Abstract
Due to accelerating climate variability and intensified anthropogenic activities, the hypothesis of stationarity of data series is no longer applicable, questioning the reliability of the traditional drought index. Thus, it is critical to develop a non-stationary hydrological drought index that takes into account the joint impacts of climate and anthropogenic changes in a drought assessment framework. In this study, using the Generalized Additive Model for Location, Scale and Shape (GAMLSS), a new Non-stationary Standardized Runoff Index (NSRI) was developed combining climate indices (CI) and modified reservoir index (MRI) as explanatory variables. This novel index was applied to the hydrological drought assessment of the Hanjiang River basin (HRB) in China, and its reliability was assessed by comparing with the traditional Standardized Runoff Index (SRI). Results indicated that the optimal non-stationary model with CI and MRI as covariates performed better than did other models. Furthermore, NSRI was more robust in identifying extreme drought events and was more effective in the study region than the conventional SRI. In addition, based on the method of Breaks for Additive Seasonal and Trend (BFAST), it was found that there were two change points in 1981 and 2003 for the NSRI series at four hydrological stations in the HRB, which indicated that hydrological drought in the basin had a prominent non-stationary behavior. Our findings may provide significant information for regional drought assessment and water resources management from a changing environment perspective.
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References
Abdelkader M, Yerdelen C (2022) Hydrological drought variability and its teleconnections with climate indices. J Hydrol 605:127290. https://doi.org/10.1016/j.jhydrol.2021.127290
Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19(6):716–723. https://doi.org/10.1109/TAC.1974.1100705
Ault T (2020) On the essentials of drought in a changing climate. Sci 368(6488):256–260. https://doi.org/10.1126/science.aaz5492
Bazrafshan J, Hejabi S (2018) A non-stationary reconnaissance drought index (NRDI) for drought monitoring in a changing climate. Water Resour Manag 32(8):2611–2624. https://doi.org/10.1007/s11269-018-1947-z
Cochrane JH (1991) A critique of the application of unit root tests. J Econ Dynam Control 15(2):275–284. https://doi.org/10.1016/0165-1889(91)90013-Q
Dracup J, Lee K, Paulson E (1980) On the definition of droughts. Water Resour Res 16(2):297–302. https://doi.org/10.1029/WR016i002p00297
Grinsted A, Moore JC, Jevrejeva S (2004) Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlin Process Geophys 11(5–6):561–566. https://doi.org/10.5194/npg-11-561-2004
Hamed KH (2008) Trend detection in hydrologic data: the Mann-Kendall trend test under the scaling hypothesis. J Hydrol 349(3–4):350–363. https://doi.org/10.1016/j.jhydrol.2007.11.009
Hao WL, Shao QX, Hao ZC, Ju Q, Baima WD, Zhang DW (2019) Non-stationary modelling of extreme precipitation by climate indices during rainy season in Hanjiang River Basin, China. Int J Climatol 39(10):4154–4169. https://doi.org/10.1002/joc.6065
Hao ZC, AghaKouchak A (2013) Multivariate standardized drought index: A parametric multi-index model. Adv in Water Resour 57:12–18. https://doi.org/10.1016/j.advwatres.2013.03.009
Huang SZ, Huang Q, Chang JX, Leng GY (2016) Linkages between hydrological drought, climate indices and human activities: a case study in the Columbia River basin. Int J Climatol 36(1):280–290. https://doi.org/10.1002/joc.4344
