Advertisement

Theoretical and Applied Climatology

, Volume 133, Issue 3–4, pp 1021–1033 | Cite as

Spatio-temporal assessment of streamflow droughts over Southern South America: 1961–2006

  • Juan Antonio Rivera
  • Olga C. Penalba
Original

Abstract

This paper performed a streamflow drought climatology considering some of the most important rivers of Southern South America, a region highly vulnerable to climatic variations, based on the analysis of monthly streamflow records. The standardized hydrological drought index (SHDI) was used in order to depict the main characteristics of droughts—number of drought events, mean duration, and mean severity—over the period 1961–2006. Firstly, the suitability of this index based on the two-parameter gamma distribution was evaluated, considering that the use of the SHDI has been limited over the region. The regional aspects of streamflow droughts were identified through a clear relationship between drought frequency and its duration, indicating different temporal variations in streamflow records over the study area. Spatial patterns exhibit heterogeneous features in terms of streamflow drought severity and can be associated to the geographical characteristics of the basins. Observed trends in the SSI are in line with the increases in precipitation totals over the second half of the twentieth century over much of the study area. Nevertheless, drought conditions are observed more often in the basins south of 40°S, in line with recent trends in large-scale climatic oscillations. The streamflow drought characteristics can provide critical values for different water-based activities, as also information to develop strategic plans that are needed for adequate water resource management considering the different climatic features over Southern South America.

Keywords

Streamflow droughts Temporal variability Water resources 

Notes

Acknowledgements

This work was supported by the University of Buenos Aires under grant UBA-20020130100263BA and the Argentinean Council of Research and Technology (CONICET) under grant PIP 11220150100137CO. We thank the Subsecretaría de Recursos Hídricos de Argentina for providing the monthly streamflow data used in the study.

