Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).
Google Scholar
MacDicken, K. G. Global forest resources assessment 2015: what, why and how? For. Ecol. Manag. 352, 3–8 (2015).
Li, M.-M. et al. An overview of the “Three-North” Shelterbelt project in China. Forestry Stud. China 14, 70–79 (2012).
Google Scholar
Zhang, P. et al. China’s forest policy for the 21st century. Science 288, 2135–2136 (2000).
Google Scholar
Chen, Y. et al. Balancing green and grain trade. Nat. Geosci. 8, 739–741 (2015).
Google Scholar
Xu, J., Yin, R., Li, Z. & Liu, C. China’s ecological rehabilitation: unprecedented efforts, dramatic impacts, and requisite policies. Ecol. Econ. 57, 595–607 (2006).
Piao, S., Fang, J., Liu, H. & Zhu, B. NDVI-indicated decline in desertification in China in the past two decades. Geophys. Res. Lett. 32, L06402 (2005).
Google Scholar
Wang, X., Chen, F., Hasi, E. & Li, J. Desertification in China: an assessment. Earth Sci. Rev. 88, 188–206 (2008).
Google Scholar
Ouyang, Z. et al. Improvements in ecosystem services from investments in natural capital. Science 352, 1455–1459 (2016).
Google Scholar
Bryan, B. A. et al. China’s response to a national land-system sustainability emergency. Nature 559, 193–204 (2018).
Google Scholar
Feng, X. et al. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nat. Clim. Chang. 6, 1019–1022 (2016).
Google Scholar
Cao, S., Zhang, J., Chen, L. & Zhao, T. Ecosystem water imbalances created during ecological restoration by afforestation in China, and lessons for other developing countries. J. Environ. Manag. 183, 843–849 (2016).
Liu, Y. et al. Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield. Environ. Res. Lett. 11, 094010 (2016).
Google Scholar
Yao, Y. et al. The effect of afforestation on soil moisture content in Northeastern China. PLoS ONE 11, e0160776 (2016).
Google Scholar
An, W. et al. Exploring the effects of the “Grain for Green” program on the differences in soil water in the semi-arid Loess Plateau of China. Ecol. Eng. 107, 144–151 (2017).
Li, Y. et al. Divergent hydrological response to large-scale afforestation and vegetation greening in China. Sci. Adv. 4, eaar4182 (2018).
Google Scholar
Global Wetland Outlook: State of the World’s Wetlands and their Services to People (Ramsar Convention Secretariat, 2018).
Baumgartner, R. J. Sustainable development goals and the forest sector—a complex relationship. Forests 10, 152 (2019).
15-year Comprehensive Plan for Ecological System Protection and Recovery Work (National Development and Reform Commission, 2020).
Prigent, C., Jimenez, C. & Bousquet, P. Satellite-derived global surface water extent and dynamics over the last 25 years (GIEMS-2). J. Geophys. Res. Atmos. 125, e2019JD030711 (2020).
Google Scholar
Krinner, G. et al. A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Glob. Biogeochem. Cy. 19, GB1015 (2005).
Google Scholar
Tootchi, A. Development of a global wetland map and application to describe hillslope hydrology in the ORCHIDEE land surface model. Sorbonne Université, https://www.metis.upmc.fr/~ducharne/documents/These_Tootchi_revised_11Sep2019.pdf (2019).
Beven, K. J. & Kirkby, M. J. A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant. Hydrol. Sci. B. 24, 43–69 (1979).
Stocker, B. D., Spahni, R. & Joos, F. DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands. Geosci. Model Dev. 7, 3089–3110 (2014).
Google Scholar
Xi, Y., Peng, S., Ciais, P. & Chen, Y. Future impacts of climate change on inland Ramsar wetlands. Nat. Clim. Chang. 11, 45–51 (2021).
Google Scholar
Kim, H. Global soil wetness project phase 3 atmospheric boundary conditions (Experiment 1). Data Integration and Analysis System (DIAS). (2017).
Cucchi, M. et al. WFDE5: bias-adjusted ERA5 reanalysis data for impact studies. Earth Syst. Sci. Data 12, 2097–2120 (2020).
Google Scholar
Donchyts, G. et al. Earth’s surface water change over the past 30 years. Nat. Clim. Chang. 6, 810–813 (2016).
