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Time trend in reference evapotranspiration: analysis of a long series of agrometeorological measurements in Southern Italy

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Irrigation and Drainage Systems

Abstract

This study aims to evaluate the potential effects of the climatic variations on the reference evapotranspiration (ET0) and, consequently, on the crop water requirements in the Apulian Tavoliere, one of the largest irrigated districts of Southern Italy. To reach this purpose, both climatic parameters (air temperature and rainfall) and estimated water requirements of ‘processing’ tomato (among the most representative irrigated crops in the district since the mid-1970s and, therefore, chosen as a study-case) were analyzed in order to find out if a time trend exists or does not. The analysis covered the period from 1957 to 2008. The analysis showed that the rainfall amounts decreased (−3.4 mm per year in the analyzed period), while air temperature increased (0.18 °C and 0.25−°C per decade for minimum and maximum, respectively). As a consequence of the climatic variation during the considered period, a growth trend of the ET0 (1.4 mm per year) and water deficit (3.2 mm per year) took place. As a consequence, the water amounts for irrigating the same crop in the considered period were growing. This increased consumption is in agreement with the perception of the farmers of the district but never documented. Through the FAO AquaCrop model, the tomato irrigation water requirements have been simulated during the considered period. The trend analysis of the seasonal evapotranspiration values simulated in 52 years confirmed the increase in tomato water requirements (0.7 mm per year).

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References

  • Aguilar E, Auer I, Brunetti M, Peterson TC, Wieringa J (2003) Guidelines on Climate Metadata and Homogenization, WCDMP No 53, WMO-TD No 1186. World Meteorological Organization, Geneve

    Google Scholar 

  • Alexandersson H (1986) A homogeneity test applied to precipitation data. Int J Climatol 6:661–675

    Article  Google Scholar 

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: guidelines for computing crop water requirements. Irrigation and Drainage, Paper No. 56 FAO, Rome

  • Brunetti M, Buffoni L, Mangianti F, Maugeri M, Nanni T (2004) Temperature, precipitation and extreme events during the last century in Italy. Global and Planetary Change 40:141–149

    Article  Google Scholar 

  • Buishand TA (1982) Some methods for testing the homogeneity of rainfall records. J Hydrol 58:11–27

    Article  Google Scholar 

  • Caliandro A, Lamaddalena N, Stelluti M, Steduto P (2005) Caratterizzazione agro-ecologica della Regione Puglia in funzione della potenzialità produttiva. Progetto ACLA 2, Ideaprint, Bari

  • Caloiero T, Coscarelli R, Ferrari E, Mancini M (2011) Precipitation change in Southern Italy linked to global scale oscillation indexes, Nat. Hazards Earth Syst Sci 11:1683–1694

    Article  Google Scholar 

  • Dastane NG (1974) Effective rainfall in irrigated agriculture. Irrigation and Drainage, Paper No. 25 FAO, Rome

  • Doll P, Kaspar P, Lehner B (2003) A global hydrological model for deriving water availability indicators: model tuning and validation. J Hydrol 270:105–134

    Google Scholar 

  • Droogers P, Allen RG (2002) Estimating reference evapotranspiration under inaccurate data conditions. Irrigat Drain Syst 16:33–45

    Article  Google Scholar 

  • Farmer W, Strzepek K, Schlosser CA, Droogers P, Gao X (2011) A Method for Calculating Reference Evapotranspiration on Daily Time Scales. MIT Joint Program on the Science and Policy of Global Change, Report No 195

  • Hansen J, Sato M, Ruedy R, Lo K, Lea DW, Medina-Elizade M (2006) Global temperature change. The National Academy of Sciences of the USA, PNAS, 103 (39): 14288-14293, URL: http://www.pnas.org_cgi_doi_10.1073_pnas.0606291103

  • Hargreaves LG, Hargreaves GH, Riley JP (1985) Irrigation water requirements for Senegal river basin. J Irrig Drain Eng 111(3):265–275. doi:10.1061/(ASCE)0733-9437(1985)111:3(265

