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Impact of land use/land cover types on surface humidity in northern China in the early 21st century

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Abstract

In the context of global change, it is essential to promote the rational development and utilization of land resources, improve the quality of regional ecological environment, and promote the harmonious development of human and nature for the regional sustainability. We identified land use/land cover types in northern China from 2001 to 2018 with ENVI images and ArcGIS software. Meteorological data were selected from 292 stations in northern China, the potential evapotranspiration was calculated with the Penman—Monteith formula, and reanalysis humidity and observed humidity data were obtained. The reanalysis minus observation (RMO, i.e., the difference between reanalysis humidity and observed humidity) can effectively characterize the impact of different land use/land cover types (forestland, grassland, cultivated land, construction land, water body and unused land) on surface humidity in northern China in the early 21st century. The results showed that from 2001 to 2018, the area of forestland expanded (increasing by approximately 1.80×104 km2), while that of unused land reduced (decreasing by approximately 5.15×104 km2), and the regional ecological environment was improved. Consequently, land surface in most areas of northern China tended to be wetter. The contributions of land use/land cover types to surface humidity changes were related to the quality of the regional ecological environment. The contributions of the six land use/land cover types to surface humidity were the highest in northeastern region of northern China, with a better ecological environment, and the lowest in northwestern region, with a fragile ecological environment. Surface humidity was closely related to the variation in regional vegetation coverage; when the regional vegetation coverage with positive (negative) contributions expanded (reduced), the land surface became wetter. The positive contributions of forestland and water body to surface humidity were the greatest. Unused land and construction land were associated with the most serious negative contributions to surface humidity. Affected by the regional distribution pattern of vegetation, surface humidity in different seasons decreased from east to west in northern China. The seasonal variation in surface humidity was closely related to the growth of vegetation: surface humidity was the highest in summer, followed by autumn and spring, and the lowest in winter. According to the results, surface humidity is expected to increase in northeastern region of northern China, decrease in northern region, and likely increase in northwestern region.

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References

  • Allen R G, Jensen M E, Wright J L, et al. 1989. Operational estimates of reference evapotranspiration. Agronomy Journal, 81(4): 650–662.

    Article  Google Scholar 

  • Allen R G, Pereira L S, Raes D, et al. 1998. Crop evapotranspiration: guidelines for computing crop water requirements. Fao Irrigation and Drainage Paper 56. Rome: Food and Agriculture Organization of the United Nations.

    Google Scholar 

  • Bian J C, Chen H B, Vömel H, et al. 2011. Intercomparison of humidity and temperature sensors: GTS1, Vaisala RS80, and CFH. Advances in Atmospheric Sciences, 28(1): 139–146.

    Article  Google Scholar 

  • Bian J J, Hao Z X, Zheng J Y, et al. 2013. The shift on boundary of climate regionalization in China from 1951 to 2010. Geographical Research, 32(7): 1179–1187. (in Chinese)

    Google Scholar 

  • Bian X H, Liu Y, Ding Q Q, et al. 2019. Response of land use and cover change to urban heat island effect in Huzhou City, Zhejiang Province. Bulletin of Soil and Water Conservation, 39(3): 263–269. (in Chinese)

    Google Scholar 

  • Braswell B H, Schimel D S, Linder E, et al. 1997. The response of global terrestrial ecosystems to interannual temperature variability. Science, 278(5339): 870–873.

    Article  CAS  Google Scholar 

  • Buitenwerf R, Rose L, Higgins S I. 2015. Three decades of multi-dimensional change in global leaf phenology. Nature Climate Change, 5(4): 364–368.

    Article  Google Scholar 

  • Cao L J, Zhang D F, Zhang Y, et al. 2010. Sensitivity research of the effects of land use change on climate and runoff over the Yangtze River basin. Chinese Journal of Atmospheric Sciences, 34(4): 726–736. (in Chinese)

    Google Scholar 

  • Dai X Q, Shen R Q, Wang J, et al. 2021. Change detection of land use in Henan Province based on GEE remote sensing cloud platform. Journal of Geomatics Science and Technology, 38(3): 287–294.

