Climatic Change

, Volume 147, Issue 3–4, pp 647–662 | Cite as

Sensitivity to climate change of land use and management patterns optimized for efficient mitigation of nutrient pollution

Article

Abstract

Beginning in the mid-1990s, re-eutrophication has reemerged as severe problems in Lake Erie. Controlling non-point source (NPS) nutrient pollution from cropland, especially dissolved reactive phosphorus (DRP), is the key to restore water quality in Lake Erie. To address NPS pollution, previous studies have analyzed the effectiveness of alternative spatially optimal land use and management strategies (represented as agricultural conservation practices (CPs)). However, few studies considered both strategies and have analyzed and compared their sensitivity to expected changes in temperature and precipitation due to climate change and increased greenhouse gas concentrations. In this study, we evaluated impacts of climatic change on the economic efficiency of these strategies for DRP abatement, using an integrated modeling approach that includes a watershed model, an economic valuation component, and a spatial optimization model. A series of climate projections representing relatively high greenhouse gas emission scenarios was developed for the western Lake Erie basin to drive the watershed model. We found that performance of solutions optimized for current climate was degraded significantly under projected future climate conditions. In terms of robustness of individual strategies, CPs alone were more robust to climate change than land use change alone or together with CPs, but relying on CPs alone fails to achieve a high (> 71%) DRP reduction target. A combination of CPs and land use changes was required to achieve policy goals for DRP reductions (targeted at ~ 78%). Our results point to the need for future spatial optimization studies and planning to consider adaptive capacity of conservation actions under a changing climate.

Supplementary material

10584_2018_2159_MOESM1_ESM.docx (38.9 mb)
ESM 1 (DOCX 39877 kb)

