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Modelling for Catchment Management

  • Aroon ParshotamEmail author
  • Dale M. Robertson
Chapter

Abstract

Catchment models are useful tools to help describe and quantify the sources, transport, and fate of sediment, nutrients, and other constituents in a landscape. Results from catchment models are used to quantify and understand existing conditions and used in restoration efforts by defining areas with highest contributions (hotspots, where actions would be most beneficial) and describing the relative importance of various sources (what types of actions would be most beneficial). In practice, a continuum of models exists from simple empirical models to complex process-driven models, each requiring different types and amounts of information. Each of these models has its strengths and weaknesses, which should be considered when deciding which model to apply to a specific area. In many applications, a combination of models can be either coupled or run in series to help describe how nutrients and sediment are transported from the field to downstream receiving water bodies. In this chapter, we describe the continuum of catchment models that exist and provide information for choosing specific models for various management applications. We then provide examples of catchment models used to address a wide range of scientific and policy driven issues: two models commonly applied in New Zealand (CLUES and GLEAMS) and one model (SPARROW) applied to a large river basin in the United States (Mississippi River Basin).

Keywords

Catchment modelling Management Regulation Water quality models 

References

  1. Alexander RB, Smith RA, Schwarz GE, Boyer EW, Nolan JV, Brakebill JW (2008) Differences in phosphorus and nitrogen delivery to the gulf of Mexico from the Mississippi River Basin. Environ Sci Tech 42:822–830CrossRefGoogle Scholar
  2. Anderson MP, Woessner WW, Hunt RJ (2015) Applied groundwater modeling: Simulation of flow and advective transport, 2nd edn. Academic Press, LondonGoogle Scholar
  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, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R, Santhi C, Harmel RD, van Griensven A, Van Liew MW, Kannan N, Jha MK (2012) SWAT: model use, calibration, and validation. Trans ASABE 55(4):1494–1508CrossRefGoogle Scholar
  5. Barnett B, Townley LR, Post V, Evans RE, Hunt RJ, Peeters L, Richardson S, Werner AD, Knapton A, Bo RA (2012) Australian groundwater modelling guidelines. Waterlines report, National Water Commission, Canberra, AustraliaGoogle Scholar
  6. Bennett ND, Croke BFW, Buariso G, Guillaume JHA, Hamilton SH, Jakeman AJ, Marsili-Libeli S, Newham LTH, Norton JP, Perrin C, Peirce SA, Robson B, Seppelt R, Voinov AA, Fath BD, Andreassian V (2013) Characterising performance of environmental models. Environ Model Softw 40:1–20CrossRefGoogle Scholar
  7. Bidwell VJ, Good JM (2007) Development of the AquiferSim model of cumulative effect on groundwater of nitrate discharge from heterogeneous land use over large regions. In: Oxley L, Kulasiri D (eds) MODSIM 2007 International congress on modelling and simulation. Modelling and Simulation Society of Australia and New Zealand, pp 74–80Google Scholar
  8. Bottcher AB, James A (2014) Watershed assessment model (WAM). In: 21st century watershed technology conference and workshop improving water quality and the environment conference proceedings, University of Waikato, New Zealand, 3–6 November 2014.  https://doi.org/10.13031/wtcw.2014-006. Accessed 8 Sept 2018
  9. Bottcher AB, Hiscock J, Pickering NB, Hilburn RT (1998) WAM-Watershed assessment model. In: Proceedings of the 1998 watershed management conference: moving from theory to implementation, Water Environment Federation, Alexandria, VA, USAGoogle Scholar
  10. Canfield DE, Bachmann RW (1981) Prediction of total phosphorus concentrations, chlorophyll-a, and Secchi depths in natural and artificial lakes. Can J Fish Aquat Sci 38:414–423CrossRefGoogle Scholar
