North Atlantic Oscillation as a Cause of the Hydrological Changes in the Mediterranean (Jucar River, Spain)

[EN] Significant changes in the Jucar River Basin District's hydrology in the Mediterranean side of Spain, have been observed during last decades. A statistical change-point in the year 1980 was detected in the basins' hydrological series in the main upper river, Jucar and Tuna basins. In the study scope are, the North Atlantic Oscillation (NAO) is linked with the winter precipitations in the Upper Basins, which are here responsible for the major part of streamflow. So changes in the rainfall has an important effect in the natural river flows. The statistical analysis detected a change at NAO's seasonal pattern, what means a considerable reduction of winter rainfalls in the Upper River basins located in the inland zone which is simultaneously the water collection and reservoirs area (a - 40% of water resources availability since 1980). Hydro-meteorological data and a Water Balance Model, Patrical, have been used to assess these water resources' reduction. Results points out to the change in the Basin's precipitation pattern in the inland areas (upper basins), associated to Atlantic weather patterns, as the main cause, while it has not been detected in the coastal areas. All these changes implies water stress for water resources planning, management and allocation, where more than 5.2 million people and irrigation of 390,000 ha are served, joint to the time variability, an important territorial imbalance exists between resources and demands. Thus, in the main upper basins, with the biggest streamflow's reductions, locate the largest reservoirs in terms of water resources collection and reserves.The authors would like to thank the Jucar RBD (Spanish Ministry of Environment) and the Confederacion Hidrografica del Jucar (Jucar River Basin Authority - RBA) for their cooperation in the compilation of this paper. The language revision of this paper was funded by the Universitat Politecnica de Valencia, Spain.Gómez Martínez, G.; Pérez-Martín, MÁ.; Estrela Monreal, T.; Amo-Merino, PD. (2018). North Atlantic Oscillation as a Cause of the Hydrological Changes in the Mediterranean (Jucar River, Spain). Water Resources Management. 32(8):2717-2734. doi:10.1007/s11269-018-1954-027172734328Alexandersson H (1986) A homogeneity test applied to precipitation data. J Climatol 6:661–675Bayazit M (2015) Nonstationarity of Hydrological Records and Recent Trends in Trend Analysis: A State-of-the-art Review. Environ Process 2:527–542. https://doi.org/10.1007/s40710-015-0081-7Bindoff NL, Stott PA, Allen MR, Gillett N, Gutzler D, Hansingo K, Hegerl G, Hu Y, Jain S, Overland J, Perlwitz J, Sebbari R, Zhang X (2013) Detection and attribution of climate change: From global to regional. In: Mokhov II, Stocker TF, Qin D, et al. (eds), Climate change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge; New York, pp. 867–952CEDEX (2009) Mapa de caudales máximos. Centro de Estudios y Experimentaciones CEDEX. Ministerio de Medio Ambiente y Medio Rural y Marino, MadridChiew FHS, McMahon TA (1993) Detection of trend or change in annual flow of Australian rivers. Int J Climatol 13:643–653. https://doi.org/10.1002/joc.3370130605CLC1990 Corine Land Cover (1990) Directorate-General for Environment. European Environment Agency (EEA)CLC2000 Corine Land Cover (2000) Directorate-General for Environment. European Environment Agency (EEA). Published 1 January 2002Chirivella V, Capilla JE, Pérez MA (2015) Modelling Regional Impacts of Climate Change on Water Resources: the Júcar Basin, Spain. Hydrol Sci J. https://doi.org/10.1080/02626667.2013.866711CHJ 2005 Provisional Art. 5 Report Pursuant to the Water Framework Directive. Júcar River Basin Authority (Confederación Hidrográfica del Júcar), Ministry of Environment, SpainCHJ (2015) Júcar RB Management Plan 2015_2021. Júcar RBA (Demarcación hidrográfica del Júcar). Confederación Hidrográfica del Júcar. Ministry of Environment, MadridDu T, Xiong L, Xu C-Y, Gippel CJ, Guo S, Liu P (2015) Return period and risk analysis of nonstationary low-flow series under climate change. J Hydrol 527:234–250. https://doi.org/10.1016/j.jhydrol.2015.04.041EEA (European Environment Agency), 2003. Indicator Factsheet WQ01c. Available online, URL: http://www.eea.europa.eu/data-and-maps/indicators/water-exploitation-indexEl Adlouni S, Ouarda TBMJ, Zhang X, Roy R, Bobee B (2007) Generalized maximum likelihood estimators for the nonstationary