References

  1. Andresen J, Hilberg S, Kunkel K (2012) Historical climate and climate trends in the midwestern USA. In: U.S. national climate assessment midwest technical input report. J. Winkler, J. Andresen, J. Hatfield, D. Bidwell, and D. Brown, coordinators. Available from the Great Lakes Integrated Sciencesand Assessments (GLISA) Center, http://glisa.msu.edu/docs/NCA/MTIT_Historical.pdf
  2. Arabi M, Govindaraju RS, Hantush MM (2006) Cost-effective allocation of watershed management practices using a genetic algorithm. Water Resour Res 42, W10429.  https://doi.org/10.1029/2006WR004931
  3. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34:73–89CrossRefGoogle Scholar
  4. Arnold JG, Gassman PW, White MJ (2010) New developments in the SWAT ecohydrology model. In: 21st Century Watershed Technology: Improving Water Quality and Environment. Universidad EARTH, Costa Rica. ASABE, St. Joseph, pp 21–24Google Scholar
  5. Basile SJS., Rauscher SASA, Steiner AL (2017) Projected precipitation changes within the Great Lakes and Western Lake Erie Basin: a multi-model analysis of intensity and seasonality. Int J Climatol 37:4864–4879.  https://doi.org/10.1002/joc.512
  6. Bosch NS, Evans MA, Scavia D, Allan JD (2014) Interacting effects of climate change and agricultural BMPs on nutrient runoff entering Lake Erie. J Great Lakes Res 40:581–589CrossRefGoogle Scholar
  7. Bryan AM, Steiner AL, Posselt DJ (2015) Regional modeling of surface-atmosphere interactions and their impact on Great Lakes hydroclimate. J Geophys Res Atmos 120:1044–1064CrossRefGoogle Scholar
  8. Burkett VR, Suarez AG, Bindi M et al (2014) Point of departure. In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea TEB MD, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy SM AN, Mastrandrea PR, LLW (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 169–194Google Scholar
  9. Carpenter SR, Stanley EH, Vander Zanden MJ (2011) State of the world’s freshwater ecosystems: physical, chemical, and biological changes. Annu Rev Environ Resour 36:75–99CrossRefGoogle Scholar
  10. Fourer R, Gay DM, Kernighan BW (1990) Modeling language for mathematical programming. Manage Sci 36:519–554.  https://doi.org/10.1287/mnsc.36.5.519
  11. Gassman PW, Reyes MR, Green CH, Arnold JG (2007) The soil and water assessment tool: historical development, applications, and future research directions. Trans ASABE 50:1211–1250CrossRefGoogle Scholar
  12. International Joint Commission (IJC) (2014) A balanced diet for Lake Erie: reducing phosphorus loadings and harmful algal blooms. Report of the Lake Erie Ecosystem Priority. http://www.ijc.org/files/publications/2014%20IJC%20LEEP%20REPORT.pdf
  13. IPCC-TGICA (2007) General guidelines on the use of scenario data for climate impact and adaptation assessment. Finnish Environ Inst 312:66Google Scholar
  14. Jin S, Yang L, Danielson P et al (2013) A comprehensive change detection method for updating the national land cover database to circa 2011. Remote Sens Environ 132:159–175CrossRefGoogle Scholar
  15. Johnston CA, Shmagin BA (2008) Regionalization, seasonality, and trends of streamflow in the US Great Lakes Basin. J Hydrol 362:69–88CrossRefGoogle Scholar
  16. Johnston RZ, Sandefur HN, Bandekar P et al (2015) Predicting changes in yield and water use in the production of corn in the United States under climate change scenarios. Ecol Eng 82:555–565CrossRefGoogle Scholar
  17. Kalcic MM, Frankenberger J, Chaubey I (2015) Spatial optimization of six conservation practices using Swat in tile-drained agricultural watersheds. JAWRA J Am Water Resour Assoc 51:956–972CrossRefGoogle Scholar
  18. Körner C, Morgan J, Norby R (2007) CO2 fertilization: when, where, how much? In: Canadell JG, Pataki DE, PLF (eds) Terrestrial ecosystems in a changing world—the IGBP series. Springer, Berlin, pp 9–21CrossRefGoogle Scholar
  19. Lobell DB, Burke MB (2008) Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation. Environ Res Lett 3:34007CrossRefGoogle Scholar
  20. Maringanti C, Chaubey I, Arabi M, Engel B (2011) Application of a multi-objective optimization method to provide least cost alternatives for NPS pollution control. Environ Manag 48:448–461CrossRefGoogle Scholar
  21. Mearns LO, Arritt R, Biner S et al (2012) The North American regional climate change assessment program overview of phase I results. Bull Am Meteorol Soc 93:1337–1362CrossRefGoogle Scholar
  22. Meehl GA, Goddard L, Murphy J et al (2009) Decadal prediction: can it be skillful? Bull Am Meteorol Soc 90:1467–1485CrossRefGoogle Scholar
  23. Mehaffey M, Smith E, Van Remortel R (2012) Midwest U.S. landscape change to 2020 driven by biofuel mandates. Ecol Appl 22:8–19.  https://doi.org/10.1890/10-1573.1
  24. Nelson E, Polasky S, Lewis DJ et al (2008) Efficiency of incentives to jointly increase carbon sequestration and species conservation on a landscape. Proc Natl Acad Sci U S A 105:9471–9476CrossRefGoogle Scholar
  25. NRC (National Research Council) (2009) Nutrient control actions for improving water quality in the Mississippi River basin and northern Gulf of Mexico. National Academies Press, Washington, D.C.Google Scholar
  26. Osmond D, Meals D, Hoag D et al (2012) Improving conservation practices programming to protect water quality in agricultural watersheds: lessons learned from the National Institute of Food and Agriculture—conservation effects assessment project. J Soil Water Conserv 67:122A–127ACrossRefGoogle Scholar
  27. Paerl HW, Paul VJ (2012) Climate change: links to global expansion of harmful cyanobacteria. Water Res 46:1349–1363CrossRefGoogle Scholar
  28. Polasky S, Nelson E, Camm J et al (2008) Where to put things? Spatial land management to sustain biodiversity and economic returns. Biol Conserv 141:1505–1524CrossRefGoogle Scholar
  29. Rabotyagov SS, Campbell TD, White M et al (2014) Cost-effective targeting of conservation investments to reduce the northern Gulf of Mexico hypoxic zone. Proc Natl Acad Sci 111:18530–18535CrossRefGoogle Scholar
  30. Scavia D, David Allan J, Arend KK et al (2014) Assessing and addressing the re-eutrophication of Lake Erie: central basin hypoxia. J Great Lakes Res 40:226–246CrossRefGoogle Scholar
  31. Shrestha RR, Dibike YB, Prowse TD (2012) Modeling climate change impacts on hydrology and nutrient loading in the upper Assiniboine catchment. JAWRA J Am Water Resour Assoc 48:74–89CrossRefGoogle Scholar
  32. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498CrossRefGoogle Scholar
  33. Tomer MD, Porter SA, James DE et al (2013) Combining precision conservation technologies into a flexible framework to facilitate agricultural watershed planning. J Soil Water Conserv 68:113A–120ACrossRefGoogle Scholar
  34. USDA NASS (2015) Quick stats. https://quickstats.nass.usda.gov/
  35. USDA NASS (2016) Cropland data layer. https://nassgeodata.gmu.edu/CropScape/
  36. USDA NRCS (2015) Soil Survey Geographic (SSURGO) Database. http://soildatamart.nrcs.usda.gov
  37. Williams JR (1995) The EPIC Model in Computer Models of Watershed Hydrology, Chapter 25. Water Resources Publications, Highlands Ranch pp 909–1000Google Scholar
  38. Woznicki SA, Nejadhashemi AP (2012) Sensitivity analysis of best management practices under climate change scenarios1. JAWRA J Am Water Resour Assoc 48:90–112CrossRefGoogle Scholar
  39. Xu H, Brown DG, Moore MR, Currie WS (2018) Optimizing spatial land management to balance water quality and economic returns in a Lake Erie watershed. Ecol Econ 145:104–114CrossRefGoogle Scholar
  40. Yang Q, Zhang X (2016) Improving SWAT for simulating water and carbon fluxes of forest ecosystems. Sci Total Environ 569–570:1478–1488CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.School for Environment and SustainabilityUniversity of MichiganAnn ArborUSA
  2. 2.Energy Systems DivisionArgonne National LaboratoryLemontUSA
  3. 3.School of Environmental and Forest SciencesUniversity of WashingtonSeattleUSA
  4. 4.Department of Climate and Space Science and EngineeringUniversity of MichiganAnn ArborUSA

Personalised recommendations