Modelling Water Quality to Support Lake Restoration

  • Moritz K. LehmannEmail author
  • David P. Hamilton


Numerous applications of deterministic models have been used to support decision making in relation to lake restoration actions in New Zealand. The most widely used are one-dimensional, coupled hydrodynamic-ecological models suitable for long-term (multi-year) simulations to explore inter-annual variability and progressive changes in response to restoration actions and global change drivers (e.g. climate change). Three-dimensional models have also been used to examine, for example, spatial variability associated with inter-basin circulation transfers in a deep hydrolake, dispersion of geothermally heated waters in a shallow volcanic lake and a double gyre circulation pattern influencing dispersion of inflows, including a wastewater discharge, to a large volcanic lake. We provide a framework for categorising these applications based on theoretical, heuristic and predictive considerations. Information on model selection, data assimilation and calibration processes presented in this chapter are designed to support increasingly sophisticated modelling approaches, many of which will be supported by autonomous sensor data. The need for these types of models is likely to increase in the future as they are used to support the goals of the National Policy Statement for Freshwater Management (MfE 2014) to maintain or improve water quality. The models will be used to assess the ecological outcomes of potential restoration actions as part of an integrated assessment that includes expert knowledge, economic considerations and social outcomes.


DYRESM-CAEDYM ELCOM-CAEDYM Restoration scenarios Theoretical model Heuristic model Predictive model Climate change Calibration Data assimilation 


  1. Abell JM, Hamilton DP (2014) Biogeochemical processes and phytoplankton nutrient limitation in the inflow transition zone of a large eutrophic lake during a summer rain event. Ecohydrology 8:243–262CrossRefGoogle Scholar
  2. Abell JM, Ozkundakci D, Hamilton DP (2010) Nitrogen and phosphorus limitation of phytoplankton growth in New Zealand lakes: implications for eutrophication control. Ecosystems 13:966–977CrossRefGoogle Scholar
  3. Abell JM, McBride CG, Hamilton DP (2015a) Lake Rotorua wastewater discharge environmental effects study. Client report prepared for Rotorua Lakes Council. University of Waikato, Hamilton, New ZealandGoogle Scholar
  4. Abell J, Jones H, Hamilton DP (2015b) Hydrodynamic–ecological modelling to support assessment of water quality management options for Wainono Lagoon. Report prepared for Environment Canterbury by Aquatic Analytics, Hamilton, New ZealandGoogle Scholar
  5. Allan MG (2014) Remote sensing, numerical modelling and ground truthing for analysis of lake water quality and temperature. Unpublished PhD Thesis, University of Waikato, Hamilton, New ZealandGoogle Scholar
  6. Allan MG (2016) A coupled hydrodynamic-ecological model of management options for restoration of Lake Ohinewai. Environmental Research Institute Report 68, University of Waikato, Hamilton, New ZealandGoogle Scholar
  7. Allan MG, Hamilton DP, Trolle D, Muraoka K, McBride CG (2016) Spatial heterogeneity in geothermally-influenced lakes derived from atmospherically corrected Landsat thermal imagery and three-dimensional hydrodynamic modelling. Int J Appl Earth Obs Geoinf 50:106–116CrossRefGoogle Scholar
