Skip to main content
SpringerLink
Log in

A Systems Approach to Climate Risk in Rainfed Farming Systems

  • Chapter
  • First Online:
Rainfed Farming Systems

Abstract

Climate is a major source of risk in rainfed farming systems. Systems thinking from natural sciences is used to define and explore concepts of weather, climate and climate change before discussion of how climate data can be used in simulation models of agricultural production systems. We then use systems engineering to consider the nature of climate risk and the use of seasonal climate forecasts in managing risk in rainfed cropping decisions in case studies from Australia and the Philippines. Finally, we consider some of the human factors in managing climate risk using soft systems methodology.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    See Glossary.

  2. 2.

    See Glossary for explanation.

  3. 3.

    See Glossary for definitions of Hard and Soft Systems methodology.

  4. 4.

    See glossary for any unfamiliar terms.

  5. 5.

    See Glossary.

  6. 6.

    See Glossary.

  7. 7.

    See Glossary for definitions of top down and bottom up approaches.

  8. 8.

    See Glossary for description of various simulation models.

  9. 9.

    See Glossary for explanation.

  10. 10.

    Bayes’ theorem relates the conditional and marginal probabilities of two random events. It is often used to compute posterior probabilities, given observations.

  11. 11.

    Deep drainage is important in this case as it may raise watertables and introduce salt into the root zone.

  12. 12.

    See Glossary for explanation.

  13. 13.

    Decision Support System for Agrotechnology Transfer Version 4.0 CERES-Maize (Crop Environment Resource Synthesis) model is a predictive, deterministic model designed to simulate corn growth, soil, water and temperature and soil nitrogen dynamics at a field scale for one growing season. The model is used for basic and applied research on the effects of climate (thermal regime, water stress) and management (fertiliser practices, irrigation) on the growth and yield of corn. It is also used to evaluate effects of nitrogen fertiliser practices on nitrogen uptake and nitrogen leaching from soil; and in global climate change research, to evaluate the potential effects of climate warming and changes in precipitation and water use efficiency due to increased atmospheric CO2.

  14. 14.

    See US National weather service Climate Prediction Centre .http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/nino_regions.shtml.

References

  • Abedullah P, Pandey S (1998) Risk and the value of rainfall forecast for rainfed rice in the Philippines. Philipp J Crop Sci 23:159–165

    Google Scholar 

  • Albarece BJ (2000) Problems of the southern Philippine corn industry in relation to food supply, distribution and household income. In: Feeding the Asian cities meeting, Bangkok, 27–30 November 2000

    Google Scholar 

  • Bawden RJ, Packham RL (1991) Improving agriculture through systemic action research. In: Squires VR, Tow PG (eds.) Dryland farming a systems approach. Sydney University Press, Sydney

    Google Scholar 

  • Beck U (1992) Risk society: towards a new modernity. Sage, London

    Google Scholar 

  • Botterill LC (2003) Government responses to drought in Australia. In: Botterill LC, Fisher M (eds.) Beyond drought: people, policy and perspectives. CSIRO, Melbourne

    Google Scholar 

  • Cline WR (2007) Global warming and agriculture. Impact estimates by country. Center for Global Development and the Peterson Institute for International Economics, Washington, DC

    Google Scholar 

  • Conway G (1985) Agroecosystem analysis. Agric Adm 20:31–55

    Google Scholar 

  • Dai A, Lamb P, Trenberth KE, Hulme M, Jones PD, Xie P (2004a) The recent Sahel drought is real. Int J Climatol 24:1323–1331

    Google Scholar 

  • Dai A, Trenberth KE, Qian T (2004b) A global data set of palmer drought severity index for 1870–2002: relationship with soil moisture and effects of surface warming. J Hydrometeorol 5:1117–1130

    Google Scholar 

  • Dent JB, Blackie MJ (1975) Systems simulation in agriculture. Applied Science, London

    Google Scholar 

  • FAO (1978) Report on the agro-ecological zones project. 1. Methodology and results for Africa. World Soil Resources Report 48. FAO, United Nations, Rome

    Google Scholar 

  • Fischer G,, van Velthuizen H,, Shah M,, Nachtergaele F (2002) Global agro-ecological assessment for agriculture in the 21st century: methodology and results. International Institute for Applied Systems Analysis Laxenburg, Austria, Food and Agriculture Organization, Italy, United Nations