    Article  Google Scholar 

  • Helsel DR, Hirsch RM (2002) Statistical methods in water resources. Techniques of Water Resources Investigations, Book 4, chapter A3. U.S. Geological Survey. 522 pages. URL: http://pubs. usgs.gov/twri/twri4a3/

  • Hillel D (2004) Introduction to environmental soil physics. Academic Press Inc 494 pp

  • Hipel KW, McLeod AI (2005) Time series modelling of water resources and environmental systems. Electronic book reprint. URL: http://www.stats.uwo.ca/faculty/aim/1994Book/

  • Jamieson PD, Porter JR, Wilson DR (1991) A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field Crop Res 27:337–350

    Article  Google Scholar 

  • Jones PD, Parker DE, Osborn TJ, Briffa KR (2009) Global and hemispheric temperature anomalies - land and marine instrumental records. In Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tenn, USA

  • Jensen ME, Haise HR (1963) Estimating evapotranspiration from solar radiation. J Irrig Drain Div 93(IR3):15–41

    Google Scholar 

  • Katerji N, Fereira I, Mastrorilli M, Losavio N (1990) A simple equation to calculate crop evapotranspiration: results of several years of experimentation. International symposium ISHS “Sheduling of irrigation for vegetable crops under field condition”. Maratea (Pz) 5–9 June 1989. Acta Hort (1990) 278: 477–489

  • Kendall MG (1975) Rank Correlation methods, 4th edn. Charles Griffin, London

    Google Scholar 

  • Klein Tank AMG, Können GP (2003) Trends in indices of daily temperature and precipitation extremes in Europe. J Climate 16:3665–3680

    Article  Google Scholar 

  • Lhomme JP, Katerji N (1991) A simple modelling of crop water balance for agrometeorological application. Ecol Model 57:11–25

    Article  Google Scholar 

  • Loague KM, Green RE (1991) Statistical and graphical methods for evaluating solute transport models: overview and application. J Contam Hydrol 7:51–73

    Article  CAS  Google Scholar 

  • Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259

    Article  Google Scholar 

  • Martinez MD, Serra C, Burgueno A, Lana X (2009) Time trends of daily maximum and minimum temperatures in Catalonia (NE Spain) for the period 1975–2004. Int J Climatol. doi:10.1002/joc.1884

  • Mastrorilli M (1999) Sviluppo di modelli idrologici per ambienti mediterranei. Bollettino SISS 48:245–250

    Google Scholar 

  • OECD (2001) Environmental Indicators for Agriculture. Volume 3. Methods and results. OECD, Paris ed 409 pp

  • Olesen JE, Bindi M (2002) Consequences of climate change for European agricultural productivity, land use and policy. Eur J Agron 16(4):239–262

    Article  Google Scholar 

  • Peterson TC, Easterling DR, Karl TR, Groisman P, Nicholls M, Plummer N, Torok S, Auer I, Boehm R, Gullet D, Vincent L, Heino R, Tuomenvirta H, Mestre O, Szentimrey T, Salinger J, Førland E, Hanssen-Bauer I, Alexandersson H, Jones P, Parker D (1998) Homogeneity adjustments of in situ atmospheric climate data: a review. Int J Climatol 18:1493–1517

    Article  Google Scholar 

  • Pettitt AN (1979) A non-parametric approach to the changepoint problem. Appl Stat 28:126–135

    Article  Google Scholar 

  • Piervitali E, Colacino M, Conte M (1997) Signals of climatic change in the central western Mediterranean basin. Theor Appl Climatol 58:211–219

    Article  Google Scholar 

  • Priestley CHB, Taylor RJ (1972) On the assessment of surface heat flux and evaporation using large scale parameters. Mon Weather Rev 100:81–92

    Article  Google Scholar 

  • R Development Core Team (2012) R: A language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org/

  • Rana G, Rinaldi M, Introna M (2004) Metodologie ed algoritmi per il controllo di qualità di dati orari e giornalieri da una rete Agrometeorologica: applicazioni alla rete lucana SAL. Rivista Italiana di Agrometeorologia 1:14–23

    Google Scholar 

  • Raes D, Steduto P, Hsiao TC, Fereres E (2009) AquaCrop—The FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agron J 101:438–447