  8. Arhonditsis GB, Brett MT (2004) Evaluation of the current state of mechanistic aquatic biogeochemical modeling. Mar Ecol Prog Ser 271:13–26CrossRefGoogle Scholar
  9. Arhonditsis GB, Qian SS, Stow CA, Lamon EC, Reckhow KH (2007) Eutrophication risk assessment using Bayesian calibration of process-based models: application to a mesotrophic lake. Ecol Model 208:215–229CrossRefGoogle Scholar
  10. Bayer TK, Burns CW, Schallenberg M (2013) Application of a numerical model to predict impacts of climate change on water temperatures in two deep, oligotrophic lakes in New Zealand. Hydrobiologia 713:53–71CrossRefGoogle Scholar
  11. Bennett ND, Croke BFW, Guariso G, Guillaume JHA, Hamilton SH, Jakeman AJ, Marsili-Libelli S, Newham LTH, Norton JP, Perrin C, Pierce SA, Robson B, Seppelt R, Voinov AA, Fath BD, Andreassian V (2013) Characterising performance of environmental models. Environ Model Softw 40:1–20CrossRefGoogle Scholar
  12. Box GEP, Draper R (1987) Empirical model-building and response surfaces. Wiley series in probability and mathematical studies, 1st edn. Wiley, New YorkGoogle Scholar
  13. Brett MT, Benjamin MM (2008) A review and reassessment of lake phosphorus retention and the nutrient loading concept. Freshw Biol 53:194–211Google Scholar
  14. Breukelaar AW, Lammens EHRR, Breteler JGPK, Tatrai I (1994) Effects of benthivorous bream (Abramis brama) and carp (Cyprinus carpio) on sediment resuspension and concentrations of nutrients and chlorophyll-a. Freshw Biol 32:113–121CrossRefGoogle Scholar
  15. Briggs J, Dowd M, Meyer R (2013) Data assimilation for large-scale spatio-temporal systems using a location particle smoother. Environmetrics 24(2):81–97CrossRefGoogle Scholar
  16. Bruggeman J, Bolding K (2014) A general framework for aquatic biogeochemical models. Environ Model Softw 61:249–265CrossRefGoogle Scholar
  17. Burger DF (2006) Benthic-pelagic coupling of nutrients in Lake Rotorua. PhD thesis, University of Waikato, Hamilton, New ZealandGoogle Scholar
  18. Burger DF, Hamilton DP, Pilditch CA, Gibbs MM (2007) Benthic nutrient fluxes in a eutrophic, polymictic lake. Hydrobiologia 584:13–25CrossRefGoogle Scholar
  19. Burger DF, Hamilton DP, Pilditch CA (2008) Modelling the relative importance of internal and external nutrient loads on water column nutrient concentrations and phytoplankton biomass in a shallow polymictic lake. Ecol Model 211:411–423CrossRefGoogle Scholar
  20. Castendyk D, Webster-Brown J (2007a) Sensitivity analysis in pit lake prediction, Martha Mine, New Zealand 2: geochemistry, water–rock reactions, and surface adsorption. Chem Geol 244:56–73CrossRefGoogle Scholar
  21. Castendyk D, Webster-Brown J (2007b) Sensitivity analysis in pit lake prediction, Martha Mine, New Zealand 1: relationship between turnover and input water density. Chem Geol 244:42–55CrossRefGoogle Scholar
  22. Collier KJ, Grainger NPJ (eds) (2015) New Zealand invasive fish management handbook. Lake ecosystem restoration New Zealand. University of Waikato and Department of Conservation, Hamilton, New ZealandGoogle Scholar
  23. Cox T, Cooke J (2014) Modelling the effects of flushing Lake Waikare with Waikato River water. Report to Waikato District Council. Streamlined Environmental Ltd, Hamilton, New ZealandGoogle Scholar
  24. Dowd M, Meyer R (2003) A Bayesian approach to the ecosystem inverse problem. Ecol Model 168:39–55CrossRefGoogle Scholar
