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Coincidence probability analysis of hydrologic low-flow under the changing environment in the Wei River Basin

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Abstract

Hydrologic characteristics including extreme-flow events in many rivers around the world have been altered due to the climate change and human activities. Most available research concerns about the extreme event trend, frequency and duration in a single river rather than the synchronicity or coincidence probability among different tributaries. Accurately knowing the coincidence probability of hydrologic extreme-flow events is vital for better water resources allocation and project design. Joint distribution constructed by the copulas function is a widely used method to conduct this issue. However, studies conducted by the copulas function are mostly carried out in a bivariate environment and ignore the nonstationary. These may not comprehensively reflect the hydrologic characteristics under the changing environment. This paper analyzes the related hydrologic low-flow changes considering the nonstationary under the changing environment in the Wei River Basin, China, where the climate tends to be drier. These analyses are obtained by using trivariate copulas function and Kendall’s return period method to derive the joint distribution of hydrologic low-flow in a seasonal time scale. The results mainly show that the coincidence probabilities of low-flow among three tributaries of the Wei River in four seasons after the change point are basically higher than those before the change point. It may indicate that the low-flow negative impacts in the whole Wei River Basin in four seasons may be intensified (which needs to be paid more attention) under the changing environment.

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References

  • Angelidis P, Maris F, Kotsovinos N, Hrissanthou V (2012) Computation of drought index SPI with alternative distribution functions. Water Resour Manage 26(9):2453–2473

    Article  Google Scholar 

  • Besselaar EJMVD, Tank AMGK, Buishand TA (2013) Trends in European precipitation extremes over 1951–2010. Int J Climatol 33(12):2682–2689

    Google Scholar 

  • Chang J, Wang Y, Istanbulluoglu E, Bai T, Huang Q, Yang D, Huang S (2015) Impact of climate change and human activities on runoff in the Weihe River Basin, China. Quat Int 380:169–179

    Article  Google Scholar 

  • Chang J, Zhang H, Wang Y, Zhu Y (2016) Assessing the impact of climate variability and human activities on streamflow variation. Hydrol Earth Syst Sci 20(4):1547–1560

    Article  Google Scholar 

  • Chang J, Guo A, Wang Y, Ha Y, Zhang R, Xue L, Tu Z (2019) Reservoir operations to mitigate drought effects with a hedging policy triggered by the drought prevention limiting water level. Water Resour Res 55(2):904–922

    Article  Google Scholar 

  • Chen Y, Chang J, Huang S, Wang Y, Guo A (2014) Variation characteristics of drought in Weihe River Basin base on Palmer drought severity index. J Nat Disasters 23(5):29–37

    Google Scholar 

  • Corbella S, Stretch DD (2012) Multivariate return periods of sea storms for coastal erosion risk assessment. Nat Hazards Earth Syst Sci 12(8):2699–2708

    Article  Google Scholar 

  • Fu G, Yu J, Yu X, Ouyang R, Zhang Y, Wang P, Liu W, Min L (2013) Temporal variation of extreme rainfall events in China, 1961–2009. J Hydrol 487:48–59

    Article  Google Scholar 

  • Genest C, Quessy JF, Rémillard B (2006) Goodness-of-fit procedures for copula models based on the probability integral transformation. Scand J Stat 33(2):337–366

    Article  Google Scholar 

  • Grimaldi S, Petroselli A, Salvadori G, De Michele C (2016) Catchment compatibility via copulas: a non-parametric study of the dependence structures of hydrologic responses. Adv Water Resour 90:116–133

    Article  Google Scholar 

  • Gringorten II (1963) A plotting rule for extreme probability paper. J Geophys Res 68(3):813–814

    Article  Google Scholar 

  • Huang XR, Zhao JW, Yang PP (2015) Wet-dry runoff correlation in Western Route of South-to-North Water Diversion Project, China. J Mt Sci 12(3):592–603

    Article  Google Scholar 

  • Jiang C, Xiong L, Xu C, Guo S (2015) Bivariate frequency analysis of nonstationary low-flow series based on the time-varying copula. Hydrol Process 29(6):1521–1534

    Article  Google Scholar 

  • Li Y, Chang J, Wang Z, Li H (2016) Detection of abrupt changes in runoff in the Weihe River Basin. Adv Meteorol 2016:1–8

    Google Scholar 

  • Liu S, Huang S, Huang Q, Xie Y, Leng G, Luan J, Song X, Wei X, Li X (2017) Identification of the non-stationarity of extreme precipitation events and correlations with large-scale ocean-atmospheric circulation patterns: a case study in the wei river basin, china. J Hydrol 548:184–195

