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Applicability of water quality models around the world—a review

  • Cássia Monteiro da Silva Burigato Costa
  • Leidiane da Silva Marques
  • Aleska Kaufmann Almeida
  • Izabel Rodrigues Leite
  • Isabel Kaufmann de AlmeidaEmail author
Review Article
  • 142 Downloads

Abstract

Water quality models are important tools used in the management of water resources. The models are usually developed for specific regions, with particular climates and physical characteristics. Thus, applying these models in regions other than those they were designed for can generate large simulation errors. With consideration to these discrepancies, the goal of this study is to identify the models employed in different countries and assist researchers in the selection of the most appropriate models for management purposes. Published studies from the last 21 years (1997–2017) that discuss the application of water quality models were selected from three engineering databases: SpringerLink, Web of Science, and Scopus. Seven models for water quality simulations have been widely applied around the world: AQUATOX, CE-QUAL-W2, EFDC, QUALs, SWAT, SPARROW, and WASP. The countries most frequently applying water quality models are the USA, followed by China, and South Korea. SWAT was the most used model, followed by the QUAL group and CE-QUAL-W2. This study provides the opportunity for researchers, who wish to study countries with fewer cases of applied water quality models, to easily identify the work from that region. Furthermore, this work collated central themes of interest and the most simulated parameters for the seven countries that most frequently employed the water quality models.

Keywords

Engineering database AQUATOX CE-QUAL-W2 SWAT QUALs water resources 

Notes

Acknowledgments

The authors are grateful to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—CAPES, to the Programa de Apoio à Pós-graduação—PROAP and to the Federal University of Mato Grosso do Sul—UFMS for their support in the development of this work.

Supplementary material

11356_2019_6637_MOESM1_ESM.docx (135 kb)
ESM 1 (DOCX 135 kb)
11356_2019_6637_MOESM2_ESM.docx (69 kb)
ESM 2 (DOCX 68 kb)

References

  1. Abbaspour KC, Rouholahnejad E, Vaghefi S, Srinivasan R, Yang H, Kløve B (2015) A continental-scale hydrology and water quality model for Europe: calibration and uncertainty of a high-resolution large-scale SWAT model. J Hydrol 524:733–752.  https://doi.org/10.1016/j.jhydrol.2015.03.027 CrossRefGoogle Scholar
  2. Abouali M, Nejadhashemi AP, Daneshvar F, Adhikari U, Herman MR, Calappi TJ, Rohn BG (2017) Evaluation of wetland implementation strategies on phosphorus reduction at a watershed scale. J Hydrol 552:105–120.  https://doi.org/10.1016/j.jhydrol.2017.06.038 CrossRefGoogle Scholar
  3. Afshar A, Masoumi F (2016) Waste load reallocation in river–reservoir systems: simulation–optimization approach. Environ Earth Sci 75(1):53 https://link.springer.com/article/10.1007/s12665-015-4812-x CrossRefGoogle Scholar
  4. Afshar A, Kazemi H, Saadatpour M (2011) Particle swarm optimization for automatic calibration of large scale water quality model (CE-QUAL-W2): application to Karkheh Reservoir, Iran. Water Resour Manag 25(10):2613–2632 https://link.springer.com/article/10.1007/s11269-011-9829-7 CrossRefGoogle Scholar
  5. Afshar A, Feizi F, Moghadam AY, Saadatpour M (2017) Enhanced CE-QUAL-W2 model to predict the fate and transport of volatile organic compounds in water body: Gheshlagh reservoir as case study. Environ Earth Sci 76(23):803.  https://doi.org/10.1016/j.jhydrol.2016.01.062 CrossRefGoogle Scholar
  6. Ali I, Bruen M (2016) Methodology and application of the combined SWAT-HSPF model. Environ Process 3(3):645–661.  https://doi.org/10.1007/s40710-016-0167-x CrossRefGoogle Scholar
  7. Almendinger JE, Murphy MS, Ulrich JS (2014) Use of the Soil and Water Assessment Tool to scale sediment delivery from field to watershed in an agricultural landscape with topographic depressions. J Environ Qual 43(1):9–17.  https://doi.org/10.2134/jeq2011.0340 CrossRefGoogle Scholar
  8. Ambrose RB, Wool TA (2009) WASP7 stream transport model theory and user’s guide. Environmental Protection Agency, Athens, GA, USA, EPA/600/R-09/100, available at: www.epa. gov/athens. Access: April 2017Google Scholar
  9. Amirkhani M, Bozorg-Haddad O, Fallah-Mehdipour E, Loáiciga HA (2016) Multiobjective reservoir operation for water quality optimization. J Irrig Drain Eng 142(12):04016065.  https://doi.org/10.1061/(ASCE)IR.1943-4774.0001105 CrossRefGoogle Scholar
