Regional Environmental Change

, Volume 11, Issue 4, pp 893–904 | Cite as

Sea-level rise in Indonesia: on adaptation priorities in the agricultural sector

  • Hannah FörsterEmail author
  • Till Sterzel
  • Christian A. Pape
  • Marta Moneo-Lain
  • Insa Niemeyer
  • Rizaldi Boer
  • Jürgen P. Kropp
Original Article


Adaptation to climate-change impacts requires understanding of where impacts are to be expected and what their magnitude may be. Adaptation funds are only a limited resource for helping affected parties in coping with climate-change impacts. The application of suitable methods helps to determine the recipients of adaptation aid. A quantification of impacts based on different impact analyses can aid in taking on various perspectives on the same problem in order to identify the appropriate perspective for the given decision-making context or for identifying impact patterns. Once executed, this prioritizes adaptation needs and finding a suitable allocation rule, given the policy makers perception of the decision-making context. The study introduces a set of methods of spatially explicit, sub-national (province level), and country-wide impact analyses regarding inundation impacts on agricultural areas for four important food crops in Indonesia. These methods are applied to a 1 and 2 m sea-level rise scenario and include a novel approach for impact analyses, data envelopment analysis, which is not widely used in environmental studies as of yet. Based on the given case study, the paper demonstrates the applicability of these methods and identifies impact patterns.


Data envelopment analysis Impact analysis Adaptation prioritization Climate change Agriculture Dietary loss 



Our study was carried in course of the ci:grasp project, funded by the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety through its International Climate Initiative. We would like to thank Matthias Lüdeke for discussions that helped to improve this paper. We would also like to thank two anonymous reviewers whose valuable remarks contributed to a significant improvement of this paper’s quality. Finally, we would like to thank the Directorate General for Food Crops, Indonesia, for making data available on very short notice.


