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Investment in Irrigation Systems under Precipitation Uncertainty

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Abstract

Efficient agricultural water management is indispensable in meeting future food demands. The European Water Framework Directive promotes several measures such as the adoption of adequate water pricing mechanisms or the promotion of water-saving irrigation technologies. We apply a stochastic dynamic programming model (SDPM) to analyze a farmer’s optimal investment strategy to adopt a water-efficient drip irrigation system or a sprinkler irrigation system under uncertainty about future production conditions, i.e. about future precipitation patterns. We assess the optimal timing to invest into either irrigation system in the planning period 2010 to 2040. We then investigate how alternative policies, (a) irrigation water pricing, and (b) equipment subsidies for drip irrigation, affect the investment strategy. We perform the analysis for the semi-arid agricultural production region Marchfeld in Austria, and use data from the bio-physical process simulation model EPIC (Environmental Policy Integrated Climate) which takes into account site and management related characteristics as well as weather parameters from a statistical climate change model. We find that investment in drip irrigation is unlikely unless subsidies for equipment cost are granted. Also water prices do not increase the probability to adopt a drip irrigation system, but rather delay the timing to invest into either irrigation system.

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Notes

  1. Due to the complex geological genesis of the Vienna Basin, about 312 soil types can be differentiated in Marchfeld (Anonymous 1972). These have been grouped into five soil clusters, according to the amount of total available soil water capacity in 1.2 cm soil depth and humus content in the topsoil (BFW 2009).

  2. In this section, profits for an irrigation system are calculated for the case that the irrigation system is switched on. This implies that it is used optimally throughout the year. Optimal use is determined endogenously by the EPIC model (cp. section 2.2.).

  3. We use mean commodity prices in our analysis as we concentrate on the effects of weather uncertainty on crop yields and consequently profits, and not market uncertainty. OECD-FAO (2011) suggests that agricultural commodity prices are likely to remain higher during the next 10 years compared to the previous decade with a risk of upside price volatility. The authors also state that yield induced fluctuations in production have been a prime source of international price volatility. They suggest that weather-induced variations in crop yields could become an even more critical driver of price volatility in the future. To account for a higher level of prices, we use average commodity prices of the years 2005–2009 (Statistics Austria), in which the price hike of the year 2008 is accounted for.

  4. Although the production of corn results in relatively high dry matter crop yields on both soil types, it yields relatively low average profits compared to, for instance, carrots production which has a relatively low dry matter crop yield but yields high average profits. Amongst others, this difference in profits can be explained by varying revenues, a product of fresh matter crop yields and commodity prices. Corn has a low dry to fresh-matter conversion coefficient of 1.17 and a relatively low average commodity price of 121.8 €/t. In contrast, dry to fresh matter crop yields of carrot production are converted by a factor of 8.3 and subject to commodity prices of 236 €/t.

References

  • Alcamo J, Moreno JM, Nováky B, Bindi M, Corobov R, Devoy RJN, Giannakopoulos C, Martin E, Olesen JE, Shvidenko A (2007) Europe. Climate change 2007: impacts, adaptation and vulnerability. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 541–580

    Google Scholar 

  • Anonymous (1972) Bodenkarte 1:25000, Kartierungsbereich Groß Enzersdorf, NÖ., Österreichische Bodenkartierung, Bundesanstalt für Bodenwirtschaft, Vienna

  • Bjornlund H, Nicol L, Klein KK (2009) The adoption of improved irrigation technology and management practices - a study of two irrigation districts in Alberta, Canada. Agr Water Manage 96:121–131

    Article  Google Scholar 

  • Blackstock KL, Ingram J, Burton R, Brown KM, Slee B (2010) Understanding and influencing behaviour change by farmers to improve water quality. Sci Total Environ 408:5631–5638

    Article  Google Scholar 

  • Brennan M, Schwartz E (1985) Evaluating natural resource investment. J Bus 58:135–157

    Article  Google Scholar 

  • Bryant K, Mjelde JW, Lacewell RD (1993) An intraseasonal dynamic optimization model to allocate irrigation water between crops. Am J Agr Econ 75(4):1021–1029

    Article  Google Scholar 

  • Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft (BMLFUW) (2008) Deckungsbeiträge und Daten für die Betriebsplanung, Berger, Horn

  • Bundesamt für Wald (BFW) (2009) Digital soil map for Austria. BFW, Vienna (unpublished data)

