Optimal Strategies for Inland and Coastal Water Monitoring

  • Katarina ElofssonEmail author


Despite the recognition of the eutrophication problem, Baltic-wide environmental targets for nutrient pollution reductions have not been met. Possible factors include inefficiency of environmental policy, and a lack of coordination between environmental policy and policies in other fields like agriculture and energy. The former requires improvements in the design of environmental policy while the latter calls for better coordination of different policies. This chapter reviews studies evaluating nutrient policies in the region, with a focus on economic and cross-disciplinary studies that carry out ex post evaluations of policy instruments. It also investigates optimal monitoring and abatement strategies where both upstream and downstream water quality pose a potential problem, looking at how monitoring and abatement costs, and the regulators’ degree of risk aversion, affect the choice of monitoring strategy.


Abatement strategies Water quality Monitoring system 



Funding from FORMAS under grant number 253-2007-1098 is gratefully acknowledged.


  1. Bond, C. A., & Loomis, J. B. (2009). Using numerical dynamic programming to compare passive and active learning in the adaptive management of nutrients in shallow lakes. Canadian Journal of Agricultural Economics, 57(4), 555–573.CrossRefGoogle Scholar
  2. Brouwer, R., & DeBlois, C. (2008). Integrated modelling of risk and uncertainty underlying the selection of cost-effective water quality measures. Environmental Modelling and Software, 23(7), 922–937.CrossRefGoogle Scholar
  3. Chai, C., Yu, Z. M., Song, X. X., & Cao, X. H. (2006). The status and characteristics of eutrophication in the Yangtze River (Changjiang) estuary and the adjacent East China Sea. China Hydrobiologia, 563(1), 313–328.CrossRefGoogle Scholar
  4. Chapman, D. (Ed.). (1992). Water quality assessments: A guide to use of biota, sediments and water in environmental monitoring. London: Chapman & Hall.Google Scholar
  5. Claassen, R., Cattaneo, R., & Johansson, R. (2008). Cost-effective design of agri-environmental payment programs: US experience in theory and practice. Ecological Economics, 65(4), 737–752.CrossRefGoogle Scholar
  6. Cunha-e-Sá, M. A., & Santos, V. (2008). Experimentation with accumulation. Journal of Economic Dynamics and Control, 32(2), 470–496.CrossRefGoogle Scholar
  7. Diaz, R. J., & Rosenberg, R. (2008). Spreading dead zones and consequences for marine ecosystems. Science, 321(5891), 926–929.CrossRefGoogle Scholar
  8. Elofsson, K. (2003). Cost efficient reductions of stochastic agricultural loads to the Baltic Sea. Ecological Economics, 47(1), 13–31.CrossRefGoogle Scholar
  9. Farzin, Y. H., & Kaplan, J. D. (2004). Nonpoint source pollution control under incomplete and costly information. Environmental & Resource Economics, 28(4), 489–506.CrossRefGoogle Scholar
  10. Fölster, J. (2014). Fixed and running costs in Swedish water quality monitoring. Mimeo: Swedish University of Agricultural Sciences.Google Scholar
  11. Gandelman, N., & Hernadez-Murillo, R. (2014). Risk Aversion at the Country Level, Federal Reserve Bank of St. Louis Working Paper 5.Google Scholar
  12. Gren, I.-M., Elofsson, K., & Jannke, P. (1997). Cost effective nutrient reductions to the Baltic Sea. Environmental & Resource Economics, 10(4), 341–362.CrossRefGoogle Scholar
  13. Gustafsson, B. G., Schenk, F., Blenckner, T., Eilola, K., Meier, H. E. M., Müller-Karulis, B., et al. (2012). Reconstructing the development of Baltic Sea eutrophication 1850–2006. Ambio, 41(6), 534–548.CrossRefGoogle Scholar
  14. Kampas, A., & White, B. (2004). Administrative costs and instrument choice for stochastic non-point pollution. Environmental & Resource Economics, 27(2), 109–133.CrossRefGoogle Scholar
  15. Kaplan, J. D., Howitt, R. E., & Farzin, Y. H. (2003). An information theoretical analysis of budget-constrained nonpoint source pollution control. Journal of Environmental Economics and Management, 46(1), 106–130.CrossRefGoogle Scholar
  16. Kelly, D. L., & Kolstad, C. D. (1999). Bayesian learning, growth and pollution. Journal of Economic Dynamics and Control, 23(4), 491–518.CrossRefGoogle Scholar
  17. Lovett, G. M., Burns, D. A., Driscoll, C. T., Jenkins, J. C., Mitchell, M. J., Rustad, L., et al. (2007). Who needs environmental monitoring? Frontiers in Ecology and the Environment, 5(5), 253–260.CrossRefGoogle Scholar
  18. Peterson, G. D., Carpenter, S. R., & Brock, W. A. (2003). Uncertainty and the management of multistate ecosystems: An apparently rational route to collapse. Ecology, 84(6), 1403–1411.CrossRefGoogle Scholar
  19. Rabotyagov, S. S., Kling, C. L., Gassman, P. W., Rabalais, N. N., & Turner, R. E. (2014). The economics of dead zones: Causes, impacts, policy challenges, and a model of the Gulf of Mexico hypoxic zone. Review of Environmental Economics and Policy, 8(1), 58–79.CrossRefGoogle Scholar
  20. Ribaudo, M. O., Horan, R. D., & Smith, M. E. (1999). Economics of water quality protection from nonpoint sources: Theory and practice. Agricultural Economic Report 782. Washington DC: Economic Research Service, US Department of Agriculture.Google Scholar
  21. Smith, V. H. (2003). Eutrophication of freshwater and coastal marine ecosystems: A global problem. Environmental Science and Pollution Research, 10(2), 1–14.CrossRefGoogle Scholar
  22. Strobl, R. O., & Robillard, P. D. (2008). Network design for water quality monitoring of surface freshwaters: A review. Journal of Environmental Management, 87(4), 639–648.CrossRefGoogle Scholar
  23. White, B. (2005). An economic analysis of ecological monitoring. Ecological Modelling, 189(3–4), 241–250.CrossRefGoogle Scholar
  24. World Meteorological Organization. (2013). Planning of water-quality monitoring systems. Technical Report Series No. 3. WMO-No. 1113, World Meteorological Organization. Accessed February 10, 2016.

Copyright information

© The Author(s) 2017

Authors and Affiliations

  1. 1.Department of EconomicsSwedish University of Agricultural SciencesUppsalaSweden

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