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GAMLSS-based nonstationary modeling of extreme precipitation in Beijing–Tianjin–Hebei region of China

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Abstract

Due to the climate variability and the intensification of human activities, the hydrological time series no longer satisfies the hypothesis of stationarity. In this study, a framework for precipitation frequency analysis is developed based on the Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS), a tool for modeling time series under nonstationary condition. Based on the 12 stations in Beijing–Tianjin–Hebei region of China, two approaches to nonstationary modeling in GAMLSS were applied to the annual maximum daily precipitation records. The results of the first approach, in which the parameters of the selected distributions are modeled as a function of time only, show the presence of clear nonstationarities in the annual maximum daily precipitation. In the second approach, the parameters of the precipitation distributions are modeled as functions of seven climate indices. The results show that the model using the second method captures more adequately the dispersion of precipitation values than the model using the first method. The application of nonstationary analysis shows the differences between the nonstationary quantiles and their stationary equivalents, which suggests the urgent need for nonstationary modeling of extreme precipitation in Beijing–Tianjin–Hebei region of China.

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References

  • Allan RJ, Nicholls N, Jones PD, Butterworth IJ (1991) A further extension of the Tahiti-Darwin SOI, early SOI results and Darwin pressure. J. Climate 4:743–749

    Article  Google Scholar 

  • Cox D, Isham V, Northrop P (2002) Floods: some probabilistic and statistical approaches. Philos Trans R Soc Lond Ser Math Phys Eng Sci 360:1389–1408

    Article  Google Scholar 

  • Deng W, Sun Z, Zeng G, Ni D (2009) Interdecadal variation of summer precipitation pattern over eastern China and its relationship with the North Pacific SST. J Atmos Sci 33:835–846 (in Chinese)

    Google Scholar 

  • Feng Z, Liu D, Zhang Y (2007) Water requirements and irrigation scheduling of spring maize using GIS and CropWat model in Beijing-Tianjin-Hebei region. Chin Geogr Sci 17:56–63

    Article  Google Scholar 

  • Gilroy KL, McCuen RH (2012) A nonstationary flood frequency analysis method to adjust for future climate change and urbanization. J Hydrol 414:40–48

    Article  Google Scholar 

  • Hao L, Ding Y, Min J, Zhang X (2011) Analysis on seasonally evolutive main modes of North China precipitation and their influence factors. Chin J Atmos Sci 35:217–234 (in Chinese)

    Google Scholar 

  • Hastie TJ, Tibshirani RJ (1990) Generalized additive models. CRC Press, Florida

  • Ishak EH, Rahman A, Westra S et al (2013) Evaluating the non-stationarity of Australian annual maximum flood. J Hydrol 494:134–145

    Article  Google Scholar 

  • Khaliq M, Ouarda T, Ondo J-C, Gachon P, Bobée B (2006) Frequency analysis of a sequence of dependent and/or non-stationary hydro-meteorological observations: a review. J Hydrol 329:534–552

    Article  Google Scholar 

  • Können GP, Jones PD, Kaltofen MH, Allan RJ (1998) Pre-1866 extensions of the Southern oscillation index using early Indonesian and Tahitian meteorological readings. J. Clim 11:2325–2339

    Article  Google Scholar 

  • Li X, Shao X (2010) East Asian summer monsoon rainfall in eastern China under the influence of spatial characteristics of the pattern analysis. J Beijing Norm Univ (Nat Sci) 46:729–732 (in Chinese)

    Google Scholar 

  • Lian Y (2012) Correlation between North Pacific Oscillation and East Asian summer monsoon. Sci Geogr Sin 27:19–27 (in Chinese)

    Google Scholar 

  • Liu Y, Ding Y (2008) Analysis and numerical simulation of the teleconnection between Indian summer monsoon and precipitation in North China. Acta Meteorol Sin 66:789–799 (in Chinese)

    Article  Google Scholar 

  • Liu X-f, Zhao L-m, Wang Y (2002) The climatic variation of precipitation in Beijing Tianjin and Hebei in spring and summer. Geogr Territorial Res 18:72–76 (in Chinese)

    Google Scholar 

  • Liu YY, Li WJ, Ai WX, Li QQ (2012) Reconstruction and application of monthly Western Pacific subtropical high indices. J Appl Meteorol Sci 23(4):414–423 (in Chinese)

    Google Scholar 

  • 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 17:3189–3203

    Article  Google Scholar 

  • Ma J, Yu B, Gao X, Li J (2008) Change of large scale circulation and its impact on the water vapor over North China. Plateau Meteorol 27:517–523 (in Chinese)

    Google Scholar 

  • McCarl BA, Villavicencio X, Wu X (2008) Climate change and future analysis: is stationarity dying? Am J Agric Econ 90:1241–1247

    Article  Google Scholar 

  • Milly PCD, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, Stouffer RJ (2008) Stationarity Is dead: whither water management? Science 319:573–574

    Article  Google Scholar 

  • Olsen JR, Lambert JH, Haimes YY (1998) Risk of extreme events under nonstationary conditions. Risk Anal 18(4):497–510

  • Qiao YT, Chen LT, Zhang QY (2002) The definition of East Asian Monsoon Indices and their relationship to climate in China. Chin J Atmos Sci 26(1):69–82 (in Chinese)

