Advertisement

Environmental Management

, Volume 58, Issue 3, pp 365–385 | Cite as

Organizing Environmental Flow Frameworks to Meet Hydropower Mitigation Needs

  • Ryan A. McManamay
  • Shannon K. Brewer
  • Henriette I. Jager
  • Matthew J. Troia
Article
  • 510 Downloads

Abstract

The global recognition of the importance of natural flow regimes to sustain the ecological integrity of river systems has led to increased societal pressure on the hydropower industry to change plant operations to improve downstream aquatic ecosystems. However, a complete reinstatement of natural flow regimes is often unrealistic when balancing water needs for ecosystems, energy production, and other human uses. Thus, stakeholders must identify a prioritized subset of flow prescriptions that meet ecological objectives in light of realistic constraints. Yet, isolating aspects of flow regimes to restore downstream of hydropower facilities is among the greatest challenges of environmental flow science due, in part, to the sheer volume of available environmental flow tools in conjunction with complex negotiation-based regulatory procedures. Herein, we propose an organizational framework that structures information and existing flow paradigms into a staged process that assists stakeholders in implementing environmental flows for hydropower facilities. The framework identifies areas where regulations fall short of the needed scientific process, and provide suggestions for stakeholders to ameliorate those situations through advanced preparation. We highlight the strengths of existing flow paradigms in their application to hydropower settings and suggest when and where tools are most applicable. Our suggested framework increases the effectiveness and efficiency of the e-flow implementation process by rapidly establishing a knowledge base and decreasing uncertainty so more time can be devoted to filling knowledge gaps. Lastly, the framework provides the structure for a coordinated research agenda to further the science of environmental flows related to hydropower environments.

Keywords

Dams Rivers Regulation Policy Environmental flow Hydrology 

Notes

Acknowledgments

This research was sponsored by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy, Wind and Water Power Technologies Program. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the US Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank Colin Shea, Kevin Whalen, and three anonymous reviewers for providing comments and editorial suggestions on earlier versions of this manuscript.

Supplementary material

267_2016_726_MOESM1_ESM.docx (24 kb)
Supplementary material 1 (DOCX 24 kb)