References

  1. Alexandersson H (1986) A homogeneity test applied to precipitation data. J Climatol 6:661–675CrossRefGoogle Scholar
  2. Amor LG, Carrasco A, Ibáñez JC (2009) Using and testing drought indicators. In: Iglesias A, Garrote L, Cancelliere A, Cubillo F, Wilhite D (eds) Coping with drought risk in agriculture and water supply systems. Drought Management and Policy Development in the Mediterranean. Springer Netherlands, Dordrecht, pp 55–65Google Scholar
  3. Anderson TW, Darling DA (1952) Asymptotic theory of certain “goodness of fit” criteria based on stochastic processes. Ann Math Stat 23:193–212CrossRefGoogle Scholar
  4. Andreadis KM, Lettenmaier DP (2006) Trends in 20th century drought over the continental United States. Geophys Res Lett 33:L10403. doi: 10.1029/2006GL025711 CrossRefGoogle Scholar
  5. Barker LJ, Hannaford J, Chiverton A, Svensson C (2016) From meteorological to hydrological drought using standardised indicators. Hydrol Earth Syst Sci 20:2483–2505CrossRefGoogle Scholar
  6. Barros V, Silvestri GE (2002) The relation between sea surface temperature at the subtropical south-central Pacific and precipitation in southeastern South America. J Clim 15:251–267CrossRefGoogle Scholar
  7. Barros VR, Castañeda ME, Doyle ME (2000) Recent precipitation trends in soUthern South America East of the Andes: an indication of a mode of climatic variability. In: Smolka PP, Volkheimer W (eds) Southern hemisphere paleo and neoclimates. Springer Berlin Heidelberg, New York, pp 187–206CrossRefGoogle Scholar
  8. Bianchi L, Rivera J, Rojas J, Britos Navarro M, Villalba R (2017) A regional water balance indicator inferred from satellite images of an Andean endorheic basin in central-western Argentina. Hydrol Sci J 62(4):533–545CrossRefGoogle Scholar
  9. Blain GC, Meschiatti MC (2015) Inadequacy of the gamma distribution to calculate the Standardized Precipitation Index. Revista Brasileira de Engenharia Agrícola e Ambiental 19(12):1129–1135CrossRefGoogle Scholar
  10. Carril AF, Cavalcanti IFA, Menéndez CG, Sörensson A, López-Franca N, Rivera JA, Robledo F, Zaninelli PG, Ambrizzi T, Penalba OC, da Rocha RP, Sánchez E, Bettolli ML, Pessacg N, Renom M, Ruscica R, Solman S, Tencer B, Grimm A, Rusticucci M, Cherchi A, Tedeschi R, Zamboni L (2016) Extreme events in La Plata basin: a retrospective analysis of what we have learned during CLARIS-LPB project. Clim Res 68:95–116CrossRefGoogle Scholar
  11. Cavalcanti IFA, Carril A, Penalba O, Grimm AM, Menendez C, Sánchez E, Cherchi A, Sörensson A, Robledo F, Rivera J, Pántano V, Bettolli ML, Zaninelli P, Zamboni L, Tedeschi RG, Dominguez M, Ruscica R, Flach R (2015) Precipitation extremes over La Plata Basin—review and new results from observations and climate simulations. J Hydrol 523:211–230CrossRefGoogle Scholar
  12. Compagnucci RH, Araneo DC (2005) Identificación de áreas de homogeneidad estadística para los caudales de ríos andinos argentinos y su relación con la circulación atmosférica y la temperatura superficial del mar. Meteor-Forschung 30(1–2):41–53Google Scholar
  13. Cuya DGP, Brandimarte L, Popescu I, Alterach J, Peviani M (2013) A GIS-based assessment of maximum potential hydropower production in La Plata Basin under global changes. Renew Energy 50:103–114CrossRefGoogle Scholar
  14. Dehghani M, Saghafian B, Nasiri Saleh F, Farokhnia A, Noori R (2014) Uncertainty analysis of streamflow drought forecast using artificial neural networks and Monte-Carlo simulation. Int J Climatol 34:1169–1180CrossRefGoogle Scholar
  15. Díaz E, Rodríguez A, Dölling O, Bertoni JC, Smrekar M (2016) Identificación y caracterización de sequías hidrológicas en Argentina. Tecnología y Ciencias del Agua 7(1):125–133Google Scholar
  16. Doyle ME, Barros VR (2011) Attribution of the river flow growth in the Plata Basin. Int J Climatol 31:2234–2248CrossRefGoogle Scholar
  17. Fernández HW, Buscemi NH (2000) Análisis y caracterización de sequías hidrológicas en el Centro Oeste de Argentina. In: Proceedings of the XVIII Congreso Nacional del Agua (CONAGUA). Universidad Nacional de Santiago del Estero, Termas de Río Hondo, CD-ROMGoogle Scholar
  18. Fernández-Larrañaga B (1997) Identificación y caracterización de sequías hidrológicas en Chile Central. Ingeniería del Agua 4(4):37–46CrossRefGoogle Scholar
  19. Feyen L, Dankers R (2009) Impact of global warming on streamflow drought in Europe. J Geophys Res 114:D17116. doi: 10.1029/2008JD011438 CrossRefGoogle Scholar
  20. Gan M, Rao V (1991) Surface cyclogenesis over South America. Mon Wea Rev 119:1293–1302CrossRefGoogle Scholar
