Spatial analysis and temporal trends of daily precipitation concentration in the Mantaro River basin: central Andes of Peru

  • Ricardo Zubieta
  • Miguel Saavedra
  • Yamina Silva
  • Lucy Giráldez
Original Paper


The analysis of annual or seasonal data can lead to misinterpretation of spatio-temporal rainfall distribution. A high percentage of total annual precipitation can fall in just a few days, causing floods or landslides. Large economic losses from these events are particularly common in Peru, where the daily precipitation has been poorly investigated. This study presents a spatio-temporal analysis of concentration index over the Mantaro River basin in the central Peruvian Andes. Daily rainfall data recorded at 46 rainfall stations between 1974 and 2004 were selected in this study. In terms of average values, the analysis of daily rainfall indicates that low-intensity events account for 38 % of rainy days but only approximately 9 % of the total rain amount. In contrast, high- and very high-intensity events account for 35 % of rainy days and approximately 71 % of the total rain amount. The results also indicate higher concentration and lower intensity over the Northern and Central regions, compared to Southern region of the basin. Rainfall concentration gives evidence of why some of these places are more likely to be affected by extreme weather events; spatial distribution of event intensity can be partly explained by daily rainfall heterogeneity and orography. Moreover, Mann–Kendall test mostly shows a significant change toward a weaker seasonality of daily precipitation distribution over high-mountain regions.


Daily precipitation Concentration index Peruvian Andes Extreme events 



The authors would like to thank the Instituto Geofísico del Perú (IGP), Servicio Nacional de Meteorologia e Hidrologia (SENAMHI), International Research Institute (IRI) and ELECTRO-PERU for providing observed data; and J. Chunga for their support in data preprocessing. The first author thanks suggestions and comments raised during the MAREMEX project (IGP), which was supported by the International Development Research Centre: IDRC-Canada. Suggestions from D. Ramirez and A. Verastegui and B. Fraser were greatly appreciated.

Supplementary material

477_2016_1235_MOESM1_ESM.docx (3.3 mb)
Supplementary material 1 (DOCX 3386 kb)