Jehanzaib M, Shah SA, Yoo J, Kim T-W (2020) Investigating the impacts of climate change and human activities on hydrological drought using non-stationary approaches. J Hydrol 588:125052. https://doi.org/10.1016/j.jhydrol.2020.125052
Jiang C, Xiong LH, Xu C-Y, Guo SL (2015) Bivariate frequency analysis of nonstationary low-flow series based on the time-varying copula. Hydrol Process 29(6):1521–1534. https://doi.org/10.1002/hyp.10288
Jiang SH, Wang MH, Ren LL, Xu C-Y, Yuan F, Liu Y, Lu YJ, Shen HR (2019) A framework for quantifying the impacts of climate change and human activities on hydrological drought in a semiarid basin of Northern China. Hydrol Process 33(7):1075–1088. https://doi.org/10.1002/hyp.13386
Jiang WX, Wang LC, Zhang M, Yao R, Chen XX, Gui X, Sun J, Cao Q (2021) Analysis of drought events and their impacts on vegetation productivity based on the integrated surface drought index in the Hanjiang River Basin, China. Atmos Res 254:105536. https://doi.org/10.1016/j.atmosres.2021.105536
Li JZ, Wang YX, Li SF, Hu R (2015) A nonstationary standardized precipitation index incorporating climate indices as covariates. J Geophys Res Atmos 120(23):12082–12095. https://doi.org/10.1002/2015JD023920
Lin QX, Wu ZY, Singh VP, Sadeghi SHR, He H, Lu GH (2017) Correlation between hydrological drought, climatic factors, reservoir operation, and vegetation cover in the Xijiang basin, South China. J Hydro 549:512–524. https://doi.org/10.1016/j.jhydrol.2017.04.020
López J, Francés F (2013) Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates. Hydrol Earth Syst Sci 17(8):3189–3203. https://doi.org/10.5194/hess-17-3189-2013
McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. 8th Conference on Applied Climatology. American Meteorological Society, Anaheim, pp 179–184
Milly PCD, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, Stouffer RJ (2008) Stationa-rity is dead: whither water management? Sci 319(5863):573–574. https://doi.org/10.1126/science.1151915
Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391(1–2):202–216. https://doi.org/10.1016/j.jhydrol.2010.07.012
Mittal N, Bhave AG, Mishra A, Singh R (2016) Impact of human intervention and climate change on natural flow regime. Water Resour Manag 30(2):685–699. https://doi.org/10.1007/s11269-015-1185-6
Moradian S, Yazdandoost F (2021) Seasonal meteorological drought projections over Iran using the NMME data. Nat Hazards 108:1089–1107. https://doi.org/10.1007/s11069-021-04721-w
Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23:881–897. https://doi.org/10.1007/s11269-008-9305-1
Palmer WC (1965) Meteorological drought. Research Paper No. 45. US Department of Commerce Weather Bureau, Washington DC
Peng T, Tian H, Singh VP, Chen M, Liu J, Ma HB, Wang JB (2020) Quantitative assessment of drivers of sediment load reduction in the Yangtze River basin, China. J Hydrol 580:124242. https://doi.org/10.1016/j.jhydrol.2019.124242
Qin ZX, Peng T, Singh VP, Chen M (2019) Spatio-temporal variations of precipitation extremes in Hanjiang River Basin, China, during 1960–2015. Theor Appl Climatol 138:1767–1783. https://doi.org/10.1007/s00704-019-02932-7
Rangecroft S, Van Loon AF, Maureira H, Verbist K, Hannah DM (2016) Multi-method assessment of reservoir effects on hydrological droughts in an arid region. Earth Syst Dynam Discuss. https://doi.org/10.5194/esd-2016-57
Rigby RA, Stasinopoulos DM (2005) Generalized additive models for location scale and shape. Appl Stat 54(3):507–554. https://doi.org/10.1111/j.1467-9876.2005.00510.x