generalized extreme value model. Water Resour Res 43:W03410. https://doi.org/10.1029/2005WR004545Estrela T, Pérez-Martín MA, Vargas E (2012) Impacts of Climate Change on Water Resources in Spain. Hydrol Sci J 57(6):1154–1167 https://doi.org/10.1080/02626667.2012.702213Ferrer J, Pérez-Martín MA, Jiménez S, Estrela T, Andreu J (2012) GIS based models for water quantity and quality assessment in the Júcar River Basin, Spain, including climate change effects. Sci Total Environ 440:42–59. https://doi.org/10.1016/j.scitotenv.2012.08.032García-Ruiz JM, López-Moreno JI, Vicente-Serrano SM, Lasanta-Martínez T, Beguería S (2011) Mediterranean water resources in a global change scenario. Earth-Sci Rev 105(2011):121–139Hegerl G, Zwiers F (2011) Use of models in detection and attribution of climate change. Wiley Interdiscip Rev Clim Chang 2(4):570–591. https://doi.org/10.1002/wcc.121)HURRELL (2016) North Atlantic Oscillation (NAO) INDEX (STATION-BASED) https://climatedataguide.ucar.edu/climate-data/hurrell-north-atlantic-oscillation-nao-index-station-basedHurrell JW, Deser C (2009) North Atlantic climate variability: The role of the North Atlantic Oscillation. J Mar Syst 78(1):28–41Kendall MG (1975) Rank Correlation Measures. Charles Griffin, LondonLivingston EH (2004) Who Was Student and Why Do We Care So Much about His t-Test? J Surg Res 118:58–65. https://doi.org/10.1016/j.jss.2004.02.003López-Bustins JA, Martín-Vide J, Sánchez-Lorenzo A (2008) Iberia winter rainfall trends based upon changes in teleconnection and circulation patterns. Glob Planet Chang 63(2008):171–176Lorenzo-Lacruz J, Vicente-Serrano SM, López-Moreno JI, Morán-Tejeda E, Zabalza J (2012) Recent trends in Iberian streamflows (1945–2005). J Hydrol 414–415(2012):463–475Martín-Vide J, Lopez Bustins JA (2006) The Western Mediterranean Oscillation and Rainfall in the Iberian Peninsula. Int J Climatol 26(11):1455–1475Merz B, Vorogushyn S, Uhlemann S, Delgado J, Hundecha Y (2012) HESS Opinions More efforts and scientific rigour are needed to attribute trends in flood time series. Hydrol Earth Syst Sci 16(5):1379–1387. https://doi.org/10.5194/hess-16-1379-2012Miao W, Chiou P (2008) Confidence intervals for the difference between two means. Comput Stat Data Anal 52(2008):2238–2248. https://doi.org/10.1016/j.csda.2007.07.017Milly PC, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP (2008) Stationary is dead: Whither water management? J Sci 318:573–574Morán-Tejeda E, López-Moreno JI, Ceballos-Barbancho A, Vicente-Serrano SM (2011) River regimes and recent hydrological changes in the Duero basin (Spain). J Hydrol 404(2011):241–258Morán-Tejeda E, Ceballos-Barbancho A, Llorente-Pinto JM, López-Moreno JI (2012) Land-cover changes and recent hydrological evolution in the Duero Basin (Spain). Reg Environ Chang 12:17–33. https://doi.org/10.1007/s10113-011-0236-7Moraes JM, Pellegrino HQ, Ballester MV, Martinelli LA, Victoria R, Krusche AV (1998) Trends in hydrological parameters of southern Brazilian watershed and its relation to human induced changes. Water Resour Manag 12:295–311. https://doi.org/10.1023/A:1008048212420Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans Am Soc Agric Biol Eng 50(3):885–900. https://doi.org/10.13031/2013.23153Nash JE, Sutcliffe, JV (1970) River flow forecasting through conceptual models part I — A discussion of principles. 10(3):282-290. https://doi.org/10.1016/0022-1694(70)90255-6National Academies of Sciences, Engineering, and Medicine (2016) Attribution of Extreme Weather Events in the Context of Climate Change. National Academies Press, Washington, D.C. https://doi.org/10.17226/21852Pajares-Candela A. 2002. Modelación cuasidistribuida de los recursos hídricos y establecimiento de zonas hidroclimáticamente afines en el ámbito de la Confederación Hidrográfica del Júcar. Escuela de Caminos Canales y Puertos, Universidad Politécnica de ValenciaPérez-Martín MA, Estrela T, Andreu J, Ferrer J (2014) Modeling Water Resources and River-Aquifer Interaction in the Júcar River Basin, Spain. Water Resour Manag 28:4337–4358. https://doi.org/10.1007/s11269-014-0755-3Perreault L, Hache M, Slivitsky M, Bobee B (1999) Detection of changes in precipitation and runoff over eastern Canada and US using a Bayesian approach. Stoch Env Res Risk A 13:201–216. https://doi.org/10.1007/s004770050039Pettit AN (1979) A non-parametric approach to the change-point problem. Appl Stat 28:126–135Pinto JG, Raible CC (2012) Past and recent changes in the North Atlantic