  25. Dowd M, Jones E, Parslow J (2014) A statistical overview and perspectives on data assimilation for marine biogeochemical models. Environmetrics 25:203–213CrossRefGoogle Scholar
  26. Evensen G (2007) Data assimilation: the ensemble Kalman filter. Springer, BerlinGoogle Scholar
  27. Flynn KJ (2005) Castles built on sand: dysfunctionality in plankton models and the inadequacy of dialogue between biologists and modellers. J Plankton Res 27:1205–1210CrossRefGoogle Scholar
  28. Franks PJS (1995) Coupled physical-biological models in oceanography. Rev Geophys 33:1177–1187CrossRefGoogle Scholar
  29. Ghil MP, Malanotte-Rizzoli P (1991) Data assimilation in meteorology and oceanography. Adv Geophys 33:41–266Google Scholar
  30. Gibbs M, Hawes I, Stephens S (2003) Lake Rotoiti—Ohau Channel: assessment of effects of engineering options on water quality. NIWA Client Report HAM2003:142, Hamilton, New ZealandGoogle Scholar
  31. Gibbs MM, Abell J, Hamilton DP (2016) Wind forced circulation and sediment disturbance in a temperate lake. N Z J Mar Freshw Res 50:209–227CrossRefGoogle Scholar
  32. Gregg WW, Friedrichs MAM, Robinson AR, Rose KA, Schlitzer R, Thompson KR, Doney SC (2009) Skill assessment in ocean biological data assimilation. J Mar Syst 76:16–33CrossRefGoogle Scholar
  33. Hamilton DP, McBride C, Uraoka K (2005) Lake Rotoiti fieldwork and modelling to support considerations of Ohau Channel diversion from Lake Rotoiti. Centre for Biodiversity and Ecology Report 96, University of Waikato, Hamilton, New ZealandGoogle Scholar
  34. Hamilton DP, O’Brien KR, Burford MA, Brookes JD, McBride CG (2010) Vertical distributions of chlorophyll in deep, warm monomictic lakes. Aquat Sci 72:295–307CrossRefGoogle Scholar
  35. Hamilton DP, Jones HFE, Özkundakci D, McBride C, Allan MG, Faber J, Pilditch CA (2012a) Waituna Lagoon modelling: developing quantitative assessments to assist with lagoon management. Environmental Research Institute Report 4, University of Waikato, Hamilton, New ZealandGoogle Scholar
  36. Hamilton DP, Özkundakci D, McBride C, Ye W, Silvester W, White P (2012b) Predicting the effects of nutrient loads, management regimes and climate change on water quality of Lake Rotorua. Centre for Biodiversity and Ecology Report 123, University of Waikato, Hamilton, New ZealandGoogle Scholar
  37. Hamilton DP, Carey CC, Arvola L, Arzberger P, Brewer C, Cole JJ, Gaiser E, Hanson PC, Ibelings BW, Jennings E, Kratz TK, Lin F-P, McBride CG, de Motta Marques D, Muraoka K, Nishri A, Qin B, Read JS, Rose KC, Ryder E, Weathers KC, Zhu G, Trolle D, Brookes JD (2014a) A Global Lake Ecological Observatory Network (GLEON) for synthesising high–frequency sensor data for validation of deterministic ecological models. Inland Waters 5:49–56CrossRefGoogle Scholar
  38. Hamilton DP, McBride CG, Jones HFE (2014b) Assessing the effects of alum dosing of two inflows to Lake Rotorua against external nutrient load reductions: model simulations for 2001–2012. Environmental Research Institute Report 49, University of Waikato, Hamilton, New ZealandGoogle Scholar
  39. Hamilton DP, Dada CA, McBride CG (2017) Water quality modelling of Te Waihora/Lake Ellesmere. Environmental Research Institute Report 100, University of Waikato, Hamilton, New ZealandGoogle Scholar
