Valuing drought information for irrigation farmers: potential development of a hydrological risk insurance in Spain
Abstract
Drought events in the Mediterranean impact ecosystems and society. When meteorological drought leads to water scarcity river basin authorities and farmers are likely to be affected. The economic value of drought information and the resulting decisions that are made are of interest to these two stakeholder groups and the information providers. Here we focus on farmers’ decision-making process to cope with drought consequences on crop production. The understanding of the dynamics of droughts and water scarcity is being improved continuously and new indicators are used to link science to policy actions. This paper analyses the effects of drought management plans on maize production in the Ebro river basin to compute the willingness to pay of the farmers for hypothetical hydrological risk insurance. We also compute the value of more accurate information about drought probability that would allow for better decision-making. If runoff is reduced, farmers can consider contracting hydrological risk insurance in order eliminate the risk of water scarcity. Alternately farmers can take the risk of water reduction maintaining their activities and accept a reduction of water supply reliability. The methodology and results presented are relevant to analyse climate change since drought events in the Mediterranean are likely to increase in frequency, duration and intensity. This information is also relevant for the revision of River Basin Management Plans of the Water Framework Directive (WFD) within the context of climate change.Downloads
References
AEMET, 2010. Series temporales en temperaturas y precipitación. Spanish Meteorological Agency [Agencia Estatal de Meteorología].
Akaike H., 1973. A maximum likelihood estimation of Gaussian autoregressive moving average models. Biometrika 60, 255-265. http://dx.doi.org/10.1093/biomet/60.2.255
Bielza M., Garrido A., 2009. Evaluating the potential of whole-farm insurance over crop-specific insurance policies. Span J Agric Res 71, 3-11. http://dx.doi.org/10.5424/sjar/2009071-393
Blattberg R., 2008. International series in quantitative marketing. In: Database marketing. Chapter 11, Springer, pp. 297-298.
Bradford R. B, 2000. Drought events in Europe. In: Drought and drought mitigation in Europe (Vogt J.V., Somma F., eds). Kluwer Academic Dordrecht, pp. 7-20. http://dx.doi.org/10.1007/978-94-015-9472-1_2
Brekke L.D., Dettinger M.D., Maurer E.P., Anderson J.D., 2008. Significance of model credibility in estimating climate projection distributions for regional hydroclimatological risk assessments. Climatic Change 893(4), 371-394. http://dx.doi.org/10.1007/s10584-007-9388-3
Brook G., Chin-Hong S., Carver R.E., 1986. Predicting well productivity using principal components analysis. Professional Geographer, 38(4), 324-331. http://dx.doi.org/10.1111/j.0033-0124.1986.00324.x
CANE M.A., ESHEL G., BUCKLAND R.W., 1994. Forecasting Zimbabwean maize yield using eastern equatorial Pacific sea surface temperature. Nature 16, 3059-3071. http://dx.doi.org/10.1038/370204a0
CASH J., BUIZER J., 2005. Knowledge-action systems for seasonal to interannual climate forecasting: summary of a workshop, report to the Roundtable on Science and Technology for Sustainability, Policy and Global Affairs. The National Academies Press, Washington D.C. Available in http://books.nap.edu/catalog/11204.html [Accessed 18 Nov 2010].
CAYAN D.R., MAURER E.P., DETTINGER M.D., TYREE M., HAYHOE K., 2008. Climate change scenarios for the California region. Climatic Change 87(Sl), S21-S42.
Cerdá E., Quiroga S., 2011. Economic value of weather forecasting: the role of risk aversion. TOP (An Official Journal of the Spanish Society of Statistics and Operations Research) 19(1), 130-149. http://dx.doi.org/10.1007/s11750-009-0114-3
Chavas J., Kim K., Lauer J., Klemme R., Bland W., 2001. An economic analysis of corn yield corn profitability and risk at the edge of the Corn Belt. J Agr Resour Econ 261, 230-247.
CHEBRO, 2004. Confederación Hidrográfica del Ebro: Revisión de las necesidades hídricas netas de los cultivos en la Cuenca del Ebro, 1961–2002, Zaragoza, Espa-a.
Christensen J.H., Christensen O.B., 2007. A summary of the PRUDENCE model projections of changes in European climate by the end of this century. Climatic Change 81, 7–30. http://dx.doi.org/10.1007/s10584-006-9210-7
Ciscar J.C., Iglesias A., Feyen L., Szabó L., Van Regemorter D., Amelung B., Nicholls R., Watkiss P., Christensen O.B., Dankers R. et al., 2011. Physical and economic consequences of climate change in Europe. P Natl Acad Sci USA 108, 2678-2683. http://dx.doi.org/10.1073/pnas.1011612108
Dixon B.L., Hollinger S.E., Garcia P., Tirapattur V., 1994. Estimating corn yield response models to predict impacts of climate change. J Agr Resour Econ 191, 58-68.