  10. Arabi M, Govindaraju RS, Hantush MM (2006) Cost-effective allocation of watershed management practices using a genetic algorithm. Water Resour Res 42(10).  https://doi.org/10.1029/2006WR004931
  11. Arnold JG, Fohrer N (2005) SWAT2000: current capabilities and research opportunities in applied watershed modelling. Hydrol Process 19(3):563–572.  https://doi.org/10.1002/hyp.5611 CrossRefGoogle Scholar
  12. Arnold JG, Williams JR, Srinivasan R, King KW (1996) SWAT manual. USDA Agricultural Service and Blackland Research Center, TempleGoogle Scholar
  13. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development 1. JAWRA Journal of the American Water Resources Association 34(1):73–89.  https://doi.org/10.1111/j.1752-1688.1998.tb05961.x CrossRefGoogle Scholar
  14. Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R et al (2012) SWAT: model use, calibration, and validation. Trans ASABE 55(4):1491–1508.  https://doi.org/10.13031/2013.42256 CrossRefGoogle Scholar
  15. Ashouri MJ, Rafei M (2018) Analysis of asymmetries in air pollution with water resources, and energy consumption in Iran. Environ Sci Pollut Res 25(18):17590–17601 https://link.springer.com/article/10.1007/s11356-018-1825-5 CrossRefGoogle Scholar
  16. Bai J, Shen Z, Yan T (2016) Effectiveness of vegetative filter strips in abating fecal coliform based on modified soil and water assessment tool. Int J Environ Sci Technol 13(7):1723–1730 https://link.springer.com/article/10.1007/s13762-016-1011-6 CrossRefGoogle Scholar
  17. Bailey RT, Ahmadi M (2014) Spatial and temporal variability of in-stream water quality parameter influence on dissolved oxygen and nitrate within a regional stream network. Ecol Model 277:87–96.  https://doi.org/10.1016/j.ecolmodel.2014.01.015 CrossRefGoogle Scholar
  18. Beeson PC, Sadeghi AM, Lang MW, Tomer MD, Daughtry CS (2014) Sediment delivery estimates in water quality models altered by resolution and source of topographic data. J Environ Qual 43(1):26–36.  https://doi.org/10.2134/jeq2012.0148 CrossRefGoogle Scholar
  19. Booty W, Benoy G (2009) Multicriteria review of nonpoint source water quality models for nutrients, sediments, and pathogens. Water Qual Res J 44(4):365–377.  https://doi.org/10.2166/wqrj.2009.037 CrossRefGoogle Scholar
  20. Borah DK, Bera M (2003) Watershed-scale hydrologic and nonpoint-source pollution models: review of mathematical bases. Trans ASAE 46(6):1553.  https://doi.org/10.13031/2013.15644 CrossRefGoogle Scholar
  21. Borah DK, Bera M (2004) Watershed-scale hydrologic and nonpoint-source pollution models: review of applications. Transactions of the ASAE 47(3):789.  https://doi.org/10.13031/2013.16110 CrossRefGoogle Scholar
  22. Bowen JD, Hieronymus JW (2003) A CE-QUAL-W2 model of Neuse Estuary for total maximum daily load development. J Water Resour Plan Manag 129(4):283–294.  https://doi.org/10.1061/(ASCE)0733-9496(2003)129:4(283 CrossRefGoogle Scholar
  23. Bressiani DA, Gassman PW, Fernandes JG, Garbossa LHP, Srinivasan R, Bonumá NB, Mendiondo EM (2015) Review of soil and water assessment tool (SWAT) applications in Brazil: challenges and prospects. Int J Agric Biol Eng 8(3):9–35.  https://doi.org/10.3965/j.ijabe.20150803.1765 CrossRefGoogle Scholar
  24. Brito D, Ramos TB, Gonçalves MC, Morais M, Neves R (2018) Integrated modelling for water quality management in a eutrophic reservoir in south-eastern Portugal. Environ Earth Sci 77(2):40.  https://doi.org/10.1007/s12665-017-7221-5 CrossRefGoogle Scholar
  25. Brown LC, Barnwell TO (1985) Computer Program Documentation for the Enhanced Stream Water Quality Model QUAL 2E (No. 471). National Council of the Paper Industry for Air and Stream Improvement, IncorporatedGoogle Scholar
  26. Brown LC, Barnwell TO (1987) The enhanced stream water quality models QUAL2E and QUAL2E-UNCAS: documentation and user manual. US Environmental Protection Agency. Office of Research and Development. Environmental Research Laboratory, Athens, p 189Google Scholar
  27. Buccola NL, Risley JC, Rounds SA (2016) Simulating future water temperatures in the North Santiam River, Oregon. J Hydrol 535:318–330.  https://doi.org/10.1016/j.jhydrol.2016.01.062 CrossRefGoogle Scholar
  28. Burn DH, McBean EA (1985) Optimization modeling of water quality in an uncertain environment. Water Resour Res 21(7):934–940.  https://doi.org/10.1029/WR021i007p00934 CrossRefGoogle Scholar
  29. Canu DM, Umgiesser G, Solidoro C (2001) Short-term simulations under winter conditions in the lagoon of Venice: a contribution to the environmental impact assessment of temporary closure of the inlets. Ecol Model 138(1-3):215–230.  https://doi.org/10.1016/S0304-3800(00)00403-8 CrossRefGoogle Scholar