  • Cai X, Rosegrant MW (2003) World water productivity: current situation and future options. In: Kijne JW, Barker R, Molden D (eds) Water productivity in agriculture: limits and opportunities for improvement. CABI Publishing, UK, pp 163–178

    Chapter  Google Scholar 

  • Carey JM, Zilberman D (2002) A model of investment under uncertainty: modern irrigation technology and emerging markets in water. Am J Agr Econ 84:171–183

    Article  Google Scholar 

  • Caswell M, Zilberman D (1985) The choices of irrigation technologies in California. Am J Agr Econ 67:224–234

    Article  Google Scholar 

  • Caswell M, Zilberman D (1990) The effects of pricing policies on water conservation and drainage. Am J Agr 72:883–890

    Article  Google Scholar 

  • Cetin O, Bilgel L (2002) Effects of different irrigation methods on shedding and yield of cotton. Agr Water Manage 54:1–15

    Article  Google Scholar 

  • Christensen J, Christensen O (2007) A summary of the PRUDENCE model projections of changes in European climate by the end of this century. Clim Chang 81:7–30

    Article  Google Scholar 

  • Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held I, Jones R, Kolli RK, Kwon WT, Laprise R, Magaña Rueda V, Mearns L, Menéndez CG, Räisänen J, Rinke A, Sarr A, Whetton P (2007) Regional climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge and New York

    Google Scholar 

  • Dinar A, Subramanian A (1998) Policy implications from water pricing experiences invarious countries. Water Policy 1:239–250

    Article  Google Scholar 

  • Döll P (2002) Impact of climate change and variability on irrigation requirements: a global perspective. Clim Chang 54:269–293

    Article  Google Scholar 

  • Dubrovský M, Svoboda MD, Trnka M, Hayes MJ, Wilhite DA, Zalud Z, Hlavinka P (2009) Application of relative drought indices in assessing climate-change impacts on drought conditions in Czechia. Theor Appl Climatol 96:155–171

    Article  Google Scholar 

  • Eitzinger J, Kersebaum C, Formayer H (2009) Landwirtschaft im Klimawandel - Auswirkungen und Anpassungsstrategien für die Land- und Forstwirtschaft in Mitteleuropa. AgriMedia, Clenze

  • European Environment Agency (EEA) (2009) Water resources across Europe - confronting water scarcity and drought. EEA Report No. 2/2009, European Environment Agency, Office for Official Publications of the European Communities, Luxembourg

  • European Water Framework Directive, DIRECTIVE 2000/60/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 23 October 2000

  • Green G, Sunding D, Zilberman D (1996) Explaining irrigation technology choices: a microparameter approach. Am J Agr Econ 78(4):1064–1072

    Article  Google Scholar 

  • Greiner R, Patterson L, Miller O (2009) Motivations, risk perceptions and adoption of conservation practices by farmers. Agr Syst 99:86–104

    Article  Google Scholar 

  • Horst L (1998) The dilemmas of water division, considerations and criteria for irrigation systems design. IWMI, Colombo

  • Huffaker R, Whittelsey N (2000) The allocative efficiency and conservation potential of water laws encouraging investments in on-farm irrigation technology. Agr Econ 24:47–60

    Article  Google Scholar 

  • Intergovernmental Panel on Climate Change (IPCC) (2000) Summary for Policymakers, Emission Scenarios: A Special Report of IPCC Working Group III, IPCC, ISBN 92-9169-113-5. http://www.ipcc.ch/pdf/special-reports/spm/sres-en.pdf. Accessed June 2012

  • Izaurralde RC, Williams JR, McGill WB, Rosenberg WB, Quiroga MC (2006) Simulating soil C dynamics with EPIC: model description and testing against long-term data. Ecol Model 192:362–384

    Article  Google Scholar 

  • Luquet D, Vidal A, Smith M, Dauzat J (2005) ‘More crop per drop’: how to make it acceptable for farmers. Agr Water Manage 76:108–119

    Article  Google Scholar 

  • Marques GF, Lund JR, Howitt RE (2005) Modeling irrigated agricultural production and water use decisions under water supply uncertainty. Water Resour Res 41:WO8423

    Article  Google Scholar 

  • Matthews KB, Rivington M, Buchan K, Miller D, Bellocchi G (2008) Characterising the agro-meteorological implications of climate change scenarios for land management stakeholders. Climate Res 37:59–75