    Google Scholar 

  • Du Y D, Liu Z X, Zhang Y F. 2001. Evaluaiton of two reference crop evapotranspiration calculation methods. Journal of Henan Agricultural University, 35(1): 57–61. (in Chinese)

    Google Scholar 

  • Dumont B, Andueza D, Niderkorn V, et al. 2015. A meta-analysis of climate change effects on forage quality in grasslands: specificities of mountain and M editerranean area. Grass and Forage Science, 70(2): 239–254.

    Article  CAS  Google Scholar 

  • Fezzi C, Harwood A R, Lovett A A, et al. 2015. The environmental impact of climate change adaptation on land use and water quality. Nature Climate Change, 5(3): 255–260.

    Article  Google Scholar 

  • Fu B J, Yu D D, Lü N. 2017. An indicator system for biodiversity and ecosystem services evaluation in China. Acta Ecologica Sinica, 37(2): 341–348. (in Chinese)

    Google Scholar 

  • Gao J B, Jiao K W, Wu S H. 2019. Investigating the spatially heterogeneous relationships between climate factors and NDVI in China during 1982 to 2013. Journal of Geographical Sciences, 29(10): 1597–1609.

    Article  Google Scholar 

  • Han H Q, Zhang C Q, Wang Y, et al. 2019. Spatial-temporal variation and influencing factors of dry and wet condition in Guizhou Province between 1961 and 2014. Journal of Shanxi Agricultural University (Nature Science Edition), 39(4): 106–112. (in Chinese)

    Google Scholar 

  • Hua W J, Chen H S, Li X. 2014. Review of land use and land cover change in China and associated climatic effects. Advances in Earth Science, 29(9): 1025–1036. (in Chinese)

    Google Scholar 

  • Hulme M, Marsh R, Jones P D. 1992. Global changes in a humidity index between 1931–1960 and 1961–1990. Climate Research, 2: 1–22.

    Article  Google Scholar 

  • Hurtt G C, Chini L P, Frolking S, et al. 2011. Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Climatic Change, 109(1–2): 117–161.

    Article  Google Scholar 

  • IPCC. 2019. Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Shukla P R, Skea J, Calvo Buendia E, et al. (eds.). [2021-08-12]. https://spiral.imperial.ac.uk/handle/10044/1/76618.

  • Jia Y Q, Zhang B. 2019. Relationship of dry-wet climate changes in Northern China in the past 57 years with Pacific Decadal Oscillation (PDO). Acta Pedologica Sinica, 56(5): 1085–1097. (in Chinese)

    Google Scholar 

  • Jing Y Q, Zhang F, Chen L H, et al. 2017. Investigation on eco-environmental effects of land use/cover-landscape pattern and climate change in Ebinur Lake Wetland Nature Reserve. Acta Scientiae Circumstantiae, 37(9): 3590–3601. (in Chinese)

    CAS  Google Scholar 

  • Kalnay E, Cai M. 2003. Impact of urbanization and land-use change on climate. Nature, 423: 528–531.

    Article  CAS  Google Scholar 

  • Kaufmann R K, Seto K C, Schneider A, et al. 2007. Climate response to rapid urban growth: Evidence of a human-induced precipitation deficit. Journal of Climate, 20: 2299–2306.

    Article  Google Scholar 

  • Lai L, Huang X, Yang H, et al. 2016. Carbon emissions from land-use change and management in China between 1990 and 2010. Science Advances, 2(11): e1601063, doi: https://doi.org/10.1126/sciadv.1601063.