  11. Chrzanowski C (2015) Development of a toolbox for integrated water quality modelling supporting river management planning river basins. In: International conference on monitoring, modelling and management of pollutants, Karlsruhe, 24–25 June 2015, 89 p. http://digbib.ubka.unikarlsruhe.de/volltexte/documents/3630105. Accessed 5 Sept 2017
  12. Collins R (2003) Predicting sediment loss under proposed development in the Waiarohia catchment. NIWA Client Report HAM2003-063. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  13. Cooper AB, Bottcher AB (1993) Basin scale modeling as a tool for water resource planning. J Water Resour Plan Manag 119:306–323CrossRefGoogle Scholar
  14. Cox T (2015) Lake Waikare water quality modelling: investigation into flushing with Waikato River water. Report prepared by Streamlined Environmental for Waikato District Council. http://www.streamlined.co.nz/wp-content/uploads/2015/09/Lake-Waikare-Flushing-WQ-Report-v4.pdf. Accessed 8 Sept 2018
  15. CRC for Catchment Hydrology (2005) Series on model choice. Cooperative research centre (CRC) for catchment hydrology (Australia) http://toolkit.ewater.org.au/tools/ModelChoice/. Accessed 5 Sept 2017
  16. David MB, Drinkwater LE, McIsaac GF (2010) Sources of nitrate yields in the Mississippi River Basin. J Environ Qual 39:1657–1667CrossRefGoogle Scholar
  17. Dewes A (2015) Economic resilience and environmental performance of dairy farms in the upper Waikato region. MSc thesis, University of Waikato, Hamilton, New ZealandGoogle Scholar
  18. Dile YT, Daggupati P, George C, Srinivasan R, Arnold J (2016) Introducing a new open source GIS user interface for the SWAT model. Environ Model Softw 85:129–138CrossRefGoogle Scholar
  19. Doherty J (2015) Calibration and uncertainty analysis for complex environmental models. Watermark Numerical Computing, Brisbane, AustraliaGoogle Scholar
  20. Donigian AS, Imhoff JC, Bicknell B, Kittle JL Jr (1984) Application guide for Hydrological Simulation Program-Fortran (HSPF): U.S. Environmental Protection Agency, Environmental Research Laboratory, Athens, GA, EPA-600/3-84-065, 177 pGoogle Scholar
  21. Durney P, Ritson, J, Druzynski A, Alkhaier F, Tutulic D, Sharma M (2014) Integrated catchment modelling of the Hinds Plains. Model development and scenario testing. Report No. R14/64 prepared for Environment Canterbury Regional Council by DHI Water & Environment, DenmarkGoogle Scholar
  22. Dymond J, Ausseil A-GE, Parfitt RL, Herzig A, McDowell R (2013) Nitrate and phosphorus leaching in New Zealand: a national perspective. N Z J Agric Res 56:49–59CrossRefGoogle Scholar
  23. Edmeades DC (1995) Modelling nutrient requirements – AgResearch’s approach. In: Currie LD, Loganathan P (eds) Fertiliser requirements of grazed pasture and field crops. Occasional report no. 8. Fertiliser and Lime Research Centre, Massey University, Palmerston North, New Zealand, pp 9–11Google Scholar
  24. Edmeades DC (2012) Developments in the management of soil fertility and pasture nutrition over the last 20 years. In: Currie LD, Christensen CL (eds) Occasional report no 25. Fertiliser and Lime Research Center, Massey University, Palmerston North, New ZealandGoogle Scholar
  25. Edmeades DC, McBride RM, Gray M (2016) An assessment of current fertiliser practices in New Zealand hill country. Hill Country Grassland Res Pract Ser 16:173–178Google Scholar
  26. Ekanayake J, Davie T (2004) The SWAT model applied to simulating nitrogen fluxes in the Motueka River catchment. Prepared for the Stakeholders of the Motueka Integrated Catchment Management Programme. Landcare ICM Report No. 2004-2005/04. Landcare Research, Lincoln, New ZealandGoogle Scholar
  27. Elliott S, Sorrell B (2002) Lake managers’ handbook: land-water interactions. Ministry for the Environment, Wellington, New ZealandGoogle Scholar
