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Quantification of human and climate contributions to multi-dimensional hydrological alterations: A case study in the Upper Minjiang River, China

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Abstract

Dual factors of climate and human on the hydrological process are reflected not only in changes in the spatiotemporal distribution of water resource amounts but also in the various characteristics of river flow regimes. Isolating and quantifying their contributions to these hydrological alterations helps us to comprehensively understand the response mechanism and patterns of hydrological process to the two kinds of factors. Here we develop a general framework using hydrological model and 33 indicators to describe hydrological process and quantify the impact from climate and human. And we select the Upper Minjiang River (UMR) as a case to explore its feasibility. The results indicate that our approach successfully recognizes the characteristics of river flow regimes in different scenarios and quantitatively separates the climate and human contributions to multi-dimensional hydrological alterations. Among these indicators, 26 of 33 indicators decrease over the past half-century (1961–2012) in the UMR, with change rates ranging from 1.3% to 33.2%, and the human impacts are the dominant factor affecting hydrological processes, with an average relative contribution rate of 58.6%. Climate change causes an increase in most indicators, with an average relative contribution rate of 41.4%. Specifically, changes in precipitation and reservoir operation may play a considerable role in inducing these alterations. The findings in this study help us better understand the response mechanism of hydrological process under changing environment and is conducive to climate change adaptation, water resource planning and ecological construction.

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References

  • Akbari S, Reddy M, 2019. Change detection and attribution of flow regime: A case study of Allegheny River catchment, PA (US). Science of The Total Environment, 662: 192–204.

    Article  Google Scholar 

  • Chen S, Zhang G, Yang S, 2003. Temporal and spatial changes of suspended sediment concentration and resuspension in the Yangtze River estuary. Journal of Geographical Sciences, 13(4): 498–506.

    Article  Google Scholar 

  • Chen Y, Li W, Chen Y et al., 2004. Physiological response of natural plants to the change of groundwater level in the lower reaches of Tarim River, Xinjiang. Progress in Natural Science, 14(11): 975–983.

    Article  Google Scholar 

  • Dey P, Mishra A, 2017. Separating the impacts of climate change and human activities on streamflow: A review of methodologies and critical assumptions. Journal of Hydrology, 548: 278–290.

    Article  Google Scholar 

  • Donat M, Lowry A, Alexander L et al., 2016. More extreme precipitation in the world’s dry and wet regions. Nature Climate Change, 6(5): 508–513.

    Article  Google Scholar 

  • Du C, Ye A, Gan Y et al., 2017. Drainage network extraction from a high-resolution DEM using parallel programming in the NET framework. Journal of Hydrology, 555: 506–517.

    Article  Google Scholar 

  • Gao B, Yang D, Zhao T et al., 2002. Changes in the eco-flow metrics of the Upper Yangtze River from 1961 to 2008. Journal of Hydrology, 448/449: 30–38.

    Google Scholar 

  • Graf W, 2006. Downstream hydrologic and geomorphic effects of large dams on American rivers. Geomorphology, 79(3): 336–360.

    Article  Google Scholar 

  • Gupta H, Sorooshian S, Yapo P, 1999. Status of automatic calibration for hydrologic models: Comparison with multilevel expert calibration. Journal of Hydrologic Engineering, 4(2): 135–143.

    Article  Google Scholar 

  • Hou J, Ye A, You J et al., 2018. An estimate of human and natural contributions to changes in water resources in the upper reaches of the Min River. Science of The Total Environment, 635: 901–912.

    Article  Google Scholar 

  • Jiang C, Zhang L, Tang Z et al., 2017. Multi-temporal scale changes of streamflow and sediment discharge in the headwaters of Yellow River and Yangtze River on the Tibetan Plateau, China. Ecological Engineering, 102: 240–254.

    Article  Google Scholar 

  • Kendall M, Gibbons J, 1948. Rank Correlation Methods. 5th ed. London, UK: Edward Arnold, 320.

    Google Scholar 

  • Kundzewicz Z, 2008. Climate change impacts on the hydrological cycle. Ecohydrology & Hydrobiology, 8(2–4): 195–203.

