Bootstrap Pettitt test for detecting change points in hydroclimatological data: case study of Itaipu Hydroelectric Plant, Brazil

References

• Aksoy, H., 2000. Use of gamma distribution in hydrological analysis. Turkish Journal of Engineering and Environmental Sciences, 24 (6), 419–428.
   Google Scholar
• Alley, R.B., et al., 2003. Abrupt climate change. Science, 299 (5615), 2005–2010. doi:10.1126/science.1081056
   PubMed Web of Science ®Google Scholar
• Andreássian, V., 2004. Water and forests: from historical controversy to scientific debate. Journal of Hydrology, 291 (1–2), 1–27. doi:10.1016/j.jhydrol.2003.12.015
   Web of Science ®Google Scholar
• Bayer, D.M. and Collischonn, W., 2013. Deforestation impacts on discharge of the Ji-Paraná River - Brazilian Amazon. In: E. Boegh, et al., eds. Climate and land surface changes in hydrology. 359th ed. Gothenburg: IAHS Publication, H01, 327–332.
   Google Scholar
• Beaulieu, C., Chen, J., and Sarmiento, J.L., 2012. Change-point analysis as a tool to detect abrupt climate variations. Philosophical Transactions of the Royal Society, 370, 1228–1249. doi:10.1098/rsta.2011.0383
   Web of Science ®Google Scholar
• Bettolli, M.L. and Penalba, O.C., 2018. Statistical downscaling of daily precipitation and temperatures in southern La Plata Basin. International Journal of Climatology, 38 (9), 3705–3722. doi:10.1002/joc.2018.38.issue-9
   Web of Science ®Google Scholar
• Bosch, J.M. and Hewlett, J.D., 1982. A review of catchment experiment to determine the effect of vegetation changes on water yield and evapotranspiration. Journal of Hydrology, 55 (1–4), 3–23. doi:10.1016/0022-1694(82)90117-2
   Web of Science ®Google Scholar
• Boulanger, J.-P., et al., 2005. Observed precipitation in the Paraná - Plata hydrological basin: long-term trends, extreme conditions and ENSO teleconnections. Climate Dynamics, 24 (4), 393–413. doi:10.1007/s00382-004-0514-x
   Web of Science ®Google Scholar
• Brannstrom, C., et al., 2008. Land change in the Brazilian Savanna (Cerrado), 1986–2002: comparative analysis and implications for land-use policy. Land Use Policy, 25 (4), 579–595. doi:10.1016/j.landusepol.2007.11.008
   Web of Science ®Google Scholar
• Brown, A.E., et al., 2013. Impact of forest cover changes on annual streamflow and flow duration curve. Journal of Hydrology, 483, 39–50. doi:10.1016/j.jhydrol.2012.12.031
   Web of Science ®Google Scholar
• Buishand, T.A., 1982. Some methods for testing the homogeneity of rainfall records. Journal of Hydrology, 58 (1–2), 11–27. doi:10.1016/0022-1694(82)90066-X
   Web of Science ®Google Scholar
• Busuioc, A. and von Storch, H., 1996. Changes in the winter precipitation in Romania and its relation to the large-scale circulation. Tellus, 48 (4), 538–552. doi:10.1034/j.1600-0870.1996.t01-3-00004.x
   Google Scholar
• Cavalcanti, I.F.A., et al., 2015. Precipitation extremes over La Plata Basin – review and new results from observations and climate simulations. Journal of Hydrology, 523, 211–230. doi:10.1016/j.jhydrol.2015.01.028
   Web of Science ®Google Scholar
• Chandler, R.E. and Scott, M., 2011. Statistical methods for trend detection and analysis in the environmental sciences. Chichester, UK: John Wiley & Sons Ltd.
   Google Scholar
• Chow, V.T., 1964. Handbook of applied hydrology. Vol. 1, New York: McGraw-Hill.
   Google Scholar
• Dailidiené, I., et al., 2011. Long term water level and surface temperature changes in the lagoons of the southern and eastern Baltic. Oceanologia, 53 (1), 293–308. doi:10.5697/oc.53-1-TI.293
   Web of Science ®Google Scholar
• Davison, A.C. and Hinkley, D.V., 1997. Bootstrap methods and their application. Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Doyle, M.E. and Barros, V.R., 2011. Attribution of the river flow growth in the Plata Basin. International Journal of Climatology, 31 (15), 2234–2248. doi:10.1002/joc.v31.15
   Web of Science ®Google Scholar
• Efron, B. and Tibshirani, R.J., 1994. An introduction to the bootstrap. Chapman & Hall/CRC Monographs on Statistics & Applied Probability. New York, NY: Taylor & Francis.
