Hostname: page-component-8448b6f56d-xtgtn Total loading time: 0 Render date: 2024-04-23T09:32:02.865Z Has data issue: false hasContentIssue false
  • English
  • Français

Reliability of current Spanish irrigation designs in a changed climate: a case study

Published online by Cambridge University Press:  10 December 2010

A. UTSET  and
B. DEL RÍO
A. UTSET*
Affiliation:
Clean Earth Consultancy, Research and Development Department, Spain
B. DEL RÍO
Affiliation:
Instituto Tecnológico Agrario de Castilla y Leon (ITACyL), Spain
*
*To whom all correspondence should be addressed. Email: autset@clnearth.com
Get access Rights & Permissions [Opens in a new window]

Summary

A very serious effort to modernize irrigation systems is being made in Spain, to reduce water and energy losses in an environmentally sustainable way. This is expensive and it is important that the new irrigation systems work properly over a long period. The systems have been designed taking into account historical evapotranspiration (ET) averages during the months of maximum demand, as well as the crop-specific ET values (Kc coefficients) of typical crops. However, the increase in ET rates due to global warming could mean that the capacity of these new and expensive irrigation systems to fulfil the crop water requirements may be exceeded in the near future. However, the expected increase in CO2 concentration could diminish crop transpiration rates for similar water demands from the atmosphere, thereby reducing irrigation requirements. A methodology was developed in order to estimate crop water requirements under climate change conditions. The reliability of a new irrigation system designed in Valladolid, Northern Spain was tested. The regionalized climate change scenarios for Valladolid, provided by the National Institute of Meteorology, were used for the periods 2011–40, 2041–70 and 2071–2100 and the A2 and B2 emission scenarios were considered using the ECHAM and coupled general circulation model (CGCM) global circulation models. A historical series of daily meteorological data for Valladolid was used to generate statistical ET distributions through the LARS-WG generator. Simulations considered each of the above periods, global circulation models (GCM) and emission scenarios. Furthermore, the Kc of the typical irrigated crops of the zone (maize, potato and sugar beet) were reduced for each period, GCM and emission scenario according to the relationships between CO2 concentrations and transpiration obtained by Kruijt et al. (2008). The results indicated that, on average, historical ET rates provide a sufficiently robust indicator to enable estimations of the crop ET in the future, particularly considering the CO2 effect in reducing crop transpiration. However, ET variability is significantly increased after 2040, especially for the A2 emission scenario. The results show that ET variability rather than global increase is the most serious risk that current irrigation systems must face in the near future in Northern Spain, as consequence of climate change. Such variability should be included in irrigation designs.

Type
Climate Change and Agriculture
Information
The Journal of Agricultural Science , Volume 149 , Issue 2 , April 2011 , pp. 171 - 183
Copyright
Copyright © Cambridge University Press 2010

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

REFERENCES

Ainsworth, E. A., Davey, P. A., Bernacchi, C. J., Dermody, O. C., Heaton, E. A., Moore, D. J., Morgan, P. B., Naidu, S. L., Ra, H. S. Y., Zhu, X. G., Curtis, P. S. & Long, S. P. (2002). A meta analysis of elevated CO2 effects on soybean (Glycine max) physiology, growth and yield. Global Change Biology 8, 695–709.CrossRefGoogle Scholar