  28. Elliott AH, Stroud, MJ (2001) Prediction of nutrient loads entering Lake Taupo under various landuse scenarios. NIWA client report prepared for Environment Waikato, Ministry for the Environment, Genesis Power, Dairy Research Institute and Tuwharetoa Maori Trust Board EVWO1224, National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  29. Elliott AH, Alexander RB, Schwarz GE, Shankar U, Sukias JPS, McBride GB (2005) Estimation of nutrient sources and transport for New Zealand using the hybrid mechanistic-statistical model SPARROW. J Hydrol 44(1):1–27Google Scholar
  30. Elliott AH, Shankar, U, Hicks DM, Woods RA, Dymond JR (2008) SPARROW regional regression for sediment yields in New Zealand rivers. In: Schmidt J, Cochrane T, Phillips C, Elliott S, Davies T, Basher L (eds) Sediment dynamics in changing environments. Proceedings of a symposium held in Christchurch, New Zealand, December 2008, IAHS Publ, vol 325. International Association of Hydrological Sciences, Wallingford, UK, pp 242–249Google Scholar
  31. Elliott S, Parshotam A, Wadhwa S (2009) Tauranga harbour sediment study: catchment model results. NIWA client report HAM2009-046 prepared for Environment Bay of Plenty. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  32. Elliott S, Semadeni-Davies A, Shankar U (2011) CLUES catchment modelling – lessons from recent applications. In: Currie LD, Christensen CL (eds) Adding to the knowledge base for the nutrient manager. Occasional report No. 24. Fertilizer and Lime Research Centre, Massey University, Palmerston North, New ZealandGoogle Scholar
  33. Engel B, Storm D, White M, Arnold J, Arabi M (2007) A hydrologic/water quality model application protocol. J Am Water Resour Assoc 43(5):1223–1236CrossRefGoogle Scholar
  34. Euser T, Winsemius HC, Hrachowitz M, Fenicia F, Uhlenbrook S, Savenije HHG (2013) A framework to assess the realism of model structures using hydrological signatures. Hydrol Earth Syst Sci 17:1893–1912CrossRefGoogle Scholar
  35. Fenton T (2009) Overview of catchment scale nutrient modelling in New Zealand. Outcomes from a Workshop in Wellington, July 2009. http://envirolink.govt.nz/assets/Envirolink/769-HBRC113.pdf. Accessed 8 Sept 2018
  36. 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
  37. Golmohammadi G, Prashe S, Madani A, Rudra R (2014) Evaluating three hydrological distributed watershed models: MIKE-SHE, APEX, SWAT. Hydrology 1:20–39CrossRefGoogle Scholar
  38. Green M (2008) Central Waitemata Harbour Contaminant Study. Predictions of sediment, zinc and copper accumulation under future development scenario 1. Auckland Regional Council Technical Report TR 2008/043, Auckland, New ZealandGoogle Scholar
  39. Green M, Zeldis J (2015) Firth of Thames water quality and ecosystem health. Waikato Regional Council Technical Report 2015/23, Hamilton, New ZealandGoogle Scholar
  40. Green M, Timperley M, Collins R, Senior A, Adams R, Swales A, Williamson B, Mills G (2004a) Prediction of contaminant accumulation in the Upper Waitemata Harbour – methods. NIWA client report: HAM2003-087/1 prepared for Auckland Regional Council, National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  41. Green SR, van den Dijssel C and Clothier BE (2004b) Monitoring of nitrates within the Hawke’s Bay: a case study of Ingleton Farm near Tikokino. HortResearch Client Report S/320132/01, Palmerston North, New ZealandGoogle Scholar
  42. Green M, Parshotam A, Elliott S, Moores J, Hreinsson E (2010) Project Twin Streams value case: stage 3. Effects of climate change on sediment generation and accumulation in the central Waitemata Harbour and on stream erosion in the Project Twin Streams catchment. NIWA Client Report AKL-2010-032, National Institute of Water and Atmospheric Research, Auckland, New ZealandGoogle Scholar
  43. Green S, Manderson A, Clothier B, Mackay A, Benson M (2012) Catchment-wide modelling of land-use impacts on the Ruataniwha Plains. 25th Annual FLRC Workshop held at Massey University, February 2012. Advanced nutrient management: Gains from the past – goals for the future. Occasional Report No. 25. Fertilizer and Lime Research Centre, Massey University, Palmerston North, New ZealandGoogle Scholar
