The projected futures of water resources vulnerability under climate and socioeconomic change in the Yangtze River Basin, China
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Hongjuan Wu | N. Dong | Xiu Zhang | Yuqing Tian | Sen Li
[1] Mohammed Abdallah,et al. Reference evapotranspiration estimation in hyper-arid regions via D-vine copula based-quantile regression and comparison with empirical approaches and machine learning models , 2022, Journal of Hydrology: Regional Studies.
[2] M. Safari,et al. IHACRES, GR4J and MISD-based multi conceptual-machine learning approach for rainfall-runoff modeling , 2022, Scientific Reports.
[3] Zongguo Wen,et al. Exploring a multisource-data framework for assessing ecological environment conditions in the Yellow River Basin, China. , 2022, The Science of the total environment.
[4] Zongguo Wen,et al. Evaluating the water quality characteristics and tracing the pollutant sources in the Yellow River Basin, China. , 2022, The Science of the total environment.
[5] Zhe Yuan,et al. Drought assessment of terrestrial ecosystems in the Yangtze River Basin, China , 2022, Journal of Cleaner Production.
[6] Du Li,et al. Measurement and analysis of ecological pressure due to industrial development in the Yangtze River economic belt from 2010 to 2018 , 2022, Journal of Cleaner Production.
[7] I. Larbi,et al. Rainfall and temperature changes under different climate scenarios at the watersheds surrounding the Ngorongoro Conservation Area in Tanzania , 2022, Environmental Challenges.
[8] Yichun Xie,et al. Spatiotemporal analysis of interactions between seasonal water, climate, land use, policy, and socioeconomic changes: Hulun-Buir Steppe as a Case Study. , 2021, Water research.
[9] Takaaki Kato,et al. Spatial-temporal analysis of urban water resource vulnerability in China , 2021, Ecological Indicators.
[10] Sen Li,et al. Identifying the drivers of water yield ecosystem service: A case study in the Yangtze River Basin, China , 2021, Ecological Indicators.
[11] Yaohui Liu,et al. Spatiotemporal change and driving factors of the Eco-Environment quality in the Yangtze River Basin from 2001 to 2019 , 2021, Ecological Indicators.
[12] S. Lwasa,et al. Greenhouse Gas Emissions from Global Cities Under SSP/RCP Scenarios, 1990 to 2100 , 2021 .
[13] Xing Yuan,et al. The key drivers for the changes in global water scarcity: Water withdrawal versus water availability , 2021 .
[14] Changchang Liu,et al. Precipitation and urban expansion caused jointly the spatiotemporal dislocation between supply and demand of water provision service. , 2021, Journal of environmental management.
[15] Andrew D. Jones,et al. Implications of warming on western United States landfalling atmospheric rivers and their flood damages , 2021 .
[16] R. Hanson,et al. Potential adverse impacts on vulnerability and availability of groundwater from climate-change and land use , 2021 .
[17] R. Moss,et al. Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6 , 2020, Earth System Dynamics.
[18] C. Ni,et al. Predictions of groundwater vulnerability and sustainability by an integrated index-overlay method and physical-based numerical model , 2021 .
[19] Ding Yongjian,et al. Assessments on surface water resources and their vulnerability and adaptability in China , 2020 .
[20] Nengcheng Chen,et al. Spatiotemporal characteristics and estimates of extreme precipitation in the Yangtze River Basin using GLDAS data , 2020, International Journal of Climatology.
[21] Khaled S. Balkhair,et al. A novel approach for predicting daily pan evaporation in the coastal regions of Iran using support vector regression coupled with krill herd algorithm model , 2020, Theoretical and Applied Climatology.
[22] Carlo Giupponi,et al. A coupled hydrologic-machine learning modelling framework to support hydrologic modelling in river basins under Interbasin Water Transfer regimes , 2020, Environ. Model. Softw..
[23] Kinh Bac Dang,et al. New approach of water quantity vulnerability assessment using satellite images and GIS-based model: An application to a case study in Vietnam. , 2020, The Science of the total environment.
[24] R. Shan,et al. Comparison of the SWAT and InVEST models to determine hydrological ecosystem service spatial patterns, priorities and trade-offs in a complex basin , 2020 .