Alcamo, J., Moreno, J. M., Nováky, B., Bindi, M., Corobov, R., Devoy, R. J. N., Giannakopoulos, C., Martin, E., Olesen, J. E. & Shvidenko, A. (2007). Europe. In Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Eds Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J. & Hanson, C. E.), pp. 541–580. Cambridge, UK: Cambridge University Press.Google Scholar
Alexandrov, V. (2002). Summarizing crop growth simulation models in Europe with potential for operational assessment of crop status and yield prognosis. In Report of the RA VI Working Group on Agricultural Meteorology (Eds Dunkel, Z., Alexandrov, V., Gat, Z., Guerreiro, R., Kleschenko, A. & Ozalp, Y.), pp. 119–214. CAgM Report No. 89, WMO/TD No. 1113. Geneva, Switzerland: Commission for Agricultural Meteorology.Google Scholar
Allen, V. G., Baker, M. T., Segarra, E. & Brown, C. P. (2007). Integrated irrigated crop–livestock systems in dry climates. Agronomy Journal 99, 346–360.CrossRefGoogle Scholar
Belmans, C., Wesseling, J. & Feddes, R. A. (1983). Simulation function of the water balance of a cropped soil: SWATRE. Journal of Hydrology 63, 271–286.CrossRefGoogle Scholar
Bernacchi, C. J., Kimball, B. A., Quarles, D. R., Long, S. P. & Ort, D. R. (2007). Decreases in stomatal conductance of soybean under open-air elevation of CO2 are closely coupled with decreases in ecosystem evapotranspiration. Plant Physiology 143, 134–144.CrossRefGoogle ScholarPubMed
Bethenod, O., Ruget, F., Katerji, N., Combe, L. & Renard, D. (2001). Impact of atmospheric CO2 concentration on water use efficiency of maize. Maydica 46, 75–80.Google Scholar
Brunet, M., Casado, M. J., De Castro, M., Galán, P., Lopez, J. A., Martín, J. M., Pastor, A., Petisco, E., Ramos, P., Ribalaygua, P., Rodríguez, E., Sanz, I. & Torres, L. (2007). Generación de Escenarios Regionalizados de Cambio Climático para España. Madrid: Instituto Nacional de Meteorología, Ministerio de Medio Ambiente.Google Scholar
Bunce, J. A. (2004). Carbon dioxide effects on stomatal responses to the environment and water use by crops under field conditions. Oecologia 140, 1–10.CrossRefGoogle Scholar
Chaudhuri, U. N., Kirkham, M. B. & Kanemasu, E. T. (1990). Carbon-dioxide and water level effects on yield and water-use of winter-wheat. Agronomy Journal 82, 637–641.CrossRefGoogle Scholar
Curtis, P. S. (1996). A meta-analysis of leaf gas exchange and nitrogen in trees grown under elevated carbon dioxide. Plant Cell & Environment 19, 127–137.CrossRefGoogle Scholar
De Silva, C. S., Weatherhead, E. K., Knox, J. W. & Rodriguez-Diaz, J. A. (2007). Predicting the impacts of climate change: a case study of paddy irrigation water requirements in Sri Lanka. Agricultural Water Management 93, 19–29.CrossRefGoogle Scholar
Elgaali, E., Garcia, L. A. & Ojima, D. S. (2006). Sensitivity of irrigation water balance to climate change in the Great Plains of Colorado. Translation of ASABE 49, 1315–1322.CrossRefGoogle Scholar
European Environment Agency (EEA). (2007). Climate Change and Water Adaptation Issues. EEA Technical Report No. 2/2007. Copenhagen: EEA.Google Scholar
Faci, J. M., Martínez-Cob, A. & Cabezas, A. (1994). Agroclimatología de los Regadíos del Bajo Gállego. Doce Años de Observaciones Diarias en Montañana (Zaragoza). Zaragoza, Spain: DGA Consejería de Agricultura, Ganadería y Montes.Google Scholar
Feddes, R. A., Kowalik, P. J. & Zaradny, H. (1978). Simulation of Field Water Use and Crop Yield. Simulation Monographs. Wageningen, The Netherlands: PUDOC.Google Scholar