    Article  Google Scholar 

  • Li M, 2014. Cumulative influence of cascade hydropower development on runoff in upper reaches of Min River [D]. Chengdu: Chengdu University of Technology. (in Chinese)

    Google Scholar 

  • Li M, Fu B, Wang Y et al., 2015. Characteristics and spatial patterns of hydropower development in the upper Min River basin. Resources and Environment in the Yangtze Basin, 24(1): 74–80. (in Chinese)

    Google Scholar 

  • Li Z, Li X, Xu Z, 2010. Impacts of water conservancy and soil conservation measures on annual runoff in the Chaohe River Basin during 1961–2005. Journal of Geographical Sciences, 20(6): 947–960.

    Article  Google Scholar 

  • Liang G, Ding S, 2004. Impacts of human activity and natural change on the wetland landscape pattern along the Yellow River in Henan Province. Journal of Geographical Sciences, 14(3): 339–348.

    Article  Google Scholar 

  • Liu X, Liu C, Luo Y et al., 2012. Dramatic decrease in streamflow from the headwater source in the central route of China’s water diversion project: Climatic variation or human influence? Journal of Geophysical Research: Atmospheres, 117: D06113.

    Google Scholar 

  • Liu X, Shen Y, Guo Y et al., 2015. Modelling demand/supply of water resources in the arid region of northwestern China during the late 1980s to 2010. Journal of Geographical Sciences, 25(5): 573–591.

    Article  Google Scholar 

  • Lu E, Zhao W, Zou X et al., 2017. Temporal-spatial monitoring of an extreme precipitation event: Determining simultaneously the time period it lasts and the geographic region it affects. Journal of Climate, 30(16): 6123–6132.

    Article  Google Scholar 

  • Lu W, Lei H, Yang D et al., 2018. Quantifying the impacts of small dam construction on hydrological alterations in the Jiulong River basin of Southeast China. Journal of Hydrology, 567: 382–392.

    Article  Google Scholar 

  • Luca P, Messori G, Wilby R et al., 2019. Concurrent wet and dry hydrological extremes at the global scale. Earth System Dynamics, 11(1): 251–266.

    Article  Google Scholar 

  • Ma F, Ye A, Gong W et al., 2014. An estimate of human and natural contributions to flood changes of the Huai River. Global and Planetary Change, 119(4): 39–50.

    Article  Google Scholar 

  • Ma H, Yang D, Tan S et al., 2010. Impact of climate variability and human activities on streamflow decrease in the Miyun Reservoir catchment. Journal of Hydrology, 389(3/4): 317–324.

    Article  Google Scholar 

  • Magilligan F, Nislow K, 2005. Changes in hydrologic regime by dams. Geomorphology, 71(1): 61–78.

    Article  Google Scholar 

  • Mann H, 1945. Nonparametric test against trend. Econometrica, 13(3): 245–259.

    Article  Google Scholar 

  • Mittal N, Bhave A, Mishra A et al., 2016. Impact of human intervention and climate change on natural flow regime. Water Resources Management, 30(2): 685–699.

    Article  Google Scholar 

  • Nachar N, 2008. The Mann-Whitney U: A test for assessing whether two independent samples come from the same distribution. Tutorials in Quantitative Methods for Psychology, 4(1): 13–20.

    Article  Google Scholar 

  • Nakayama T, 2011. Simulation of the effect of irrigation on the hydrologic cycle in the highly cultivated Yellow River Basin. Agricultural and Forest Meteorology, 151(3): 314–327.

    Article  Google Scholar 

  • Nash J, Sutcliffe J, 1970. River flow forecasting through conceptual models: Part 1 A discussion of principles. Journal of Hydrology, 10(3): 282–290.

    Article  Google Scholar 

  • Räsänen T, Someth P, Lauri H et al., 2017. Observed river discharge changes due to hydropower operations in the Upper Mekong Basin. Journal of Hydrology, 545: 28–41.

    Article  Google Scholar 

  • Richter B, Baumgartner J, Powell J et al., 1996. A method for assessing hydrologic alteration within ecosystems. Conservation Biology, 10(4): 1163–1174.

    Article  Google Scholar 

  • Shepard D, 1984. Computer mapping: The SYMAP interpolation algorithm. In: Spatial Statistics and Models. Dordrecht: Springer, 133–145.

    Google Scholar 

  • Shrestha S, Htut A, 2016. Land use and climate change impacts on the hydrology of the Bago River Basin, Myanmar. Environmental Modelling & Assessment, 21(6): 819–833.

    Article  Google Scholar 

  • Sun Q, Miao C, Duan Q, 2015. Projected changes in temperature and precipitation in ten river basins over China in 21st century. International Journal of Climatology, 35(6): 1125–1141.