  30. Chang C, Sun D, Feng P, Zhang M, Ge N (2017) Impacts of nonpoint source pollution on water quality in the Yuqiao reservoir. Environ Eng Sci 34(6):418–432.  https://doi.org/10.1089/ees.2016.0124 CrossRefGoogle Scholar
  31. Chen Y, Zou R, Han S, Bai S, Faizullabhoy M, Wu Y, Guo H (2017) Development of an integrated water quality and macroalgae simulation model for Tidal Marsh eutrophication control decision support. Water 9(4):277.  https://doi.org/10.3390/w9040277 CrossRefGoogle Scholar
  32. Chinyama A, Ochieng GM, Nhapi I, Otieno FAO (2014) A simple framework for selection of water quality models. Rev Environ Sci Biotechnol 13(1):109–119 https://link.springer.com/article/10.1007/s11157-013-9321-3 CrossRefGoogle Scholar
  33. Chung SW, Gu RR (2009) Prediction of the fate and transport processes of atrazine in a reservoir. Environ Manag 44(1):46–61 https://link.springer.com/article/10.1007/s00267-009-9312-x CrossRefGoogle Scholar
  34. Cole TM, Wells SA (2006) CE-QUAL-W2: A two-dimensional, laterally averaged, hydrodynamic and water quality model, version 3.5Google Scholar
  35. Cools J, Broekx S, Vandenberghe V, Sels H, Meynaerts E, Vercaemst P et al (2011) Coupling a hydrological water quality model and an economic optimization model to set up a cost-effective emission reduction scenario for nitrogen. Environ Model Softw 26(1):44–51.  https://doi.org/10.1016/j.envsoft.2010.04.017 CrossRefGoogle Scholar
  36. Cox BA (2003) A review of currently available in-stream water-quality models and their applicability for simulating dissolved oxygen in lowland rivers. Sci Total Environ 314:335–377.  https://doi.org/10.1016/S0048-9697(03)00063-9 CrossRefGoogle Scholar
  37. Dai T, Labadie JW (2001) River basin network model for integrated water quantity/quality management. J Water Resour Plan Manag 127(5):295–305.  https://doi.org/10.1061/(ASCE)0733-9496(2001)127:5(295 CrossRefGoogle Scholar
  38. Debele B, Srinivasan R, Parlange JY (2008) Coupling upland watershed and downstream waterbody hydrodynamic and water quality models (SWAT and CE-QUAL-W2) for better water resources management in complex river basins. Environ Model Assess 13(1):135–153 https://link.springer.com/article/10.1007/s10666-006-9075-1 CrossRefGoogle Scholar
  39. Defne Z; Spitz FJ, DePaul V, Wool TA (2017) Toward a comprehensive water-quality modeling of Barnegat Bay: development of ROMS to WASP coupler. In: Buchanan GA, Belton TJ, Paudel B (eds), A Comprehensive Assessment of Barnegat Bay-Little Egg Harbor, New JerseyGoogle Scholar
  40. Di Luzio M, Arnold JG, Srinivasan R (2004) Integration of SSURGO maps and soil parameters within a geographic information system and nonpoint source pollution model system. J Soil Water Conserv 59(4):123–133Google Scholar
  41. Di Toro DM, Fitzpatrick JJ, Thomann RV (1983) Documentation for water quality analysis simulation program (WASP) and model verification program (MVP). Environmental Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Washington, DCGoogle Scholar
  42. Douglas-Mankin KR, Srinivasan R, Arnold JG (2010) Soil and Water Assessment Tool (SWAT) model: current developments and applications. Trans ASABE 53(5):1423–1431.  https://doi.org/10.13031/2013.34915 CrossRefGoogle Scholar
  43. Ehtiat M, Mousavi SJ, Srinivasan R (2018) Groundwater modeling under variable operating conditions using SWAT, MODFLOW and MT3DMS: A catchment scale approach to water resources management. Water Resour Manag 32(5):1631–1649.  https://doi.org/10.1007/s11269-017-1895-z CrossRefGoogle Scholar
  44. Ekdal A, Gürel M, Guzel C, Erturk A, Tanik A, Gonenc IE (2011) Application of WASP and SWAT models for a Mediterranean coastal lagoon with limited seawater exchange. J Coast Res:1023–1027Google Scholar
  45. Ennet P, Pachel K, Viies V, Jurimagi L, Elken R (2008) Estimating water quality in river basins using linked models and databases/andmebaasidel rajanev veekvaliteedi modelleerimine. Estonian. J Ecol 57(2):83–100Google Scholar
  46. Fan C, Ko CH, Wang WS (2009) An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation. J Environ Manag 90(5):1824–1832.  https://doi.org/10.1016/j.jenvman.2008.11.011 CrossRefGoogle Scholar
  47. Fohrer N, Dietrich A, Kolychalow O, Ulrich U (2014) Assessment of the environmental fate of the herbicides flufenacet and metazachlor with the SWAT model. J Environ Qual 43(1):75–85.  https://doi.org/10.2134/jeq2011.0382 CrossRefGoogle Scholar
  48. Franceschini S, Tsai CW (2010) Assessment of uncertainty sources in water quality modeling in the Niagara River. Adv Water Resour 33(4):493–503.  https://doi.org/10.1016/j.advwatres.2010.02.001 CrossRefGoogle Scholar