  44. Harper S (2010) Western ring route – Waterview connection. Assessment of associated sediment and contaminant loads. NIWA report prepared for NZ Transport Agency (NZTA), National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  45. Jacobson LM, David MB, Drinkwater LE (2011) A spatial analysis of phosphorus in the Mississippi River basin. J Environ Qual 40:931–941CrossRefGoogle Scholar
  46. Johnes PJ (1996) Evaluation and management of the impact of land use change on the nitrogen and phosphorus load delivered to surface waters: the export coefficient modelling approach. J Hydrol 183(3–4):323–349CrossRefGoogle Scholar
  47. Jones H, Hamilton DP (2014) Hydrodynamic modelling of Lake Whangape and Lake Waahi. Waikato Regional Council Technical Report 2014/24 prepared by University of Waikato, Hamilton, New ZealandGoogle Scholar
  48. Kelly R (2015) Papamoa East – a humdinger of a catchment. Stormwater conference 2015, Water New Zealand, 20–22 May, 2015, Auckland, New Zealand, http://www.waternz.org.nz/Article?Action=View&Article_id=390. Accessed 5 Sept 2017
  49. Knisel WG (1980) CREAMS: a field scale model for chemicals, runoff and erosion from agricultural management systems. Conservation Research Report No. 26. United States Department of Agriculture, Washington, DCGoogle Scholar
  50. Knisel W (1993) GLEAMS, groundwater loading effects of agricultural management systems. Version 2.1. UGA-CPES-BAED Publication No. 5. Prepared by University of Georgia Coastal Plain Experimental Station in co-operation with USDA-ARS Southeast Watershed Research Lab., Tifton, GAGoogle Scholar
  51. Krueger T, Quinton JN, Freer J, Macleod CJA, Bilotta GS, Brazier R, Butler P, Haygarth PM (2009) Uncertainties in data and models to describe event dynamics of agricultural sediment and phosphorus transfer. J Environ Qual 38(3):1137–1148CrossRefGoogle Scholar
  52. Larson SJ, Gilliom RJ (2001) Regression models for estimating herbicide concentrations in U.S. streams from watershed characteristics. J Am Water Resour Assoc 37:1349–1367CrossRefGoogle Scholar
  53. Larson SJ, Crawford CG, Gilliom RJ (2004) Development and application of watershed regressions for pesticides (WARP) for estimating atrazine concentration distributions in streams: U.S. Geological Survey Water-Resources investigations report 03-4047, Sacramento, CaliforniaGoogle Scholar
  54. LERNZdb (2015) LERNZ freshwater database. http://lernzdb.its.waikato.ac.nz. Accessed 5 Sept 2017
  55. Lilburne LR, Hewitt A, Webb T (2012) Soil and informatics science combine to develop Smap: a new generation soil information system for New Zealand. Geoderma 170:232–238CrossRefGoogle Scholar
  56. Lundquist C, Oldman J, Lewis M (2009) Predicting suitability of cockle Austrovenus stutchburyi restoration sites using hydrodynamic models of larval dispersal. N Z J Mar Freshw Res 43:735–748CrossRefGoogle Scholar
  57. McBride GB, Chapra SC (2011) Models of indicator organisms and zoonotic pathogens in agricultural watersheds. Ecol Model 222:2093–2102CrossRefGoogle Scholar
  58. Me W, Abell JM, Hamilton DP (2015) Effects of hydrologic conditions on SWAT model performance and parameter sensitivity for a small, mixed land use catchment in New Zealand. Hydrol Earth Syst Sci 19:4127–4147CrossRefGoogle Scholar
  59. Monaghan RM, Wilcock RJ, Smith LC, Rikkisetty B, Thorrold BS, Costall D (2006) Linkages between land management activities and water quality in an intensively farmed catchment in southern New Zealand. Agric Ecosyst Environ 118:211–222CrossRefGoogle Scholar
  60. MPCA (Minnesota Pollution Control Agency) (2007) Lake Pepin Watershed TMDL, Eutrophication and turbidity impairments project overview. https://www.pca.state.mn.us/sites/default/files/wq-iw9-01a.pdf. Accessed 5 Sept 2017
  61. MPCA (Minnesota Pollution Control Agency) (2010) Lake watershed total maximum daily load studies, Guidance document, https://www.pca.state.mn.us/sites/default/files/wq-strm7-38a.pdf. Accessed 5 Sept 2017