Russo S, Dosio A, Sterl A, Barbosa P, Vogt J (2013) Projection of occurrence of extreme dry-wet years and seasons in Europe with stationary and nonstationary Standardized Precipitation Indices. J Geophys Res Atmos 118(14):7628–7639. https://doi.org/10.1002/jgrd.50571
Sepulcre-Canto G, Horion S, Singleton A, Carrao H, Vogt J (2012) Development of a Combined Drought Indicator to detect agricultural drought in Europe. Nat Hazards Earth Syst Sci 12:3519–3531. https://doi.org/10.5194/nhess-12-3519-2012
Shafer BA, Dezman LE (1982) Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. Proceedings of the 50th Annual Western Snow Conference, Colorado State University, Fort Collins, CO, pp 164–175
Sharma TC, Panu US (2014) Modeling of hydrological drought durations and magnitudes: experiences on Canadian streamflows. J Hydrol Reg Stud 1:92–106. https://doi.org/10.1016/j.ejrh.2014.06.006
Sheffield J, Wood EF, Roderick ML (2012) Little change in global drought over the past 60 years. Nat 491(7424):435–438. https://doi.org/10.1038/nature11575
Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35(2). https://doi.org/10.1029/2007GL032487
Su CJ, Chen XH (2019) Assessing the effects of reservoirs on extreme flows using nonstationary flood frequency models with the modified reservoir index as a covariate. Adv Water Resour 124:29–40. https://doi.org/10.1016/j.advwatres.2018.12.004
Talaee P, Tabari H, Ardakani S (2014) Hydrological drought in the west of Iran and possible association with large-scale atmospheric circulation patterns. Hydrol Process 28(3):764–773. https://doi.org/10.1002/hyp.9586
Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteorol Soc 79(1):61–78. https://doi.org/10.1175/1520-0477(1998)079%3c0061:APGTWA%3e2.0.CO;2
Tsakiris G, Pangalou D, Vangelis H (2007) Regional drought assessment based on the reconnaissance drought index (RDI). Water Resour Manag 21(5):821–833. https://doi.org/10.1007/s11269-006-9105-4
Tu XJ, Wu HO, Singh VP, Chen XH, Lin KR, Xie YT (2018) Multivariate design of socioeconomic drought and impact of water reservoirs. J Hydrol 566:192–204. https://doi.org/10.1016/j.jhydrol.2018.09.012
Van Loon AF, Gleeson T, Clark J, Dijk AV, Stahl K, Hannaford J, Baldassarre GD, Teuling AJ, Tallaksen LM, Uijlenhoet R (2016) Drought in the Anthropocene Nat Geosci 9(2):89–91. https://doi.org/10.1038/ngeo2646
Verbesselt J, Hyndman R, Zeileis A, Culvenor D (2010) Phenological change detection while accounting for abrupt and gradual trends in satellite image time series. Remote Sens Environ 114(12):2970–2980. https://doi.org/10.1016/j.rse.2010.08.003
Wang MH, Jiang SH, Ren LL, Xu C-Y, Wei LY, Cui H, Yuan F, Liu Y, Yang XL (2022) The development of a nonstationary standardized streamflow index using climate and reservoir indices as covariates. Water Resour Manag. https://doi.org/10.1007/s11269-022-03088-2
Wang YX, Duan LM, Liu TX, Li JZ, Feng P (2020) A non-stationary standardized streamflow index for hydrological drought using climate and human-induced indices as covariates. Sci Total Environ 699:134278. https://doi.org/10.1016/j.scitotenv.2019.134278
Watts LM, Laffan SW (2014) Effectiveness of the BFAST algorithm for detecting vegetation response patterns in a semi-arid region. Remote Sens Environ 154:234–245. https://doi.org/10.1016/j.rse.2014.08.023
Wei J, Wang WG, Shao QX, Rong YS, Xing WQ, Liu C (2020) Influence of mature El Nino-Southern Oscillation phase on seasonal precipitation and streamflow in the Yangtze River Basin, China. Int J Climatol 40(8):3885–3905. https://doi.org/10.1002/joc.6433
Wen L, Rogers K, Ling J, Saintilan N (2011) The impacts of river regulation and water diversion on the hydrological drought characteristics in the lower Murrumbidgee River, Australia. J Hydrol 405(3–4):382–391. https://doi.org/10.1016/j.jhydrol.2011.05.037
