Abstract
Climate change has greatly impacted hydrologic regimes of lakes in sub-tropical and tropical areas. However, three major challenges impede the accuracy of hydrological simulation and impact assessment processes, namely avoiding uncertainties caused by climate scenarios, selecting comprehensive hydrological indicators, and enhancing spatiotemporal precision of hydrological simulation. To address these issues, the current case study used the Lake Dianchi Basin (LDB) to demonstrate a sub-catchment scale and detailed integrated model framework. This framework was generated based on localized climate change possibilities, detailed hydrological simulation results, and a comprehensive assessment of the impacts of climate change on hydrologic regimes. The results showed that (1) the sub-tropical LDB has hydrologic regimes that are significantly impacted by climate change with changes in precipitation exerting a greater impact than air temperature changes. (2) The annual scale runoff, as well as 16 other hydrological indicators exhibit large variation among the 18 climate scenarios. Wet season and 1/3/7-day minimums/maximums may be more significantly impacted by climate change than dry season and other indicators. (3) The hydrologic regimes of the LDB is vulnerable to climate change, which may pose enormous ecological and socio-economic risk to the LDB. Among all six sub-catchments, Sub_06, characterized by a hilly landscape, would be impacted the most by climate change. Collectively, the findings of this study indicate that regions with complex climatic conditions and topography have different responses in annual scale runoff and extreme indicators, which must be fully considered.
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Availability of data and materials
Meteorological, digital elevation model (DEM), land use, and flow gauge data used in this study were available from Chinese National Center for Meteorological Data Science, Chinese Resource and Environment Science and Data Center, and Chinese National Science & Technology Infrastructure.
Code availability
The BASINS-CAT and HSPF used in this study were open access software of the US EPA, and they can be downloaded from the EPA website. (https://www.epa.gov/ceam/basins-framework-and-features). The IHA software also was an open access software which can be downloaded from the web site of The Nature Conservancy. (http://www.conservationgateway.org/ConservationPractices/Freshwater/EnvironmentalFlows/MethodsandTools/IndicatorsofHydrologicAlteration/Pages/IHA-Software-Download.aspx).
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Acknowledgements
The authors thank the Yunnan State Key Laboratory for Plateau Mountain Ecology and Restoration of Degraded Environments for providing the opening funding for this study.
Funding
This work was supported by Program for Guangdong Introducing Innovative and Entrepreneurial Teams (2019ZT08L213), National Natural Science Foundation of China (No.41701631), Guangdong Provincial Key Laboratory Project (2019B121203011), and Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0403).
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ZD, conceptual, writing, data process, model running. MW, conceptual, writing, data process, model calibration. YL, conceptual, supervision, editing. WG, conceptual, editing, funding. XC, conceptual, supervision, editing.
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No animal or plant experiments were involved in this study. Meteorological, digital elevation model (DEM), land use, and flow gauge data used in this study were available from Chinese National Center for Meteorological Data Science, Chinese Resource and Environment Science and Data Center, and Chinese National Science & Technology Infrastructure. This study does not harm the interests of any individual or organism by obtaining data.
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Duan, Z., Wang, M., Liu, Y. et al. Predicting hydrological alterations to quantitative and localized climate change in plateau regions: A case study of the Lake Dianchi Basin, China. Stoch Environ Res Risk Assess 36, 969–983 (2022). https://doi.org/10.1007/s00477-021-02126-6
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DOI: https://doi.org/10.1007/s00477-021-02126-6