    Article  Google Scholar 

  • Talukdar S, Pal S, 2019. Effects of damming on the hydrological regime of Punarbhaba River basin wetlands. Ecological Engineering, 135: 61–74.

    Article  Google Scholar 

  • Wan Z, Chen X et al., 2020. Streamflow reconstruction and variation characteristic analysis of the Ganjiang River in China for the past 515 years. Sustainability, 12(3): 1168.

    Article  Google Scholar 

  • Wang G, Xia J, Chen J, 2009. Quantification of effects of climate variations and human activities on runoff by a monthly water balance model: A case study of the Chaobai River basin in northern China. Water Resources Research, 45: W00A11.

    Article  Google Scholar 

  • Wang G, Xia J, Tan G et al., 2002. A research on distributed time variant gain model: A case study on Chaohe River Basin. Progress in Geography, 21(6): 573–582. (in Chinese)

    Google Scholar 

  • Wang J, Dai Z, Mei X et al., 2018. Immediately downstream effects of Three Gorges Dam on channel sandbars morphodynamics between Yichang-Chenglingji Reach of the Changjiang River, China. Journal of Geographical Sciences, 28(5): 629–646.

    Article  Google Scholar 

  • Wang X, 2014. Advances in separating effects of climate variability and human activities on stream discharge: An overview. Advances in Water Resources, 71: 209–218.

    Article  Google Scholar 

  • Wang X, Yang T, Wortmann M et al., 2017. Analysis of multi-dimensional hydrological alterations under climate change for four major river basins in different climate zones. Climatic Change, 141(3): 483–498.

    Article  Google Scholar 

  • Wei W, Shi P, Zhou J et al., 2013. Environmental suitability evaluation for human settlements in an arid inland river basin: A case study of the Shiyang River Basin. Journal of Geographical Sciences, 23(2): 331–343.

    Article  Google Scholar 

  • Wu J, Miao C, Zhang X et al., 2017. Detecting the quantitative hydrological response to changes in climate and human activities. Science of The Total Environment, 586: 328–337.

    Article  Google Scholar 

  • Wu J, Miao C, Wang Y et al., 2016. Contribution analysis of the long-term changes in seasonal runoff on the Loess Plateau, China, using eight Budyko-based methods. Journal of Hydrology, 545: 263–275.

    Article  Google Scholar 

  • Wu X, Wang Z, Zhou X et al., 2016. Observed changes in precipitation extremes across 11 basins in China during 1961–2013. International Journal of Climatology, 36(8): 2866–2885.

    Article  Google Scholar 

  • Xia J, 1991. Identification of a constrained nonlinear hydrological system described by volterra functional series. Water Resources Research, 27(9): 2415–2420.

    Article  Google Scholar 

  • Xia J, Wang G, Lv A et al., 2003. A research on distributed time variant gain modelling. Acta Geographica Sinica, 58(5): 789–796. (in Chinese)

    Google Scholar 

  • Xia J, Wang G, Tan G et al., 2005. Development of distributed time-variant gain model for nonlinear hydrological systems. Science in China Series D: Earth Sciences, 48(6): 713–723.

    Article  Google Scholar 

  • Xin Z, Li Y, Zhang L et al., 2019. Quantifying the relative contribution of climate and human impacts on seasonal streamflow. Journal of Hydrology, 574: 936–945.

    Article  Google Scholar 

  • Xu C, Wang J, Li Q, 2018: A new method for temperature spatial interpolation based on sparse historical stations. Journal of Climate, 31: 1757–1770.

    Article  Google Scholar 

  • Yang S, Milliman J, Li P et al., 2011. 50,000 dams later: Erosion of the Yangtze River and its delta. Global and Planetary Change, 75(1/2): 14–20.

    Article  Google Scholar 

  • Yang T, Cui T, Xu C et al., 2017. Development of a new IHA method for impact assessment of climate change on flow regime. Global & Planetary Change, 156(9): 68–79.

    Article  Google Scholar 

  • Yang T, Zhang Q, Chen Y et al., 2008. A spatial assessment of hydrologic alteration caused by dam construction in the middle and lower Yellow River, China. Hydrological Processes, 22(18): 3829–3843.

    Article  Google Scholar 

  • Yang Z, Yan Y, Liu Q, 2012. Assessment of the flow regime alterations in the Lower Yellow River, China. Ecological Informatics, 10(7): 56–64.