El-Baroudy I., Simonovic S.P., 2004. Fuzzy criteria for the evaluation of water resource systems performance. Water Resour Res 40 W10503, http://dx.doi.org/10.1029/2003WR002828
FAOSTAT, 2010. Food and Agriculture Organization, Statistical Division. Available in http://apps.fao.org. [Accessed 30 Sep 2010].
Ferreyra R.A, Podestá G.P., Messina C.D., Lestón D., Dardanelli J., Guevara E., Meira S., 2001. A linked-modelling framework to estimate maize production risk associated with ENSO-related climate variability in Argentina. Agr Forest Meteorol, 107, 177-192. http://dx.doi.org/10.1016/S0168-1923(00)00240-9
Fowler H.J., Kilsby C.G., Stunell J., 2007. Modelling the impacts of projected future climate change on water resources in north-west England. Hydrol Earth Syst Sci 113, 1115–1126. http://dx.doi.org/10.5194/hess-11-1115-2007
Fronzek S., Carter T., 2007. Assessing uncertainties in climate change impacts on resource potential for Europe based on projections from RCMs and GCMs. Climatic Change 81, 357-371. http://dx.doi.org/10.1007/s10584-006-9214-3
Garrote L., Flores F., Iglesias A., 2007. Linking drought indicators to policy: the case of the Tagus basin drought plan. Water Resour Manage 21(5), 873-882. http://dx.doi.org/10.1007/s11269-006-9086-3
Gil M., Garrido A., Gomez-Ramos A., 2010. How to link agricultural productivity, water availability and water demand in a risk context: A model to manage hydrological risks. Span J Agric Res 8(S2), 207-220. http://dx.doi.org/10.5424/sjar/201008S2-1363
Gil M., Garrido A., Gomez-Ramos A., 2011. Economic analysis of drought risks: an application to irrigated agriculture in Spain. Agric Water Manage 98(5), 823-833. http://dx.doi.org/10.1016/j.agwat.2010.12.008
Giorgi F., Lionello P., 2008. Climate change projections for the Mediterranean region. Global Planet Change 63, 90–104. http://dx.doi.org/10.1016/j.gloplacha.2007.09.005
Gómez-Limón J.A., Arriaza M., Riesgo L., 2003. An MCDM analysis of agricultural risk aversion. Eur J Oper Res, 151(3), 569-585. http://dx.doi.org/10.1016/S0377-2217(02)00625-2
Gómez-Limón J.A., Riesgo L., Arriaza M., 2004. Multi-criteria analysis of input use in agriculture. J Agr Econ 55(3), 541-564. http://dx.doi.org/10.1111/j.1477-9552.2004.tb00114.x
Gong X., Barnston A., Ward M., 2003. The effect of spatial aggregation on the skill of seasonal precipitation forecasts. J Clim 16, 3059-3071. 2.0.CO;2" target="_blank">http://dx.doi.org/10.1175/1520-0442(2003)016<3059:TEOSAO>2.0.CO;2
Hansen J.W., Indeje M., 2004. Linking dynamic seasonal climate forecasats with crop simulation for maize yield prediction in semi-arid Kenya. Agric Meteorol 125, 143-157. http://dx.doi.org/10.1016/j.agrformet.2004.02.006
Hansen J.W., Challinor A., Ines A., Wheeler T., Moron V., 2006. Translating climate forecasts into agricultural terms: advances and challenges. Clim Res 33, 27-41. http://dx.doi.org/10.3354/cr033027
Hashimoto T., Stedinger J.R., Loucks D.P., 1982a. Reliability, resiliency, and vulnerability criteria for water resources system performance evaluation. Water Resour Res 18, 14-20. http://dx.doi.org/10.1029/WR018i001p00014
Hashimoto T., Loucks D.P., Stedinger J.R., 1982b. Robustness of water resources systems. Water Resour Res 18, 21-26. http://dx.doi.org/10.1029/WR018i001p00021
Hayes M., 2002. Drought indexes // Drought indices. Univ Nebraska Lincoln, NE, USA, 9 pp.
