Hostname: page-component-848d4c4894-wg55d Total loading time: 0 Render date: 2024-05-28T12:57:49.654Z Has data issue: false hasContentIssue false
  • English
  • Français

Regional assessment of green and blue water consumption for tomato cultivated in Southern Italy

Published online by Cambridge University Press:  14 December 2017

D. Ventrella Open the ORCID record for D. Ventrella [Opens in a new window] ,
L. Giglio ,
P. Garofalo  and
A. Dalla Marta
D. Ventrella*
Affiliation:
Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria – Centro di ricerca Agricoltura e Ambiente (CREA-AA), via Celso Ulpiani 5, 70125 Bari, Italy
L. Giglio
Affiliation:
Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria – Centro di ricerca Agricoltura e Ambiente (CREA-AA), via Celso Ulpiani 5, 70125 Bari, Italy
P. Garofalo
Affiliation:
Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria – Centro di ricerca Agricoltura e Ambiente (CREA-AA), via Celso Ulpiani 5, 70125 Bari, Italy
A. Dalla Marta
Affiliation:
Dipartimento di Scienze delle Produzioni Agroalimentari e dell'Ambiente (DISPAA), Università degli Studi di Firenze, piazzale delle Cascine, 18 – 50144 Firenze, Italy
*
Author for correspondence: D. Ventrella, E-mail: domenico.ventrella@crea.gov.it
Get access Rights & Permissions [Opens in a new window]

Abstract

In the current regional-scale study, the model DSSAT CROPGRO was applied in order to simulate the cultivation of industrial tomato and to estimate the green water (GW), blue water (BW), blue water requirement (BWR) and water footprint (WFP) through a dual-step approach (with and without full irrigation). Simulation covered a period of 30 years for three climate scenarios including a reference period and two future scenarios based on forecast global average temperature increases of 2 and 5 °C. The spatial patterns of indicators relating to the whole territory of Puglia region (Southern Italy), characterized by the high evaporative demand of the atmosphere, are discussed and analysed. Considering the climatic pattern, the analysis was developed for three areas (Northern, Central and Southern). Future scenarios affected all indicators significantly, particularly the Northern area, characterized by higher temperature and rainfall anomalies. Under the A5 scenario, compared with the baseline, this area was forecast to have a large increase of BW (+30%) and reduction in yield (−20%). As a consequence, the BWR and WFP were predicted to increase dramatically, up to 40 and >65%, respectively. On the other hand, Central and Southern areas, with lower anomalies of temperature and rainfall, were forecast to be less vulnerable to climate change. The distributed analysis performed could be important for water policy, allowing most efficient allocation of scarce water resources and concentrating them where the WFP is lowest, or in other words, water use efficiency is highest.

Keywords

Climate changeirrigationmodel simulationtomato water usewater footprint
Type
Crops and Soils Research Paper
Information
The Journal of Agricultural Science , Volume 156 , Themed Issue 5: Themed Issue: Assessment and monitoring of crop water use and productivity under present and future climate , July 2018 , pp. 689 - 701
Check for updates
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