    Google Scholar 

  • Flood RL, Jackson MC (1991) Creative problem solving. Wiley, Chichester

    Google Scholar 

  • Giddens A (2002) Runaway world. How globalisation is reshaping our lives. Profile Books, London

    Google Scholar 

  • Hammer GL, Nicholls NN (1996) Managing for climate variability – the role of seasonal climate forecasting in improving agricultural systems. In: Proceedings of the 2nd Australian conference on agricultural meteorology, Brisbane, pp 19–27

    Google Scholar 

  • Hansen JW (2002) Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges. Agric Syst 74:309–330

    Google Scholar 

  • Hare FK (1987) Drought and desiccation: twin hazards of a variable climate. In: Wilhite DA, Easterling WA, Wood DA (eds.) Planning for drought. Westview Press, Boulder, pp 3–11

    Google Scholar 

  • Harger JRE (1995) ENSO variations and drought occurrence in Indonesia and the Philippines. Atmos Environ 29:1943–1955

    CAS  Google Scholar 

  • Hayman PT (2004) Decision support systems – a promising past, a disappointing present and an uncertain future, Invited paper to the 4th International Crop Science Congress, Brisbane. www.cropscience.org.au/icsc2004/symposia/4/1/1778_haymanp.htm

  • Hayman PT, Cox PG (2005) Drought risk as a negotiated construct. In: Botterill LC, Wilhite DA (eds) From disaster response to risk management. Australia’s national drought policy. Springer, Dordrecht, pp 113–126

    Google Scholar 

  • Hayman PT, Crean J, Parton KA, Mullen JM (2007) How do seasonal climate forecasts compare to other innovations that farmers are encouraged to adopt? Aust J Agric Res 58:975–984

    Google Scholar 

  • Hilario F, Hayman PT, Alexander BM, de Guzman R, Ortega D (2008) El Nino southern oscillation in the Philippines and Australia: impacts, forecast and implications for risk management. In: 6th Asian Society of Agricultural Economists International Conference in Makati City, Manila, 28–30 August 2008

    Google Scholar 

  • Howden SM, Soussana JF, Tubiello FN, Chhetri N, Dunlop M, Meinke HM (2007) Adapting agriculture to climate change. Proc Natl Acad Sci 104:19691–19696

    PubMed  CAS  Google Scholar 

  • Hunt JM, Hochman Z, Long W, Holzworth D, Whitbread A, van Rees S (2008) Using Yield Prophet® to determine the likely impacts of climate change on wheat and barley production. In: Unkovich M (ed.) Proceedings of the 14th Australian agronomy conference, Australian Society of Agronomy, Adelaide

    Google Scholar 

  • IPCC (2007) Climate change 2007: impacts, adaptation and vulnerability. contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge

    Google Scholar 

  • Ison RL (1998) The search for system. In: Michalk DL, Pratley JE (eds.) Proceedings of the 9th Australian agronomy conference Charles Sturt University, Wagga Wagga, pp 149–58

    Google Scholar 

  • Jose AM (2002) ENSO impacts in the Philippines examples of ENSO-society interactions. http://iri.columbia.edu/climate/ENSO/societal/example/Jose.html

  • Keating B, Carberry PS (2008) Emerging opportunities for Australian agriculture. In: Unkovich M (ed.) Proceedings of the 14th Australian agronomy conference, Australian Society of Agronomy, Adelaide

    Google Scholar 

  • Keogh M (2008) Knowledge gaps and opportunities for research to inform and position Australian primary industries to respond to a future national greenhouse emissions trading scheme. A report prepared for the National Climate Change Research Strategy for Primary Industries by the Australian Farm Institute. Land and Water Australia, Canberra

    Google Scholar 

  • Lansigan FP (2003) Assessing the impacts of climate variability on crop production and developing coping strategies in rainfed agriculture. In: Yokoyama S, Concepcion RN (eds.) Coping against El Nino for stabilizing rainfed agriculture: lessons from Asia and the Pacific. Proceedings of a joint workshop, CGPRT monograph number 43, cebu, 17–19 September 2002, pp 21–36

    Google Scholar 

  • Mabutt JA (1981) Risks of desertification in dry-farming areas: the lesson of the Mallee. In: Sutton DR, de Kantzow BG (eds.) Cropping at the margin – potential for overuse of semi-arid lands. AIAS, Sydney, pp 1–7