References

  1. Anderson KE, Paul AJ, McCauley E, Jackson LJ, Post JR, Nisbet RM (2006) Instream flow needs in streams and rivers: the importance of understanding ecological dynamics. Front Ecol Environ 4:309–318CrossRefGoogle Scholar
  2. Annear T, Chisholm I, Beecher H, Locke A, et al (2004) Instream flows for riverine resource stewardship, revised edition. Instream Flow Council, CheyenneGoogle Scholar
  3. Arthington AH, Bunn SE, Poff NL, Naiman RJ (2006) The challenge of providing e-flow rules to sustain river systems. Ecol Appl 16:1311–1318CrossRefGoogle Scholar
  4. Bailey RG (1983) Delineation of ecosystem regions. Environ Manag 7:365–373CrossRefGoogle Scholar
  5. Bednarek AT, Hart DD (2005) Modifying dam operations to restore rivers ecological responses to Tennessee River dam mitigation. Ecol Appl 15:997–1008CrossRefGoogle Scholar
  6. Bevelhimer MS, McManamay RA, O’Connor B (2014) Characterizing sub-daily flow regimes: implications of hydrologic resolution on ecohydrology studies. River Res Appl. doi: 10.1002/rra.2781 Google Scholar
  7. Bovee KD, Lamb BL, Bartholow JM, Stalnaker CB, Taylor J, Henriksen J (1998) Stream habitat analysis using the instream flow incremental methodology. U.S. Geological Survey Information and Technology Report 1998-0004. Reston, VAGoogle Scholar
  8. Carlisle DM, Wolock DM, Meador MR (2011) Alteration of streamflow magnitudes and potential ecological consequences: a multiregional assessment. Front Ecol Environ 9:264–270CrossRefGoogle Scholar
  9. Chan TU, Hart BT, Kennard MJ, Pusey BJ, Shenton W, Douglas MM, Valentine E, Patel S (2012) Bayesian network models for environmental flow decision making In the Daly River, northern territory, Australia. River Res Appl 28:283–301CrossRefGoogle Scholar
  10. Cushman RM (1985) Review of ecological effects of rapidly varying flows downstream from hydroelectric facilities. N Am J Fish Manag 5:330–339CrossRefGoogle Scholar
  11. Esselman PC, Infante DM, Wang L, Wu D, Cooper AR, Taylor WW (2011) An index of cumulative disturbance to river fish habitats of the conterminous United States from landscape anthropogenic activities. Ecol Restor 29:133–151CrossRefGoogle Scholar
  12. FERC (Federal Energy Regulatory Commission) (2007) Final Environmental Impact Statement (FEIS) evaluates relicensing of the 1167-megawatt Hells Canyon Hydroelectric Project (P-1971-079) in Idaho and Oregon. Issued: August 31, 2007. https://www.ferc.gov/industries/hydropower/enviro/eis/2007/08-31-07.asp Accessed 20 July 2013
  13. FERC (Federal Energy Regulatory Commission) (2015) Licensing processes. http://www.ferc.gov/industries/hydropower/gen-info/licensing/licen-pro.asp. Accessed 12 Aug 2015
  14. Flinders CA, Hart DD (2009) Effects of pulsed flows on nuisance periphyton growths in rivers: a mesocosm study. River Res Appl 1330:1320–1330CrossRefGoogle Scholar
  15. Haas NA, O’Connor BL, Hayse JW, Bevelhimer MS, Endreny TA (2014) Analysis of daily-peaking and run-of-river dam operations on flow variability metrics considering subdaily to seasonal time scales. J Am Water Res Assoc 50:1622–1640CrossRefGoogle Scholar
  16. Han M, Fukushima M, Kameyama S, Fukushima T, Matsushita B (2008) How do dams affect freshwater fish distributions in Japan? Statistical analysis of native and nonnative species with various life histories. Ecol Res 23:735–743CrossRefGoogle Scholar
  17. Hart BT, Pollino CA (2009) Bayesian modelling for risk-based environmental water allocation, Waterlines Report Series No 14. National Water Commission:Canberra. http://archive.nwc.gov.au/library/waterlines/14, Accessed 12 Sep 2015
  18. Hartwig JJ (1998) Recreational use, social and economic characteristics of the Smith River and Philpott Reservoir fisheries, Virginia. MS thesis, Virignia Polytechnic Institute and State University, Blackburg, VAGoogle Scholar