  49. Frey SK, Topp E, Edge T, Fall C, Gannon V, Jokinen C et al (2013) Using SWAT, Bacteroidales microbial source tracking markers, and fecal indicator bacteria to predict waterborne pathogen occurrence in an agricultural watershed. Water Res 47(16):6326–6337.  https://doi.org/10.1016/j.watres.2013.08.010 CrossRefGoogle Scholar
  50. Fu C, James AL, Yao H (2014) SWAT-CS: revision and testing of SWAT for Canadian Shield catchments. J Hydrol 511:719–735.  https://doi.org/10.1016/j.jhydrol.2014.02.023 CrossRefGoogle Scholar
  51. Galbiati L, Bouraoui F, Elorza FJ, Bidoglio G (2006) Modeling diffuse pollution loading into a Mediterranean lagoon: development and application of an integrated surface–subsurface model tool. Ecol Model 193(1-2):4–18.  https://doi.org/10.1016/j.ecolmodel.2005.07.036 CrossRefGoogle Scholar
  52. Gao L, Li D (2014) A review of hydrological/water-quality models. Front Agric Sci Eng 1(4):267.  https://doi.org/10.15302/J-FASE-2014041 CrossRefGoogle Scholar
  53. 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(4):1211–1250.  https://doi.org/10.13031/2013.23637 CrossRefGoogle Scholar
  54. Gassman PW, Sadeghi AM, Srinivasan R (2014) Applications of the SWAT model special section: overview and insights. J Environ Qual 43(1):1–8.  https://doi.org/10.2134/jeq2013.11.0466 CrossRefGoogle Scholar
  55. Ghosh NC, McBean EA (1998) Water quality modeling of the Kali River, India. Water Air Soil Pollut 102(1-2):91–103 https://link.springer.com/article/10.1023/A:1004912216834 CrossRefGoogle Scholar
  56. Hamrick JM (1992) A three-dimensional environmental fluid dynamics computer code: Theoretical and computational aspects.Google Scholar
  57. Han KY, Kim SH, Bae DH (2001) Stochastic water quality analysis using reliability method 1. JAWRA Journal of the American Water Resources Association 37(3):695–708.  https://doi.org/10.1111/j.1752-1688.2001.tb05504.x CrossRefGoogle Scholar
  58. Himanshu SK, Pandey A, Shrestha P (2017) Application of SWAT in an Indian river basin for modeling runoff, sediment and water balance. Environ Earth Sci 76(1):3 https://link.springer.com/article/10.1007/s12665-016-6316-8 CrossRefGoogle Scholar
  59. Hoang L, Schneiderman EM, Moore KE, Mukundan R, Owens EM, Steenhuis TS (2017) Predicting saturation-excess runoff distribution with a lumped hillslope model: SWAT-HS. Hydrol Process 31(12):2226–2243.  https://doi.org/10.1002/hyp.11179 CrossRefGoogle Scholar
  60. Hoang BH, Hien HN, Dinh NTN, Thao NA, Ha PTT, Kandasamy J, Nguyen TV (2019) Integration of SWAT and QUAL2K for water quality modeling in a data scarce basin of Cau River basin in Vietnam. Ecohydrol Hydrobiol.  https://doi.org/10.1016/j.ecohyd.2019.03.005 CrossRefGoogle Scholar
  61. Hwang JY, Do Kim Y, Kwon JH, Park JH, Noh JW, Yi YK (2014) Hydrodynamic and water quality modeling for gate operation: A case study for the Seonakdong River basin in Korea. KSCE J Civ Eng 18(1):73–80 https://link.springer.com/article/10.1007/s12205-013-0025-6 CrossRefGoogle Scholar
  62. Jager HI, Baskaran LM, Schweizer PE, Turhollow AF, Brandt CC, Srinivasan R (2015) Forecasting changes in water quality in rivers associated with growing biofuels in the Arkansas-White-Red river drainage, USA. GCB Bioenergy 7(4):774–784.  https://doi.org/10.1111/gcbb.12169 CrossRefGoogle Scholar
  63. Jayakody P, Parajuli PB, Brooks JP (2014) Evaluating spatial and temporal variability of fecal coliform bacteria loads at the Pelahatchie watershed in Mississippi. Hum Ecol Risk Assess 20(4):1023–1041.  https://doi.org/10.1080/10807039.2013.784155 CrossRefGoogle Scholar
  64. Jayakrishnan RSRS, Srinivasan R, Santhi C, Arnold JG (2005) Advances in the application of the SWAT model for water resources management. Hydrological Processes: An International Journal 19(3):749–762.  https://doi.org/10.1002/hyp.5624 CrossRefGoogle Scholar
  65. Jeong H, Kim H, Jang T, Park S (2016) Assessing the effects of indirect wastewater reuse on paddy irrigation in the Osan River watershed in Korea using the SWAT model. Agric Water Manag 163:393–402.  https://doi.org/10.1016/j.agwat.2015.08.018 CrossRefGoogle Scholar
  66. Jha M, Babcock BA, Gassman PW, Kling CL (2009) Economic and environmental impacts of alternative energy crops. Int Agric Eng J 18(3/4):15–23Google Scholar
  67. Jia H, Wang S, Wei M, Zhang Y (2011) Scenario analysis of water pollution control in the typical peri-urban river using a coupled hydrodynamic-water quality model. Front Environ Sci Eng China 5(2):255–265.  https://doi.org/10.1007/s11783-010-0279-x CrossRefGoogle Scholar