Google Scholar
Zhu, Q. et al. Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades. Sci. Rep. 6, 38020 (2016).
Google Scholar
Mao, D. et al. Remote observations in China’s Ramsar Sites: wetland dynamics, anthropogenic threats, and implications for sustainable development goals. J. Remote Sens. 2021, 9849343 (2021).
Google Scholar
Budyko, M. I. Climate and Life (Academic Press, 1974).
Zhang, L., Dawes, W. R. & Walker, G. R. Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour. Res. 37, 701–708 (2001).
Google Scholar
Woodward, C., Shulmeister, J., Larsen, J., Jacobsen, G. E. & Zawadzki, A. The hydrological legacy of deforestation on global wetlands. Science 346, 844–847 (2014).
Google Scholar
Zhang, Z., Zimmermann, N. E., Kaplan, J. O. & Poulter, B. Modeling spatiotemporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties. Biogeosciences 13, 1387–1408 (2016).
Google Scholar
Ringeval, B. et al. Modelling sub-grid wetland in the ORCHIDEE global land surface model: evaluation against river discharges and remotely sensed data. Geosci. Model Dev. 5, 941 (2012).
Google Scholar
Tootchi, A., Jost, A. & Ducharne, A. Multi-source global wetland maps combining surface water imagery and groundwater constraints. Earth Syst. Sci. Data 11, 189–220 (2019).
Google Scholar
List of Protected Wetlands in China. http://www.zrbhq.cn/web/confirm.html (National Forestry and Grassland Administration, 2011).
Lehner, B. & Grill, G. Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrol. Process. 27, 2171–2186 (2013).
Google Scholar
Lu, F. et al. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010. Proc. Natl Acad. Sci. USA 115, 4039–4044 (2018).
Google Scholar
Warszawski, L. et al. The inter-sectoral impact model intercomparison project (ISI–MIP): project framework. Proc. Natl Acad. Sci. USA 111, 3228–3232 (2014).
Google Scholar
Levia, D. F. et al. Homogenization of the terrestrial water cycle. Nat. Geosci. 13, 656–658 (2020).
Google Scholar
Zhang, J., Fu, B., Stafford-Smith, M., Wang, S. & Zhao, W. Improve forest restoration initiatives to meet sustainable development goal 15. Nat. Ecol. Evol. 5, 10–13 (2020).
Zeng, Z. et al. Impact of earth greening on the terrestrial water cycle. J. Clim. 31, 2633–2650 (2018).
Google Scholar
Lewis, S. L., Wheeler, C. E., Mitchard, E. T. A. & Koch, A. Restoring natural forests is the best way to remove atmospheric carbon. Nature 568, 25–28 (2019).
Google Scholar
Bastin, J.-F. et al. The global tree restoration potential. Science 365, 76–79 (2019).
Google Scholar
Meier, R. et al. Empirical estimate of forestation-induced precipitation changes in Europe. Nat. Geosci. 14, 473–478 (2021).
Google Scholar
Bosch, J. M. & Hewlett, J. D. A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration. J. Hydrol. 55, 3–23 (1982).
Google Scholar
Teuling, A. J. & Hoek van Dijke, A. J. Forest age and water yield. Nature 578, E16–E18 (2020).
Google Scholar
Doelman, J. C. et al. Afforestation for climate change mitigation: Potentials, risks and trade-offs. Glob. Change Biol. 26, 1576–1591 (2020).
Google Scholar
Peng, S. et al. Afforestation in China cools local land surface temperature. Proc. Natl Acad. Sci. USA 111, 2915–2919 (2014).
Google Scholar
Seddon, N., Turner, B., Berry, P., Chausson, A. & Girardin, C. A. J. Grounding nature-based climate solutions in sound biodiversity science. Nat. Clim. Chang. 9, 84–87 (2019).
Google Scholar
Brown, I. Challenges in delivering climate change policy through land use targets for afforestation and peatland restoration. Environ. Sci. Policy 107, 36–45 (2020).
The 2nd – 9th National Forest Resource Inventory Report (State Forestry Administration of the People’s Republic of China, 1973–2018).
Fang, J. et al. Forest biomass carbon sinks in East Asia, with special reference to the relative contributions of forest expansion and forest growth. Glob. Change Biol. 20, 2019–2030 (2014).