   Google Scholar
• Fu, G., et al., 2004. Hydro-climatic trends of the Yellow river basin for the last 50 years. Climatic Change, 65 (1), 149–178. doi:10.1023/B:CLIM.0000037491.95395.bb
   Web of Science ®Google Scholar
• Gao, P., et al., 2015. Streamflow regimes of the yanhe river under climate and land use change, Loess Plateau, China. Hydrological Processes, 29 (10), 2402–2413. doi:10.1002/hyp.10309
   Web of Science ®Google Scholar
• Garcı́a, N.O. and Vargas, W.M., 1998. The temporal climatic variability in the “Rı́o de La Plata” basin displayed by the river discharges. Climatic Change, 38 (3), 359–379. doi:10.1023/A:1005386530866
   Web of Science ®Google Scholar
• Garcı́a, N.O., Vargas, W.M., and Del Valle Venencio, M., 2002. About of the 1970/71 climatic jump on the “Rı́o de La Plata” basin. In: Land atmosphere interactions, 16th Conference on Hydrology and 13th Symposium on Global Change and Climate Variations. No. JP1.11, Orlando, 1 p.
   Google Scholar
• INMET (Instituto Nacional de Meteorologia), 1992. Normais climatologicas do Brasil 1961–1990 [online]. http://www.inmet.gov.br/portal/index.php?r=clima/normaisclimatologicas [Accessed June 2017].
   Google Scholar
• IPCC (Intergovernmental Panel on Climate Change), 1992. Climate Change: The 1990 and 1992 IPCC assessments. First assessment report overview and policy-maker summaries and 1992 IPPC supplement. Technical report. Geneva, Switzerland: UNEP and WMO.
   Google Scholar
• IPCC, 1995. IPCC second assessment climate change 1995. A report of the Intergovernmental Panel on Climate Change. Technical report. Geneva, Switzerland: UNEP and WMO.
   Google Scholar
• IPCC, 2001. Climate change 2001: the scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. UNEP and WMO. Cambridge, UK and New York, NY: Cambridge University Press.
   Google Scholar
• IPCC, 2007. Climate change 2007: synthesis report. Contribution of working groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Technical report. Geneva, Switzerland: UNEP and WMO.
   Google Scholar
• IPCC, 2014. Climate change 2014: synthesis report. Contribution of working groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Technical report. Geneva, Switzerland: WMO and UNEP.
   Google Scholar
• IPCC, 2018. Summary for policymakers. In: Global warming of 1.5ºC. An IPCC Special Report on the impacts of global warming of 1.5ºC above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty (V. Masson-Delmotte et al., Eds.). Geneva, Switzerland: World Meteorological Organization.
   Google Scholar
• ITAIPU, 2019. Itaipu binacional [online]. https://www.itaipu.gov.br/ [Accessed January 2019].
   Google Scholar
• Jiang, S., et al., 2011. Quantifying the effects of climate variability and human activities on runoff from the Laohahe basin in northern China using three different methods. Hydrological Processes, 25 (16), 2492–2505. doi:10.1002/hyp.v25.16
   Web of Science ®Google Scholar
• Karabörk, M., Kahya, E., and Kömüşçü, A.U., 2007. Analysis of Turkish precipitation data: homogeneity and the Southern Oscillation forcings on frequency distributions. Hydrological Processes, 21 (23), 3203–3210. doi:10.1002/hyp.6524
   Web of Science ®Google Scholar
• Kruskal, W.H. and Wallis, A.W., 1952. Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47 (260), 583–621. doi:10.1080/01621459.1952.10483441
   Web of Science ®Google Scholar
• Kundzewicz, Z.W. and Robson, A., 2000. Detecting trend and other changes in hydrological data. Technical report. Geneva, Switzerland: World Climate Programme-Water.
   Google Scholar
• Kundzewicz, Z.W. and Robson, A., 2004. Change detection in hydrological records - a review of the methodology. Hydrological Sciences Journal, 49 (1), 7–19. doi:10.1623/hysj.49.1.7.53993
   Web of Science ®Google Scholar
• Leese, M.N., 1973. Use of censored data in the estimation of Gumbel distribution parameters for annual maximum flood series. Water Resources Research, 9 (6), 1534–1542. doi:10.1029/WR009i006p01534
   Web of Science ®Google Scholar
• Liu, D., et al., 2010. Impacts of climate change and human activities on surface runoff in the Dongjiang River basin of China. Hydrological Processes, 24 (11), 1487–1495. doi:10.1002/hyp.v24:11
   Web of Science ®Google Scholar
• Liu, L., Xu, Z.-X., and Huang, J.-X., 2012. Spatio-temporal variation and abrupt changes for major climate variables in the Taihu basin, China. Stochastic Environmental Research and Risk Assessment, 26 (6), 777–791. doi:10.1007/s00477-011-0547-8
   Web of Science ®Google Scholar
• Loucks, D.P. and van Beek, E. with contributions from Jery R Stedinger, E., Dijkman, J. P. M., Villars, M. T., 2005. Water resources systems planning and management. Paris, France: United Nations Educational, Scientific and Cultural Organization – UNESCO.
