Abstract
Peruvian Pacific drainage catchments only benefit from 2% of the total national available freshwater while they concentrate almost 50% of the population of the country. This situation is likely to lead a severe water scarcity and also constitutes an obstacle to economic development. Catchment runoff fluctuations in response to climate variability and/or human activities can be reflected in extreme events, representing a serious concern (like floods, erosion, droughts) in the study area. To document this crucial issue for Peru, we present here an insightful analysis of the water quantity resource variability of this region, exploring the links between this variability and climate and/or anthropogenic pressure. We first present a detailed analysis of the hydroclimatologic variability at annual timescale and at basin scale over the 1970–2008 period. In addition to corroborating the influence of extreme El Niño events over precipitation and runoff in northern catchments, a mean warming of 0.2 °C per decade over all catchments was found. Also, higher values of temperature and potential and actual evapotranspiration were found over northern latitudes. We chose to apply the Budyko-Zhang framework that characterizes the water cycle as a function of climate only, allowing the identification of catchments with significant climatic and anthropogenic influence on water balance. The Budyko-Zhang methodology revealed that 11 out of 26 initial catchments are characterized by low water balance disparity related to minor climatic and anthropogenic influence. These 11 catchments were suitable for identifying catchments with contrasting change in their hydroclimatic behavior using the Budyko trajectories. Our analysis further reveals that six hydrological catchment responses can be characterized by high sensitivity to climate variability and land use changes.
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References
ANA (2012) Recursos Hídricos en el Peru, 2nd edn. Ministerio de Agricultura. Autoridad Nacional del Agua, Lima, pp 45–189
Bourrel L, Rau P, Dewitte B, Labat D, Lavado W, Coutaud A, Vera A, Alvarado A, Ordoñez J (2015) Low-frequency modulation and trend of the relationship between ENSO and precipitation along the northern to centre Peruvian Pacific coast. Hydrol Process 29(6):1252–1266
Brouwer C, Heibloem M (1986) Irrigation water measurement: irrigation water needs, vol 3. United Nations Food and Agriculture Organization, Rome, p 102
Brown AE, Zhang L, McMahon TA, Western AW, Vertessy RA (2005) A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation. J Hydrol 310:28–61
Budyko MI (1958) The heat balance of the Earth’s surface. U.S. Department of Commerce, Washington, p 259
Budyko MI (1974) Climate and life. International geophysics series, vol 18. Academic, New York, p 508
Chen Z, Chen Y, Li B (2013) Quantifying the effects of climate variability and human activities on runoff for Kaidu River basin in arid region of northwest China. Theor Appl Climatol 111:537–545
Coron L, Andréassian V, Perrin C, Le Moine N (2015) Graphical tools based on Turc-Budyko plots to detect changes in catchment behaviour. Hydrol Sci J 60(7–8):1394–1407
DeFries R, Hansen M, Townshend JRG, Sohlberg R (1998) Global land cover classifications at 8 km spatial resolution: the use of training data derived from Landsat imagery in decision tree classifiers. Int J Remote Sens 19(16):3141–3168
Donohue RJ, Roderick ML, McVicar TR (2007) On the importance of including vegetation dynamics in Budyko’s hydrological model. Hydrol Earth Syst Sci 11:983–995
Donohue RJ, Roderick ML, McVicar TR (2011) Assessing the differences in sensitivities of runoff to changes in climatic conditions across a large basin. J Hydrol 406:234–244
Greve P, Gudmundsson L, Orlowsky B, Seneviratne S (2015) Introducing a probabilistic Budyko framework. Geophys Res Lett 42(7):2261–2269
Hansen M, DeFries R, Townshend JRG, Sohlberg R (2000) Global land cover classification at 1 km resolution using a decision tree classifier. Int J Remote Sens 21:1331–1365
Hassan H, Dregne HE (1997) Natural habitats and ecosystems management in drylands: an overview. Environment department paper N51. World Bank, Washington, pp 1–53
Hublart P, Ruelland D, Dezetter A, Jourde H (2015) Reducing structural uncertainty in conceptual hydrological modelling in the semi-arid Andes. Hydrol Earth Syst Sci 19:2295–2314
Hublart P, Ruelland D, García de Cortázar-Atauri I, Gascoin S, Lhermitte S, Ibacache A (2016) Reliability of lumped hydrological modeling in a semi-arid mountainous catchment facing water-use changes. Hydrol Earth Syst Sci 20:3691–3717
Jaramillo F, Destouni G (2014) Developing water change spectra and distinguishing change drivers worldwide. Geophys Res Lett 41:8377–8386