  1. Alijani B, O’Brien J, Yarnal B (2008) Spatial analysis of precipitation intensity and concentration in Iran. Theor Appl Climatol 94:107–124. doi: 10.1007/s00704-007-0344-y CrossRefGoogle Scholar
  2. Brooks CEP, Carruthers N (1953) Handbook of statistical methods in meteorology. Meteorological Office, LondonGoogle Scholar
  3. Brunet-Moret Y (1979) Homogénéisation des précipitations. Cahiers ORSTOM Sér Hydrol 16:3–4Google Scholar
  4. Buytaert W, Celleri R, Willems P (2006) Spatial and temporal rainfall variability in mountainous areas: a case study from the south Ecuadorian Andes. J Hydrol 329:413–421. doi: 10.1016/j.jhydrol.2006.02.031. ISSN:0022-1694
  5. Celleri R, Willems P, Buytaert W, Feyen J (2007) Space–time rainfall variability in the Paute basin, Ecuadorian Andes. Hydrol Process 21:3316–3327. doi: 10.1002/hyp.6575 CrossRefGoogle Scholar
  6. Cortesi N, Gonzalez-Hidalgo JC, Brunetti M, Martin-Vide J (2012) Daily precipitation concentration across Europe 1971–2010. Nat Hazards Earth Syst Sci 12:2799–2810. doi: 10.5194/nhess-12-2799-2012 CrossRefGoogle Scholar
  7. Coscarelli R, Caloiero T (2012) Analysis of daily and monthly rainfall concentration in Southern Italy (Calabria region). J Hydrol 416–417:145–156. doi: 10.1016/j.jhydrol.2011.11.047 CrossRefGoogle Scholar
  8. De Luis M, Gonzalez-Hidalgo JC, Brunetti M, Longares LA (2011) Precipitation concentration changes in Spain 1946–2005. Nat Hazards Earth Syst Sci 11:1259–1265. doi: 10.5194/nhess-11-1259-2011 CrossRefGoogle Scholar
  9. Espinoza JC, Ronchail J, Guyot JL, Cocheneau G, Filizola N, Lavado W, de Oliveira E, Pombosa R, Vauchel P (2009) Spatio-temporal rainfall variability in the Amazon Basin Countries (Brazil, Peru, Bolivia, Colombia and Ecuador). Int J Climatol 29:1574–1594. doi: 10.1002/joc.1791 CrossRefGoogle Scholar
  10. Garreaud RD (1999) Multiscale analysis of the summertime precipitation over the central Andes. Mon Weather Rev 127(5):901–921CrossRefGoogle Scholar
  11. Giráldez L, Silva Y, Trasmonte G (2012) Impacto de los veranillos en la agricultura del valle del Mantaro. Libro Manejo de riesgos de desastres ante eventos meteorológicos extremos en el valle del Mantaro, Volumen II. Resultados del proyecto MAREMEX. Instituto Geofísico del Perú, LimaGoogle Scholar
  12. Hiez G (1977) L’homogénéité des données pluviométriques. Cahiers ORSTOM Sér Hydrol 14:129–172Google Scholar
  13. IGP (2005a) Vulnerabilidad actual y futura ante el cambio climático y medidas de adaptación en la Cuenca del Río Mantaro. Fondo Editorial del CONAM, LimaGoogle Scholar
  14. IGP (2005b) Diagnóstico de la cuenca del río Mantaro bajo la visión de cambio climático. Fondo Editorial CONAM, LimaGoogle Scholar
  15. IGP (2005c) Atlas Climatológico de precipitaciones y temperaturas en la Cuenca del Mantaro. Fondo Editorial CONAM, LimaGoogle Scholar
  16. IGP (2012) Manejo de riesgos de desastres ante eventos meteorológicos extremos en el valle delMantaro, Volumen II. Resultados del proyecto MAREMEX. Instituto Geofísico del Perú, LimaGoogle Scholar
  17. Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University Press, New YorkGoogle Scholar
  18. Jolliffe IT, Hope PB (1996) Representation of daily rainfall distributions using normalized rainfall curves. Int J Climatol 16:1157–1163CrossRefGoogle Scholar
  19. Junquas C, Li L, Vera CS, Le Treut H, Takahashi K (2015) Influence of South America orography on summer time precipitation in Southeastern South America. Clim Dyn. doi: 10.1007/s00382-015-2814-8 Google Scholar
  20. Kendall MG (1975) Rank correlation methods. Griffin, LondonGoogle Scholar
  21. Lavado WC, Labat D, Ronchail J, Espinoza JC, Guyot JL (2012) Trends in rainfall and temperature in the Peruvian Amazon-Andes basin over the last 40 years (1965–2007). Hydrol Process 27:2944–2957. doi: 10.1002/hyp.9418 Google Scholar
  22. Lichtenstern A (2013) Kriging methods in spatial statistics, Bachelor’s Thesis, Department of Mathematics, Tecnische Universität MünchenGoogle Scholar
  23. López-Moreno I, Fontaneda S, Bazo J, Revuelto J, Azorin-Molina C, Valero-Garcés B, Morán-Tejeda E, Vicente-Serrano SM, Zubieta R, Alejo-Cochachín J (2014) Recent glacier retreat and climate trends in Cordillera Huaytapallana, Peru. Glob Planet Change 112(2014):1–11. doi: 10.1016/j.gloplacha.2013.10.010 CrossRefGoogle Scholar
  24. Lowman LEL, Barros AP (2014) Investigating links between climate and orography in the central Andes: coupling erosion and precipitation using a physical-statistical model. J Geophys Res Earth Surf 119:1322–1353. doi: 10.1002/2013JF002940 CrossRefGoogle Scholar
  25. Ly S, Charles C, Degré A (2011) Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium. Hydrol Earth Syst Sci 15:2259–2274. doi: 10.5194/hess-15-2259-2011 CrossRefGoogle Scholar
  26. Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259CrossRefGoogle Scholar
  27. Martin-Vide J (2004) Spatial distribution of a daily precipitation concentration index in Peninsular Spain. Int J Climatol 24:959–971. doi: 10.1002/joc.1030 CrossRefGoogle Scholar