   Google Scholar
• Mallakpour, I. and Villarini, G., 2016. A simulation study to examine the sensitivity of the Pettitt test to detect abrupt changes in mean. Hydrological Sciences Journal, 61 (2), 245–254. doi:10.1080/02626667.2015.1008482
   Web of Science ®Google Scholar
• Mann, H.B. and Whitney, D.R., 1947. On a test of whether one of two random variables is stochastically larger than the other. The Annals of Mathematical Statistics, 18 (1), 50–60. doi:10.1214/aoms/1177730491
   Google Scholar
• Montgomery, D.C. and Runger, G.C., 2006. Applied statistics and probability for engineers. 4th ed. Wiley. National Academies of Sciences, E., Medicine, 2016. Attribution of Extreme Weather Events in the Context of Climate Change. Washington, DC: The National Academies Press.
   Google Scholar
• Montroull, N.B., Saurral, R.I., and Camilloni, I.A., 2018. Hydrological impacts in La Plata basin under 1.5, 2 and 3 ºC global warming above the pre-industrial level. International Journal of Climatology, 38 (8), 3355–3368. doi:10.1002/joc.5505
   Web of Science ®Google Scholar
• National Academy of Sciences, 2002. Abrupt climate change: inevitable surprises. Washington, DC: Committee on Abrupt Climate Change, Ocean Studies Board, Polar Research Board, Board on Atmospheric Sciences and Climate, Division on Earth and Life Studies, National Research Council.
   Google Scholar
• National Research Council, 2010. Assessment of intraseasonal to interannual climate prediction and predictability. Washington, DC: The National Academies Press.
   Google Scholar
• Nóbrega, R.L.B., et al., 2018. Impacts of land-use and land-cover change on stream hydrochemistry in the Cerrado and Amazon biomes. Science of the Total Environment, 635, 259–274. doi:10.1016/j.scitotenv.2018.03.356
   PubMed Web of Science ®Google Scholar
• ONS, 2017. Séries históricas de vazões [online]. http://ons.org.br/Paginas/resultados-da-operacao/historico-da-operacao/dados_hidrologicos_vazoes.aspx [Accessed June 2017].
   Google Scholar
• ONS, 2019. Glossário [online]. http://ons.org.br/paginas/conhecimento/glossario [Accessed January 2019].
   Google Scholar
• Pettitt, A.N., 1979. A non-parametric approach to the change-point problem. Journal of the Royal Statistical Society: Series C (Applied Statistics), 28 (2), 126–135.
   Google Scholar
• Puig, A., Salinas, H.F.O., and Borús, J.A., 2016. Recent changes (1973–2014 versus 1903–1972) in the flow regime of the lower Paraná river and current fluvial pollution warnings in its Delta biosphere reserve. Environmental Science and Pollution Research, 23 (12), 11471–11492. doi:10.1007/s11356-016-6501-z
   PubMed Web of Science ®Google Scholar
• R Core Team, 2017. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/
   Google Scholar
• Reis, S. and Yilmaz, H.M., 2008. Temporal monitoring of water level changes in Seyfe Lake using remote sensing. Hydrological Processes, 22 (22), 4448–4454. doi:10.1002/hyp.v22:22
   Web of Science ®Google Scholar
• Rizzo, M.L., 2007. Statistical computing with R. New York, NY: Chapman & Hall/CRC.
   Google Scholar
• Rosenzweig, C., et al., 2008. Attributing physical and biological impacts to anthropogenic climate change. Nature Publishing Group, 453, 353–358.