ACLA2 (2001) Caratterizzazione Agroecologica della Regione Puglia in Funzione della Potenzialità Produttiva – Annesso 2: Carta Pedologica in Scala 1:100.000 (Agro-ecological Characterization of Puglia Region in Function of Productive Potential – Annex 2: Pedological Chart on a Scale of 1:100 000). Progetto ACLA2, P.O.P. Puglia 94–99. Bari, Puglia, Italy: Sottoprogramma FEOGA.Google Scholar
Ainsworth, EA and Long, SP (2005) What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytologist 165, 351–372.Google Scholar
Aldaya, MM and Hoekstra, AY (2010) The water needed for Italians to eat pasta and pizza. Agricultural Systems 103, 351–360.Google Scholar
Alexandrov, VA and Eitzinger, J (2005) The potential effect of climate change and elevated air carbon dioxide on agricultural crop production in central and Southeastern Europe. Journal of Crop Improvement 13, 291–331.Google Scholar
Attri, SD and Rathore, LS (2003) Simulation of impact of projected climate change on wheat in India. International Journal of Climatology 23, 693–705.Google Scholar
Bindi, M and Olesen, JE (2011) The responses of agriculture in Europe to climate change. Regional Environmental Change 11(Suppl. 1), 151–158.Google Scholar
Bindi, M, Fibbi, L, Gozzini, B, Orlandini, S and Miglietta, F (1996) Modelling the impact of future climate scenarios on yield and yield variability of grapevine. Climate Research 7, 213–224.Google Scholar
Chapagain, AK and Hoekstra, AY (2007) The water footprint of coffee and tea consumption in the Netherlands. Ecological Economics 64, 109–118.Google Scholar
Chapagain, AK and Hoekstra, AY (2011) The blue, green and grey water footprint of rice from production and consumption perspectives. Ecological Economics 70, 749–758.Google Scholar
Chapagain, AK and Orr, S (2009) An improved water footprint methodology linking global consumption to local water resources: a case of Spanish tomatoes. Journal of Environmental Management 90, 1219–1228.Google Scholar
Chapagain, AK, Hoekstra, AY, Savenije, HHG and Gautam, R (2006) The water footprint of cotton consumption: an assessment of the impact of worldwide consumption of cotton products on the water resources in the cotton producing countries. Ecological Economics 60, 186–203.Google Scholar
Dalla Marta, A, Mancini, M, Natali, F, Orlando, F and Orlandini, S (2012) From water to bioethanol: the impact of climate variability on the water footprint. Journal of Hydrology 444–445, 180–186.Google Scholar
Dettori, M, Cesaraccio, C, Motroni, A, Spano, D and Duce, P (2011) Using CERES-wheat to simulate durum wheat production and phenology in Southern Sardinia, Italy. Field Crops Research 120, 179–188.Google Scholar
Donatelli, M, Van Ittersum, MK, Bindi, M and Porter, RJ (2002) Modelling cropping systems – highlights of the symposium and preface to the special issues. European Journal of Agronomy 18, 1–11.Google Scholar
Ferrise, R, Moriondo, M and Bindi, M (2011) Probabilistic assessments of climate change impacts on durum wheat in the Mediterranean region. Natural Hazards and Earth System Sciences 11, 1293–1302.Google Scholar
Gerbens-Leenes, PW, Hoekstra, AY and Van Der Meer, TH (2009) The water footprint of bioenergy. Proceedings of the National Academy of Sciences USA 106, 10219–10223.Google Scholar
Giannakopoulos, C, Le Sager, P, Bindi, M, Moriondo, M, Kostopoulou, E and Goodess, CM (2009) Climatic changes and associated impacts in the Mediterranean resulting from a 2 °C global warming. Global and Planetary Change 68, 209–224.Google Scholar
Giorgi, F (2006) Climate change hot-spots. Geophysical Research Letters 33, L08707. doi: 10.1029/2006GL025734.Google Scholar
Guereña, A, Ruiz-Ramos, M, Díaz-Ambrona, CH, Conde, JR and Mínguez, MI (2001) Assessment of climate change and agriculture in Spain using climate models. Agronomy Journal 93, 237–249.Google Scholar
Hoekstra, AY, Chapagain, AK, Aldaya, MM and Mekonnen, MM (2011) The Water Footprint Assessment Manual: Setting the Global Standard. London, UK: Earthscan.Google Scholar
IPCC (2014) Summary for policymakers. In Field, CB, Barros, VR, Dokken, DJ, Mach, KJ, Mastrandrea, MD, Bilir, TE, Chatterjee, M, Ebi, KL, Estrada, YO, Genova, RC, Girma, B, Kissel, ES, Levy, AN, MacCracken, S, Mastrandrea, PR and White, LL (eds). Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press, pp. 1–32.Google Scholar
Jin, ZQ and Zhu, DW (2008) Impacts of changes in climate and its variability on food production in Northeast China. Acta Agronomica Sinica 34, 1588–1597.Google Scholar
Jones, JW, Hoogenboom, G, Porter, CH, Boote, KJ, Batchelor, WD, Hunt, LA, Wilkens, PW, Singh, U, Gijsman, AJ and Ritchie, JT (2003) The DSSAT cropping system model. European Journal of Agronomy 18, 235–265.Google Scholar
Kharin, VV, Zwiers, FW, Zhang, X and Wehner, M (2013) Changes in temperature and precipitation extremes in the CMIP5 ensemble. Climatic Change 119, 345–357.Google Scholar
Kimball, BA, Kobayashi, K and Bindi, M (2002) Responses of agricultural crops to free-air CO2 enrichment. Advances in Agronomy 77, 293–368.Google Scholar
Klein Goldenwijk, K and Ramankutty, N (2004) Land use changes during the past 300 years. In Verheye, W (ed.). Natural Resources Policy and Management. Encyclopedia of Life Support Systems (EOLSS). Oxford, UK: Eolss Pubblishers, pp. 147–168.Google Scholar