  28. Montecinos A, Aceituno P (2003) Seasonality of the ENSO-related rainfall variability in central Chile and associated circulation anomalies. J Clim 16:281–296. doi: 10.1175/1520-0442(2003)016<0281:SOTERR>2.0.CO;2 CrossRefGoogle Scholar
  29. Montecinos A, Díaz A, Aceituno P (2000) Seasonal diagnostic and predictability of rainfall in subtropical South America based on tropical Pacific SST. J Clim 13:746–758. doi: 10.1175/1520-0442(2000)013<0746:SDAPOR>2.0.CO;2 CrossRefGoogle Scholar
  30. Pepin E, Guyot J, ArmijosE Bazan H, Fraizy P, Moquet JS, Noriega L, Lavado W, Pombosa R, Vauchel P (2013) Climatic control on eastern Andean denudation rates (Central Cordillera from Ecuador to Bolivia). J S Am Earth Sci 44:85–93. doi: 10.1016/j.jsames.2012.12.010 CrossRefGoogle Scholar
  31. Ramos MC, Martinez JA (2006) Trends in precipitation concentration and extremes in the Mediterranean Penedès—Anoia Region, Ne Spain. Clim Change 74:457–474. doi: 10.1007/s10584-006-3458-9 CrossRefGoogle Scholar
  32. Rutllant J, Fuenzalida H (1991) Synoptic aspects of the central Chile rainfall variability associated with the Southern Oscillation. Int J Climatol 11:63–76. doi: 10.1002/joc.3370110105 CrossRefGoogle Scholar
  33. Saavedra N, Müller EP, Foppiano AJ (2002) Monthly mean rainfall frequency model for the Central Chile coast: some climatic inferences. Int J Climatol 22:1495–1509. doi: 10.1002/joc.806 CrossRefGoogle Scholar
  34. Sarricolea P, Herrera MJ, Araya C (2013) Análisis de la concentración diaria de las precipitaciones en Chile central y su relación con la componente zonal (subtropicalidad) y meridiana (orográfica). Investig Geogr Chile 45:37–50Google Scholar
  35. Shi P, Qiao X, Chen X, Zhou M, Qu S, Ma X, Zhang Z (2013a) Spatial distribution and temporal trends in daily and monthly precipitation concentration indices in the upper reaches of the Huai River, China. Stoch Environ Res Risk Assess. doi: 10.1007/s00477-013-0740-z Google Scholar
  36. Shi W, Yu X, Liao W, Wang Y, Jia B (2013b) Spatial and temporal variability of daily precipitation concentration in the Lancang River basin. J Hydrol. doi: 10.1016/j.jhydrol.2013.05.002 Google Scholar
  37. Silva Y, Takahashi K, Chávez R (2008) Dry and wet rainy seasons in the Mantaro river basin (Central Peruvian Andes). Adv Geosci 14:261–264. doi: 10.5194/adgeo-14-261-2008 CrossRefGoogle Scholar
  38. Suhaila J, Jemain AA (2012) Spatial analysis of daily rainfall intensity and concentration index in Peninsular Malaysia. Theor Appl Climatol 108:235–245. doi: 10.1007/s00704-011-0529-2 CrossRefGoogle Scholar
  39. Sulca J, Vuille M, Silva Y, Takahashi K (2016) Teleconnections between the Peruvian Central Andes and Northeast Brazil during extreme rainfall events in Austral summer. J Hydrometeorol 17:499–515. doi: 10.1175/JHM-D-15-0034.1 CrossRefGoogle Scholar
  40. Zhang Q, Xu CY, Gemmer M, Chen YQ, Liu CL (2009) Changing properties of precipitation concentration in the Pearl River basin, China. Stoch Environ Res Risk Assess 23:377–385. doi: 10.1007/s00477-008-0225-7 CrossRefGoogle Scholar
  41. Zhiqing X, Yin D, Aijun J, Yuguo D (2005) Climatic trends of different intensity heavy precipitation events concentration in China. J Geogr Sci 15(4):459–466. doi: 10.1360/gs050409 CrossRefGoogle Scholar
  42. Zhou J, Lau KM (1998) Does a monsoon climate exist over South America? J Clim 11:1020–1040. doi: 10.1175/1520-0442(1998)011<1020:DAMCEO>2.0.CO;2 CrossRefGoogle Scholar
  43. Zubieta R, Lagos P (2010) Cambios de la superficie glaciar en la cordillera Huaytapallana: Periodo 1976–2006. Libro Cambio climático en la cuenca del río Mantaro. Balance de 7 años de estudio en la cuenca del Mantaro. Instituto Geofísico del PerúGoogle Scholar
  44. Zubieta R, Saavedra M (2013) Distribución espacial del índice de concentración de precipitación diaria en los Andes centrales peruanos: valle del río Mantaro. Revista del Encuentro Científico Internacional ECI Peru 9(2):61–70Google Scholar
  45. Zubieta R, Quijano J, Latínez K, Guillermo P (2012) Evaluación de las zonas de peligro frente a inundaciones por máximas avenidas en el valle del río Mantaro. Manejo de riesgos de desastres ante eventos meteorológicos extremos en el valle del Mantaro, vol II. Proyecto Maremex Mantaro. Instituto Geofísico del Perú, LimaGoogle Scholar
  46. Zubieta R, Geritana A, Espinoza JC, Lavado W (2015) Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the western Amazon basin of Peru and Ecuador. J Hydrol. doi: 10.1016/j.jhydrol.2015.06.064 Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Ricardo Zubieta
    • 1
    • 2
  • Miguel Saavedra
    • 1
  • Yamina Silva
    • 1
  • Lucy Giráldez
    • 1
  1. 1.Subdirección de Ciencias de la Atmósfera e Hidrósfera (SCAH)Instituto Geofísico del Perú (IGP)LimaPeru
  2. 2.Programa de Doctorado en Recursos HídricosUniversidad Nacional Agraria La MolinaLimaPeru

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