Jones J, Creed I, Hatcher K, Warren R, Adams M, Benson M et al (2012) Ecosystem processes and human influences regulate streamflow response to climate change at long-term ecological research sites. Bioscience 62(4):390–404
Kendall MG (1975) Rank correlation measures. Charles Griffin, London, p 202
Lavado WS, Ronchail J, Labat D, Espinoza JC, Guyot JL (2012) Basin-scale analysis of rainfall and runoff in Peru (1969–2004): Pacific, Titicaca and Amazonas drainages. Hydrol Sci J 57(4):625–642
Lavado WS, Labat D, Ronchail J, Espinoza JC, Guyot JL (2013) Trends in rainfall and temperature in the Peruvian Amazon-Andes basin over the last 40 years (1965–2007). Hydrol Process 27:2944–2957
Mann HB (1945) Non-parametric tests against trend. Econometrica 13:245–259
Mortimore M (2009) Dryland opportunities. International Union for Conservation of Nature and Natural Resources. IUCN. IIED. UNDP, Gland-Switzerland, p 86
Oudin L, Hervieu F, Michel C, Perrin C, Andreassian V, Anctil F, Loumagne C (2005) Which potential evapotranspiration input for a lumped rainfall-runoff model? Part 2—towards a simple and efficient potential evapotranspiration model for rainfall-runoff modeling. J Hydrol 303:290–306
Pettitt AN (1979) A non-parametric approach to the change-point problem. Appl Stat 28:126–135
Rau P, Bourrel L, Labat D, Melo P, Dewitte B, Frappart F, Lavado W, Felipe O (2016) Regionalization of rainfall over the Peruvian Pacific slope and coast. Int J Climatol. https://doi.org/10.1002/joc.4693
Renner M, Bernhofer C (2012) Applying simple water-energy balance frameworks to predict the climate sensitivity of streamflow over the continental United States. Hydrol Earth Syst Sci 16:2531–2546
Ruelland D, Dezetter A, Hublart P (2014) Sensitivity analysis of hydrological modelling to climate forcing in a semi-arid mountainous catchment. In: Hydrology in a changing world: environmental and human dimensions (Proc. 7th FRIEND-Water Int. Conf., Montpellier, France, 7–10 Oct. 2014). IAHS Publ 363:145–150
Searcy JK, Hardison CH (1960) Double-mass curves. US Geol Survey Water-Supply Paper 1541-B:31–66
Sivapalan M, Thompson SE, Harman CJ, Basu NB, Kumar P (2011) Water cycle dynamics in a changing environment: improving predictability through synthesis. Water Resour Res 47(10):W00J01
Valéry A, Andréassian V, Perrin C (2010) Regionalization of precipitation and air temperature over high-altitude catchments—learning from outliers. Hydrol Sci J 55(6):928–940
van der Velde Y, Vercauteren N, Jaramillo F, Dekker S, Destouni G, Lyon S (2013) Exploring hydroclimatic change disparity via the Budyko framework. Hydrol Process 28:4110–4118
Vuille M, Franquist E, Garreaud R, Lavado W, Caceres B (2015) Impact of the global warming hiatus on Andean temperature. J Geophys Res Atmos 120:3745–3757
Wagener T, Sivapalan M, Troch PA, McGlynn BL, Harman CJ, Gupta HV, Kumar P, Rao PSC, Basu NB, Wilson JS (2010) The future of hydrology: an evolving science for a changing world. Water Resour Res 46(5):W05301
Wang D, Hejazi M (2011) Quantifying the relative contribution of the climate and direct human impacts on mean annual streamflow in the contiguous United States. Water Resour Res 47(10):W00J12
Wang W, Shao Q, Yang T, Peng S, Xing W, Sun F, Luo Y (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. Hydrol Process 27:1158–1174
Yang D, Shao W, Yeh P, Yang H, Kanae S, Taikan O (2009) Impact of vegetation coverage on regional water balance in the nonhumid regions of China. Water Resour Res 45:W00A14
Zhang L, Dawes WR, Walker GR (2001) The response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour Res 37:701–708
Zhang S, Lu XX (2009) Hydrological responses to precipitation variation and diverse human activities in a mountainous tributary of the lower Xijiang, China. Catena 77:130–142
Zhao G, Mu X, Tian P, Wang F, Gao P (2013) Climate changes and their impacts on water resources in semiarid regions: a case study of the Wei River basin, China. Hydrol Process 27:3852–3863
Acknowledgements
The authors would like to thank SENAMHI (Meteorological and Hydrological Service of Peru) for providing complete hydrometeorological raw dataset. We thank the anonymous reviewer for his constructive comments that helped improve the original manuscript. B. Dewitte acknowledges supports from FONDECYT (projects 1171861 and 1151185).
Funding
This work was supported by Peruvian Ministry of Education (MINEDU-PRONABEC scholarship).
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Rau, P., Bourrel, L., Labat, D. et al. Hydroclimatic change disparity of Peruvian Pacific drainage catchments. Theor Appl Climatol 134, 139–153 (2018). https://doi.org/10.1007/s00704-017-2263-x
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DOI: https://doi.org/10.1007/s00704-017-2263-x