    Google Scholar 

  • Malcolm LR (2000) Farm management economic analysis: a few disciplines, a few perspectives, a few figurings, a few futures. Invited paper presented to the annual conference of AARE, Sydney

    Google Scholar 

  • Marshall GR, Parton KA, Hammer GL (1996) Risk attitude, planting conditions and the value of seasonal forecasts to a dryland wheat grower. Aust J Agric Econ 40:211–234

    Google Scholar 

  • Maunder WJ (1989) The human impact of climate uncertainty. Routledge, London

    Google Scholar 

  • McCown RL, Cox PG, Keating BA, Hammer GL, Carberry PS, Probert ME, Freebairn DM (1993) The development of strategies for improved agricultural systems and land-use management. In: Goldsworthy P FWT, Penning de Vries Proceedings of an international workshop on systems research methods in agriculture in developing countries, Mexico, pp 81–96

    Google Scholar 

  • McCown RL, Hochman Z, Carberry PS (2002) Probing the enigma of the decision support system for farmers: learning from experience and from theory. In: McCown RL, Hochman Z, Carberry PS (eds) Agricultural systems, vol 74. Elsevier, Dordrecht, pp 1–10

    Google Scholar 

  • McGuire R, Higgs R (1977) Cotton, corn and risk in the nineteenth century: another view. Explor Econ Hist 14:167–182

    Google Scholar 

  • McKeon G, Hall W, Henry B, Stone G, Watson I (eds.) (2004) Pasture degradation and recovery in Australia’s Rangelands – learning from history. Department of Natural Resources, Mines and Energy, Brisbane

    Google Scholar 

  • Meinke H, Stone RS (2005) Seasonal and interannual climate forecasting: the new tool for increasing preparedness to climate variability and change in agricultural planning and operations. Clim Change 70:221–253

    Google Scholar 

  • Meinke H, Wright W, Hayman P, Stephens D (2003) Managing cropping systems in variable climates. In: Pratley J (ed.) Principles of field crop production, 4th edn. Oxford University Press, Oxford, pp 26–77

    Google Scholar 

  • Milly PCD, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, Stouffer RJ (2008) Climate change: stationarity is dead: whither water management? Science 319:573–574

    PubMed  CAS  Google Scholar 

  • Nelson R, Howden M, Stafford Smith M (2008) Using adaptive governance to rethink the way science supports Australian drought policy. Environ Sci Policy 11:588–601

    Google Scholar 

  • Nicholls N, Wong K (1990) Dependence of rainfall variation on mean rainfall, latitude and the southern oscillation. J Climate 3:163–170

    Google Scholar 

  • Nidumolu UB, de Bie CAJM, van Keulen H, Skidmore AK, Harmsen K (2006) Review of a land use planning programme through the soft systems methodology. Land Use Policy 23:187–203

    Google Scholar 

  • O’Brien K, Eriksen S, Schjolden A, Nygaard L (2004) What’s in a word? Conflicting interpretations of vulnerability in climate change research, CICERO Working Paper 2004:04, CICERO, Oslo

    Google Scholar 

  • Opie J (1993) Ogallala: water for a dry land. University of Nebraska Press, Lincoln

    Google Scholar 

  • Parry ML, Carter TR (1988) The assessment of climatic variations on agriculture: a summary of results from studies in semi-arid regions. In: Parry ML, Carter TR, Konijn NT (eds.) The impact of climatic variations on agriculture, vol 2, Assessments in semi-arid regions. Kluwer, Dordrecht, pp 9–60

    Google Scholar 

  • Predo C, Hayman PT, Crean J, Hilario F, deGuzman F, Juanillo E (2008) Assessing the economic value of seasonal climate forecasts for corn-based farming systems in Leyte, Philippines. In: 6th Asian Society of Agricultural Economists International Conference in Makati City, Manila, 28–30 August 2008

    Google Scholar 

  • Rainman-Clewett JF, Clarkson NM, George DA, Ooi SH, Owens DT, Partridge IJ, Simpson GB (2003) Rainman StreamFlow version 4.3: a comprehensive climate and streamflow analysis package on CD to assess seasonal forecasts and manage climate risk, QI03040, Department of Primary Industries, Queensland

    Google Scholar 

  • Ringrose-Voase AJR, Young RZ, Paydar I, Huth NL, Bernardi AP, Cresswell HA, Keating BF, Scott JM, Stauffacher G, Banks RF, Holland JM, Johnston RW, Green TJ, Gregory LI, Daniells R, Farquharson J Drinkwaster R (2003) Deep drainage under different land uses in the liverpool plains catchment, Report 3: Agricultural Resource Management Report Series, NSW Agriculture