  68. Jia H, Liang S, Zhang Y (2015) Assessing the impact on groundwater safety of inter-basin water transfer using a coupled modeling approach. Front Environ Sci Eng (1):84–95.  https://doi.org/10.1007/s11783-014-0741-2 CrossRefGoogle Scholar
  69. Justić D, Wang L (2014) Assessing temporal and spatial variability of hypoxia over the inner Louisiana–upper Texas shelf: application of an unstructured-grid three-dimensional coupled hydrodynamic-water quality model. Cont Shelf Res 72:163–179.  https://doi.org/10.1016/j.csr.2013.08.006 CrossRefGoogle Scholar
  70. Kannel PR, Kanel SR, Lee S, Lee YS, Gan TY (2011) A review of public domain water quality models for simulating dissolved oxygen in rivers and streams. Environ Model Assess 16(2):183–204 https://link.springer.com/article/10.1007/s10666-010-9235-1CrossRefGoogle Scholar
  71. Khatami A, Siosemarde M (2016) The Simulation of Mahabad Dam Eutrophication by Multidimensional CE-QUAL-W2 model. Int J Adv Biotechnol Res 7:1466–1474Google Scholar
  72. Kim CG, Park SW, Kim NW (2011) Analyzing hydrological transport characteristics of nonpoint source pollutants using SWAT. Appl Eng Agric 27(6):905–915.  https://doi.org/10.13031/2013.40630 CrossRefGoogle Scholar
  73. Kim DK, Zhang W, Hiriart-Baer V, Wellen C, Long T, Boyd D, Arhonditsis GB (2014a) Towards the development of integrated modelling systems in aquatic biogeochemistry: a Bayesian approach. J Great Lakes Res 40:73–87.  https://doi.org/10.1016/j.jglr.2014.04.005 CrossRefGoogle Scholar
  74. Kim K, Park M, Min JH, Ryu I, Kang MR, Park LJ (2014b) Simulation of algal bloom dynamics in a river with the ensemble Kalman filter. J Hydrol 519:2810–2821.  https://doi.org/10.1016/j.jhydrol.2014.09.073 CrossRefGoogle Scholar
  75. Lai YC, Yang CP, Hsieh CY, Wu CY, Kao CM (2011) Evaluation of non-point source pollution and river water quality using a multimedia two-model system. J Hydrol 409(3-4):583–595.  https://doi.org/10.1016/j.jhydrol.2011.08.040 CrossRefGoogle Scholar
  76. Lee JM, Park YS, Kum D, Jung Y, Kim B, Hwang SJ et al (2014) Assessing the effect of watershed slopes on recharge/baseflow and soil erosion. Paddy Water Environ 12(1):169–183. https://link.springer.com/article/10.1007/s10333-014-0448-9 CrossRefGoogle Scholar
  77. LEI B, HUANG S, QIAO M, LI T, WANG Z (2008) Prediction of the environmental fate and aquatic ecological impact of nitrobenzene in the Songhua River using the modified AQUATOX model. J Environ Sci 20(7):769–777.  https://doi.org/10.1016/S1001-0742(08)62125-7 CrossRefGoogle Scholar
  78. Liang W, Yang M (2019) Urbanization, economic growth and environmental pollution: evidence from China. Sust Comput Inform Syst 21(1-9).  https://doi.org/10.1016/j.suscom.2018.11.007 Google Scholar
  79. Lin CH, Huang TH, Shaw D (2010a) Applying water quality modeling to regulating land development in a watershed. Water Resour Manag 24(4):629–640 https://link.springer.com/article/10.1007/s11269-009-9462-x CrossRefGoogle Scholar
  80. Lin CE, Kao CM, Jou CJ, Lai YC, Wu CY, Liang SH (2010b) Preliminary identification of watershed management strategies for the Houjing river in Taiwan. Water Sci Technol 62(7):1667–1675.  https://doi.org/10.2166/wst.2010.460 CrossRefGoogle Scholar
  81. Liu WC, Chen HH, Hsieh WH, Chang CH (2006) Linking watershed and eutrophication modelling for the Shihmen Reservoir, Taiwan. Water Sci Technol 54(11-12):39–46.  https://doi.org/10.2166/wst.2006.834 CrossRefGoogle Scholar
  82. Liu Y, Yang W, Leon L, Wong I, McCrimmon C, Dove A, Fong P (2016) Hydrologic modeling and evaluation of Best Management Practice scenarios for the Grand River watershed in Southern Ontario. J Great Lakes Res 42(6):1289–1301.  https://doi.org/10.1016/j.jglr.2016.02.008 CrossRefGoogle Scholar
  83. Luo F, Li R (2009) 3D Water environment simulation for North Jiangsu offshore sea based on EFDC. J Water Resour Protect 1(1):41CrossRefGoogle Scholar
  84. Mekonnen BA, Mazurek KA, Putz G (2017) Modeling of nutrient export and effects of management practices in a cold-climate prairie watershed: Assiniboine River watershed, Canada. Agric Water Manag 180:235–251.  https://doi.org/10.1016/j.agwat.2016.06.023 CrossRefGoogle Scholar
  85. Meric D, Hellweger F, Barbuto S, Rahbar N, Alshawabkeh AN, Sheahan TC (2012) Model prediction of long-term reactive core mat efficacy for capping contaminated aquatic sediments. J Environ Eng 139(4):564–575.  https://doi.org/10.1061/(ASCE)EE.1943-7870.0000635 CrossRefGoogle Scholar
  86. Moses SA, Janaki L, Joseph S, Joseph J (2015) Water quality prediction capabilities of WASP model for a tropical lake system. Lakes Reserv Res Manag 20(4):285–299.  https://doi.org/10.1111/lre.12110 CrossRefGoogle Scholar