  • Rigby R, Stasinopoulos D (2005) Generalized additive models for location, scale and shape. J Roy Stat Soc: Ser C (Appl Stat) 54:507–554

    Article  Google Scholar 

  • Salas JD (1993) Analysis and modeling of hydrologic time series. Handb Hydrol 19:1–72

    Google Scholar 

  • Salas JD, Obeysekera J (2013) Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. J Hydrol Eng 19(3):554–568

  • Seidou O, Ramsay A, Nistor I (2012) Climate change impacts on extreme floods II: improving flood future peaks simulation using non-stationary frequency analysis. Nat Hazards 60(2):715–726

    Article  Google Scholar 

  • Sivapalan M, Samuel JM (2009) Transcending limitations of stationarity and the return period: process based approach to flood estimation and risk assessment. Hydrol processes 23(11):1671–1675

  • Stasinopoulos DM, Rigby RA (2007) Generalized additive models for location scale and shape (GAMLSS) in R. J Stat Softw 23:1–46

    Google Scholar 

  • Sui B, Sui G, Sui D (2007) Correlation analysis between the indexes of subtropical high over West Pacific, Zonal circulation indexes, polar vortex indexes and the summer precipitation in China. Sci Geogr Sin 27:69–77 (in Chinese)

    Google Scholar 

  • Sun ZH, Feng SY, Yang ZS, Wu H (2007) Primary analysis of the precipitation characteristics for Beijing during the period from 1950 to 2005. J Irrig Drain 26:12–16

    Google Scholar 

  • Tan M, Li X, Xie H, Lu C (2005) Urban land expansion and arable land loss in China—a case study of Beijing-Tianjin-Hebei region. Land use policy 22:187–196

    Article  Google Scholar 

  • Villarini G, Smith JA, Serinaldi F, Bales J, Bates PD, Krajewski WF (2009) Flood frequency analysis for nonstationary annual peak records in an urban drainage basin. Adv Water Resour 32:1255–1266

    Article  Google Scholar 

  • Villarini G, Smith JA, Napolitano F (2010) Nonstationary modeling of a long record of rainfall and temperature over Rome. Adv Water Resour 33(10):1256–1267

  • Wang T, Lu C, Yu B (2011a) Production potential and yield gaps of summer maize in the Beijing-Tianjin-Hebei region. J Geogr Sci 21:677–688

    Article  Google Scholar 

  • Wang Z, Luo Y, Liu C, Xia J, Zhang M (2011b) Spatial and temporal variations of precipitation in Haihe River Basin, China: six decades of measurements. Hydrol Process 25:2916–2923

    Article  Google Scholar 

  • Yang X, Xie Q, Zhu Y, Sun X, Guo Y (2005) Decadal-to-interdecadal variability of precipitation in North China and associated atmospheric and oceanic anomaly patterns. Chin J Geophys 48:789–797 (in Chinese)

    Google Scholar 

  • Yu X, Yang G, Zhou Z, Wang J, Qin D (2008) Variation of summer precipitation in Tianjin region and its urbanization effect. Prog Geogr 5:008

    Google Scholar 

  • Zhang D-D, Yan D-H, Wang Y-C, Lu F, Wu D (2014) Changes in extreme precipitation in the Huang-Huai-Hai River basin of China during 1960–2010. Theor Appl Climatol:1-15. doi: 10.1007/s00704-014-1159-2

  • Zhao J, Feng G, Yang J, Zhi R, Wang Q (2012) Analysis of the distribution of the large-scale drought/flood of summer in China under different types of the western Pacific subtropical high. Acta Meteorol Sin 70:1021–1031 (in Chinese)

    Google Scholar 

Download references

Acknowledgments

The climate data are provided by the National Meteorological Information Center of China. This study is jointly funded by the National Basic Research Program of China (Grant No. 2015CB452701 and 2013CB036406) and the Innovation Research Group Foundation Program of Natural Science Foundation of China (Grant No. 51109224), and major program foundation of the Chinese academy of sciences (Grant No.2012-ZD-13). We acknowledge D. M. Stasinopoulos and R. A. Rigby for making the GAMLSS package freely available in R.

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Authors and Affiliations

  1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, 1-A Fuxing Road, Haidian District, Beijing, 100038, People’s Republic of China

    Dong-dong Zhang, Deng-hua Yan, Yi-Cheng Wang, Fan Lu & Shao-hua Liu

  2. Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing, 100038, People’s Republic of China

    Dong-dong Zhang, Deng-hua Yan, Yi-Cheng Wang, Fan Lu & Shao-hua Liu

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  1. Dong-dong Zhang
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  2. Deng-hua Yan
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  3. Yi-Cheng Wang
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  4. Fan Lu
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  5. Shao-hua Liu
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Correspondence to Deng-hua Yan.

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Zhang, Dd., Yan, Dh., Wang, YC. et al. GAMLSS-based nonstationary modeling of extreme precipitation in Beijing–Tianjin–Hebei region of China. Nat Hazards 77, 1037–1053 (2015). https://doi.org/10.1007/s11069-015-1638-5

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  • DOI: https://doi.org/10.1007/s11069-015-1638-5

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