  21. Garreaud RD, Vuille M, Compagnucci R, Marengo J (2009) Present-day South American climate. Palaeogeogr Palaeoclimatol Palaeoecol 281:180–195CrossRefGoogle Scholar
  22. Hamed KH, Rao AR (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204(1–4):182–196CrossRefGoogle Scholar
  23. Hayes M, Svoboda M, Wall N, Widham M (2011) The Lincoln declaration on drought indices: universal meteorological drought index recommended. Bull Am Meteorol Soc 92(4):485–488CrossRefGoogle Scholar
  24. Heim RR (2002) A review of twentieth century drought indices used in the United States. Bull Am Meteorol Soc 83:1149–1165CrossRefGoogle Scholar
  25. Hisdal H, Tallaksen L (2003) Estimation of regional meteorological and hydrological drought characteristics: a case study for Denmark. J Hydrol 281:230–247CrossRefGoogle Scholar
  26. Kane RP (2005) Spectral characteristics and ENSO relationship of the Paraná river streamflow. Mausam 56(2):367–374Google Scholar
  27. Khaliq MN, Ouarda TBMJ, Gachon P (2009) Identification of temporal trends in annual and seasonal low flows occurring in Canadian rivers: the effect of short- and long-term persistence. J Hydrol 369:183–197CrossRefGoogle Scholar
  28. Kulkarni A, Von Storch H (1995) Monte-Carlo experiments on the effect of serial correlation on the Mann-Kendall test for trend. Meteorol Z 4(2):82–85CrossRefGoogle Scholar
  29. Laio F (2004) Cramer–von Mises and Anderson-Darling goodness of fit tests for extreme value distributions with unknown parameters. Water Resour Res 40:W09308. doi: 10.1029/2004WR003204 CrossRefGoogle Scholar
  30. Lloyd-Hughes B, Saunders MA (2002) A drought climatology for Europe. Int J Climatol 22(13):15711592CrossRefGoogle Scholar
  31. Marshall GJ (2003) Trends in the southern annular mode from observations and Reanalyses. J Clim 16:4134–4143CrossRefGoogle Scholar
  32. Masiokas M, Villalba R, Luckman B, Le Quesne C, Aravena JC (2006) Snowpack variations in the Central Andes of Argentina and Chile, 1951-2005: large-scale atmospheric influences and implications for water resources in the region. J Clim 19:6334–6352CrossRefGoogle Scholar
  33. McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of the Eight Conference on Applied Climatology. American Meteorological Society, Anaheim, pp 179–184Google Scholar
  34. Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23:881–897CrossRefGoogle Scholar
  35. Núñez J, Rivera D, Oyarzún R, Arumí JL (2014) On the use of standardized drought indices under decadal climate variability: critical assessment and drought policy implications. J Hydrol 517:458–470CrossRefGoogle Scholar
  36. Penalba OC, Rivera JA (2013) Future changes in drought characteristics over southern South America projected by a CMIP5 ensemble. Am J Clim Chang 2(3):173–182CrossRefGoogle Scholar
  37. Penalba OC, Rivera JA (2016) Precipitation response to El Niño/La Niña events in Southern South America—emphasis in regional drought occurrences. Adv Geosci 42:1–14CrossRefGoogle Scholar
  38. Penalba OC, Rivera JA, Pántano VC (2014) The CLARIS LPB database: constructing a long-term daily hydro-meteorological dataset for La Plata Basin, Southern South America. Geosci Data J 1:20–29CrossRefGoogle Scholar
  39. 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. doi: 10.5194/esd-2016-57
  40. Rivera JA (2014) Aspectos climatológicos de las sequías meteorológicas en el sur de Sudamérica. Análisis regional y proyecciones futuras. University of Buenos Aires. http://digital.bl.fcen.uba.ar/Download/Tesis/Tesis_5504_Rivera.pdf. Accessed 7 October 2016
  41. Rivera JA, Penalba OC (2014) Trends and spatial patterns of drought affected area in southern South America. Climate 2:264–278CrossRefGoogle Scholar
  42. Rivera JA, Araneo DC, Penalba OC (2017a) Threshold level approach for streamflow droughts analysis in the Central Andes of Argentina: a climatological assessment. Hydrol Sci J (in press)Google Scholar
  43. Rivera JA, Araneo DC, Penalba OC, Villalba R (2017b) Regional aspects of streamflow droughts in the Andean rivers of Patagonia. Argentina Links with large-scale climatic oscillations Hydrology Research. doi: 10.2166/nh.2017.207
  44. Scarpati OE, Spescha L, Fioriti MJ, Capriolo AD (2001) El Niño driven climate variability and drainage anomalies in Patagonian region, Argentina. Cuadernos de Investigación Geográfica 27:179–191CrossRefGoogle Scholar
  45. Shiferaw B, Tesfaye K, Kassie M, Abate T, Prasanna BM, Menkir A (2014) Managing vulnerability to drought and enhancing livelihood resilience in sub-Saharan Africa: technological, institutional and policy options. Weather and Climate Extremes 3:67–79CrossRefGoogle Scholar