[25] Hilppa Gregow,et al. GCMeval – An interactive tool for evaluation and selection of climate model ensembles , 2020 .
[26] Xingliang Guan,et al. The assessment of forest ecological security and its determining indicators: A case study of the Yangtze River Economic Belt in China. , 2020, Journal of environmental management.
[27] M. Rosas-Casals,et al. A water balance model to estimate climate change impact on groundwater recharge in Yucatan Peninsula, Mexico , 2020 .
[28] A. Russo,et al. Crops' exposure, sensitivity and adaptive capacity to drought occurrence , 2019 .
[29] T. Jiang,et al. Effect of Fertility Policy Changes on the Population Structure and Economy of China: From the Perspective of the Shared Socioeconomic Pathways , 2019, Earth's Future.
[30] P. Sanzana,et al. Value of distributed water level and soil moisture data in the evaluation of a distributed hydrological model: Application to the PUMMA model in the Mercier catchment (6.6 km2) in France , 2019, Journal of Hydrology.
[31] P. Kyle,et al. Water Sector Assumptions for the Shared Socioeconomic Pathways in an Integrated Modeling Framework , 2018, Water Resources Research.
[32] Andrew Allan,et al. Applying the global RCP-SSP-SPA scenario framework at sub-national scale: A multi-scale and participatory scenario approach. , 2018, The Science of the total environment.
[33] Hui Lin,et al. Land use projections in China under global socioeconomic and emission scenarios: Utilizing a scenario-based land-use change assessment framework , 2018 .
[34] Jatin Anand,et al. Prediction of land use changes based on Land Change Modeler and attribution of changes in the water balance of Ganga basin to land use change using the SWAT model. , 2017, The Science of the total environment.
[35] Rui Yao,et al. Urbanization Effects on Vegetation and Surface Urban Heat Islands in China's Yangtze River Basin , 2017, Remote. Sens..
[36] Hans Estrup Andersen,et al. Future water availability in the largest freshwater Mediterranean lake is at great risk as evidenced from simulations with the SWAT model. , 2017, The Science of the total environment.
[37] Wolfgang Lutz,et al. The human core of the shared socioeconomic pathways: Population scenarios by age, sex and level of education for all countries to 2100 , 2017, Global environmental change : human and policy dimensions.
[38] K. Riahi,et al. The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century , 2017 .
[39] Zailin Huo,et al. Optimizing regional irrigation water use by integrating a two-level optimization model and an agro-hydrological model , 2016 .
[40] G. Ziv,et al. Empirical validation of the InVEST water yield ecosystem service model at a national scale. , 2016, The Science of the total environment.
[41] Qiuhong Tang,et al. Projected impacts of climate change on hydropower potential in China , 2016 .
[42] Olli Varis,et al. China's water resources vulnerability: A spatio-temporal analysis during 2003-2013 , 2015 .
[43] Mauro Sulis,et al. A Scale-Consistent Terrestrial Systems Modeling Platform Based on COSMO, CLM, and ParFlow , 2014 .
[44] Keywan Riahi,et al. A new scenario framework for climate change research: the concept of shared climate policy assumptions , 2014, Climatic Change.
[45] L. V. Beek,et al. Water balance of global aquifers revealed by groundwater footprint , 2012, Nature.
[46] T. McVicar,et al. Roots, storms and soil pores: Incorporating key ecohydrological processes into Budyko’s hydrological model , 2012 .
[47] Chi Yang,et al. Probabilistic precipitation forecasting based on ensemble output using generalized additive models and Bayesian model averaging , 2012, Acta Meteorologica Sinica.
[48] B. V. Mudgal,et al. Impact of urbanization on flooding: The Thirusoolam sub watershed – A case study , 2012 .
[49] A. Thomson,et al. The representative concentration pathways: an overview , 2011 .
[50] H. Pan. Evaluating the Vulnerability of the Water Resources System of Yarkent River Basin under the Background of Accelerating Glacier Melt in the Future , 2011 .
[51] Jing-nan Sun,et al. Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. , 2006, Journal of environmental sciences.
[52] Andrew W. Western,et al. A rational function approach for estimating mean annual evapotranspiration , 2004 .