    Article  Google Scholar 

  • Li S Y, Chen H B, Li W. 2008. The impact of urbanization on city climate of Beijing region. Plateau Meteorology, 27(5): 1102–1110. (in Chinese)

    Google Scholar 

  • Li S Y, Liu X P, Li X, et al. 2017. Simulation model of land use dynamics and application: progress and prospects. Journal of Remote Sensing, 21(3): 329–340. (in Chinese)

    Google Scholar 

  • Lin L, Fan H, Jin Y. 2020. Multi-scale and multi-model simulation of land use/land cover change in the mountainous county: A case study of Mengla County in Yunnan Province, China. Mountain Research, 38(4): 630–642. (in Chinese)

    Google Scholar 

  • Liu J Y, Zhang Z X, Xu X L, et al. 2010. Spatial patterns and driving forces of land use change in China during the early 21st century. Journal of Geographical Sciences, 20(4): 483–494.

    Article  Google Scholar 

  • Liu J Y, Kuang W H, Zhang Z X, et al. 2014. Spatiotemporal characteristics, patterns and causes of land use changes in China since the late 1980s. Acta Geographica Sinica, 69(1): 3–14. (in Chinese)

    Google Scholar 

  • Luo Q H, Ning H S, Chen Q M. 2016. Trends of surface dry-wet state of Ganjiahu in Xinjiang based on humid index. Arid Zone Research, 33(5): 921–926. (in Chinese)

    Google Scholar 

  • Mao F, Sun H, Yang H L. 2011. Research progress in dry/wet climate zoning. Progress in Geography, 30(1): 17–26. (in Chinese)

    CAS  Google Scholar 

  • Mao R X, Chen G, Zhang S Q. 2017. Several problems in the construction of the Three-North Shelter Forest Program and suggestions for its countermeasures. Protection Forest Science and Technology, (10): 58–59, 61. (in Chinese)

  • Mooney H A, Duraiappah A, Larigauderie A. 2013. Evolution of natural and social science interactions in global change research programs. Proceedings of the National Academy of Sciences of the United States of America, 110(Suppl 1): 3665–3672.

    Article  CAS  Google Scholar 

  • National Research Council. 2005. Radiative Forcing of Climate Change: Expanding the Concept and Addressing Uncertainties. Washington D.C.: National Academies Press, 1–208.

    Google Scholar 

  • Oleson K, Bonan G Feddema J, et al. 2008. An urban parameterization for a global climate model. Part I: Formulation and evaluation for two cities. Journal of Applied Meteorology and Climatology, 47(4): 1038–1060.

    Article  Google Scholar 

  • Pitman A J, Noblet-Ducoudé N, Cruz F T, et al. 2009. Uncertainties in climate responses to past land cover change: First results from the LUCID intercomparison study. Geophysical Research Letters, 36(14): L14814, doi: https://doi.org/10.1029/2009GL039076.

    Article  Google Scholar 

  • Shao P, Zeng X D. 2012. Progress in the study of the effects of land use and land cover change on the climate system. Climatic and Environmental Research, 17(1): 103–111. (in Chinese)

    Google Scholar 

  • Sterling S M, Ducharne A, Polcher J. 2012. The impact of global land-cover change on the terrestrial water cycle. Nature Climate Change, 3(4): 385–390.

    Article  Google Scholar 

  • Sun L, Wu G X, Sun S F. 2000. Numerical simulations of effects of land surface processes on climate implementing of SSiB in IAP/LASG AGCM L9R15 and its performance. Acta Meteorologica Sinica, 58(2): 179–193. (in Chinese)

    Google Scholar 

  • Sun Q, Qi W, Yu X Y. 2021. Impacts of land use change on ecosystem services in the intensive agricultural area of North China based on Multi-scenario analysis. Alexandria Engineering Journal, 60(1): 1703–1716.

    Article  Google Scholar 

  • Tian H Q, Chen G, Zhang C, et al. 2012. Century-scale response of ecosystem carbon storage to multifactorial global change in the Southern United States. Ecosystems, 15: 674–694.

    Article  CAS  Google Scholar 

  • Tuffour-Mills D, Antwi-Agyei P, Addo-Fordjour P. 2020. Trends and drivers of land cover changes in a tropical urban forest in Ghana. Trees, Forests and People, 2, doi: https://doi.org/10.1016/j.tfp.2020.100040.

