Climatic Change

, Volume 124, Issue 1–2, pp 271–284 | Cite as

Optimal water depth management on river-fed National Wildlife Refuges in a changing climate

  • Sam NicolEmail author
  • Brad Griffith
  • Jane Austin
  • Christine M. Hunter


The prairie pothole region (PPR) in the north-central United States and south-central Canada constitutes the most important waterfowl breeding area in North America. Projected long-term changes in precipitation and temperature may alter the drivers of waterfowl abundance: wetland availability and emergent vegetation cover. Previous studies have focused on isolated wetland dynamics, but the implications of changing precipitation on managed, river-fed wetlands have not been addressed. Using a structured decision making (SDM) approach, we derived optimal water management actions for 20 years at four river-fed National Wildlife Refuges (NWRs) in North and South Dakota under contrasting increasing/decreasing (+/−0.4 %/year) inflow scenarios derived from empirical trends. Refuge pool depth is manipulated by control structures. Optimal management involves setting control structure heights that have the highest probability of providing a desired mix of waterfowl habitat, given refuge capacities and inflows. We found optimal seasonal control structure heights for each refuge were essentially the same under increasing and decreasing inflow trends of 0.4 %/year over the next 20 years. Results suggest managed pools in the NWRs receive large inflows relative to their capacities. Hence, water availability does not constrain management; pool bathymetry and management tactics can be greater constraints on attaining management objectives than climate-mediated inflow. We present time-dependent optimal seasonal control structure heights for each refuge, which are resilient to the non-stationary precipitation scenarios we examined. Managers can use this information to provide a desired mixture of wildlife habitats, and to re-assess management objectives in reserves where pool bathymetry prevents attaining the currently stated objectives.


Vegetation Density Emergent Vegetation Stochastic Dynamic Programming Prairie Pothole Region Pool Depth 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



National wildlife refuge


Prairie pothole region


Structured decision making


Stochastic dynamic programming



The authors thank the staff of Arrowwood, Lacreek, Sand Lake and Tewaukon NWRs. The authors also thank Julien Martin and Jennifer Roach for their constructive comments. Funding was provided by the U.S. Fish and Wildlife Service and the U.S. Geological Survey. The use of trade names or products does not constitute endorsement by the U.S. Government.