  40. Harris GP (1997) Algal biomass and biogeochemistry in catchments and aquatic ecosystems: scaling of processes, models and empirical tests. Hydrobiologia 349:19–26CrossRefGoogle Scholar
  41. Hipsey MR, Romero JR, Antenucci JP, Hamilton DP (2007) Computational aquatic ecosystem dynamics model: CAEDYM V2. Centre for Water Research Report 2006/1/16, University of Western Australia, Perth, AustraliaGoogle Scholar
  42. Hipsey MR, Salmon SU, Mosley LM (2014) A three-dimensional hydro-geochemical model to assess lake acidification risk. Environ Model Softw 61:433–457CrossRefGoogle Scholar
  43. Hodges BR, Imberger J, Saggio A, Winters KB (2000) Modeling basin-scale internal waves in a stratified lake. Limnol Oceanogr 45:1603–1620CrossRefGoogle Scholar
  44. Hu F, Bolding K, Bruggeman J, Jeppesen E, Flindt MR, van Gerven L, Janse JH, Janssen ABG, Kuiper JJ, Mooij WM, Trolle D (2016) FABM-PCLake—linking aquatic ecology with hydrodynamics. Geosci Model Dev 9:2271–2278CrossRefGoogle Scholar
  45. Janse JH (1997) A model of nutrient dynamics in shallow lakes in relation to multiple stable states. Hydrobiologia 342:1–8Google Scholar
  46. Janssen ABG, Arhonditsis GB, Beusen A, Bolding K, Bruce L, Bruggeman J, Couture RM, Downing AS, Elliott JA, Frassl MA, Gal G, Gerla DJ, Hipsey MR, Hu FJ, Ives SC, Janse JH, Jeppesen E, Johnk KD, Kneis D, Kong XZ, Kuiper JJ, Lehmann MK, Lemmen C, Ozkundakci D, Petzoldt T, Rinke K, Robson BJ, Sachse R, Schep SA, Schmid M, Scholten H, Teurlincx S, Trolle D, Troost TA, Van Dam AA, Van Gerven LPA, Weijerman M, Wells SA, Mooij WM (2015) Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective. Aquat Ecol 49:513–548CrossRefGoogle Scholar
  47. Jones HFE, Hamilton DP (2014) Hydrodynamic modelling of Lake Whangape and Lake Waahi. Environmental Research Institute Report 31, University of Waikato, Hamilton, New ZealandGoogle Scholar
  48. Jones, H, Hamilton D, Muraoka K (2013) Facilitating rafting on the Kaituna River: the effect of manipulating Lake Rotoiti outflow on the function of the Ohau diversion wall. Environmental Research Institute Report 23, University of Waikato, Hamilton, New ZealandGoogle Scholar
  49. Jones H, Özkundakci D, Kochendoerfer S, McBride C, Hamilton D (2014) Lake Rotokakahi water quality modelling. Environmental Research Institute Report 33, University of Waikato, Hamilton, New ZealandGoogle Scholar
  50. Jørgensen SE (1976) A eutrophication model for a lake. Ecol Model 2:147–165CrossRefGoogle Scholar
  51. Kara EL, Hanson P, Hamilton DP, Hipsey MR, McMahon KD, Read JS, Winslow L, Dedrick J, Rose K, Carey CC, Bertilsson S, da Motta Marques D, Beversdorf L, Miller T, Wu C, Hsieh Y-E, Gaiser E, Kratz T (2012) Time-scale dependence in numerical simulations: assessment of physical, chemical, and biological predictions in a stratified lake at temporal scales of hours to months. Environ Model Softw 35:104–121CrossRefGoogle Scholar
  52. Kim K, Park M, Min JH, Ryu L, Kang MR, Park LJ (2014a) Simulation of algal bloom dynamics in a river with the ensemble Kalman filter. J Hydrol 519:2810–2821CrossRefGoogle Scholar
  53. Kim S, Seo DJ, Riazi H, Shin C (2014b) Improving water quality forecasting via data assimilation—application of maximum likelihood ensemble filter to HSPF. J Hydrol 519:2797–2809CrossRefGoogle Scholar
  54. Langseth BJ, Rogers M, Zhang H (2012) Modeling species invasions in Ecopath with Ecosim: an evaluation using Laurentian Great Lakes models. Ecol Model 247:251–261CrossRefGoogle Scholar