  87. Muenich RL, Chaubey I, Pyron M (2016) Evaluating potential water quality drivers of a fish regime shift in the Wabash River using the SWAT model. Ecol Model 340:116–125.  https://doi.org/10.1016/j.ecolmodel.2016.09.010 CrossRefGoogle Scholar
  88. Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2011) Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute, College StationGoogle Scholar
  89. Ning SK, Chang NB, Yang L, Chen HW, Hsu HY (2001) Assessing pollution prevention program by QUAL2E simulation analysis for the Kao-Ping River Basin, Taiwan. J Environ Manag 61(1):61–76.  https://doi.org/10.1006/jema.2000.0397 CrossRefGoogle Scholar
  90. Noh J, Kim JC, Park J (2014) Turbidity control in downstream of the reservoir: the Nakdong River in Korea. Environ Earth Sci 71(4):1871–1880 https://link.springer.com/article/10.1007%2Fs12665-013-2589-3 CrossRefGoogle Scholar
  91. Nourmohammadi Dehbalaei F, Javan M, Eghbalzaeh A, Eftekhari M, Fatemi SE (2016) Assessment of Ilam reservoir eutrophication response in controlling water inflow. Civil Eng Infrastructures J 49(2):215–234.  https://doi.org/10.7508/CEIJ.2016.02.003 CrossRefGoogle Scholar
  92. Nyeko M (2015) Hydrologic modelling of data scarce basin with SWAT model: capabilities and limitations. Water Resour Manag 29(1):81–94 https://link.springer.com/article/10.1007/s11269-014-0828-3 CrossRefGoogle Scholar
  93. Panagopoulos Y, Gassman PW, Jha MK, Kling CL, Campbell T, Srinivasan R et al (2015) A refined regional modeling approach for the Corn Belt–Experiences and recommendations for large-scale integrated modeling. J Hydrol 524:348–366.  https://doi.org/10.1016/j.jhydrol.2015.02.039 CrossRefGoogle Scholar
  94. Pandey VK, Panda SN, Sudhakar S (2005) Modelling of an agricultural watershed using remote sensing and a geographic information system. Biosyst Eng 90(3):331–347.  https://doi.org/10.1016/j.biosystemseng.2004.10.001 CrossRefGoogle Scholar
  95. Park RA (1974) A generalized model for simulating lake ecosystems. SIMULATION 23(2):33–50.  https://doi.org/10.1177/003754977402300201 CrossRefGoogle Scholar
  96. Park RA, Clough JS (2014) Aquatox (Release 3.1 plus). Modeling environmental fate and ecological effects in aquatic ecosystems.Technical Documentation, Volume 2, Environmental Protection AgencyGoogle Scholar
  97. Park SS, Lee YS (2002) A water quality modeling study of the Nakdong River, Korea. Ecol Model 152(1):65–75.  https://doi.org/10.1016/S0304-3800(01)00489-6 CrossRefGoogle Scholar
  98. Park RA, Connolly CI, Albanese JR, Clesceri LS, Heitzman GW (1982) Modeling the fate of toxic organic materials in aquatic environments. US Environmental Protection Agency, Environmental Research Laboratory, Washington, D.C.Google Scholar
  99. Park RA, Anderson JJ, Swartzman GL, Morison R, Emlen JM (1988) Assessment of risks of toxic pollutants to aquatic organisms and ecosystems using a sequential modeling approach. In Fate and Effects of Pollutants on Aquatic Organisms and Ecosystems. Proceedings of USA-USSR Symposium, Athens, Georgia October 19-21, 1987. ReportGoogle Scholar
  100. Park RA, Firlie B, Camacho R, Sappington K, Coombs M, Mauriello D (1995) AQUATOX, a general fate and effects model for aquatic ecosystems. Water Environ Fede 3:7–17Google Scholar
  101. Park RA, Clough JS, Wellman MC (2008) AQUATOX: modeling environmental fate and ecological effects in aquatic ecosystems. Ecol Model 213(1):1–15.  https://doi.org/10.1016/j.ecolmodel.2008.01.015 CrossRefGoogle Scholar
  102. Park JY, Park GA, Kim SJ (2013) Assessment of future climate change impact on water quality of Chungju Lake, South Korea, Using WASP Coupled with SWAT. J Am Water Resour Assoc 49(6):1225–1238.  https://doi.org/10.1111/jawr.12085 CrossRefGoogle Scholar
  103. Park JY, Yu YS, Hwang SJ, Kim C, Kim SJ (2014) SWAT modeling of best management practices for Chungju dam watershed in South Korea under future climate change scenarios. Paddy Water Environ 12(1):65–75 https://link.springer.com/article/10.1007/s10333-014-0424-4 CrossRefGoogle Scholar
  104. Parmar DL, Keshari AK (2014) Wasteload allocation using wastewater treatment and flow augmentation. Environ Model Assess 19(1):35–44 https://link.springer.com/article/10.1007/s10666-013-9378-y CrossRefGoogle Scholar
  105. Pelletier G, Chapra S (2006) A modeling framework for simulating river and stream water quality. Environmental Assessment Program, Olympia, pp 98504–97710Google Scholar
  106. Pelletier GJ, Chapra SC, Tao H (2006) QUAL2Kw–A framework for modeling water quality in streams and rivers using a genetic algorithm for calibration. Environ Model Softw 21(3):419–425.  https://doi.org/10.1016/j.envsoft.2005.07.002 CrossRefGoogle Scholar