  19. Jackson CR, Pringle CM (2010) Ecological benefits of reduced hydrologic connectivity in intensively developed landscapes. BioScience 60:37–46CrossRefGoogle Scholar
  20. Jager HI (2014) Thinking outside the channel: timing pulse flows to benefit salmon via indirect pathways. Ecol Model 273:117–127CrossRefGoogle Scholar
  21. Jager HI, Bevelhimer MS (2007) How run-of-river operation affects hydropower generation. Environ Manag 40:1004–1015CrossRefGoogle Scholar
  22. Jager HI, Uria-Martinez R (2012) Optimizing river flows for salmon and energy. Oak Ridge National Laboratory, ORNL/TM-2012/500, Oak Ridge, TN, USA, p 24Google Scholar
  23. Kendy E, Apse C, Blann K (2012) A practical guide to environmental flows for policy and planning with nine case studies in the United States. The Nature Conservancy. http://conserveonline.org/workspaces/eloha/documents/template-kyle. Accessed 18 July 2012
  24. Kennen JG, Kauffman LJ, Ayers MA, Wolock DM, Colarullo SJ (2008) Use of an integrated flow model to estimate ecologically relevant hydrologic characteristics at stream biomonitoring sites. Ecol Model 211:57–76CrossRefGoogle Scholar
  25. King J, Louw D (1998) Instream flow assessments for regulated rivers in South Africa using the building block methodology. Aquat Ecosyst Health Manage 1:109–124Google Scholar
  26. King J, Brown C, Sabet H (2003) A scenario-based holistic approach to environmental flow assessment for rivers. Riv Res Appl 19:619–639CrossRefGoogle Scholar
  27. Knight RR, Gregory MB, Wales AK (2008) Relating streamflow characteristics to specialized insectivores in the Tennessee River valley: a regional approach. Ecohydrology 1:394–407CrossRefGoogle Scholar
  28. Kondolf GM (1997) Hungry water: effects of dams and gravel mining on river channels. Environ Manag 21:533–551CrossRefGoogle Scholar
  29. Konrad CP, Olden JD, Lytle DA et al (2011) Large-scale flow experiments for managing river systems. BioScience 61:948–959CrossRefGoogle Scholar
  30. Korb KB, Nicholson AE (2004) Bayesian Artificial Intelligence. Chapman and Hall CRC Press, LondonGoogle Scholar
  31. Krause CW, Newcomb TJ, Orth D (2005) Thermal habitat assessment of alternative flow scenarios in a tailwater fishery. River Res Appl 21:581–593CrossRefGoogle Scholar
  32. Lamouroux N, Olivier JM, Capra H, Zylberblat M, Chandesris A, Roger P (2006) Fish community changes after minimum flow increase: testing quantitative predictions in the Rhone River at Pierre-Benite, France. Freshw Biol 51:1730–1743CrossRefGoogle Scholar
  33. Landuyt D, Broekx S, D’hondt R et al (2013) A review of Bayesian belief networks in ecosystem service modelling. Environ Model Softw 46:1–11CrossRefGoogle Scholar
  34. Layman SR, Springer FE, Moore DM (2006) Selecting a licensing process: which approach is best for your project? Hydro Rev 25:26–33Google Scholar
  35. Lessard JL, Hicks DM, Snelder TH, Arscott DB, Larned ST, Booker D, Suren AM (2013) Dam design can impede adaptive management of environmental flows: a case study from the Opuha Dam, New Zealand. Environ Manag 51:459–473CrossRefGoogle Scholar
  36. Liermann CAR, Olden JD, Beechie TJ, Kennard MJ, Skidmore PB, Konrad CP, Imaki H (2012) Hydrogeomorphic classification of Washington state rivers to support emerging e-flow management strategies. River Res Appl 28:1340–1775CrossRefGoogle Scholar
  37. McCargo J, Peterson J (2010) An evaluation of the influence of seasonal base flow and geomorphic stream characteristics on Coastal Plain stream fish assemblages. Trans Am Fish Soc 139:29–48CrossRefGoogle Scholar
  38. McCartney M (2009) Living with dams: managing the environmental impacts. Water Policy 11:121–139CrossRefGoogle Scholar