  55. Lehmann, MK, Hamilton DP, Muraoka K, Tempero GW, Collier KJ, Hicks BJ (2017) Waikato shallow lakes modelling. Environmental Research Institute Report 94, University of Waikato, Hamilton, New ZealandGoogle Scholar
  56. Lotka AJ (1925) Elements of physical biology. Williams & Wilkins, BaltimoreGoogle Scholar
  57. Luo YQ, Ogle K, Tucker C, Fei SF, Gao C, LaDeau S, Clark JS, Schimel DS (2011) Ecological forecasting and data assimilation in a data-rich era. Ecol Appl 21:1429–1442PubMedCrossRefPubMedCentralGoogle Scholar
  58. Lynch DR, McGillicuddy DJ, Werner FE (2009) Skill assessment for coupled biological/physical models of marine systems. J Mar Syst 76:1–3CrossRefGoogle Scholar
  59. Makler-Pick V, Gal G, Gorfine M, Hipsey MR, Carmel Y (2011) Sensitivity analysis for complex ecological models—a new approach. Environ Model Softw 26:124–134CrossRefGoogle Scholar
  60. Mattern JP, Dowd M, Fennel K (2013) Particle filter-based data assimilation for a three-dimensional biological ocean model and satellite observations. J Geophys Res Oceans 118:2746–2760CrossRefGoogle Scholar
  61. May RM (1974) Stability and complexity in model ecosystems. Princeton University Press, PrincetonGoogle Scholar
  62. McBride CG, Hamilton DP (2016) Catchment and lake water quality modelling to assess management pptions for Lake Tutira. Environmental Research Institute Report 97, University of Waikato, Hamilton, New ZealandGoogle Scholar
  63. McBride CG, Muraoka K, Hamilton DP (2014) A water quality model for Lake Tikitapu. Environmental Research Institute Report 71, University of Waikato, Hamilton, New ZealandGoogle Scholar
  64. McIntosh J (2014) Ohau Channel diversion wall monitoring. Bay of Plenty Regional Council, Whakatane, New ZealandGoogle Scholar
  65. MfE (Ministry for the Environment) (2014) National policy statement for freshwater management 2014. Ministry for the Environment, New ZealandGoogle Scholar
  66. Mills C, Dallimore C, O’Neill C, Cinque K, Haydon S (2013) Development and use of a decision support tool for supporting the operation of Melbourne water’s drinking water reservoirs, Victoria, Australia. 19 International Congress on Modelling and Simulation, 12–16 Dec 2011, Perth, AustraliaGoogle Scholar
  67. Mooij WM, Brederveld RJ, de Klein JJM, DeAngelis DL, Downing AS, Faber M, Gerla DJ, Hipsey MR, Hoen J, Janse JH, Janssen ABG, Jeuken M, Kooi BW, Lischke B, Petzoldt T, Postma L, Schep SA, Scholten H, Teurlincx S, Thiange C, Trolle D, van Dam AA, van Gerven LPA, van Nes EH, Kuiper JJ (2014) Serving many at once: how a database approach can create unity in dynamical ecosystem modelling. Environ Model Softw 61:266–273CrossRefGoogle Scholar
  68. Morgan DJK, Hicks BJ (2013) A metabolic theory of ecology applied to temperature and mass dependence of N and P excretion by common carp. Hydrobiologia 705:135–145CrossRefGoogle Scholar
  69. Nielsen A, Trolle D, Bjerring R, Søndergaard M, Olesen JE, Janse JH, Mooij WM, Jeppesen E (2014) Effects of climate and nutrient load on the water quality of shallow lakes assessed through ensemble runs by PCLake. Ecol Appl 24(8):1926–1944PubMedCrossRefPubMedCentralGoogle Scholar
  70. Norton N, Spigel B, Sutherland D, Trolle D, Plew D (2009) Lake Benmore water quality: a modelling method to assist with assessments of nutrient loadings. NIWA Report No: R09/70, NIWA, Christchurch, New ZealandGoogle Scholar