    Article  Google Scholar 

  • McDonald R, Siegel D (1986) The value of waiting to invest. Q J Econ 101:707–723

    Article  Google Scholar 

  • McGuckin T, Mapel C, Lansford R (1987) Optimal control of irrigation scheduling using a random time frame. Am J Agr Econ 69(1):123–133

    Article  Google Scholar 

  • Michailides A, Mattas K, Tzouramani I, Karamouzis D (2009) A socioeconomic valuation of an irrigation system project based on real option analysis approach. Water Resour Manag 23:1989–2001

    Article  Google Scholar 

  • Michailidis A, Mattas K (2007) Using real options theory to dam investment analysis: an application of binomial option pricing model. Water Resour Manag 21:1717–1733

    Article  Google Scholar 

  • Molden D (2006) Water management for agriculture. In: Giordano MA, Rijberman FR, Saleth RM (eds) More crop per drop: revisiting a research paradigm: results and synthesis of IWMI’s Research: 1996–2005. IWA Publishing, London, pp 178–195

    Google Scholar 

  • Moore M, Gollehon NR, Carey MB (1994) Multicrop production decisions in western irrigated agriculture: the role of water price. Am J Agr Econ 76(4):859–874

    Article  Google Scholar 

  • OECD/FAO (2011) OECD-FAO Agricultural Outlook 2011–2020, OECD Publishing and FAO, http://dx.doi.org/10.1787/agr_outlook-2011-en. Accessed march 2012

  • Olesen JE, Trnka M, Kersebaum KC, Skjelvåg AO, Seguin B, Peltonen-Sainio P, Rossi F, Kozyra J, Micale F (2011) Impacts and adaptation of European crop production systems to climate change. Eur J Agron 34:96–112

    Article  Google Scholar 

  • Pal JS, Giorgi F, Bi X (2004) Consistency of recent European summer precipitation trends and extremes with future regional climate projections. Geophys Res Lett 31:L13202

    Article  Google Scholar 

  • Peterson JM, Ding Y (2005) Economic adjustments to groundwater depletion in the high plains: do water-saving irrigation systems save water? Am J Agr Econ 87(1):147–159

    Article  Google Scholar 

  • Pindyck R (1980) Uncertainty and exhaustible resource markets. J Polit Econ 88:1203–1225

    Article  Google Scholar 

  • Playán E, Mateos L (2006) Modernization and optimization of irrigation systems to increase water productivity. Agr Water Manage 80:100–116

    Article  Google Scholar 

  • Rajak D, Manjunatha MV, Rajkumar GR, Hebbara M, Minhas PS (2006) Comparative effects of drip and furrow irrigation on the yield and water productivity of cotton (Gossypium hirsutum L.) in a saline and waterlogged vertisol. Agr Water Manage 83:30–36

    Article  Google Scholar 

  • Sauer T, Havlík P, Schneider UA, Schmid E, Kindermann G, Obersteiner M (2010) Agriculture and resource availability in a changing world: the role of irrigation. Water Resour Res 46:W06503

    Article  Google Scholar 

  • Schmid E, Sinabell F, Liebhard P (2004) Effects of reduced tillage systems and cover crops on sugar beet yield and quality, ground water recharge and nitrogen leaching in the pannonic Region Marchfeld, Austria. Pflanzenbauwissenschaften 8(1):1–9

    Google Scholar 

  • Schmid E, Sinabell F, Hofreither MF (2007) Sustainability in practice: a case study on the reorientation of the common agricultural policy in Austria. In: Schubert U, Störmer E (eds) Sustainable development in Europe: concepts, evaluation and application. Edward Elgar, Cheltenham and Northhampton, pp 109–122

    Google Scholar 

  • Shiferaw BA, Wani SP, Nageswara Rao GD (2003) Irrigation investment and groundwater depletion in Indian semi-arid villages: the effect of alternative water pricing regimes. (Working Paper Series no. 17.), International Crops Research Institute for the Semi-Arid Tropics, India

  • Stenitzer E, Hoesch J (2005) Grundwasserneubildung im Marchfeld - Lysimetermessungen und Modellrechnungen, 11. Gumpensteiner Lysimetertagung, 5 und 6. April 2005, Höhere Bundeslehr- und Forstanstalt für Landwirtschaft Irdning, Austria; http://www.dafne.at/. Accessed March 2012