Ferrer, F. J. (1993). Recomendaciones para el Cálculo Hidrometeorológico de Avenidas. Madrid: CEDEX, Centro de Estudios Hidrográficos.Google Scholar
Gonzalez-Camacho, J. M., Mailhol, J. C. & Ruget, F. (2008). Local impact of increasing CO2 on maize crop water productivity in the Drome Valley, France. Irrigation and Drainage 57, 229–243.Google Scholar
Guereña, A., Ruiz-Ramos, M., Díaz-Ambrona, C. H., Conde, J. R. & Mínguez, M. I. (2001). Assessment of climate change and agriculture in Spain using climate models. Agronomy Journal 93, 237–249.CrossRefGoogle Scholar
Hansen, J. W., Challinor, A., Ines, A., Wheeler, T. & Moron, V. (2006). Translating climate forecasts into agricultural terms: advances and challenges. Climate Research 33, 27–41.CrossRefGoogle Scholar
Hoogenboom, G., Jones, J. W., Wilkens, P. W., Batchelor, W. D., Bowen, W. T., Hunt, L. A., Pickering, N. B., Singh, U., Godwin, D. C., Baer, B., Boote, K. J., Ritchie, J. T. & White, J. W. (1994). Crop models. In DSSAT Version 3, vol. 2. (Eds Tsuji, G. Y., Uehara, G. & Balas, S.), pp. 95–244. Honolulu, HI: University of Hawaii.Google Scholar
Iglesias, A., Estrela, T. & Gallart, F. (2005). Impactos sobre los recursos hídricos. In Evaluación Preliminar de los Impactos en España for Efecto del Cambio Climático (Ed. Moreno, J. M.), pp. 303–353. Madrid, Spain: Ministerio de Medio Ambiente.Google Scholar
Iglesias, A. & Quiroga, S. (2007). Cambio Climático y Medidas de Adaptación para la Agricultura: Implicaciones para Castilla y Leon. Valladolid, Spain: Innovación y Tecnología Agroalimentaria.Google Scholar
Iglesias, A., Rosenzweig, C. & Pereira, D. (2000). Agricultural impacts of climate change in Spain: developing tools for a spatial analysis. Global Environmental Change 10, 69–80.CrossRefGoogle Scholar
Instituto Tecnologico Agrario de Castilla y Leon (ITACyL). (2007). Modernización de Regadíos en la Comunidad de Regantes de Geria-Simancas-Villamarciel. Valladolid, Spain: Innovación y Tecnología Agroalimentaria.Google Scholar
IPCC (2007). Summary for policymakers. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on climate change (Eds Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J. & Hanson, C. E.), pp. 7–22. Cambridge, UK: Cambridge University Press.Google Scholar
Jacobs, C. M. J. & De Bruin, H. A. R. (1992). The sensitivity of regional transpiration to land-surface characteristics – significance of feedback. Journal of Climate 5, 683–698.2.0.CO;2>CrossRefGoogle Scholar
Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J. & Ritchie, J. T. (2003). The DSSAT cropping system model. European Journal of Agronomy 18, 235–265.CrossRefGoogle Scholar
Kang, S., Zhang, F., Hu, X. & Zhang, J. (2002). Benefits of CO2 enrichment on crop plants are modified by soil water status. Plant and Soil 238, 69–77.CrossRefGoogle Scholar
Katerji, N., Mastrorilli, B. & Rana, G. (2008). Water use efficiency of crops cultivated in the Mediterranean region: review and analysis. European Journal of Agronomy 28, 493–507.CrossRefGoogle Scholar
Katz, R. W. & Brown, B. G. (1992). Extreme events in a changing climate: variability is more important than averages. Climate Change 21, 289–302.CrossRefGoogle Scholar
Kim, S. H., Sicher, R. C., Bae, H., Gitz, D. C., Baker, J. T., Timlin, D. J. & Reddy, V. R. (2006). Canopy photosynthesis, evapotranspiration, leaf nitrogen, and transcription profiles of maize in response to CO2 enrichment. Global Change Biology 12, 588–600.CrossRefGoogle Scholar
Kimball, B. A., Kobayashi, K. & Bindi, M. (2002). Responses of agricultural crops to free air CO2 enrichment. Advanced Agronomy 7, 293–368.CrossRefGoogle Scholar