Supplementary material

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  1. Ades A, Lu G, Claxton K (2004) Expected value of sample information calculations in medical decision modeling. Med Decis Mak 24:207–227CrossRefGoogle Scholar
  2. Bellman R (1957) Dynamic programming. Princeton University Press, PrincetonGoogle Scholar
  3. Bruce J, Martin H, Colucci P, McBean G, McDougall J, Shrubsole D, Whalley J, Halliday R (2003) Climate change impacts on boundary and transboundary water management. Final report. Climate change action fund project A458/402. Natural Resources Canada, Ottawa, OntarioGoogle Scholar
  4. Conroy MJ, Runge MC, Nichols JD, Stodola KW, Cooper RJ (2011) Conservation in the face of climate change: the roles of alternative models, monitoring, and adaptation in confronting and reducing uncertainty. Biol Conserv 144:1204–1213CrossRefGoogle Scholar
  5. Covich AP, Fritz SC, Lamb PJ, Marzolf RD, Matthews WJ, Poiani KA, Prepas EE, Richman MB, Winter TC (1997) Potential effects of climate change on aquatic ecosystems of the great plains of North America. Hydrol Process 11:993–1021CrossRefGoogle Scholar
  6. Eisenlohr W (1972) Hydrologic investigations of prairie potholes in North Dakota, 1959–68. US Geological Survey Professional Paper 585-AGoogle Scholar
  7. Fredrickson L, Taylor T (1982) Management of seasonally flooded impoundments for wildlife. US Fish and Wildlife Service Resource Publication 148Google Scholar
  8. Gregory R, Failing L, Harnstone M, Long G, McDaniels T, Ohlson D (2012) Structured decision making: a practical guide to environmental management choices. John Wiley and Sons, ChichesterCrossRefGoogle Scholar
  9. Johnson F, Moore C, Kendall W, Dubovsky J, Caithamer D, Kelley J, Williams B (1997) Uncertainty and the management of mallard harvests. J Wildl Manag 61:202–216CrossRefGoogle Scholar
  10. Johnson WC, Millett BV, Gilmanov T, Voldseth RA, Guntenspergen GR, Naugle DE (2005) Vulnerability of Northern Prairie wetlands to climate change. Bioscience 55:863–872CrossRefGoogle Scholar
  11. Lamond B, Boukhtouta A (1996) Optimizing long-term hydro power production using Markov decision processes. Int Trans Oper Res 3:223–241CrossRefGoogle Scholar
  12. Larson DL (1995) Effects of climate on numbers of northern prairie wetlands. Clim Chang 30:169–180CrossRefGoogle Scholar
  13. Lempert R, Groves D (2010) Identifying and evaluating robust adaptive policy responses to climate change for water management agencies in the American West. Technol Forecast Soc Chang 77:960–974CrossRefGoogle Scholar
  14. Martin J, Fackler P, Nichols J, Lubow B, Eaton M, Runge M, Stith B, Langtimm C (2011) Structured decision making as a proactive approach to dealing with sea level rise in Florida. Clim Chang 107:185–202CrossRefGoogle Scholar
  15. Menne M, Williams C, Vose R (2011) United States historical climatology network. Accessed: 2nd November 2011
  16. Millett B, Johnson WC, Guntenspergen G (2009) Climate trends of the North American prairie pothole region 1906–2000. Clim Chang 93:243–267CrossRefGoogle Scholar
  17. Nichols JD, Koneff MD, Heglund PJ, Knutson MG, Seamans ME, Lyons JE, Morton JM, Jones MT, Boomer GS, Williams BK (2011) Climate change, uncertainty, and natural resource management. J Wildl Manag 75:6–18CrossRefGoogle Scholar
  18. NOAA (2011) Calculated evaporation climatology: national oceanic and atmospheric administration national weather service. Accessed: 3rd January 2012
  19. Pinheiro J, Bates D (2000) Mixed-effects models in S and S-PLUS. Springer-Verlag, New YorkCrossRefGoogle Scholar
  20. Poiani KA, Johnson WC (1993) Potential effects of climate change on a semi-permanent prairie wetland. Clim Chang 24:213–232CrossRefGoogle Scholar
  21. Poiani KA, Johnson WC, Kittel TGF (1995) Sensitivity of a prairie wetland to increased temperature and seasonal precipitation changes. JAWRA J Am Water Resour Assoc 31:283–294CrossRefGoogle Scholar
  22. Puterman M (2005) Markov decision processes: discrete stochastic dynamic Programming. Wiley-InterscienceGoogle Scholar
  23. R Development Core Team (2011) R: A language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  24. Runge M, Converse S, Lyons J (2011) Which uncertainty? Using expert elicitation and expected value of information to design an adaptive program. Biol Conserv 144:1214–1223CrossRefGoogle Scholar
  25. Solomon S, Qin D, Manning M, Alley R, Berntsen T, Bindoff N, Chen Z, Chidthaisong C, Gregory J, Hegerl G, Heimann M, Hewitson B, Hoskins B, Joos F, Jouzel J, Kattsov V, Lohmann U, Matsuno T, Molina M, Nicholls N, Overpeck J, Raga G, Ramaswamy V, Ren J, Rusticucci M, Somerville R, Stocker T, Whetton P, Wood RA, Wratt D (2007) Technical summary. 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, United Kingdom and New York, NY, USAGoogle Scholar
  26. Sorenson LG, Goldberg R, Root TL, Anderson MG (1998) Potential effects of global warming on waterfowl populations breeding in the Northern Great Plains. Clim Chang 40:343–369CrossRefGoogle Scholar
  27. Tanaka S, Zhu T, Lund J, Howitt R, Jenkins M, Pulido M, Tauber M, Ritzema R, Ferreira I (2006) Climate warming and water management adaptation for California. Clim Chang 76:361–387CrossRefGoogle Scholar
  28. US Fish and Wildlife Service (2000) Tewaukon National Wildlife Refuge Comprehensive Conservation PlanGoogle Scholar
  29. US Fish and Wildlife Service (2005) Sand Lake National Wildlife Refuge Comprehensive Conservation PlanGoogle Scholar
  30. US Fish and Wildlife Service (2006) Lacreek National Wildlife Refuge Comprehensive Conservation PlanGoogle Scholar
  31. US Fish and Wildlife Service (2007) Arrowwood National Wildlife Refuge Comprehensive Conservation PlanGoogle Scholar
  32. Weller M (1978) Management of freshwater marshes for wildlife. In: Good R, Whigham D, Simpson R (eds) Freshwater wetlands: ecological processes and management potential. Academic Press, New York, pp 267–284Google Scholar
  33. Winter TC, Rosenberry DO (1998) Hydrology of prairie pothole wetlands during drought and deluge: a 17-year study of the cottonwood lake wetland complex in North Dakota in the perspective of longer term measured and proxy hydrological records. Clim Chang 40:189–209CrossRefGoogle Scholar
  34. Yang W (2011) A multi-objective optimization approach to allocate environmental flows to the artificially restored wetlands of China’s Yellow River delta. Ecol Model 222:261–267CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht (except in the USA) 2014

Authors and Affiliations

  • Sam Nicol
    • 1
    • 4
    Email author
  • Brad Griffith
    • 1
    • 2
  • Jane Austin
    • 3
  • Christine M. Hunter
    • 1
  1. 1.Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksUSA
  2. 2.U.S. Geological Survey, Alaska Cooperative Fish and Wildlife Research UnitFairbanksUSA
  3. 3.U.S. Geological SurveyNorthern Prairie Wildlife Research CenterJamestownUSA
  4. 4.CSIRO Ecosystem SciencesBrisbaneAustralia

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