  107. Peng S, Fu GYZ, Zhao XH (2010) Integration of USEPA WASP model in a GIS platform. J Zhejiang Univ Sci A 11(12):1015–1024 https://link.springer.com/article/10.1631/jzus.A1000244 CrossRefGoogle Scholar
  108. Peng H, Zheng X, Chen L, Wei Y (2016) Analysis of numerical simulations and influencing factors of seasonal manganese pollution in reservoirs. Environ Sci Pollut Res 23(14):14362–14372 https://link.springer.com/article/10.1007/s11356-016-6380-3 CrossRefGoogle Scholar
  109. Privette CV, Smink J (2017) Assessing the potential impacts of WWTP effluent reductions within the Reedy River watershed. Ecol Eng 98:11–16.  https://doi.org/10.1016/j.ecoleng.2016.10.058 CrossRefGoogle Scholar
  110. Quijano JC, Zhu Z, Morales V, Landry BJ, Garcia MH (2017) Three-dimensional model to capture the fate and transport of combined sewer overflow discharges: a case study in the Chicago Area Waterway System. Sci Total Environ 576:362–373.  https://doi.org/10.1016/j.scitotenv.2016.08.191 CrossRefGoogle Scholar
  111. Rajib MA, Ahiablame L, Paul M (2016) Modeling the effects of future land use change on water quality under multiple scenarios: a case study of low-input agriculture with hay/pasture production. Sustain Water Qual Ecol 8:50–66.  https://doi.org/10.1016/j.swaqe.2016.09.001 CrossRefGoogle Scholar
  112. Rim CS, Lee JT, Yoon SE, Shin JK (2006) Prediction of pollutant movement in a regulated large river. In: Proceedings of the Institution of Civil Engineers-Water Management, vol 159, No. 4. Thomas Telford Ltd, London, pp 225–233Google Scholar
  113. Robertson DM, Saad DA, Christiansen DE, Lorenz DJ (2016) Simulated impacts of climate change on phosphorus loading to Lake Michigan. J Great Lakes Res 42(3):536–548.  https://doi.org/10.1016/j.jglr.2016.03.009 CrossRefGoogle Scholar
  114. Rose PE, Pedersen JA (2005) Fate of oxytetracycline in streams receiving aquaculture discharges: model simulations. Environ Toxicol Chem 24(1):40–50.  https://doi.org/10.1897/03-640.1 CrossRefGoogle Scholar
  115. Rousseau AN, Savary S, Hallema DW, Gumiere SJ, Foulon É (2013) Modeling the effects of agricultural BMPs on sediments, nutrients, and water quality of the Beaurivage River watershed (Quebec, Canada). Can Water Resour J 38(2):99–120.  https://doi.org/10.1080/07011784.2013.780792 CrossRefGoogle Scholar
  116. Ryu J, Jang W, Kim J, Jung Y, Engel B, Lim K (2016) Development of field pollutant load estimation module and linkage of QUAL2E with watershed-scale L-THIA ACN model. Water 8(7):292.  https://doi.org/10.3390/w8070292 CrossRefGoogle Scholar
  117. Salvetti R, Azzellino A, Vismara R (2006) Diffuse source apportionment of the Po river eutrophying load to the Adriatic sea: assessment of Lombardy contribution to Po river nutrient load apportionment by means of an integrated modelling approach. Chemosphere 65(11):2168–2177.  https://doi.org/10.1016/j.chemosphere.2006.06.012 CrossRefGoogle Scholar
  118. Salvetti R, Acutis M, Azzellino A, Carpani M, Giupponi C, Parati P et al (2008) Modelling the point and non-point nitrogen loads to the Venice Lagoon (Italy): the application of water quality models to the Dese-Zero basin. Desalination 226(1-3):81–88.  https://doi.org/10.1016/j.desal.2007.01.236 CrossRefGoogle Scholar
  119. Schroeder F (1997) Water quality in the Elbe estuary: significance of different processes for the oxygen deficit at Hamburg. Environ Model Assess 2(1-2):73–82 https://link.springer.com/article/10.1023/A:1019032504922 CrossRefGoogle Scholar
  120. Schwarz GE, Hoos AB, Alexander RB, Smith RA (2006) The SPARROW surface water-quality model: theory, application and user documentation. US geological survey techniques and methods report, book, 6(10), 248Google Scholar
  121. Seo D, Kim M, Ahn JH (2012) Prediction of chlorophyll-a changes due to weir constructions in the Nakdong River using EFDC-WASP modelling. Environ Eng Res 17(2):95–102.  https://doi.org/10.4491/eer.2012.17.2.095 CrossRefGoogle Scholar
  122. Seo M, Jaber F, Srinivasan R, Jeong J (2017) Evaluating the impact of Low Impact Development (LID) practices on water quantity and quality under different development designs using SWAT. Water 9(3):193.  https://doi.org/10.3390/w9030193 CrossRefGoogle Scholar
  123. Sharma D, Kansal A (2013) Assessment of river quality models: a review. Rev Environ Sci Biotechnol 12(3):285–311 https://link.springer.com/article/10.1007/s11157-012-9285-8 CrossRefGoogle Scholar