  62. Murphy A (1988) Skill scores based on the mean square error and their relationships to the correlation coefficient. Mon Weather Rev 116:2417–2424CrossRefGoogle Scholar
  63. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part IA discussion of principles. J Hydrol 10:282–290CrossRefGoogle Scholar
  64. Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2005) Soil and water assessment tool: theoretical documentation, version 2005. Texas A&M University System, TexasGoogle Scholar
  65. Nielsen A, Trolle D, Me W, Luo L, Han B-P, Liu Z, Olesen J, Jeppesen E (2013) Assessing ways to combat eutrophication in a Chinese drinking water reservoir using SWAT. Mar Freshw Res 64:1–18CrossRefGoogle Scholar
  66. Oldman JW, Swales A (1999) Maungamaungaroa Estuary numerical modelling and sedimentation. NIWA Client Report AEC70224, prepared for Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  67. Oldman J, Stroud MJ, Cummings VJ, Cooper AB (1998) Mahurangi land use scenario modelling. Client Report ARC70216/2, National Institute of Water and Atmsopheric Research, Hamilton, New ZealandGoogle Scholar
  68. Palliser CC, Parshotam A, Rutherford JC (2011) Using the ROTAN model to predict nitrogen loads to Lake Rotorua, New Zealand. In: Chan F, Marinova D, Anderssen RS (eds) MODSIM2011, 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, pp 2367–2373Google Scholar
  69. Park S (2014) Using OVERSEER within rules for the Lake Rotorua catchment. Report prepared by Headway Ltd for the Bay of Plenty Regional Council, Tauranga, New ZealandGoogle Scholar
  70. Parliamentary Commissioner for the Environment (2013) Water quality in New Zealand. Land use and nutrient pollution. http://www.pce.parliament.nz/assets/Uploads/PCE-Water-quality-land-use-web-amended.pdf. Accessed 15 Aug 2017
  71. Parshotam A (2008) South Eastern Manukau Harbour contaminant study. Sediment load model results. NIWA Client Report HAM2008-168 prepared for Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  72. Parshotam A (2010) GLEAMS model suite documentation and manual, NIWA Client Report HAM2010-093. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  73. Parshotam A (2015) Guidelines for the admissibility of farm and catchment models in the New Zealand environment courts. In: Weber T, McPhee MJ, Anderssen RS (eds) MODSIM2015, 21st International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2015, pp 490–496Google Scholar
  74. Parshotam A, Elliott S (2009) Application of CLUES to five monitored dairy catchments in New Zealand. NIWA Client Report HAM2009-132 prepared for AgResearch. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  75. Parshotam A, Wadhwa S (2007a) Predicting sediment generation in the Central Waitemata Harbour: land use scenarios for GLEAMS-CWH modelling. NIWA Client Report HAM2007-163 prepared for Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  76. Parshotam A, Wadhwa S (2007b) Predicting sediment generation in the Central Waitemata Harbour: model structure, setup and input data requirements. NIWA Client Report HAM2007-162 prepared for Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  77. Parshotam A, Wadhwa S (2008) Central Waitemata Harbour contaminant study. Model results for rural and earthworks sediment loads from the catchment. NIWA Client Report HAM2007-055 prepared for Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  78. Parshotam A, Wadhwa S, Samadeni-Davies A, Woods R (2008a) South Eastern Manukau Harbour contaminant study. Sediment load model structure, setup and input data. NIWA Client Report HAM2008-161 prepared for Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  79. Parshotam A, Wadhwa S, Samadeni-Davies A, Moores J (2008b) South eastern Manukau Harbour contaminant study. Landuse analysis. NIWA Client Report HAM2008-162 prepared for Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  80. Parshotam A, Moores J, Pattinson P, Harper S (2008c) South eastern Manukau Harbour contaminant study. Sediment load model evaluation. NIWA Client Report HAM2008-167 prepared for Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  81. Parshotam A, Hume T, Elliott S, Green M, Wadhwa S (2008d) Tauranga Harbour sediment study: specification of scenarios. NIWA Client Report HAM2008-117 prepared for Environment Bay of Plenty. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  82. Poeter E, Hill M, Banta E, Mehl S, Christensen S (2005) UCODE– 2005 and six other computer codes for universal sensitivity analysis, calibration, and uncertainty evaluation, Technical methods 6–a11. United States Geological Survey, Reston, VAGoogle Scholar
  83. Preston SD, Alexander RB, Woodside MD, Hamilton PA (2009) SPARROW modeling—enhancing understanding of the nation’s water quality: U.S. Geological Survey Fact Sheet 2009–3019Google Scholar
  84. Preston SD, Alexander RB, Schwarz GE, Crawford CG (2011) Factors affecting stream nutrient loads: a synthesis of regional SPARROW model results for the continental united states. J Am Water Res Assoc 47:891–915CrossRefGoogle Scholar
  85. Pritchard M, Reeve G, Swales A (2009a) Modelling storm-load sediment deposition thresholds for potential ecological effects in Okura Estaury/Karepiro Bay. Auckland Council Technical Report TR 2010/024, Auckland, New ZealandGoogle Scholar
  86. Pritchard M, Gorman R, Hume T (2009b) Tauranga Harbour sediment study: hydrodynamic and sediment transport modelling. NIWA client report HAM2009-032 prepared for Environment Bay of Plenty Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  87. Qian SS, Reckhow KH, Zhai J, McMahon G (2005) Nonlinear regression modeling of nutrient loads in streams: a Bayesian approach. Water Resour Res 41:W07012CrossRefGoogle Scholar
  88. Reckhow KH, Beaulac MN, Simpson JT (1980) Modeling phosphorus loading and lake response under uncertainty: a manual and compilation of export coefficients. Michigan State University, East Lansing, MIGoogle Scholar
  89. Refsgaard JC, van der Sluijs JP, Højberg AL, Vanrolleghem PA (2007) Uncertainty in the environmental modelling process – a framework and guidance. Environ Model Softw 22:1543–1155CrossRefGoogle Scholar
  90. Robertson DM, Saad DA (2013) SPARROW models used to understand nutrient sources in the Mississippi/Atchafalaya River Basin. J Environ Qual 42(5):1422–1440CrossRefGoogle Scholar
  91. Robertson DM, Saad DA, Schwarz GE (2014) Spatial variability in nutrient transport by HUC8, State, and Subbasin based on Mississippi/Atchafalaya River Basin SPARROW models.  https://doi.org/10.1111/jawr.12153 CrossRefGoogle Scholar
  92. Rodda H, Shankar U, Thorrold B (1997) The development of decision support tools for managing water quality in agricultural landscapes: Year 2. NIWA Consultancy Report MAF7021. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  93. Rutherford K, Palliser C, Wadhwa S (2009) Nitrogen exports from the Lake Rotorua catchment – calibration of the ROTAN model. NIWA Client Report to Bay of Plenty Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  94. Rutherford JC, Palliser C, Wadhwa S (2011) Prediction of loads to Lake Rotorua using ROTAN model. NIWA Client Report HAM2010-134. Prepared for the Bay of Plenty Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  95. Scavia D, Evans, MA (2012) Gulf of Mexico Forecast and Measurement. University of Michigan. http://download.pdf-world.net/2012-Gulf-of-Mexico-Hypoxia-Forecast-and-Measurement-Donald-Scavia-pdf-e1168.pdf. Accessed 13 March 2016
  96. Schoumans OF, Silgram M, Groenendijk P, Bouraou F, Andersen HE, Kronvang B, Behrendt H, Arheimer B, Johnsson H, Panagopoulos Y, Mimikou M, Lo Porto A, Reisser H, Le Gall G, Barr A, Anthony SG (2009) Description of nine nutrient loss models: capabilities and suitability based on their characteristics. J Environ Monit 11:506–514CrossRefGoogle Scholar
  97. Schwarz GE, Hoos AB, Alexander RB, Smith RA (2006) The SPARROW surface water-quality model: theory, application and user documentation. U.S. Geological survey techniques and methods report, Book 6, Chapter B3, Reston, VAGoogle Scholar