  39. McManamay RA (2014) Quantifying and generalizing hydrologic responses to dam regulation using a statistical modeling approach. J Hydrol 519:1278–1296CrossRefGoogle Scholar
  40. McManamay RA, Orth DJ, Dolloff CA, Mathews DC (2013a) Application of the ELOHA framework to regulated rivers in the Upper Tennessee River basin. Environ Manag 51:1210–1235CrossRefGoogle Scholar
  41. McManamay RA, Orth DJ, Kauffman J, Davis MM (2013b) A database and meta-analysis of ecological responses to stream flow in the South Atlantic region. Southeast Nat 12:1–36CrossRefGoogle Scholar
  42. McManamay RA, Oigbokie CO, Kao S-C, Bevelhimer MS (2016) A classification of US hydropower dams by their modes of operation. River Res Appl. doi: 10.1002/rra.3004
  43. McManamay RA, Peoples BK, Orth DJ, Dollof CA, Matthews DC (2015) Isolating causal pathways between flow and fish in the regulated river hierarchy. Can J Fish Aquat Sci. doi: 10.1139/cjfas-2015-0227 Google Scholar
  44. Meile T, Boillat JL, Schleiss A (2011) Hydropeaking indicators for characterization of the Upper-Rhone River in Switzerland. Aquat Sci 73:171–182CrossRefGoogle Scholar
  45. Moir HJ, Gibbins CN, Soulsby C, Youngson AF (2005) PHABSIM modelling of Atlantic salmon spawning habitat in an upland stream: testing the influence of habitat suitability indices on model output. River Res Appl 21:1021–1034CrossRefGoogle Scholar
  46. Mount J, Moyle PB, Lund J, Doremus H (2007) Regional Agreements, adaptation, and climate change: New approaches to FERC Licensing in the Sierra Nevada. University of California Davis Center for Watershed Sciences. Project Report. August 2007. https://watershed.ucdavis.edu/library/regional-agreements-adaptation-and-climate-change-new-approaches-ferc-licensing-sierra. Accessed 1 May 2016
  47. Nislow KH, Magilligan FJ, Fassnacht H, Bechtel D, Ruesink A (2002) Effects of dam impoundment on the flood regime of natural floodplain communities in the upper Connecticut River. J Am Water Resour Assoc 38:1533–1548CrossRefGoogle Scholar
  48. Norris RH, Webb JA, Nichols SJ, Stewardson MJ, Harrison ET (2012) Analyzing cause and effect in environmental assessments: using weighted evidence from the literature. Freshw Sci 31:5–21CrossRefGoogle Scholar
  49. Olden JD, Naiman RJ (2010) Incorporating thermal regimes into e-flows assessments: modifying dam operations to restore freshwater ecosystem integrity. Freshw Biol 55:86–107CrossRefGoogle Scholar
  50. Olden JD, Poff NL (2003) Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River Res Appl 19:101–121CrossRefGoogle Scholar
  51. Olivero AP, Anderson MG (2008) Northeast aquatic habitat classification system. The Nature Conservancy, Eastern Regional Office, Boston, MA. http://southeastaquatics.net/resources/sifnresources/documents/general-sarp-instream-flow-resources/northeast-aquatic-habitat-classification/northeast-aquatic-habitat-classification. Accessed 22 June 2016
  52. Poff NL, Hart DD (2002) How dams vary and why it matters for the emerging science of dam removal. BioScience 52:659–738CrossRefGoogle Scholar
  53. Poff NL, Zimmerman JZH (2010) Ecological responses to altered flow regimes: a literature review to inform the science and management of e-flows. Freshw Biol 55:194–205CrossRefGoogle Scholar
  54. Poff NL, Allan JD, Bain MB, Karr JR, Prestegaard KL, Richter BD, Sparks RE, Stromberg JC (1997) The natural flow regime: a paradigm for river conservation and restoration. BioScience 47:769–784CrossRefGoogle Scholar
  55. Poff NL, Richter BD, Arthington AH, Bunn SE, Naiman RJ et al (2010) The ecological limits of hydrologic alteration (ELOHA): a new framework for developing regional e-flow standards. Freshw Biol 55:147–170CrossRefGoogle Scholar