  71. Özkundakci D, Hamilton DP, Gibbs M (2010) Hypolimnetic phosphorus and nitrogen dynamics in a small, eutrophic lake with a seasonally anoxic hypolimnion. Hydrobiologia 661:5–20CrossRefGoogle Scholar
  72. Özkundakci D, Hamilton DP, Trolle D (2011) Modelling the response of a highly eutrophic lake to reductions in external and internal nutrient loading. N Z J Mar Freshw Res 45:165–185CrossRefGoogle Scholar
  73. Özkundakci D, McBride CG, Hamilton DP (2012) Parameterisation of sediment geochemistry for simulating water quality responses to long-term catchment and climate changes in polymictic, eutrophic Lake Rotorua, New Zealand. In: Brebbia CA (ed) Water Pollution XI, 11th International Conference on Water Pollution: Modelling, Monitoring and Management, 10–12 July 2012, New Forest, UK. WIT Trans Ecol Environ 164:171–182CrossRefGoogle Scholar
  74. Paul W, Özkundakci D, Hamilton DP (2008) Modelling of restoration scenarios for Lake Ngaroto. Centre for Biodiversity and Ecology Research Report 81, University of Waikato, Hamilton, New ZealandGoogle Scholar
  75. Paul WJ, McBride CG, Hamilton DP, Hopkins A, Özkundakci D (2011) Restoration of Lake Hakanoa: results of model simulations. Centre for Biodiversity and Ecology Research Report 88, University of Waikato, Hamilton, New ZealandGoogle Scholar
  76. Pridmore RD (1987) Phytoplankton response to changed nutrient concentrations. In: Lake managers handbook. Water and soil miscellaneous publication 103. Ministry of Works and Development, Wellington, pp 183–194Google Scholar
  77. Priscu JC, Spigel RH, Gibbs MM, Downs MT (1986) A numerical analysis of hypolimnetic nitrogen and phosphorus transformations in Lake Rotoiti, New Zealand. Limnol Oceanogr 31:812–831CrossRefGoogle Scholar
  78. Quinn JM, Monaghan RM, Bidwell V, Harris SR (2013) A Bayesian belief network approach to evaluating complex effects of irrigation-driven agricultural intensification scenarios on future aquatic environmental and economic values in a New Zealand catchment. Mar Freshw Res 64:460–474CrossRefGoogle Scholar
  79. Recknagel F, Benndorf J (1982) Validation of the ecological simulation model “SALMO”. Int Rev Gesamten Hydrobiol 67:113–125Google Scholar
  80. Recknagel F, Branco CWC, Cao H, Huszar VLM (2015) Modelling and forecasting the heterogeneous distribution of picocyanobacteria in the tropical Lajes Reservoir (Brazil) by evolutionary computation. Hydrobiologia 749:53–67CrossRefGoogle Scholar
  81. Reynolds CS (1997) Successional development, energetics and diversity in planktonic communities. In: Abe T, Levin SR, Higashi M (eds) Biodiversity: an ecological perspective. Springer, New York, pp 167–202CrossRefGoogle Scholar
  82. Reynolds CS, Irish AE, Elliott JA (2001) The ecological basis for simulating phytoplankton responses to environmental change (PROTECH). Ecol Model 140:271–291CrossRefGoogle Scholar
  83. Robson BJ (2014a) State of the art in modelling of phosphorus in aquatic systems: Review, criticisms and commentary. Environ Model Softw 61:339–359CrossRefGoogle Scholar
  84. Robson BJ (2014b) When do aquatic systems models provide useful predictions, what is changing, and what is next? Environ Model Softw 61:287–296CrossRefGoogle Scholar
  85. Robson BJ, Hamilton DP, Webster IT, Chan T (2008) Ten steps applied to development and evaluation of process-based biogeochemical models of estuaries. Environ Model Softw 23:369–384CrossRefGoogle Scholar