Google Scholar
Hou, X. Vegetation atlas of China. Chinese Academy of Science, the editorial board of vegetation map of China (2001).
Xi, Y. et al. Contributions of climate change, CO2, land-use change, and human activities to changes in river flow across 10 Chinese Basins. J. Hydrometeorol. 19, 1899–1914 (2018).
Google Scholar
Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).
Google Scholar
Klein Goldewijk, K., Beusen, A., Doelman, J. & Stehfest, E. Anthropogenic land use estimates for the Holocene – HYDE 3.2. Earth Syst. Sci. Data 9, 927–953 (2017).
Google Scholar
Fluet-Chouinard, E., Lehner, B., Rebelo, L.-M., Papa, F. & Hamilton, S. K. Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data. Remote Sens. Environ. 158, 348–361 (2015).
Google Scholar
Herold, M., Van Groenestijn, A., Kooistra, L., Kalogirou, V. & Arino, O. Land cover CCI, product user guide version 2.0. https://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf (2015).
Pekel, J. F., Cottam, A., Gorelick, N. & Belward, A. S. High-resolution mapping of global surface water and its long-term changes. Nature 540, 418–422 (2016).
Google Scholar
Zhou, G. et al. Global pattern for the effect of climate and land cover on water yield. Nat. Commun. 6, 5918 (2015).
Google Scholar
Yang, H. et al. Changing retention properties of catchments and their influence on runoff under climate change. Environ. Res. Lett. 13, 094019 (2018).
Google Scholar
Berghuijs, W. R., Larsen, J. R., van Emmerik, T. H. M. & Woods, R. A. A global assessment of runoff sensitivity to changes in precipitation, potential evaporation, and other factors. Water Resour. Res. 53, 8475–8486 (2017).
Google Scholar
Piao, S. et al. Changes in climate and land use have a larger direct impact than rising CO2 on global river runoff trends. Proc. Natl Acad. Sci. USA 104, 15242 (2007).
Google Scholar
Guimberteau, M. et al. Testing conceptual and physically based soil hydrology schemes against observations for the Amazon Basin. Geosci. Model Dev. 7, 1115–1136 (2014).
Google Scholar
Traore, A. K. et al. Evaluation of the ORCHIDEE ecosystem model over Africa against 25 years of satellite-based water and carbon measurements. J. Geophys. Res. Biogeosci. 119, 1554–1575 (2014).
de Rosnay, P. & Polcher, J. Impact of a physically based soil water flow and soil‐plant interaction representation for modeling large‐scale land surface processes. J. Geophys. Res. Atmos. 107, ACL 3-1–ACL 3-19 (2002).
Campoy, A. et al. Influence of soil bottom hydrological conditions on land surface fluxes and climate in a general circulation model. J. Geophys. Res. Atmos. 118, 10725–10739 (2013).
Google Scholar
Guimberteau, M. et al. Discharge simulation in the sub-basins of the Amazon using ORCHIDEE forced by new datasets. Hydrol. Earth Syst. Sci. 16, 11171–11232 (2012).
Boucher, O. et al. Presentation and evaluation of the IPSL-CM6A-LR climate model. J. Adv. Model. Earth Sy. 12, e2019MS002010 (2020).
Google Scholar
Fan, Y. et al. Hillslope hydrology in global change research and earth system modeling. Water Resour. Res. 55, 1737–1772 (2019).
Google Scholar
Rayner, P. J. et al. Two decades of terrestrial carbon fluxes from a carbon cycle data assimilation system (CCDAS). Glob. Biogeochem. Cy. 19, GB2026 (2005).
Google Scholar
Ducharne, A. Reducing scale dependence in TOPMODEL using a dimensionless topographic index. Hydrol. Earth Syst. Sci. 13, 2399–2412 (2009).
Google Scholar
Niu, G., Yang, Z., Dickinson, R. E. & Gulden, L. E. A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models. J. Geophys. Res. 110, D21106 (2005).
Google Scholar
Xi, Y. et al. Monthly inundated fraction over China for 2000-2015 from GIEMS-2 (Version v1.0). Zenodo https://doi.org/10.5281/zenodo.5750962 (2021).
Xi, Y. et al. Code of wetland simulation for trade-off between tree planting and wetland conservation in China (Version v1.0). Zenodo https://doi.org/10.5281/zenodo.4435082 (2021).
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