Kimball, B. A., Pinter, P. J., Garcia, R. L., Lamorte, R. L., Wall, G. W., Hunsaker, D. J., Wechsung, G., Wechsung, F. & Kartschall, T. (1995). Productivity and water use of wheat under free-air CO2 enrichment. Global Change Biology 1, 429–442.CrossRefGoogle Scholar
Kroes, J. G. & Van Dam, J. C. (2003). Reference Manual SWAP version 3.0.3. Alterra-rapport 773. Wageningen, The Netherlands: Alterra.Google Scholar
Kruijt, B., Witte, J.-P. M., Jacobs, C. M. J. & Kroon, T. (2008). Effects of rising atmospheric CO2 on evapotranspiration and soil moisture: a practical approach for the Netherlands. Journal of Hydrology 349, 257–267.CrossRefGoogle Scholar
Kundzewicz, Z. W., Parry, M. L., Cramer, W., Holten, J. I., Kaczmarek, Z., Martens, P., Nicholls, R. J., Oquist, M., Rounsevell, M. D. A. & Szolgay, J. (2001). Europe. In Climate Change 2001: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on climate change (Eds McCarthy, J. J., Canziani, O. F.Leary, N. A., Dokken, D. J. & White, K. S.), pp. 641–692. Cambridge, UK: Cambridge University Press.Google Scholar
Long, S. P. (1991). Modification of the response of photosynthetic productivity to rising temperature by atmospheric CO2 concentrations: has its importance been underestimated? Plant Cell and Environment 14, 729–739.CrossRefGoogle Scholar
Long, S. P., Ainsworth, E. A., Leakey, A. D. B., Nosberger, J. & Ort, D. R. (2006). Food for thought: Lower-than-expected crop yield stimulation with rising CO2 concentrations. Science 312, 1918–1921.CrossRefGoogle ScholarPubMed
Magliulo, V., Bindi, M. & Rana, G. (2003). Water use of irrigated potato (Solanum tuberosum L.) grown under free air carbon dioxide enrichment in central Italy. Agriculture, Ecosystems and Environment 97, 65–80.CrossRefGoogle Scholar
Mearns, L. O., Rosenzweig, C. & Goldberg, R. (1997). Mean and variance change in climate scenarios: methods, agricultural applications, and measures of uncertainty. Climatic Change 35, 367–396.CrossRefGoogle Scholar
Meza, F. J., Silva, D. & Vigil, H. (2008). Climate change impacts on irrigated maize in Mediterranean climates: evaluation of double cropping as an emerging adaptation alternative. Agricultural Systems 98, 21–30.CrossRefGoogle Scholar
Mínguez, M. I., Ruiz-Ramos, M., Díaz-Ambrona, C. H., Quemada, M. & Sau, F. (2007). First-order impacts on winter and summer crops assessed with various high-resolution climate models in the Iberian Peninsula. Climatic Change 81 (Suppl. 1), 343–355.CrossRefGoogle Scholar
Ministerio de Agricultura y Pesca (MAPA). (2005). Plan Nacional de Regadíos (in Spanish). Madrid, Spain: MAPA. Available at: http://www.mapa.es/es/desarrollo/pags/pnr/principal.htm (verified 2 November 2010).Google Scholar
Mitchell, R. A. C., Mitchell, V. J. & Lawlor, D. W. (2001). Response of wheat canopy CO2 and water gas-exchange to soil water content under ambient and elevated CO2. Global Change Biology 7, 599–611.CrossRefGoogle Scholar
Moreno, J. M. (2005). A Preliminary General Assessment of the Impacts in Spain Due to the Effects of Climate Change. ECCE Project – Final Report. Madrid, Spain: Spanish Ministry of Environment.Google Scholar
Neira, X. X., Alvarez, C. J., Cuesta, T. S. & Cancela, J. J. (2005). Evaluation of water-use in traditional irrigation: an application to the Lemos Valley irrigation district, northwest of Spain. Agricultural Water Management 75, 137–151.CrossRefGoogle Scholar
Nonhebel, S. (1994). The effects of use of average instead of daily weather data in crop growth simulation models. Agricultural Systems 44, 377–396.CrossRefGoogle Scholar