  86. Rutherford JC, Dumnov SM, Ross AH (1996) Predictions of phosphorus in Lake Rotorua following loads reductions. N Z J Mar Freshw Res 30:383–396CrossRefGoogle Scholar
  87. Schallenberg M, Sorrell B (2009) Factors related to clear water vs. turbid water regime shifts in New Zealand lakes and implications for management and restoration. N Z J Mar Freshw Res 43:701–712CrossRefGoogle Scholar
  88. Schallenberg M, Hamilton DP, Hicks AS, Robertson HA, Scarsbrook M, Robertson B, Wilson K, Whaanga D, Jones HFE, Hamill K (2017) Multiple lines of evidence determine robust nutrient load limits required to safeguard a threatened lake/lagoon system. N Z J Mar Freshw Res 51:78–95CrossRefGoogle Scholar
  89. Schladow SG, Hamilton DP (1997) Prediction of water quality in lakes and reservoirs: part II: model calibration, sensitivity analysis and application. Ecol Model 96:111–123CrossRefGoogle Scholar
  90. Sharma A (2011) A modelling approach to assist with managing water quality in a catchment subject to rapid urbanisation: Lake Rotokauri, Hamilton, New Zealand. Unpublished MSc thesis, University of Waikato, Hamilton, New ZealandGoogle Scholar
  91. Smith VH, Wood SA, McBride CG, Atalah J, Hamilton DP, Abell J (2016) Phosphorus and nitrogen loading restraints are essential for successful eutrophication control of Lake Rotorua, New Zealand. Inland Waters 6:273–283CrossRefGoogle Scholar
  92. Spigel R (2007) Lake Ototoa study: modelling thermal stratification. NIWA Client Report HC2007-133, National Institute of Water and Atmospheric Research, Christchurch, New ZealandGoogle Scholar
  93. Spigel R, McKerchar A (2008) Lake Brunner study: modelling thermal stratification. NIWA Client Report CHC2008-080, National Institute of Water and Atmospheric Research, Christchurch, New ZealandGoogle Scholar
  94. Spigel R, Howard-Williams C, Gibbs M, Stephens S, Waugh B (2005) Field calibration of a formula for entrance mixing of river inflows to lakes: Lake Taupo, North Island, New Zealand. N Z J Mar Freshw Res 39:785–802CrossRefGoogle Scholar
  95. Stephens S (2004) Modelling diversion walls for diverting the Ohau Channel inflow from Lake Rotoiti. NIWA Client Report HAM2004–164, NIWA, Hamilton, New ZealandGoogle Scholar
  96. Stewart-Koster B, Bunn SE, Mackay SJ, Poff NL, Naiman RJ, Lake PS (2010) The use of Bayesian networks to guide investments in flow and catchment restoration for impaired river ecosystems. Freshw Biol 55:243–260CrossRefGoogle Scholar
  97. Stillman RA, Wood KA, Goss-Custard JD (2016) Deriving simple predictions from complex models to support environmental decision-making. Ecol Model 326:134–141CrossRefGoogle Scholar
  98. Stow CA, Jolliff J, McGillicuddy DJ, Doney SC, Allen JL, Friedrichs MAM, Rose KA, Wallhead GP (2009) Skill assessment for coupled biological/physical models of marine systems. J Mar Syst 76:4–15PubMedCrossRefPubMedCentralGoogle Scholar
  99. Trolle D, Skovgaard H, Jeppesen E (2008) The water framework directive: setting the phosphorus loading target for a deep lake in Denmark using the 1D lake ecosystem model DYRESM–CAEDYM. Ecol Model 219:138–152CrossRefGoogle Scholar
  100. Trolle D, Hamilton DP, Pilditch CA, Duggan IC, Jeppesen E (2011) Predicting the effects of climate change on trophic status of three morphologically varying lakes: implications for lake restoration and management. Environ Model Softw 26(4):354–370CrossRefGoogle Scholar