Mekonnen, MM and Hoekstra, AY (2011) The green, blue and grey water footprint of crops and derived crop products. Hydrology and Earth System Sciences 15, 1577–1600.Google Scholar
Moriondo, M, Bindi, M, Kundzewicz, ZW, Szwed, M, Chorynski, A, Matczak, P, Radziejewski, M, McEvoy, D and Wreford, A (2010) Impact and adaptation opportunities for European agriculture in response to climatic change and variability. Mitigation and Adaptation Strategies for Global Change 15, 657–679.Google Scholar
Moriondo, M, Bindi, M, Fagarazzi, C, Ferrise, R and Trombi, G (2011) Framework for high-resolution climate change impact assessment on grapevines at a regional scale. Regional Environmental Change 11, 553–567.Google Scholar
New, M (2005) Arctic climate change with a 2 °C global warming. In Rosentrater, L (ed.). 2° is Too Much! Evidence and Implications of Dangerous Climate Change in the Arctic. Oslo, Norway: WWF International Arctic Program, pp. 7–24.Google Scholar
Parry, ML, Canziani, OF, Palutikof, JP, van der Linden, PJ and Hanson, CE (2007) Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press.Google Scholar
Paxian, A, Hertig, E, Seubert, S, Vogt, G, Jacobeit, J and Paeth, H (2014) Present-day and future Mediterranean precipitation extremes assessed by different statistical approaches. Climate Dynamics 44, 845–860.Google Scholar
Priestley, CHB and Taylor, RJ (1972) On assessment of surface heat flux and evaporation using large-scale parameters. Monthly Weather Review 100, 81–92.Google Scholar
Rinaldi, M, Ventrella, D and Gagliano, C (2007) Comparison of nitrogen and irrigation strategies in tomato using CROPGRO model. A case study from Southern Italy. Agricultural Water Management 87, 91–105.Google Scholar
Saadi, S, Todorovic, M, Tanasijevic, L, Pereira, LS, Pizzigalli, C and Lionello, P (2015) Climate change and Mediterranean agriculture: impacts on winter wheat and tomato crop evapotranspiration, irrigation requirements and yield. Agricultural Water Management 147, 103–115.Google Scholar
SAS Institute Inc. (2013) Base SAS® 9.4 Procedures Guide: Statistical Procedures, 2nd edn. Cary, NC, USA: SAS Institute Inc.Google Scholar
Semenov, MA (2007) Development of high resolution UKCIP02-based climate change scenarios in the UK. Agricultural and Forest Meteorology 144, 127–138.Google Scholar
Semenov, MA and Barrow, EM (1997) Use of a stochastic weather generator in the development of climate change scenarios. Climatic Change 35, 397–414.Google Scholar
Siebert, S and Döll, P (2010) Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation. Journal of Hydrology 384, 198–217.Google Scholar
Sigria-Progetto Casi 3 (2002) S.I.G.R.I.A. Sistema Informativo per la Gestione delle risorse Idriche in Agricoltura (Informative System for Water Resources Management in Agriculture) Progetto CASI 3 – Studio sull'uso irriguo della risorsa idrica nelle regioni Obiettivo 1. Rome, Italy: Istituto Nazionale di Economia Agraria.Google Scholar
Soil Survey Staff (1998) Keys to Soil Taxonomy, 8th edn. Washington, DC, USA: USDA-NRCS.Google Scholar
Soltani, A and Hoogenboom, G (2007) Assessing crop management options with crop simulation models based on generated weather data. Field Crop Research 103, 198–207.Google Scholar
Toreti, A, Naveau, P, Zampieri, M, Schindler, A, Scoccimarro, E, Xoplaki, E, Dijkstra, HA, Gualdi, S and Luterbacher, J (2013) Projections of global changes in precipitation extremes from coupled model intercomparison project phase 5 models. Geophysical Research Letters 40, 4887–4892.Google Scholar
Troccoli, A, De Gregorio, V, Carrabs, G, Selvaggio, V, Olivieri, A, Demaio, G, Toriaco, A, De Sio, F, Rapacciuolo, M, Trifirò, A, Bonaventura, G and Pecchioni, N (2016) Prove su pomodoro da industria, situazione delle rese al Sud [trials on industrial tomato, situation of yields in the South]. L'informatore Agrario 11, 61–64.Google Scholar
Ventrella, D, Charfeddine, M, Moriondo, M, Rinaldi, M and Bindi, M (2012 a) Agronomic adaptation strategies under climate change for winter durum wheat and tomato in southern Italy: irrigation and nitrogen fertilization. Regional Environmental Change 12, 407–419.Google Scholar
Ventrella, D, Giglio, L, Charfeddine, M, Lopez, R, Castellini, M, Sollitto, D, Castrignanò, A and Fornaro, F (2012 b) Climate change impact on crop rotations of winter durum wheat and tomato in southern Italy: yield analysis and soil fertility. Italian Journal of Agronomy 7, e15. doi: 10.4081/ija.2012.e15.Google Scholar
Ventrella, D, Charfeddine, M, Giglio, L and Castellini, M (2012 c) Application of DSSAT models for an agronomic adaptation strategy under climate change in southern Italy: optimum sowing and transplanting time for winter durum wheat and tomato. Italian Journal of Agronomy 7, e16. doi: 10.4081/ija.2012.e16.Google Scholar
Ventrella, D, Giglio, L, Charfeddine, M and Dalla Marta, A (2015) Consumptive use of green and blue water for winter durum wheat cultivated in southern Italy. Italian Journal of Agrometeorology 20, 33–44.Google Scholar
Yang, X, Chen, C, Luo, Q, Li, L and Yu, Q (2011) Climate change effects on wheat yield and water use in oasis cropland. International Journal of Plant Production 5, 83–94.Google Scholar