Hill H.S.J., Mjelde J.W., 2002. Challenges and opportunities provided by seasonal climate forecasts: a literature review. J Agr Appl Econ 34(3), 603-632. http://dx.doi.org/10.1017/S1074070800009330
Iglesias A., Rosenzweig C., Pereira D., 2000. Agricultural impacts of climate in Spain: developing tools for a spatial analysis. Global Environ Change 10, 69-80. http://dx.doi.org/10.1016/S0959-3780(00)00010-8
Iglesias A., Quiroga S., 2007. Measuring the risk of climate variability to cereal production at five sites in Spain. Clim Res 34, 45-57. http://dx.doi.org/10.3354/cr034047
IGLESIAS A., GARROTE L., FLORES F., MONEO M., 2007. Challenges to manage the risk of water scarcity and climate change in the Mediterranean. Water Resour Manage 215, 227-288. http://dx.doi.org/10.1007/s11269-006-9111-6
Iglesias A., Cancelliere A., Cubillo F., Garrote L., Wilhite D.A., 2008. Coping with drought risk in agriculture and water supply systems: drought management and policy development in the Mediterranean. Springer, The Netherlands.
Iglesias A., Mougou R., Moneo M., Quiroga S., 2010. Towards adaptation of agriculture to climate change in the Mediterranean. Regional Environmental Change 11 (Suppl 1), S159-S166. http://dx.doi.org/10.1007/s10113-010-0187-4
Iglesias A., Garrote L., Quiroga S., Moneo M., 2011. A regional comparison of the effects of climate change on agriculture in Europe. Climatic Change (In press).
IPCC, 2007. Climate change. Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge Univ Press. Cambridge, UK.
Jeffers J.N.R., 1967. Two case studies in the application of principal component analysis. Appl Stat 16, 225- 236. http://dx.doi.org/10.2307/2985919
Jolliffe I., 1982. A note on the use of principal components in regression. Appl Stat 31(3), 300-303. http://dx.doi.org/10.2307/2348005
Jolliffe I., 1986. Principal component analysis. Springer-Verlag, NY. http://dx.doi.org/10.1007/978-1-4757-1904-8
Katz R.W., 1993. Dynamic cost-loss ratio decision making model with an autocorrelated climate variable. J Climate 5, 151-160. 2.0.CO;2" target="_blank">http://dx.doi.org/10.1175/1520-0442(1993)006<0151:DCLRDM>2.0.CO;2
Katz R.W., Ehrendorfer M., 2006. Bayesian approach to decision making using Ensemble weather forecasts, Weather Forecast 21, 220-231. http://dx.doi.org/10.1175/WAF913.1
KENDALL M., 1957. A course in multivariate analysis. Ed. Griffin. London.
Kerr R.A., 2005. Confronting the Bogeyman of the climate system. Science 310, 432-433. http://dx.doi.org/10.1126/science.310.5747.432
Keyantash J., Dracup J.A., 2002. The quantification of drought. An evaluation of drought indices. Bull Am Meteorol Soc 83(8), 1167–1180. 2.3.CO;2" target="_blank">http://dx.doi.org/10.1175/1520-0477(2002)083<1191:TQODAE>2.3.CO;2
Khan M.S., Coulibaly P., Dibike Y., 2006. Uncertainty analysis of statistical downscaling methods. J Hydrol 319(1-4), 357-382. http://dx.doi.org/10.1016/j.jhydrol.2005.06.035
Lobell D.B., Burke M.B., Tebaldi C., Mastrandrea M.D., Falcon W.P., Naylor R.L., 2008. Prioritizing climate change adaptation needs for food security in 2030. Science 319(5863), 607-610. http://dx.doi.org/10.1126/science.1152339
Luo H., Skees J.R., Marchant M.A., 1994. Weather information and the potential for the inter-temporal adverse selection in crop insurance. Rev Agr Econ 16, 441-451. http://dx.doi.org/10.2307/1349702
MARM, 2006. Plan Nacional de Adaptación al Cambio Climático PNACC. Ministerio de Medio Ambiente y Medio Rural y Marino, Madrid, Spain. Available in http://www.mma.es/portal/secciones/cambio_climatico/areas_tematicas/impactos_cc/pdf/pna_v3.pdf [Accessed 10 Oct 2010].
MARM, 2010. Anuarios de estadística agroalimentaria, years 1976–2010. Spanish Ministry of Environment and Rural and Marine, Statistical Division, Madrid.
Mas-Colell A., Whinston M.D., Green J.R. 1995. Choice under uncertainty. Microeconomic theory, Chapter 6, Oxford Univ Press, NY. pp. 167-197.
McKee T.B., Doesken N.J., Kleist J., 1993. The relationship of drought frequency and duration to time scales. 8th Conf on Applied Climatology, Anaheim, CA, USA.