Oficina Española de Cambio Climático (OECC). (2006). Plan Nacional de Adaptación al Cambio Climático (PNACC). Madrid, Spain: Ministerio de Medio Ambiente.Google Scholar
Olesen, J. E., Carter, T. R., Díaz-Ambrona, C. H., Fronzek, S., Heidmann, T., Hickler, T., Holt, T., Minguez, M. I., Morales, P., Palutikof, J. P., Quemada, M., Ruiz-Ramos, M., Rubæk, G. H., Sau, F., Smith, B. & Sykes, M. T. (2007). Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models. Climatic Change 81, 123–143.CrossRefGoogle Scholar
Papadakis, J. (1966). Climates of the World and Their Agricultural Potentialities. Cordoba, Buenos Aires: J. Papadakis.Google Scholar
Peart, R. M., Jones, J. W., Curry, R. B., Boote, K. J. & Allen, L. H. (1989). Impact of climate change on crop yield in the southeastern USA: a simulation study. In The Potential Effects of Global Climate Change on the United States: Report to Congress (Eds Smith, J. B. & Tirpak, D. A.), pp. 89–118. Washington, DC: US Environmental Protection Agency (EPA).Google Scholar
Playan, E. & Mateos, L. (2005). Modernization and optimization of irrigation systems to increase water productivity. Agricultural Water Management 80, 100–116.CrossRefGoogle Scholar
Priestley, C. H. B. & Taylor, R. J. (1972). On the assessment of the surface heat flux and evapotranspiration using large-scale parameters. Monthly Weather Review 100, 81–92.2.3.CO;2>CrossRefGoogle Scholar
Reilly, J. M., Tubiello, F., McCarl, B. A. & Melillo, J. (2001). Climate change and agriculture in the United States. In Climate Change Impacts on the United States: Foundation Report (Ed. National Assessment Synthesis Team), pp. 379–403. Cambridge, UK: Cambridge University Press.Google Scholar
Ritchie, J. T. (1972). Model for predicting evaporation from a row crop with an incomplete cover. Water Resources Research 8, 1204–1212.CrossRefGoogle Scholar
Rodríguez Díaz, J. A., Weatherhead, E. K., Knox, J. W. & Camacho, E. (2007). Climate change impacts on irrigation water requirements in the Guadalquivir river basin in Spain. Regional Environmental Change 7, 149–159.CrossRefGoogle Scholar
Rosenzweig, C. & Iglesias, A. (1998). The use of crop models for international climate change impact assessment. In Understanding Options for Agricultural Production (Eds Tsuji, G. Y., Hoogenboom, G. & Thornton, P. K.), pp. 267–292. Dordrecht, The Netherlands: Kluwer Academic Publishers.CrossRefGoogle Scholar
Rosenzweig, C. & Tubiello, F. N. (2007). Adaptation and mitigation strategies in agriculture: an analysis of potential synergies. Mitigation and Adaptation Strategies on Global Change 12, 855–873.CrossRefGoogle Scholar
Semenov, M. A. (2008). Simulation of weather extreme events by a stochastic weather generator. Climate Research 35, 203–212.CrossRefGoogle Scholar
Semenov, M. A. & Barrow, E. M. (2002). LARS-WG. A Stochastic Weather Generator for Use in Climate Impact Studies. User Manual. Hertfordshire, UK: Rothamstead Research.Google Scholar
Semenov, M. A. & Jamieson, P. D. (2001). Using weather generators in crop modelling. In Climate Prediction and Agriculture, Proceedings of the START/WMO International Workshop held in Geneva, Switzerland, 27–29 September 1999, Washington D.C. (Ed. Sivakumar, M. V. K.), pp. 119–142. Washington, DC: International START Secretariat.Google Scholar
Semenov, M. A., Wolf, J., Evans, L. G., Eckersten, H. & Iglesias, A. (1996). Comparison of wheat simulation models under climate change. II. Application of climate change scenarios. Climate Research 7, 271–281.CrossRefGoogle Scholar
Stockle, C. O., Donatelli, M. & Nelson, R. (2003). CropSyst, a cropping systems simulation model. European Journal of Agronomy 18, 289–307.CrossRefGoogle Scholar