  56. Propst DL, Gido KB (2004) Responses of native and nonnative fishes to natural flow regime mimicry in the San Juan River. Trans Am Fish Soc 133:922–931CrossRefGoogle Scholar
  57. Reid SM, Mandrak NE, Carl LM, Wilson CC (2008) Influence of dams and habitat condition on the distribution of redhorse (Moxostoma) species in the Grand River watershed, Ontario. Environ Biol Fish 81:111–125CrossRefGoogle Scholar
  58. Richhter BD, Baumgartner JV, Powell J, Braun DP (1996) A method for assessing hydrologic alteration within ecosystems. Conserv Biol 10:1163–1174CrossRefGoogle Scholar
  59. Richhter BD, Baumgartner JV, Wigington R, Braun DP (1997) How much water does a river need? Freshw Biol 37:231–249CrossRefGoogle Scholar
  60. Richter BD (2010) Re-thinking environmental flows: from allocations and reserves to sustainability boundaries. River Res Appl 26:1052–1063Google Scholar
  61. Richter BD, Warner AT, Meyer JL, Lutz K (2006) A collaborative and adaptive process for developing e-flow recommendations. River Res Appl 22:297–318CrossRefGoogle Scholar
  62. Richter DB, Davis MM, Apse C, Konrad C (2012) A presumptive standard for e-flow protection. River Res Appl 28:1312–1321CrossRefGoogle Scholar
  63. Rolls RJ, Arthington AH (2014) How do low magnitudes of hydrologic alteration impact riverine fish populations and assemblage characteristics? Ecol Indic 39:179–188CrossRefGoogle Scholar
  64. Roni P, Beechie TJ, Bilby RE, Leonetti FE, Pollock MM, Pess GR (2002) A review of stream restoration techniques and a hierarchical strategy for prioritizing restoration in Pacific northwest watersheds. N Am J Fish Manag 22:1–20CrossRefGoogle Scholar
  65. Roni P, Hanson K, Beechie T (2008) Global review of the physical and biological effectiveness of stream habitat rehabilitation techniques. N Am J Fish Manag 28:856–890CrossRefGoogle Scholar
  66. Rosgen DL (1994) A classification of natural rivers. Catena 22:169–199CrossRefGoogle Scholar
  67. Shea CP, Bettoli PW, Potoka KM, Saylor CF, Shute PW (2015) Use of dynamic occupancy models to assess the response of darters (Teleostei: percidae) to varying hydrothermal conditions in a Southeastern United States tailwater. River Res Appl 31:676–691CrossRefGoogle Scholar
  68. Shenton W, Hart BT, Chan TU (2013) A Bayesian network approach to support environmental flow restoration decisions in the Yarra River, Australia. Stoch Environ Res Risk Assess 28:57–65CrossRefGoogle Scholar
  69. Shresha BP, Duckstein I, Stakhi EA (1996) Fuzzy rule-based modelling of reservoir operation. J Water Resour Plan Manage 122:262–269CrossRefGoogle Scholar
  70. Stalnaker, C., B.L. Lamb, J. Henriksen, K. Bovee, and J. Barthalow (1995) The instream flow incremental methodology: a primer for IFIM. National Biological Service Biological Report 29, Fort Collins, COGoogle Scholar
  71. Stedinger JR, Sule BF, Loucks DP (1985) Stochastic dynamic programming models for reservoir operation optimization. Water Resour Res 20:1499–1505CrossRefGoogle Scholar
  72. Stewart-Koster B, Bunn SE, Mackay SJ et al (2010) The use of Bayesian networks to guide investments in flow and catchment restoration for impaired river ecosystems. Freshw Biol 55:243–260CrossRefGoogle Scholar
  73. Taylor JM, Seilheimer TS, Fisher WL (2014) Downstream fish assemblage response to river impoundment varies with degree of hydrologic alteration. Hydrobiologia 728:23–39CrossRefGoogle Scholar
  74. Tear TH, Kareiva P, Angermeier PL, Comer P, Czech B, Kautz R, Landon L, Mehlman D, Murphy K, Ruckelshaus M, Scott JM, Wilhere G (2005) How much is enough? The recurrent problem of setting measurable objectives in conservation. BioScience 55:835–849CrossRefGoogle Scholar
  75. Tennant DL (1976) Instream flow regimens for fish, wildlife, recreation and related environmental resources. Fish 1:6–10CrossRefGoogle Scholar