  98. Semadeni-Davies A, Shankar U, McBride G, Elliott S (2011) The CLUES project: tutorial manual for CLUES 3.1. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  99. Semadeni-Davies A, Hughes A, Elliott S (2015) Assessment of the CLUES Model for the Implementation of the National Policy Statement for Freshwater Management in the Auckland Region. Prepared by NIWA for Auckland Council. Auckland Council Technical Report 2015/014. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  100. Senior A, Oldman J, Green MO, Norkko A, Hewitt J, Collins RP, Stroud MJ, Cooper AB, Thrush S (2003) Risks to estuarine biota under proposed development in the Whitford catchment. NIWA Client Report HAM2003-016. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  101. SEWRPC (Southeastern Wisconsin Regional Planning Commission) (2015). Regional water quality plan. http://www.sewrpc.org/SEWRPC/Environment/LakeandStreamManagement.htm. Accessed 15 Aug 2017
  102. Shmueli G (2010) To explain or to predict? Stat Sci 25:289–310CrossRefGoogle Scholar
  103. Smith RA, Schwarz GE, Alexander RB (1997) Regional interpretation of water-quality monitoring data. Water Resour Res 33:2781–2798CrossRefGoogle Scholar
  104. Soranno PA, Hubler SL, Carpenter SR, Lathrop RC (1996) Phosphorus loads to surface waters: a simple model to account for spatial pattern of land use. Ecol Appl 6:865–878CrossRefGoogle Scholar
  105. Stroud MJ (2003) Modelling long-term daily sediment loads to the Mahurangi Estuary. NIWA Client Report HAM2003-144. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  106. Stroud MJ, Cooper AB (1997) Modelling sediment loads to the Mahurangi Estuary. NIWA Client Report ARC60211 to Auckland Regional Council. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  107. Stroud MJ, Cooper AB (1998) Predicting soil loss under outdoor vegetable production at Pukekohe. NIWA client report ARC60202. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  108. Stroud MJ, Cooper AB (1999) Assessment of sediment impacts on Okura estuary associated with catchment developments. Effects of sediment controls. NIWA client report ARC00202. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  109. Stroud MJ, Cooper AB, Bottcher AB, Hiscock JG, Pickering NB (1999) Sediment run-off from the catchment of Okura estuary. NIWA Client Report ARC90241/1. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  110. Thodsen H, Andersen HE, Blicher-Mathiesen G, Trolle D (2015) The combined effects of fertilizer reduction on high risk areas and increased fertilization on low risk areas, investigated using the SWAT model for a Danish catchment. Acta Agric Scand Sect B Soil Plant Sci 65:217–227Google Scholar
  111. Thorrold B, Rodda H, Monaghan R (1998) Modelling land use effects on water quality in the Oteramika catchment: final report on the Oteramika trial catchment project. Report prepared for the Southland Regional Council. AgResearch, Hamilton, New ZealandGoogle Scholar
  112. Tuckey B (2014) Kaituna River re-diversion and Ongatoro/Maketu Estuary Enhancement project numerical modelling. Report prepared for Bay of Plenty Regional Council, DHI Water and Environment Ltd, Auckland, New ZealandGoogle Scholar
  113. UNDP (2013) Issue brief: ocean hypoxia-‘dead zones’. United Nations Development Programme. http://www.undp.org/content/undp/en/home/librarypage/environmentenergy/water_governance/ocean_and_coastalareagovernance/issue-brief%2D%2D-ocean-hypoxia%2D%2Ddead-zones-.html. Accessed 8 Sept 2018
  114. USGS (2000) National land cover dataset: USGS Fact Sheet 1008–00. United States Geological Survey. https://pubs.usgs.gov/fs/2000/0108/report.pdf. Accessed 8 Sept 2018
  115. Vache K, McDonnell JJ (2006) A process-based rejectionist framework for evaluating catchment runoff model structure. Water Resour Res 42:W02409CrossRefGoogle Scholar
