Use and Socioeconomic Change in the Middle and Lower Reaches of the Yellow River Basin

Wang,

Xi,

Sun

et al. 2023

Sustainability

View full text Add to dashboard Cite

This paper assesses the sustainability impacts in the middle and lower reaches of the Yellow River in China after the Xiaolangdi Dam was constructed. Based on land use data interpreted from Landsat remote sensing images, covering the time period from 2000 to 2020 at 5-year intervals, this research uses a land dynamic attitude index and comprehensive index of land use degree to reveal the degree of land use type change in the study area and analyze the relationship between land use and social economy. The results show that urban and rural construction land is the land use type with the largest annual change rate, and the increase is most obvious from 2005 to 2010, growing by nearly 900 km2. The six types of land use in the research area changed sharply from 2000 to 2010, with grassland and unused land showing the most significant change. On the whole, the dynamic attitude of comprehensive land use tends to be stable. The comprehensive index analysis of land use degree indicates that the study area has developed in the direction of urban settlement. Population and GDP are the main driving factors affecting the constant change in land use types in this region, in which population growth and rapid economic development are the main factors leading to the decline of grassland area, and are also the main driving factors for the expansion of construction land. The research results provide a scientific basis for sustainable land use and development in the middle and lower reaches of the Yellow River Basin.

show abstract

Effects of Land Use and Land Cover Change on Temperature in Summer over the Yellow River Basin, China

Cited by 7 publications

References 76 publications

Effects of Land Use/Cover and Meteorological Changes on Regional Climate under Different SSP-RCP Scenarios: A Case Study in Zhengzhou, China

Effects of Land Use/Cover and Meteorological Changes on Regional Climate under Different SSP-RCP Scenarios: A Case Study in Zhengzhou, China

Impacts of land cover changes on dust emissions in northern China (2000–2020)

Assessing the Sustainability Impacts of the Xiaolangdi Dam: Land Use and Socioeconomic Change in the Middle and Lower Reaches of the Yellow River Basin

Contact Info

Product

Resources

About