    Article  Google Scholar 

  • Lyu J, Shen B, Li H (2015) Dynamics of major hydro-climatic variables in the headwater catchment of the Tarim River Basin, Xinjiang, China. Quat Int 380:143–148

    Article  Google Scholar 

  • Marengo JA, Torres RR, Alves LM (2017) Drought in Northeast Brazil—past, present, and future. Theoret Appl Climatol 129(3–4):1189–1200

    Article  Google Scholar 

  • Milly PC, Wetherald RT, Dunne KA, Delworth TL (2002) Increasing risk of great floods in a changing climate. Nature 415(6871):514

    Article  Google Scholar 

  • Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23(5):881–897

    Article  Google Scholar 

  • Pettitt AN (1979) A non-parametric approach to the change-point problem. Appl Stat 28(2):126–135

    Article  Google Scholar 

  • Salvadori G, De Michele C (2007) On the use of copulas in hydrology: theory and practice. J Hydrol Eng 12(4):369–380

    Article  Google Scholar 

  • Salvadori G, Durante F, De Michele C (2011) On the return period and design in a multivariate framework. Hydrol Earth Syst Sci 15:3293–3305

    Article  Google Scholar 

  • Santos CACD, Neale CMU, Rao TVR, Silva BBD (2011) Trends in indices for extremes in daily temperature and precipitation over Utah, USA. Int J Climatol 31(12):1813–1822

    Article  Google Scholar 

  • Shiau JT (2006) Fitting drought duration and severity with two-dimensional copulas. Water Resour Manag 20(5):795–815

    Article  Google Scholar 

  • Verdon-Kidd DC, Kiem AS (2015) Regime shifts in annual maximum rainfall across Australia—implications for intensity–frequency–duration (IFD) relationships. Hydrol Earth Syst Sci 19(12):4735–4746

    Article  Google Scholar 

  • Villarini G, Serinaldi F, Smith JA, Krajewski WF (2009) On the stationarity of annual flood peaks in the continental United States during the 20th century. Water Resour Res 45:1–17

    Google Scholar 

  • Wang Y, Yang J, Chang J (2019) Development of a coupled quantity-quality-environment water allocation model applying the optimization-simulation method. J Clean Prod 213:944–955

    Article  Google Scholar 

  • Wani O, Scheidegger A, Cecinati F, Espadas G, Rieckermann J (2019) Exploring a copula-based alternative to additive error models-for non-negative and autocorrelated time series in hydrology. J Hydrol 575:1031–1040

    Article  Google Scholar 

  • Weltzin JF, Loik ME, Schwinning S, Williams DG, Fay PA, Haddad BM, Harte J, Huxman TE, Knapp AK, Lin G, Pockman WT, Shaw RM, Small EE, Smith MD, Smith SD, Tissue DT, Zak JC (2003) Assessing the response of terrestrial ecosystems to potential changes in precipitation. Bioscience 53(10):941–952

    Article  Google Scholar 

  • Yan B, Chen L (2013) Coincidence probability of precipitation for the middle route of south-to-north water transfer project in China. J Hydrol 499(9):19–26

    Article  Google Scholar 

  • Yang J, Chang J, Wang Y, Li Y, Hu H, Chen Y, Huang Q, Yao J (2018) Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index. J Hydrol 667:651–667

    Article  Google Scholar 

  • Yang J, Yang YCE, Chang J, Zhang J, Yao J (2019) Impact of dam development and climate change on hydroecological conditions and natural hazard risk in the Mekong River Basin. J Hydrol 579:124177

    Article  Google Scholar 

  • Zhao J, Huang S, Huang Q, Wang H, Leng G (2018) Detecting the dominant cause of streamflow decline in the Loess Plateau of China based on the Latest Budyko Equation. Water 10(9):1277

    Article  Google Scholar 

  • Zou L, Xia J, She D (2017) Drought characteristic analysis based on an improved PDSI in the Wei River Basin of China. Water 9(3):178

    Article  Google Scholar 

Download references

Acknowledgements

This study is supported by The National Key Research and Development Program of China (2016YFC0400906), National Natural Science Foundation of China (91647112, 51679189, 51679187). The authors sincerely appreciate the editors and reviewers for their professional comments.

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Correspondence to Jianxia Chang.

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Yang, J., Wang, Y., Yao, J. et al. Coincidence probability analysis of hydrologic low-flow under the changing environment in the Wei River Basin. Nat Hazards 103, 1711–1726 (2020). https://doi.org/10.1007/s11069-020-04051-3

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  • DOI: https://doi.org/10.1007/s11069-020-04051-3

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