  116. Verburg P, Parshotam A, Palliser CC (2012) Nutrient budget for Lake Omapere. Prepared for Te Roopu Taiao o Utakura. NIWA Client Report HAM2012-030. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  117. Vesselinov V, Harp D (2012) Model analysis and decision support (MADS) for complex physics models. In: XIX International Conference on Water Resources – CMWR 2012, University of Illinois Urbana-Champaign, Illinois, USAGoogle Scholar
  118. Wagener T (2003) Evaluation of catchment models. Hydrol Process 17:2275–3378Google Scholar
  119. Walker WW Jr (1996) Simplified procedures for eutrophication assessment and prediction: U.S Army Corps of Engineers, Instruction Report W–96–2, Washington, DCGoogle Scholar
  120. Wellen C, Kamran-Disfani A-R, Arhonditsis GB (2015) Evaluation of the current state of distributed watershed nutrient water quality modeling. Environ Sci Technol 49:3278–3290CrossRefGoogle Scholar
  121. Wheeler D, Ledgard SF, Monaghan RM, McDowell R, DeKlein CAM (2006) Overseer development – what it is, what it does. In: Currie LD, Hanly JA (eds) Implementing sustainable nutrient management strategies in agriculture. Occasional Report No. 19. Fertiliser and Lime Research Centre, Massey University. Palmerston North, New Zealand, pp 231–236Google Scholar
  122. White MJ, Santhi C, Kannan N, Arnold JG, Harme RD, Norfleet L, Allen P, Diluzio M, Wang X, Attwood J, Haney E, Johnson M (2014) Nutrient delivery from the Mississippi River to the Gulf of Mexico and the effects of cropland conservation. J Soil Water Conserv 60:26–40CrossRefGoogle Scholar
  123. Wilcock RJ, Monaghan RM, Thorrold BS, Meredith AS, Betteridge K, Duncan MJ (2007) Land-water interactions in five contrasting dairying catchments: issues and solutions. Land Use Water Resour Res 7:2.1–2.10Google Scholar
  124. Williams JR, Izaurralde RC (2005) The APEX model. In: Singh VP, Frevert DK (eds) Watershed models. CRC Press, Boca Raton, FL, pp 437–482Google Scholar
  125. Williams R, Brown H, Ford R, Lilburne L, Pinxterhuis I, Robson M, Snow V, Taylor K, von Pein T (2014) The matrix of good management: defending good management practices and associated nutrient losses across primary industries. In: Currie LD, Christensen CL (eds) Nutrient management for the farm, catchment and community. Occasional Report No. 27. Fertilizer and Lime Research Centre, Massey University, Palmerston North, New ZealandGoogle Scholar
  126. Williamson B, Mills G (2009) The impacts of stormwater in Auckland’s aquatic receiving environment. A review of information 2005–2008. Report prepared by Diffuse Sources Ltd for Auckland Regional Council, TR 2009/111. Hamilton, New ZealandGoogle Scholar
  127. Williamson RB, Green MO, Stroud MJ, Hume TM, Pridmore RD (1998) Sedimentation in Orewa estuary: impacts of further urban and motorway development. NIWA Client Report to Auckland Regional Council, ARC80234. National Institute of Water and Atmospheric Research, Hamilton, New ZealandGoogle Scholar
  128. Woods R, Elliott S, Shankar U, Bidwell V, Harris S, Wheeler D, Clothier B, Green S, Hewitt A, Gibb R, Parfitt R (2006) The CLUES project: predicting the effects of land use on water quality – Stage II. NIWA Client Report CHC2006–09 prepared for Ministry of Agriculture and Forestry. National Institute of Water and Atmospheric Research, Christchurch, New ZealandGoogle Scholar
  129. WWF (2008) Breathless coastal seas. Worldwide wildlife fund – Germany. In: Lamp J (ed) Briefing paper: dead ocean zones – a global problem of the 21st century. WWF Deutschland, Frankfurt/MainGoogle Scholar
  130. Zeldis J, Shankar U, Plew D, Unwin M, Hoyle J (2012) Potential nutrient concentrations of Waikato Region Estuaries and preliminary estimates of their trophic state. Prepared for Waikato Regional Council. NIWA Client Report CHC2012-022. National Institute of Water and Atmospheric Research, Christchurch, New ZealandGoogle 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.Cleanwaters NZHamiltonNew Zealand
  3. 3.U.S. Geological Survey, Upper Midwest Water Science CenterMiddletonUSA

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