Williams AP, Cook ER, Smerdon JE, Cook BI, Abatzoglou JT, Bolles K, Baek SH, Badger AM, Livneh B (2020) Large contribution from anthropogenic warming to an emerging North American megadrought. Sci 368(6488):314–318. https://doi.org/10.1126/science.aaz9600
Wilhite DA, Glantz MH (1985) Understanding the drought phenomenon: the role of definitions. Water Int 10(3):111–120. https://doi.org/10.1080/02508068508686328
Wu JF, Chen XH, Chang T-J (2020) Correlations between hydrological drought and climate indices with respect to the impact of a large reservoir. Theor Appl Climatol 139:727–739. https://doi.org/10.1007/s00704-019-02991-w
Xiao MZ, Zhang Q, Singh VP (2015) Influences of ENSO, NAO, IOD and PDO on seasonal precipitation regimes in the Yangtze River basin, China. Int J Climatol 35(12):3556–3567. https://doi.org/10.1002/joc.4228
Xiong LH, Du T, Xu C-Y, Guo SL, Jiang C, Gippel CJ (2015) Non-stationary annual maximum flood frequency analysis using the norming constants method to consider non-stationarity in the annual daily flow series. Water Resour Manag 29(10):3615–3633. https://doi.org/10.1007/s11269-015-1019-6
Xu Y, Zhang X, Hao ZC, Hao FH, Li C (2021) Projections of future meteorological droughts in China under CMIP6 a three-dimensional perspective. Agr Water Manag 252:106849. https://doi.org/10.1016/j.agwat.2021.106849
Yang P, Zhang SQ, Xia J, Zhan CS, Cai W, Wang WY, Luo XG, Chen NC, Li J (2022) Analysis of drought and flood alternation and its driving factors in the Yangtze River Basin under climate change. Atmos Res 270:106087. https://doi.org/10.1016/j.atmosres.2022.106087
Yevjevich VM (1967) An objective approach to definitions and investigations of continental hydrologic droughts. J Hydrol 7(3):353. https://doi.org/10.1016/0022-1694(69)90110-3
Zhang Q, Gu XH, Singh VP, Xiao MZ, Chen XH (2015) Evaluation of flood frequency under non-stationarity resulting from climate indices and reservoir indices in the East River basin, China. J Hydrol 527:565–575. https://doi.org/10.1016/j.jhydrol.2015.05.029
Zhang T, Su XL, Feng K (2021) The development of a novel nonstationary meteorological and hydrological drought index using the climatic and anthropogenic indices as covariates. Sci Total Environ 786:147385. https://doi.org/10.1016/j.scitotenv.2021.147385
Zou L, Xia J, She DX (2018) Analysis of impacts of climate change and human activities on hydrological drought: A case study in the Wei River Basin, China. Water Resour Manag 32(4):1421–1438. https://doi.org/10.1007/s11269-017-1877-1
Funding
This study was supported by the National Natural Science Foundation of China (52009065), the Natural Science Foundation of Hubei Province (2020CFB293), the Natural Science Research Project of Yichang (A21-3–004), and the Key Science Research Project of Water Conservancy in Hubei Province (HBSLKY202109).
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Conceptualization: Y. Wang, T. Peng, X. Dong, C. Chen; Methodology: Y. Wang, T. Peng; Investigation: T. Peng, J. Liu, W. Chang, G. Wang; Original draft preparation: Y. Wang, T. Peng; Writing – review & editing: Y. Wang, T. Peng, Q. Lin, VP. Singh; Supervision: T. Peng.
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Wang, Y., Peng, T., Lin, Q. et al. A New Non-stationary Hydrological Drought Index Encompassing Climate Indices and Modified Reservoir Index as Covariates. Water Resour Manage 36, 2433–2454 (2022). https://doi.org/10.1007/s11269-022-03151-y
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DOI: https://doi.org/10.1007/s11269-022-03151-y