  76. Tharme RE (2003) A global perspective on e-flow assessment: emerging trends in the development and application of environmental flow methodologies for rivers. River Res Appl 19:397–441CrossRefGoogle Scholar
  77. Travnicheck VH, Bain MB, Maceina MJ (1995) Recovery of a warmwater fish assemblage afer the initiation of a minimum-flow release downstream from a hydroelectric dam. Trans Am Fish Soc 124:836–844CrossRefGoogle Scholar
  78. Trush WJ, McBain SM, Leopold LB (2000) Attributes of an alluvial river and their relation to water policy and management. Proc Natl Acad Sci USA 97:11858–11863CrossRefGoogle Scholar
  79. Uría-Martínez, R, O’Connor PW, Johnson MM (2015) 2014 Hydropower Market Report. Wind and Water Power Technologies Office, Department of Energy. April 2015. http://nhaap.ornl.gov/HMR/2014. Accessed 28 May 2015
  80. USACE (United States Army Corps of Engineers) (2015) Corps Map. National Inventory of Dams. https://nid.usace.army.mil. Accessed 7 Aug 2015
  81. USACE (US Army Corps of Engineers) (2012) Environmental assessment for the Gathright Dam Low Flow Augmentation Project, Alleghany County, Virginia. USACE Norfolk District, Norfolk, VA. 89 pp. http://www.nao.usace.army.mil/Portals/31/docs/regulatory/publicnotices/2012/Dec/GathrightDamLowFlowAugmentation_EA.pdf. Accessed 9 Oct 2015
  82. Vaughn CC, Taylor CM (1999) Impoundments and the decline of freshwater mussels: a case study of an extinction gradient. Conserv Biol 13:912–920CrossRefGoogle Scholar
  83. Ward JV, Stanford JA (1983) The serial discontinuity concept of lotic ecosystems. In: Fontaine TD, Bartell SM (eds) Dynamics of lotic ecosytems. Ann Arbor Sciences, Ann Arbor, pp 29–42Google Scholar
  84. Webb JA, De Little SC, Miller KA et al (2015) A general approach to predicting ecological responses to environmental flows: making best use of the literature, expert knowledge, and monitoring data. River Res Appl 31:505–514CrossRefGoogle Scholar
  85. Wehrly KE, Wiley MJ, Seelbach PW (2003) Classifying regional variation in thermal regime based on stream fish community patterns. Trans Am Fish Soc 132:18–38CrossRefGoogle Scholar
  86. Wollock DM, Winter TC, McMahon G (2004) Delineation and evaluation of hydrologic-landscape regions in the United States using geographic information system tools and multivariate statistical analyses. Env Manag 34:71–88CrossRefGoogle Scholar
  87. Worthington TA, Brewer SK, Grabowski TB, Mueller J (2014) Backcasting the decline of a vulnerable Great Plains reproductive ecotype: identifying threats and conservation priorities. Glob Change Biol 20:89–102CrossRefGoogle Scholar
  88. Wurbs RA (1993) Reservoir-system simulation and optimization models. J Water Resour Plan Manag 119:455–472CrossRefGoogle Scholar
  89. Yeh WW-G (1985) Reservoir management and operations models: a state-of-the-art review. Water Resour Res 21:1797–1818CrossRefGoogle Scholar
  90. Zhou Z, Chan WK (2009) Reducing electricity price forecasting error using seasonality and higher-order crossing information. IEEE Trans Power Syst 24:1126–1135CrossRefGoogle Scholar
  91. Zimmerman JKH, Letcher BH, Nislow KH, Lutz KA, Magillan FJ (2010) Determining the effects of dams on subdaily variation in river flows at a whole-basin scale. River Res Appl 26:1246–1260CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York (outside the USA) 2016

Authors and Affiliations

  • Ryan A. McManamay
    • 1
  • Shannon K. Brewer
    • 2
  • Henriette I. Jager
    • 1
  • Matthew J. Troia
    • 1
  1. 1.Environmental Sciences DivisionOak Ridge National LaboratoryOak RidgeUSA
  2. 2.U.S. Geological Survey, Oklahoma Cooperative Fish and Wildlife Research UnitOklahoma State UniversityStillwaterUSA

Personalised recommendations