   Google Scholar
• Rougé, C., Ge, Y., and Cai, X., 2013. Detecting gradual and abrupt changes in hydrological records. Advances in Water Resources, 53, 33–44. doi:10.1016/j.advwatres.2012.09.008
   Web of Science ®Google Scholar
• Serinaldi, F. and Kilsby, C.G., 2016. The importance of prewhitening in change point analysis under persistence. Stochastic Environmental Research and Risk Assessment, 30 (2), 763–777. doi:10.1007/s00477-015-1041-5
   Web of Science ®Google Scholar
• Suhaila, J. and Yusop, Z., 2017. Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia. Meteorology and Atmospheric Physics, 130 (5), 565–581. doi:10.1007/s00703-017-0537-6
   Web of Science ®Google Scholar
• Tarhule, A. and Woo, M.-K., 1998. Changes in rainfall characteristics in northern Nigeria. International Journal of Climatology, 18 (11), 1261–1271. doi:10.1002/(ISSN)1097-0088
   Web of Science ®Google Scholar
• Tucci, C.E.M. and Clarke, R.T., 1998. Environmental issues in the La Plata basin. International Journal of Water Resources Development, 14 (2), 157–173. doi:10.1080/07900629849376
   Google Scholar
• UNDP, 2007. Human development report 2007/2008: fighting climate change: human solidarity in a divided world. London: Palgrave Macmillan.
   Google Scholar
• Villarini, G., et al., 2009. On the stationarity of annual flood peaks in the continental United States during the 20th century. Water Resources Research, 45 (8), 1–17. doi:10.1029/2008WR007645
   Web of Science ®Google Scholar
• Villarini, G. and Smith, J.A., 2010. Flood peak distributions for the eastern United States. Water Resources Research, 46 (6), 1–17. doi:10.1029/2009WR008395
   Web of Science ®Google Scholar
• Walpole, R.E., et al., 2006. Probability & statistics for engineers & scientists. 8th ed. London, UK: Prentice Hall.
   Google Scholar
• Wang, W., et al., 2013. Quantitative assessment of the impact of climate variability and human activities on runoff changes: a case study in four catchments of the Haihe River basin, China. Hydrological Processes, 27 (8), 1158–1174. doi:10.1002/hyp.9299
   Web of Science ®Google Scholar
• Wang, Y.-J. and Qin, D.-H., 2017. Influence of climate change and human activity on water resources in arid region of northwest china: an overview. Advances in Climate Change Research, 8 (4), 268–278. doi:10.1016/j.accre.2017.08.004
   Web of Science ®Google Scholar
• Wijngaard, J.B., Tank, A.M.G.K., and Konnen, G.P., 2003. Homogeneity of 20th century European daily temperature and precipitation series. International Journal of Climatology, 23 (6), 679–692. doi:10.1002/joc.906
   Web of Science ®Google Scholar
• WMO (World Meteorological Organization), 1988. Analysing long time series of hydrological data with respect to climate variability. Technical report 224. WMO.
   Google Scholar
• WMO, 2016. WMO statement on the state of the global climate in 2016. Technical report 1189. WMO.
   Google Scholar
• Worsley, K.J., 1979. On the likelihood ratio test for a shift in location of normal populations. Journal of the American Statistical Association, 74 (366a), 365–367.
   Google Scholar
• Xie, H., Li, D., and Xiong, L., 2014. Exploring the ability of the Pettitt method for detecting change point by Monte Carlo simulation. Stochastic Environmental Research and Risk Assessment, 28 (7), 1643–1655. doi:10.1007/s00477-013-0814-y
   Web of Science ®Google Scholar
• Yoo, C., Jung, K.-S., and Kim, T.-W., 2005. Rainfall frequency analysis using a mixed gamma distribution: evaluation of the global warming effect on daily rainfall. Hydrological Processes, 19 (19), 3851–3861. doi:10.1002/(ISSN)1099-1085
   Web of Science ®Google Scholar
• Yue, S., et al., 1999. The Gumbel mixed model for flood frequency analysis. Journal of Hydrology, 226 (1–2), 88–100. doi:10.1016/S0022-1694(99)00168-7
   Web of Science ®Google Scholar
• Yue, S., Ouarda, T.B.M.J., and Bobée, B., 2001. A review of bivariate gamma distribution for hydrological application. Journal of Hydrology, 246 (1), 1–18. doi:10.1016/S0022-1694(01)00374-2
   Web of Science ®Google Scholar
• Zhang, M., et al., 2017. A global review on hydrological responses to forest change across multiple spatial scales: importance of scale, climate, forest type and hydrological regime. Journal of Hydrology, 546, 44–59. doi:10.1016/j.jhydrol.2016.12.040
   Web of Science ®Google Scholar
• Zhang, X., et al., 2007. Detection of human influence on twentieth-century precipitation trends. Nature Publishing Group, 448, 461–466.
   Google Scholar
• Zuo, D., et al., 2012. Spatiotemporal variations and abrupt changes of potential evapotranspiration and its sensitivity to key meteorological variables in the Wei River basin, China. Hydrological Processes, 26 (8), 1149–1160. doi:10.1002/hyp.8206
   Web of Science ®Google Scholar