  • Strauss F, Formayer H, Schmid E (2012a) High resolution climate data for Austria in the period from 2008 to 2040 from a statistical climate change model. Int J Climatol. doi:10.1002/joc.3434

  • Strauss F, Schmid E, Moltchanova E, Formayer H, Wang X (2012b) Modeling climate change and biophysical impacts of crop production in the Austrian Marchfeld region. Clim Chang 111:641–664. doi:10.1007/s10584-011-0171-0

    Article  Google Scholar 

  • Suttinon P, Nasu S (2010) Real options for increasing value in industrial water infrastructure. Water Resour Manag 24(12):2881–2892

    Article  Google Scholar 

  • Thaler S, Eitzinger J, Rischbeck P, Dubrovský M, Trnka M (2010) Vulnerability of crops to climate change in Northeastern Austria. Bulg J Meteorolo Hydrolog 15(1):50–61

    Google Scholar 

  • Törnqvist R, Jarsjö J (2011) Water savings through improved irrigation techniques: basin-scale quantification in semi-arid environments. Water Resour Manag. doi:10.1007/s11269-011-9819-9

  • Tozer PR (2009) Uncertainty and investment in precision agriculture- is it worth the money? Agr Sys 100:80–87

    Article  Google Scholar 

  • Trnka M, Dubrovský M, Svoboda M, Semerádová D, Hayes M, Žalud Z, Wilhite D (2009) Developing a regional drought climatology for the Czech Republic. Int J Climatol 29:863–883

    Article  Google Scholar 

  • Trnka M, Eitzinger J, Dubrovský M, Semerádová D, Štepánek P, Hlavinka P, Balek J, Skalák P, Farda A, Formayer H, Žalud Z (2010) Is rainfed crop production in central Europe at risk? Using a regional climate model to produce high resolution agroclimatic information for decision makers. J Agr Sci 148:639–656

    Article  Google Scholar 

  • Turral H, Svendsen M, Faures JM (2010) Investing in irrigation: reviewing the past and looking to the future. Agr Water Manage 97:551–560

    Article  Google Scholar 

  • Vidal A, Comeau A, Plusquellec H, Gadelle F (2001) Case studies on water conservation in the Mediterranean region. IPTRID/FAO, Rome. http://www.fao.org/DOCREP/005/Y1275E/Y1275E00.HTM. Accessed March 2012

  • Ward FA, Pulido-Velazquez M (2008) Water conservation in irrigation can increasewater use. P Natl Acad Sci USA 105:18215–18220

    Article  Google Scholar 

  • Williams JR (1995) The EPIC model. In: Singh VP (ed) Computer models of watershed hydrology. Water Resources Publications, Highlands Ranch, pp 909–1000

    Google Scholar 

  • Yaron D, Dinar A (1982) Optimal allocation of farm irrigation water during peak seasons. Am J Agr Econ 64(4):681–689

    Article  Google Scholar 

  • Yohannes F, Tadesse T (1998) Effect of drip and furrow irrigation and plant spacing on yield of tomato at Dire Dawa, Ethiopia. Agr Water Manage 35:201–207

    Article  Google Scholar 

  • Zavaleta LR, Lacewell RD, Taylor CR (1980) Open-loop stochastic control of grain sorghum irrigation levels and timing. Am J Agr Econ 62:785–792

    Article  Google Scholar 

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Acknowledgments

This study was supported by the EU commission through the FP7 projects A European Approach to GEOSS (EuroGEOSS, www.eurogeoss.eu), Paradigm Shifts Modelling and Innovative Approaches (PASHMINA, www.pashmina-project.eu) and the ACRP-project Climate change in agriculture and forestry: an integrative assessment of mitigation and adaptation measures in Austria (CAFEE). We especially thank Bernhard Stürmer, Steffen Fritz and Mathias Kirchner for their support. The study has been realized in the course of the Young Scientists Summer Program (YSSP) of the International Institute for Applied Systems Analysis (IIASA).

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Correspondence to Christine Heumesser.

Appendix

Appendix

Table 4 Summary statistics and information on data source for each crop and irrigation system
Table 5 Summary statistics of relevant variables for both soil types and all irrigation options for the period 2008–2040

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Heumesser, C., Fuss, S., Szolgayová, J. et al. Investment in Irrigation Systems under Precipitation Uncertainty. Water Resour Manage 26, 3113–3137 (2012). https://doi.org/10.1007/s11269-012-0053-x

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