    Article  Google Scholar 

  • Ye A, Duan Q, Chu W et al., 2014. The impact of the south-north water transfer project (CTP)’s central route on groundwater table in the Hai River Basin, North China. Hydrological Processes, 28(23): 5755–5768.

    Article  Google Scholar 

  • Ye A, Duan Q, Schaake J et al., 2015. Post-processing of ensemble low flow forecasts. Hydrological Processes, 29: 2438–2453.

    Article  Google Scholar 

  • Ye A, Duan Q, Zeng H et al., 2010. A distributed time-variant gain hydrological model based on remote sensing. Journal of Resources and Ecology, 1(3): 222–230.

    Google Scholar 

  • Ye A, Duan Q, Zhan C et al., 2013. Improving kinematic wave routing scheme in Community Land Model. Hydrology Research, 44(5): 886–903.

    Article  Google Scholar 

  • Ye A, Xia J, Wang G, 2006. Dynamic network-based distributed kinematic wave affluent model. Yellow River, 28(2): 26–29. (in Chinese)

    Google Scholar 

  • Zhai H, Cui B, Hu B et al., 2010. Prediction of river ecological integrity after cascade hydropower dam construction on the mainstream of rivers in Longitudinal Range-Gorge Region (LRGR), China. Ecological Engineering, 36(4): 361–372.

    Article  Google Scholar 

  • Zhang M, Wei X, Sun P et al., 2012. The effect of forest harvesting and climatic variability on runoff in a large watershed: The case study in the Upper Min River of Yangtze River Basin. Journal of Hydrology, 464: 1–11.

    Article  Google Scholar 

  • Zhao G, Tian P, Mu X et al., 2014. Quantifying the impact of climate variability and human activities on stream-flow in the middle reaches of the Yellow River Basin, China. Journal of Hydrology, 519: 387–398.

    Article  Google Scholar 

  • Zhao L, Peng Q, Li C et al., 2014. Analysis of eco-hydrological alteration of upper Yangtze mainstream sections in the nature reserves for rare and endemic fishes. Journal of Hydroelectric Engineering, 33(3): 106–111. (in Chinese)

    Google Scholar 

  • Zhao Q, Liu S, Deng L et al., 2012. The effects of dam construction and precipitation variability on hydrologic alteration in the Lancang River Basin of Southwest China. Stochastic Environmental Research and Risk Assessment, 26(7): 993–1011.

    Article  Google Scholar 

  • Zhou B, Wen, Q, Xu Y et al., 2014. Projected changes in temperature and precipitation extremes in China by the CMIP5 multi-model ensembles. Journal of Climate, 27(17): 6591–6611.

    Article  Google Scholar 

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Authors and Affiliations

Authors

Corresponding author

Correspondence to Aizhong Ye.

Additional information

Foundation

Natural Science Foundation of China, No.51879009, No.52079143; Second Tibetan Plateau Scientific Expedition and Research Program, No.2019QZKK0405; National Key Research and Development Program of China, No.2018YFE0196000, No.2017YFC0404405; Interdisciplinary Research Foundation of Beijing Normal University for the First-Year Doctoral Students, No.BNUXKJC1905; Independent Research Projects of POWERCHINA Chengdu Engineering Corporation Limited, No.P34516

Author

Zhang Yuhang (1994-), specialized in hydrometeorological ensemble forecast. E-mail: zhangyh19@mail.bnu.edu.cn

Data availability

The gridded daily precipitation data and gauge-based meteorological data can be obtained from the National Climate Centre of the Chinese Meteorological Administration (CMA-NCC, http://data.cma.cn/data/cdcdetail/dataCode/SURF_CLI_CHN_PRE_DAY_GRID_0.5.html); Daily and monthly streamflow records for the ZPP hydrological station were collected from the Hydrological Yearbook of the Bureau of Hydrology, Yangtze River Water Resources Commission, in China; Digital elevation model (DEM) data with a spatial resolution of 3 arc-seconds were downloaded from NASA’s Shuttle Radar Topography Mission website (SRTM, http://srtm.csi.cgiar.org/); The land use data were provided by the National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://www.geodata.cn); The soil types data can be downloaded from the world soil data-base (Harmonized World Soil Database version 1.2, http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/).

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Zhang, Y., Ye, A., You, J. et al. Quantification of human and climate contributions to multi-dimensional hydrological alterations: A case study in the Upper Minjiang River, China. J. Geogr. Sci. 31, 1102–1122 (2021). https://doi.org/10.1007/s11442-021-1887-z

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