  101. Trolle D, Hamilton DP, Hipsey MR, Bolding K, Bruggeman J, Mooij WM, Janse JH, Nielsen A, Jeppesen E, Elliott JA, Makler-Pick V, Petzoldt T, Rinke K, Flindt MR, Arhonditsis GB, Gal G, Bjerring R, Tominaga K, Hoen J-T, Downing AS, Marques DM, Fragoso CR, Søndergaard M Hanson PC (2012) A community-based framework for aquatic ecosystem models. Hydrobiologia 683:25–34CrossRefGoogle Scholar
  102. Trolle D, Elliott JA, Mooij WM, Janse JH, Bolding K, Hamilton DP, Jeppesen E (2014a) Advancing projections of phytoplankton responses to climate change through ensemble modelling. Environ Model Softw 61:371–379CrossRefGoogle Scholar
  103. Trolle D, Spigel B, Hamilton DP, Norton N, Sutherland D, Plew D, Allan MG (2014b) Application of a three-dimensional water quality model as a decision support tool for the management of land-use changes in the catchment of an oligotrophic lake. Environ Manag 54:479–493CrossRefGoogle Scholar
  104. Tsehaye I, Jones ML, Bence JR, Brenden TO, Madenjian CP, Warner DM (2014) A multispecies statistical age-structured model to assess predator-prey balance: application to an intensively managed Lake Michigan pelagic fish community. Can J Fish Aquat Sci 71:627–644CrossRefGoogle Scholar
  105. Twigt D, Tyrell D, Lima Rego J, Troost T (2011) Water quality forecasting systems: advanced warning of harmful events and dissemination of public alerts. In: Santos MA, Sousa L, Portela E (eds) Information systems for crisis response and management, ISCRAM, 8th International Conference, Lisbon, PortugalGoogle Scholar
  106. Vincent WF, Gibbs MM, Dryden SJ (1984) Accelerated eutrophication in a New-Zealand lake—Lake Rotoiti, central North Island. N Z J Mar Freshw Res 18(4):431–440CrossRefGoogle Scholar
  107. Vollenweider RA (1976) Advances in defining critical loading levels for phosphorus in lake eutrophication. Memorie dell’ Istituto Italiano di Idrobiologia 33:53–83Google Scholar
  108. Volterra V (1926) Variazioni e fluttuazioni del numero d’individui in specie animali conviventi. Memorie della Reale Accademia Nazionale dei Lincei Series 2:31–113Google Scholar
  109. Von Westernhagen N (2010) Measurements and modelling of eutrophication processes in Lake Rotoiti. In: Unpublished PhD thesis. University of Waikato, Hamilton, New ZealandGoogle Scholar
  110. Wade AJ, Durand PVB, Wessel WW Raat KJ, Whitehead PG, Butterfield D, Rankinen K, Lepisto A (2002) A nitrogen model for European catchments: INCA, new model structure and equations. Hydrol Earth Syst Sci 6:559–582CrossRefGoogle Scholar
  111. Weber MJ, Brown ML (2015) Biomass-dependent effects of age-0 common carp on aquatic ecosystems. Hydrobiologia 742:71–80CrossRefGoogle Scholar
  112. Whitehead PG, Wilson EJ, Butterfield D (1998) A semi-distributed Integrated Nitrogen model for multiple source assessment in Catchments (INCA): part I—model structure and process equations. Sci Total Environ 210:547–558CrossRefGoogle Scholar
  113. Zeckoski RW, Smolen MD, Moriasi DN, Frankenberger JR, Feyereisen GW (2015) Hydrologic and water quality terminology as applied to modeling. Trans ASABE 58:1619–1635CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Environmental Research InstituteThe University of WaikatoHamiltonNew Zealand
  2. 2.Australian Rivers InstituteGriffith UniversityBrisbaneAustralia

Personalised recommendations