    Article  Google Scholar 

  • Reilly J, Tubiello F, McCarl B, Abler D, Darwin R, Fuglie K, Hollinger S, Zaurralde C, Jagtap S, Jones J, Mearns I, Ojima D, Paul E, Paustian K, Riha S, Rosenberg N, Rosenzweig C (2003) U.S. Agriculture and Climate Change: New Results. Clim Chang 57:43–69

    Article  Google Scholar 

  • Reeves J, Chen J, Wang XL, Lund R, Lu QQ (2007) A review and comparison of changepoint detection techniques for climate data. J Appl Meteor Climatol 46:900–915

    Article  Google Scholar 

  • Rosenzweig C, Parry ML (1994) Potential impacts of climate changes on world food supply. Nature 367:133–138

    Article  Google Scholar 

  • Rosenzweig C, Tubiello FN (1997) Impacts of global climate change on mediterranean agriculture: current methodologies and future directions. An Introductory Essay Mitig Adapt Strategies Global Change 1(3):219–232

    Article  Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Amer Stat Assoc 63:1379–1389

    Article  Google Scholar 

  • Sivakumar MVK (2006) Requirements for Agrometeorological Services: International Perspectives. In: Motha RP, Sivakumar MVK, Bernardi M (Eds) Strengthening Operational Agrometeorological Services at the National Level. Proceedings of the Inter-Regional Workshop, March 22–26, 2004, Manila, Philippines. 101–113

  • Steduto P, Caliandro A, Rubino P, Ben Mechlia N, Masmoudi M, Martinez-Co A, Jose Faci M, Rana G, Mastrorilli M, El Mourid M, Karrou M, Kanber R, Kirda C, El Quosi D, EL Askari K, Ait Ali M, Zareb D, Snyder RL (1996) Penman-Monteith reference evapotranspiration estimates in the Mediterranean region. In: Evapotranspiration and irrigation scheduling. Editors: Camp CR, Sadler EJ, Yoder RE, ASAE, 357–364

  • Steduto P, Hsiao TC, Raes D, Fereres E (2009) AquaCrop -The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agron J 101:426–437

    Article  Google Scholar 

  • Todisco F, Vergni L (2008) Climatic changes in Central Italy and their potential effects on corn water consumption. Agric Forest Meteorol 148(1):1–11

    Article  Google Scholar 

  • Vitale D, Rana G, Soldo P (2010) Trends and extremes analysis of daily weather data in the capitanata plain. Ital J Agron 5(2):133–143

    Google Scholar 

  • von Neumann J (1941) Distribution of the ratio of the mean square successive difference to the variance. Ann Math Statist 12(4):367–395

    Article  Google Scholar 

  • Weiß M, Menzel L (2008) A global comparison of four potential evapotranspiration equations and their relevance to stream flow modelling in semi-arid environments. Adv Geosci 18:15–23

    Article  Google Scholar 

  • Wijngaard JB, Klein Tank MG, Können GP (2003) Homogeneity of 20th century European daily temperature and precipitation series. Int J Climatol 23:679–692

    Article  Google Scholar 

Download references

Acknowledgments

This research was funded by CLIMESCO (‘Evolution of cropping systems as affected by climate change’) project, contract n. 285, 20/02/2006 (Ministry for Education, University and Research, Italy).

The Authors thank Dr. G. Rana (CRA-SCA) for the discussion about the available methods to estimate evapotranspiration.

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Authors and Affiliations

  1. Research Unit for Cropping Systems in Dry Environments, Agricultural Research Council, via Celso Ulpiani, 5-70125, Bari, Italy

    A. Domenico Palumbo, Domenico Vitale, Pasquale Campi & Marcello Mastrorilli

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  1. A. Domenico Palumbo
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  2. Domenico Vitale
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  3. Pasquale Campi
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  4. Marcello Mastrorilli
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Correspondence to A. Domenico Palumbo.

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Palumbo, A.D., Vitale, D., Campi, P. et al. Time trend in reference evapotranspiration: analysis of a long series of agrometeorological measurements in Southern Italy. Irrig Drainage Syst 25, 395–411 (2011). https://doi.org/10.1007/s10795-012-9132-7

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