Meinke H., Nelson R., Kokic P., Stone R., Selvaraju R., Baethgen W., 2006. Actionable climate knowledge: from analysis to synthesis. Clim Res 33, 101-110. http://dx.doi.org/10.3354/cr033101
Moss C.B., Shonkwiler J.S., 1993. Estimating yield distributions with a stochastic trend and nonnormal errors. Am J Agr Econ 75, 1056-1062. http://dx.doi.org/10.2307/1243993
Moss R.H., Edmonds J.A., Hibbard K.A., Manning M.R., Rose S.K., Van Vuuren D.P., Carter T.R., Emori S., Kainuma M., Kram T. et al., 2010. The next generation of scenarios for climate change research and assessment. Nature 463, 747-756. http://dx.doi.org/10.1038/nature08823
Murphy A.H., Ehrendorfer M., 1987. On the relationship between the accuracy and value of forecasts in the cost-loss ratio situation. Weather Forecast 2, 243-251. 2.0.CO;2" target="_blank">http://dx.doi.org/10.1175/1520-0434(1987)002<0243:OTRBTA>2.0.CO;2
Murphy A.H., Katz R.W., Winkler R.L., Hsu W., 1985. Repetitive decision making and the value of forecasts in the cost-loss ratio situation: a dynamic model. Mon Weather Rev 113, 801-813. 2.0.CO;2" target="_blank">http://dx.doi.org/10.1175/1520-0493(1985)113<0801:RDMATV>2.0.CO;2
NAKICENOVIC N., ALCAMO J., DAVIS G., DE VRIES B., FENHANN J., GAFFIN S., GREGORY K., GRÜBLER A. et al., 2000. Special report on emissions scenarios, Working Group III, Intergovernmental Panel on Climate Change IPCC, Cambridge Univ Press, Cambridge, UK, 595 pp. Available in http://www.grida.no/climate/ipcc/emission/index.htm. [Accessed 02 Dec 2010]
Palacios-Huerta I., 2003. An empirical analysis of the risk properties of human capital returns. Am Econ Rev 933, 948-964. http://dx.doi.org/10.1257/000282803322157197
Palmer T.N., 2002. The economic value of ensemble forecasts as a tool for risk assessment: from days to decades. Quart J Roy Meteorol Soc 128, 747-774. http://dx.doi.org/10.1256/0035900021643593
Parry M.A., Rosenzweig C., Iglesias A., Livermore M., Fischer G., 2004. Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Global Environ Change 14, 53–67. http://dx.doi.org/10.1016/j.gloenvcha.2003.10.008
Quiroga S., Iglesias A., 2009. A comparison of the climate risks of cereal, citrus, grapevine and olive production in Spain. Agr Syst 101, 91-100. http://dx.doi.org/10.1016/j.agsy.2009.03.006
Quiroga S., Garrote L., Iglesias A., Fernández-Haddad Z., Schlickenrieder J., De Lama B., Mosso C., Sánchez-Arcilla A., 2011. The economic value of drought information for water management under climate change: a case study in the Ebro basin. Nat Hazard Earth Syst Sci 11, 643-657. http://dx.doi.org/10.5194/nhess-11-643-2011
Raskin R., Cochran M.J., 1986. Interpretations and transformations of scale for the Pratt-Arrow absolute risk aversion coefficient: Implications for generalized stochastic dominance. Western J Agr Econ 112, 204-210.
Rubas D.J., Hill S.J.H., Mjelde J.W., 2006. Economics and climate applications: exploring the frontier. Clim Res 33, 43-54. http://dx.doi.org/10.3354/cr033043
Schwarz G., 1978. Estimating the dimension of a model. Ann Stat 6, 461-464. http://dx.doi.org/10.1214/aos/1176344136
Sivakumar M.V.K., 2006. Climate prediction and agriculture: current status and future challenges. Clim Res 33, 3-17. http://dx.doi.org/10.3354/cr033003
Stanger T.F., Lauer, J.G., Chavas J.P., 2008. The profitability and risk of Long-term cropping systems featuring different rotations and nitrogen rates. Agron J 100, 105-113. http://dx.doi.org/10.2134/agrojnl2006.0322
Steinmann A., Hayes M., Cavalcanti L., 2005. Drought indicators and triggers. In: Drought and water crises. Science, technology and management issues (Wilhite D.A., ed.). Chapter 4, CRC Press, NY. pp 71-92.
Tsakiris G., Loukas A., Pangalou D., Vangelis H., Tigkas D., Rossi G., Cancelliere A., 2007. Drought characterization. In: Drought management guidelines technical annex (Iglesias A. et al., eds.) Chapter 7. Options Méditerranéennes Series B. No. 58, pp. 85-102.
White H., 1980. A heteroscedasticity-consistent covariance matrix estimator and a direct test for heteroscedasticity. Econometrica 48, 817-838. http://dx.doi.org/10.2307/1912934
ZHU T., JENKINS M.W., LUND J.R., 2005. Estimated impacts of climate warming on California water availability under twelve future climate scenarios. J Water Resour Plann Manage 415, 1027–1038. http://dx.doi.org/10.1111/j.1752-1688.2005.tb03783.x
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