  • Verbeeck H, Kearsley E. 2015. The importance of including lianas in global vegetation models. Proceedings of the National Academy of Sciences of the United States of America, 113(1): E4, doi: https://doi.org/10.1073/pnas.1521343113.

    Google Scholar 

  • Wang J H, Zhang L Y. 2008. Systematic errors in global radiosonde precipitable water data from comparisons with ground-based GPS measurements. Journal of Climate, 21(10): 2218–2238.

    Article  Google Scholar 

  • Wang M N, Ha Z, Zhang Q Y. 2016. Impact of land use and cover change in the semi-arid regions of China on the temperature in the early 21st century. Climatic and Environmental Research, 21(1): 65–77. (in Chinese)

    Google Scholar 

  • Wang Q, Zhang Q P, Zhou W. 2012. Grassland coverage changes and analysis of the driving forces in Maqu County. Physics Procedia, 33: 1292–1297.

    Article  Google Scholar 

  • Wang X L, Liu Y, Zhang Y, et al. 2021. Exploration and prediction of land use/cover change in western Jilin province based on Ca-markov model. Science Technology and Engineering, 21(19): 7942–7948. (in Chinese)

    Google Scholar 

  • Weinert M, Mathis M, Kröncke I, et al. 2016. Modelling climate change effects on benthos: Distributional shifts in the North Sea from 2001 to 2099. Estuarine, Coastal and Shelf Science, 175(20): 157–168.

    Article  Google Scholar 

  • Yang X C, Zhang Y L, Liu L S, et al. 2009. Sensitivity of surface air temperature change to land types in China. Science in China Series D-Earth Sciences, 52(8): 1207–1215.

    Article  Google Scholar 

  • Yao W, Ma Y, Gao L N. 2017. Comparison of relative humidity data between L-band and 59–701 sounding system. Journal of Applied Meteorological Science, 28(2): 218–226. (in Chinese)

    Google Scholar 

  • Yuan Q Z, Wu S H, Dai E F, et al. 2017. Spatio-temporal variation of the wet-dry conditions from 1961–2015 in China. Science China: Earth Sciences, 47(11): 1339–1348.

    Google Scholar 

  • Zhang C L, Chen F, Miao S G, et al. 2009. Impacts of urban expansion and future green planting on summer precipitation in the Beijing metropolitan area. Journal of Geophysical Research, 114: D02116, doi: https://doi.org/10.1029/2008JD010328.

    Google Scholar 

  • Zhang X R, Song W, Lang Y Q, et al. 2020. Land use changes in the coastal zone of China’s Hebei Province and the corresponding impacts on habitat quality. Land Use Policy, 99, doi: https://doi.org/10.1016/j.landusepol.2020.104957.

  • Zhang Z X, Liu L M, Jia Y, et al. 2009. Climatic ecological adaptation of shelter forests in Three-North Regions. Chinese Journal of Ecology, 28(9): 1696–1701. (in Chinese)

    Google Scholar 

  • Zhao N, Liu S H, Yu H Y. 2011. Urbanization effects on local climate in Beijing in recent 48 years. Chinese Journal of Atmospheric Sciences, 35(2): 373–385. (in Chinese)

    Google Scholar 

  • Zheng S Y, Liu S H. 2008. Urbanization effect on climate in Beijing. Climate and Environmental Research, 13(2): 123–133. (in Chinese)

    Google Scholar 

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Acknowledgements

This study was funded by the National Natural Science Foundation of China (42071112, 41771110). We thank the editors and anonymous reviewers whose insights and suggestions have greatly improved this manuscript.

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Correspondence to Shuyan Yin.

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Jin, J., Yin, S. & Yin, H. Impact of land use/land cover types on surface humidity in northern China in the early 21st century. J. Arid Land 14, 705–718 (2022). https://doi.org/10.1007/s40333-022-0055-3

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