    Google Scholar 

  • Robinson JB, Butler DG (2002) An alternative method for assessing the value of the southern oscillation index SOI, including case studies of its value for crop management in the northern grainbelt of Australia. Afr J Agric Res 53:423–428

    Google Scholar 

  • Ropelewaski CF, Halpert MS (1987) Global and regional scale precipitation patterns associated with El Nino/southern oscillation ENSO. Mon Weather Rev 115:1606–1626

    Google Scholar 

  • Sadras VO, Monzon JP (2006) Modelled wheat phenology captures rising temperature trends: shortened time to flowering and maturity in Australia and Argentina. Field Crop Res 99:136–146

    Google Scholar 

  • Schneider S (2004) Climate change. http://stephenschneider.stanford.edu/

  • Scott JF, Farquharson RJ, Mullen JD, (2004) Farming systems in the northern cropping region of NSW: an economic analysis. Economic Research Report No. 20, Tamworth

    Google Scholar 

  • Sherratt T (2005) Human elements. In: Sherrat T, Griffiths T, Robin L (eds.) A change in the weather; climate and culture in Australia. National Museum of Australia, Canberra

    Google Scholar 

  • Spedding CRW (1979) An introduction to agricultural systems. Elsevier, London

    Google Scholar 

  • Squires VR (1991) A systems approach to agriculture. In: Squires VR, Tow PG (eds.) Dryland farming a systems approach. Sydney University Press, Sydney

    Google Scholar 

  • Tow PG (1991) Factors in the development and classification of dryland farming systems. In: Squires VR, Tow PG (eds.) Dryland farming a systems approach. Sydney University Press, Sydney

    Google Scholar 

  • Ullman E (1997) Close to the machine: technophilia and its discontents. City Lights Books, San Francisco

    Google Scholar 

  • UNESCO (1977) World maps of desertification. United Nations conference on desertification. A/Conf. 74/2. FAO, United Nations, Rome

    Google Scholar 

  • Vickers G (1983) Human systems are different. Harper & Row, London

    Google Scholar 

  • Walker BH, Salt D (2006) Resilience thinking, sustaining ecosystems and people in a changing world. Island Press, Washington, DC

    Google Scholar 

  • Wilhite DA (2005) Drought policy and preparedness: the Australian experience in an international context. In: Botterill LC, Wilhite DA (eds.) From disaster response to risk management. Australia’s national drought policy. Springer, Dordrecht, pp 113–126

    Google Scholar 

  • Wilson J (1988) Changing agriculture: an introduction to systems thinking. Kangaroo Press, Sydney

    Google Scholar 

Download references

Acknowledgements

Crean and Predo’s time was funded by the ACIAR project ‘Bridging the Gap Between Seasonal Climate Forecasts and Decision Makers in Australia and The Philippines.’ Hayman’s time was funded by the same ACIAR project and a project with the Centre for Natural Resource Management. Dr Uday Nidumolu contributed useful discussion on soft and hard systems and the image for Fig. 3.3.

Author information

Authors and Affiliations

  1. South Australian Research and Development Institute, Adelaide, Australia

    Peter Hayman

  2. Charles Sturt University, Orange Campus, Orange, Australia

    Jason Crean

  3. Department of Primary Industries, South Australian Research and Development Institute, Orange, New South Wales, Australia

    Jason Crean

  4. Visayas Sate University, Baybay, Leyte, Philippines

    Canesio Predo

Authors
  1. Peter Hayman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jason Crean
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Canesio Predo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Hayman .

Editor information

Editors and Affiliations

  1. Gawler, South Australia, Australia

    Philip Tow

  2. Alexander Avenue, Bibaringa, 5118, South Australia, Australia

    Ian Cooper

  3. Toowoomba, Queensland, Australia

    Ian Partridge

  4. Tasmanian Institute of Agricultural Rese, Leader, Vegetable Centre, Burnie, 7320, Tasmania, Australia

    Colin Birch

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Hayman, P., Crean, J., Predo, C. (2011). A Systems Approach to Climate Risk in Rainfed Farming Systems. In: Tow, P., Cooper, I., Partridge, I., Birch, C. (eds) Rainfed Farming Systems. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9132-2_3

Download citation

Publish with us

Policies and ethics

Search

Navigation