Timbal, B., Fernandez, E. & Li, Z. (2009). Generalization of a statistical downscaling model to provide local climate change projections for Australia. Environmental Modelling and Software 24, 341–358.CrossRefGoogle Scholar
Timbal, B. & Jones, D. A. (2006). Future projections of winter rainfall in southeast Australia using a statistical downscaling technique. Climatic Change 86, 165–187.CrossRefGoogle Scholar
Triggs, J. M., Kimball, B. A., Pinter, P. J., Wall, G. W., Conley, M. M., Brooks, T. J., Lamorte, R. L., Adam, N. R., Ottman, M. J., Mathiass, A. D., Leavitt, S. W. & Cerveny, R. S. (2004). Free-air CO2 enrichment effects on the energy balance and evapotranspiration of sorghum. Agricultural and Forest Meteorology 124, 63–79.CrossRefGoogle Scholar
Tubiello, F. N., Amthor, J. S., Boote, K. J., Donatelli, M., Easterling, W., Fischer, G., Gifford, R. M., Howden, M., Reilly, J. & Rosenzweig, C. (2007). Crop response to elevated CO2 and world food supply A comment on: “Food for Thought…” by Long et al. Science 312, 1918–1921, 2006. European Journal of Agronomy 26, 215–223.Google Scholar
Tubiello, F. N. & Ewert, F. (2002). Simulating the effects of elevated CO2 on crops: approaches and applications for climate change. European Journal of Agronomy 18, 57–74.CrossRefGoogle Scholar
Utset, A. (2009). Opportunities and challenges of using modelling tools for agricultural decision-making under climate change conditions. In Climate Variability, Modelling Tools and Agricultural Decison-Making (Ed. Utset, A.), pp. 165–182. New York: Nova Science Publisher.Google Scholar
Utset, A., Del Río, B., Martínez, J. C., Martínez, D., Provedo, R. & Martín, J. C. (2006). El plan de experimentación agraria desarrollado por ITACyL y los regantes de Castilla y León. Tierras de Castilla 128, 6–13.Google Scholar
Utset, A., Farre, I., Martínez-Cob, A. & Cavero, J. (2004). Comparing Penman–Monteith and Priestley–Taylor approaches as reference-evapotranspiration inputs for modeling maize water-use under Mediterranean conditions. Agricultural Water Management 66, 205–219.CrossRefGoogle Scholar
Utset, A., Velicia, H., Del Rio, B., Morillo, R., Centeno, J. A. & Martínez, J. C. (2007). Calibrating and validating an agrohydrological model to simulate sugarbeet water use under Mediterranean conditions. Agricultural Water Management 94, 11–21.CrossRefGoogle Scholar
Villalobos, F. J. & Fereres, E. (2004). Climate change effects on crop water requirements in Southern Spain. II. Contrasting meteorological and agronomic viewpoints. In Proceedings of VIII Congress of the European Society of Agronomy (Eds Jacobsen, S. E., Jensen, C. R. & Porter, J. R.), pp. 349–350. Copenhagen: KVL.Google Scholar
Watson, R. T., Zinyowera, M. C., Hoss, R. M. & Dokken, D. J. (2001). Climate Change 1995: Impacts, Adaptations and Mitigation of Climate Change: Scientific-Technical Analysis. Contribution of Working Group II to the Second Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press.Google Scholar
Wetterhall, F., Halldin, S. & Xu, C. (2005). Statistical precipitation downscaling in central Sweden with the analogue method. Journal of Hydrology 306, 174–190.CrossRefGoogle Scholar
Wilby, R. I. & Wigley, T. M. L. (2000). Downscaling general circulation issues in climate prediction. In Climate Prediction and Agriculture, Proceedings of the START/WMO International Workshop held in Geneva, Switzerland, 27–29 September 1999, Washington D.C. (Ed. Sivakumar, M. V. K.), pp. 39–68. Washington, DC: International START Secretariat.Google Scholar