  46. Shin H, Jung Y, Jeong C, Heo J-H (2012) Assessment of modified Anderson–Darling test statistics for the generalized extreme value and generalized logistic distributions. Stoch Environ Res Risk Assess 26:105–114CrossRefGoogle Scholar
  47. Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35:L02405. doi: 10.1029/2007GL032487 CrossRefGoogle Scholar
  48. Sienz F, Bothe O, Fraedrich K (2012) Monitoring and quantifying future climate projections of dryness and wetness extremes: SPI bias. Hydrol Earth Syst Sci 16:2143–2157CrossRefGoogle Scholar
  49. Soláková T, De Michele C, Vezzoli R (2014) Comparison between parametric and nonparametric approaches for the calculation of two drought indices: SPI and SSI. J Hydrol Eng 19(9). doi: 10.1061/(ASCE)HE.1943-5584.0000942
  50. Sousa PM, Trigo RM, Aizpurua P, Nieto R, Gimeno L, Garcia-Herrera R (2011) Trends and extremes of drought indices throughout the 20th century in the Mediterranean. Nat Hazards Earth Syst Sci 11:33–51CrossRefGoogle Scholar
  51. Stagge JH, Tallaksen LM, Gudmundsson L, Van Loon AF, Stahl K (2015) Candidate distributions for climatological drought indices (SPI and SPEI). Int J Climatol 35(13):4027–4040CrossRefGoogle Scholar
  52. Stephens MA (1976) Asymptotic power of EDF statistics for exponentiality against gamma and Weibull alternatives. Technical report no. 297, Department Statistic Stanford UniversityGoogle Scholar
  53. Svensson C, Hannaford J, Prosdocimi I (2017) Statistical distributions for monthly aggregations of precipitation and streamflow in drought indicator applications. Water Resour Res 53. doi: 10.1002/2016WR019276
  54. Tabari H, Nikbakht J, Talaee PH (2013) Hydrological drought assessment in northwestern Iran based on streamflow drought index (SDI). Water Resour Manag 27:137–151CrossRefGoogle Scholar
  55. Van Loon AF (2015) Hydrological drought explained. WIREs Water 2015. doi: 10.1002/wat2.1085
  56. Vera CS, Vigliarolo PK, Berbery EH (2002) Cold season synoptic scale waves over subtropical South America. Mon Wea Rev 130:684–699CrossRefGoogle Scholar
  57. Vicente-Serrano SM, López-Moreno JI, Beguería S, Lorenzo-Lacruz J, Azorin-Molina C, Morán-Tejada E (2012) Accurate computation of a streamflow drought index. J Hydrol Eng 17:318–332CrossRefGoogle Scholar
  58. Vich A, Bizzotto F, Vaccarino E, Correas M, Manduca F (2010) Tendencias y cambios abruptos en el escurrimiento de algunos ríos con nacientes en la cordillera y serranías del oeste argentino. In: Paoli CU, Malinow GV (eds) Criterios para la determinación de crecidas de diseño en sistemas climáticos cambiantes. Universidad Nacional del Litoral, Santa Fe, pp 149–166Google Scholar
  59. Vich AIJ, Norte FA, Lauro C (2014) Análisis regional de frecuencias de caudales de ríos pertenecientes a cuencas con nacientes en la Cordillera de Los Andes. Meteorologica 39:3–26Google Scholar
  60. Wilhite DA, Sivakumar MVK, Pulwarty R (2014) Managing drought risk in a changing climate: the role of national drought policy. Weather and Climate Extremes 3:4–13CrossRefGoogle Scholar
  61. Wong G, Van Lanen HAJ, Torfs PJJF (2013) Probabilistic analysis of hydrological drought characteristics using meteorological drought. Hydrol Sci J 58(2):253–270CrossRefGoogle Scholar
  62. World Meteorological Organization (WMO) (2008) Manual on Low-flow Estimation and Prediction. WMO No. 1029, Geneva, SwitzerlandGoogle Scholar
  63. Wu H, Soh L-K., Samal A, Chen X-H (2007a) Trend analysis of streamflow drought events in Nebraska. Water Resour Manag, doi: 10.1007/s11269-006-9148-6
  64. Wu H, Svoboda MD, Hayes MJ, Wilhite DA, Wen F (2007b) Appropriate application of the standardized precipitation index in arid locations and dry seasons. Int J Climatol 27:65–79CrossRefGoogle Scholar
  65. Zanvettor R, Ravelo A (2000) Using the SPI to monitor the 1999-2000 drought in Northeastern Argentina. Drought Network News 12(3):3–4Google Scholar
  66. Zhang Q, Li J, Singh VP, Bai Y (2012) SPI-based evaluation of drought events in Xinjiang, China. Nat Hazards 64:481–492CrossRefGoogle Scholar
  67. Zhu Y, Chang J, Huang S, Huang Q (2016) Characteristics of integrated droughts based on a nonparametric standardized drought index in the Yellow River Basin, China. Hydrol Res 47(2):454–467Google Scholar

Copyright information

© Springer-Verlag GmbH Austria 2017

Authors and Affiliations

  1. 1.Instituto Argentino de NivologíaGlaciología y Ciencias Ambientales (IANIGLA)MendozaArgentina
  2. 2.Universidad Juan Agustín MazaMendozaArgentina
  3. 3.Departamento de Ciencias de la Atmósfera y los Océanos, Facultad de Ciencias Exactas y NaturalesUniversidad de Buenos AiresBuenos AiresArgentina
  4. 4.Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)Buenos AiresArgentina

Personalised recommendations