oscillation. WIREs Clim Change 2012(3):79–90. https://doi.org/10.1002/wcc.150Rasmussen P (2001) Bayesian estimation of change points using the general linear model. Water Resour Res 37:2723–2731. https://doi.org/10.1029/2001WR000311Reeves J, Chen J, Wang XL, Lund R, Lu Q (2007) A Review and Comparison of Changepoint Detection Techniques for Climate Data. J Appl Meteorol Climatol. https://doi.org/10.1175/JAM2493.1Satterthwaite FE (1946) An approximate distribution of estimates of variance components. Biom Bull 2:110–114Senatore A et al 2011 Regional climate change projections and hydrological impact analysis for a Mediterranean basin in Southern Italy. Alfonso Senatore, Giuseppe Mendicino, Gerhard Smiatekb, Harald Kunstmann. a Dipartimento di Difesa del Suolo, Università della Calabria, P.te P. Bucci 41b, 87036 Rende (CS), Italy. b Institute for Meteorology and Climate Research (IMK-IFU), Karlsruhe Institute of Technology, Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, Germany. J Hydrol 399 (1–2):70–92Huang S, Liu D Huang Q, Chen Y (2016) Contributions of climate variability and human activities to the variation of runoff in the Wei River Basin, China. ISSN: 0262–6667 (Print) 2150–3435 (Online) JournalStott PA, Stone DA, Allen MR (2004) Human contribution to the European heatwave of 2003. Nature 432:610–614Stott PA, Christidis N, Otto FEL, Sun Y, Vanderlinden J-P, van Oldenborgh GJ, Vautard R, von Storch H, Walton P, Yiou P, Zwiers FW (2016) Attribution of extreme weather and climate-related events. Wiley Interdiscip Rev Clim Chang 7(1):23–41. https://doi.org/10.1002/wcc.380Strupczewski WG, Kaczmarek Z (2001) Non-stationary approach to at-site flood frequency modeling II. Weighted least squares estimation. J Hydrol 248:143–151. https://doi.org/10.1016/S0022-1694(01)00398-5Strupczewski WG, Singh VP, Feluch W (2001a) Non-stationary approach to at-site flood frequency modeling I. Maximum likelihood estimation. J Hydrol 248:123–142. https://doi.org/10.1016/S0022-1694(01)00397-3Strupczewski WG, Singh VP, Mitosek HT (2001b) Nonstationary approach to at-site flood frequency modeling III. Flood analysis of Polish rivers. J Hydrol 248:152–167. https://doi.org/10.1016/S0022-1694(01)00399-7Sridhar V, Nayak A (2010) Implications of climate-driven variability and trends for the hydrologic assessment of the Reynolds Creek Experimental Watershed, Idaho. J Hydrol 385(2010):183–202Tao H, Gemmer M, Bai Y, Su B, Mao W (2011) Trends of streamflow in the Tarim River Basin during the past 50 years: Human impact or climate change? J Hydrol 400(2011):1–9Trenberth KE, Fasullo JT, Shepherd TG (2015) Attribution of climate extreme events. Nat Clim Chang 5(8):725–730. https://doi.org/10.1038/nclimate2657Valero Villarroya M 2007 Evaluación de los efectos del cambio en los usos del suelo mediante el uso de un modelo de simulación del ciclo hidrológico aplicado en la cuenca del Júcar. Ejercicio final de carrera. Escuela de Caminos Canales y Puertos, Universidad Politécnica de ValenciaVillarini G, Serinaldi F, Smith JA, Krajewski WF (2009) On the stationarity of annual flood peaks in the Continental United States during the 20th Century. Water Resour Res 45:W08417. https://doi.org/10.1029/2008WR007645Villarini G, Smith JA, Napolitano F (2010) Nonstationary modeling of a long record of rainfall and temperature over Rome. Adv Water Resour 33:1256–1267. https://doi.org/10.1016/j.advwatres.2010.03.013Welch BL (1938) The significance of the difference between two means when the population variances are unequal. Biometrika 29:350–362Wong H, Hu BQ, Ip WC, Xia J (2006) Change-point analysis of hydrological time series using grey relational method. J Hydrol 324:323–338. https://doi.org/10.1016/j.jhydrol.2005.10.007Xie H, Li D, Xiong L (2014) Exploring the ability of the Pettit method for detecting change point by Monte Carlo simulation. Stoch Env Res Risk A 28(7):1643–1655. https://doi.org/10.1007/s00477-013-0814-yXiong L, Jiang C, Xu C-Y, Yu K-x, Guo S (2015) A framework of change-point detection for multivariate hydrological series Water Resour Res 51. doi: https://doi.org/10.1002/2015WR017677Yue S, Pilon P, Cavadias G (2002) Power of the Mann–Kendall and Sperman’s rho tests for detecting monotonic trends in hydrological series. J Hydrol 259:254–271. https://doi.org/10.1016/S0022-1694(01)00594-7Zhang Q, Singh VP, Sun P, Chen X, Zhang Z, Li J (2011) Precipitation and streamflow changes in China: Changing patterns, causes and implications. J Hydrol 410(2011):204–21