  1. Asian Development Bank (2009a) Key indicators for Asia and the Pacific 2008Google Scholar
  2. Asian Development Bank (2009b) Key indicators for Asia and the Pacific 2009Google Scholar
  3. Asian Development Bank (2009c) The economics of climate change in Southeast Asia: a regional reviewGoogle Scholar
  4. Bernstein L, Bosch P, Canziani O, Chen Z, Christ R, Davidson O, Hare W, Huq S, Karoly D, Kattsov V, Kundzewicz Z, Liu J, Lohmann U, Manning M, Matsuno T, Menne B, Metz B, Mirza M, Nichols N, Nurse L, Pachauri R, Palutikof J, Parry M, Qin D, Ravindranath N, Reisinger A, Ren J, Riahi K, Rosenzweig C, Rusticucci M, Schneider S, Sokona Y, Solomon S, Stottt P, Stouffer R, Sugiyama T, Swart R, Tirpak D, Vogel C, Yohe G (2007) Climate change 2007: an assessment of the intergovernmental panel on climate change. Technical report, IPCCGoogle Scholar
  5. Bian Y, Yang F (2010) Resource and environment efficiency analysis of provinces in China : a DEA approach based on Shannon’s entropy. Energy Policy 38:1909–1917CrossRefGoogle Scholar
  6. Bosetti V, Buchner B (2009) Data envelopment analysis of different climate policy scenarios. Ecol Econ 68(5):1340–1354CrossRefGoogle Scholar
  7. BPS (2010) Average daily per capita consumption of energy per commodity group 1999, 2001–2009. Database, Jakarta,, last accessed: July 09, 2010
  8. Charnes A, Cooper WW, Rhodes EL (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444CrossRefGoogle Scholar
  9. Coelli T (1996) A guide to DEAP version 2.1: a data envelopment analysis (computer) program. Working paper no. 8/96, University of New England, ArmindaleGoogle Scholar
  10. Cooper WW, Seiford LM, Zhu J (2004) Handbook on data envelopment analysis, 2nd edn. Kluwer Academics, Norwell. UndefinedGoogle Scholar
  11. Directorate General of Food Crops (2010) Planting area (ha) of lowland rice, upland rice, cassava, and maize, 2008. last accessed: December 17, 2010Google Scholar
  12. Dyson R (2001) Pitfalls and protocols in DEA. Eur J Oper Res 132(2):245–259CrossRefGoogle Scholar
  13. Emrouznejad A, Parker BR, Tavares G (2008) Evaluation of research in efficiency and productivity: a survey and analysis of the first 30 years of scholarly literature in DEA. Socio Econ Plan Sci 42(3):151–157CrossRefGoogle Scholar
  14. Ericson J, Vörösmarty C, Dingman S, Ward L, Meybeck M (2006) Effective sea-level rise and deltas: causes of change and human dimension implications. Global Planet Change 50(1–2):63–82CrossRefGoogle Scholar
  15. FAO (2010) Food balance sheets. Data, Food and Agriculture Organization of the United Nations, Rome. “”, last accessed: August 2009
  16. Farrell MJ (1957) The measurement of productive efficiency. J R Stat Soc 120(3):253–290CrossRefGoogle Scholar
  17. Government of Republic of Indonesia (2007) Indonesia country report: climate variability and climate changes, and their implication. Technical report, Ministry of Environment, JakartaGoogle Scholar
  18. Hijmans R, Garcia N, Wieczorek J (2010) Global administrative units V. 1.0. Data. “” last accessed: September 2009
  19. Jarvis A, Reuter H, Nelson A, Guevara E (2008) Hole-filled seamless SRTM Data V4. Data. “”, last accessed: August 2009
  20. Jevrejeva S, Moore JC, Grinsted A (2010) How will sea level respond to changes in natural and anthropogenic forcings by 2100? Geophys Res Lett 37(7):1–5CrossRefGoogle Scholar
  21. Klein RJT, Amanatidis G (2004) Dynamic interactive vulnerability assessment. Technical report, Potsdam Institute for Climate Impact Research, PotsdamGoogle Scholar
  22. Las I, Surmaini E, Ruskandar A (2008) Anticipation of climate change: technology innovation and research direction of rice paddy in Indonesia. In: Proceeding of National Seminar on Technology Innovation for Rice in anticipating global climate change toward food security, Bogar. Sukamandi Research and Development Agency for RiceGoogle Scholar
  23. Meodiarta R, Stalker P (2007) The other half of climate change. Why Indonesia must adapt to protect its poorest people. Technical report, United Nations Development Program Indonesia, JakartaGoogle Scholar
  24. Ministry of Environment (2010) Indonesia Second National CommunicationGoogle Scholar
  25. Monfreda C (2008) Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biogeochem Cycles 22(1):1–19CrossRefGoogle Scholar
  26. Monfreda C, Ramankutty N, Foley JA (2008) Harvested area and yields of 175 crops (M3-Crops Data). Dataset, McGill University, Montreal. last accessed: August 2009Google Scholar
  27. Nicholls R, Mimura N (1998) Regional issues raised by sea-level rise and their policy implications. Clim Res 11:5–18CrossRefGoogle Scholar
  28. Nicholls RJ, Cazenave A (2010) Sea-level rise and its impact on coastal zones. Science (New York) 328(5985):1517–1520CrossRefGoogle Scholar
  29. Parry ML, Canziani OF, Palutikof JP, van Der Linden PJ, Hanson CE (2007) Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. CambridgeGoogle Scholar
  30. Pfeffer WT, Harper JT, O’Neel S (2008) Kinematic constraints on glacier contributions to 21st-century sea-level rise. Science (New York) 321(5894):1340–1343CrossRefGoogle Scholar
  31. Poulter B, Halpin PN (2008) Raster modelling of coastal flooding from sea-level rise. Int J Geogr Inf Sci 22(2):167–182CrossRefGoogle Scholar
  32. Rahmstorf S (2007) A semi-empirical approach to projecting future sea-level rise. Sci Agric 315:19–21Google Scholar
  33. Ramanathan R (2003) An introduction to data envelopment analysis. Sage Publications, New DelhiGoogle Scholar
  34. Republic of Indonesia (2009) Blueprint for Indonesia climate change trust fund (ICCTF). Technical report, Republic of Indonesia, JakartaGoogle Scholar
  35. Saidy AR, Azis Y (2009) Sea level rise in South Kalimantan, Indonesia—an economic analysis of adaptation strategies in agriculture. Research report, Economy and Environment Program for Southeast Asia, SingaporeGoogle Scholar
  36. State Ministry of Environment I (2007) National action plan addressing climate change. Technical report, State Ministry of Environment, JakartaGoogle Scholar
  37. Suroso DSA, Hadi TW, Latief H, Sofian I, Kasih A, Riawan E (2010) Study on patterns of vulnerability on Coastal zone of Indonesia. Report, Institute of Technology, BandungGoogle Scholar
  38. Suroso DSA, Hadi TW, Salim W (2009) Indonesia climate change sectoral roadmap ICCSR—synthesis report. Technical report, Republic of Indonesia, JakartaGoogle Scholar
  39. USDA (2010) USDA national nutrient database for standard reference. Technical report, Washington, DC. “”, last accessed: June 11, 2010
  40. Vermeer M, Rahmstorf S (2009) Global sea level linked to global temperature. Proc Natl Acad Sci USA 106(51):21527–21532CrossRefGoogle Scholar
  41. Wei Y-M, Fan Y, Lu C, Tsai H-T (2004) The assessment of vulnerability to natural disasters in China by using the DEA method. Environ Impact Assess 24:427–439CrossRefGoogle Scholar
  42. Zhou P, Ang B, Poh K (2006) Decision analysis in energy and environmental modeling: an update. Energy Convers Manag 31(14):2604–2622Google Scholar
  43. Zou L-L, Wei Y-M (2009) Impact assessment using DEA of coastal hazards on social-economy in Southeast Asia. Nat Hazards 48:167–189CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Hannah Förster
    • 1
    Email author
  • Till Sterzel
    • 1
  • Christian A. Pape
    • 1
  • Marta Moneo-Lain
    • 1
  • Insa Niemeyer
    • 1
  • Rizaldi Boer
    • 2
  • Jürgen P. Kropp
    • 1
  1. 1.Potsdam Institute for Climate Impact ResearchPotsdamGermany
  2. 2.Center for Climate Risk and Opportunity Management in Southeast Asia and Pacific (CCROM-SEAP)Bogor Agriculture UniversityJawa BaratIndonesia

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