  124. Sharma D, Kansal A, Pelletier G (2017) Water quality modeling for urban reach of Yamuna river, India (1999–2009), using QUAL2Kw. Appl Water Sci 7(3):1535–1559 https://link.springer.com/article/10.1007/s13201-015-0311-1 CrossRefGoogle Scholar
  125. Shokri A, Haddad OB, Mariño MA (2014) Multi-objective quantity–quality reservoir operation in sudden pollution. Water Resour Manag 28(2):567–586.  https://doi.org/10.1007/s11269-013-0504-z CrossRefGoogle Scholar
  126. Smith RA, Schwarz GE, Alexander RB (1997) Regional interpretation of water-quality monitoring data. Water Resour Res 33(12):2781–2798.  https://doi.org/10.1029/97WR02171 CrossRefGoogle Scholar
  127. Srivastava P, Hamlett JM, Robillard PD, Day RL (2002) Watershed optimization of best management practices using AnnAGNPS and a genetic algorithm. Water Resour Res 38(3):3–1.  https://doi.org/10.1029/2001WR000365 CrossRefGoogle Scholar
  128. Sun J, Wang MH, Ho YS (2012) A historical review and bibliometric analysis of research on estuary pollution. Mar Pollut Bull 64(1):13–21.  https://doi.org/10.1016/j.marpolbul.2011.10.034 CrossRefGoogle Scholar
  129. Tan ML, Gassman PW, Srinivasan R, Arnold JG, Yang X (2019) A review of swat studies in southeast asia: applications, challenges and future directions. Water 11(5):914.  https://doi.org/10.3390/w11050914 CrossRefGoogle Scholar
  130. Taner MÜ, Carleton JN, Wellman M (2011) Integrated model projections of climate change impacts on a North American lake. Ecol Model 222(18):3380–3393.  https://doi.org/10.1016/j.ecolmodel.2011.07.015 CrossRefGoogle Scholar
  131. Tang PK, Huang YC, Lin YJ (2012) Sustainable management strategies for an urban-type and low dissolved oxygen stream using measured biochemical coefficients. Desalin Water Treat 47(1-3):69–77.  https://doi.org/10.1080/19443994.2012.696793 CrossRefGoogle Scholar
  132. Tang PK, Huang YC, Kuo WC, Chen SJ (2014) Variations of model performance between QUAL2K and WASP on a river with high ammonia and organic matters. Desalin Water Treat 52(4-6):1193–1201.  https://doi.org/10.1080/19443994.2013.826887 CrossRefGoogle Scholar
  133. Tech T (2007) The environmental fluid dynamics code theory and computation volume 3: water quality module. In: Technical report. Tetra Tech, Inc., FairfaxGoogle Scholar
  134. Tuppad P, Douglas-Mankin KR, Lee T, Srinivasan R, Arnold JG (2011) Soil and Water Assessment Tool (SWAT) hydrologic/water quality model: extended capability and wider adoption. Trans ASABE 54(5):1677–1684.  https://doi.org/10.13031/2013.39856 CrossRefGoogle Scholar
  135. Udías A, Efremov R, Galbiati L, Cañamón I (2014) Simulation and multicriteria optimization modeling approach for regional water restoration management. Ann Oper Res 219(1):123–140CrossRefGoogle Scholar
  136. Umgiesser G, Canu DM, Solidoro C, Ambrose R (2003) A finite element ecological model: a first application to the Venice Lagoon. Environ Model Softw 18(2):131–145.  https://doi.org/10.1016/S1364-8152(02)00056-7 CrossRefGoogle Scholar
  137. Van Griensven A, Ndomba P, Yalew S, Kilonzo F (2012) Critical review of SWAT applications in the Upper Nile basin countries. Hydrol Earth Syst Sci:3371–3381.  https://doi.org/10.5194/hess-16-3371-2012 CrossRefGoogle Scholar
  138. Wambu EW, Ho YS (2016) A bibliometric analysis of drinking water research in Africa. Water SA 42(4):612–620.  https://doi.org/10.4314/wsa.v42i4.12 CrossRefGoogle Scholar
  139. Wang X, Yang W (2008) Modelling potential impacts of coalbed methane development on stream water quality in an American watershed. Hydrological Processes: An International Journal 22(1):87–103.  https://doi.org/10.1002/hyp.6647 CrossRefGoogle Scholar
  140. Wang MH, Yu TC, Ho YS (2009) A bibliometric analysis of the performance of Water Research. Scientometrics 84(3):813–820 https://akademiai.com/doi/abs/10.1007/s11192-009-0112-0 CrossRefGoogle Scholar
  141. Wang MH, Li J, Ho YS (2011) Research articles published in water resources journals: a bibliometric analysis. Desalin Water Treat 28(1-3):353–365.  https://doi.org/10.5004/dwt.2011.2412 CrossRefGoogle Scholar
  142. Wang X, Zhang S, Liu S, Chen J (2012) A two-dimensional numerical model for eutrophication in Baiyangdian Lake. Frontiers of Environmental Science & Engineering 6(6):815–824 https://link.springer.com/article/10.1007/s11783-011-0383-6 CrossRefGoogle Scholar
  143. Wang Q, Li S, Jia P, Qi C, Ding F (2013) A review of surface water quality models. Sci World J 2013:1–7.  https://doi.org/10.1155/2013/231768 CrossRefGoogle Scholar
  144. Wang Y, Xiang C, Zhao P, Mao G, Du H (2016) A bibliometric analysis for the research on river water quality assessment and simulation during 2000–2014. Scientometrics 108(3):1333–1346 https://link.springer.com/article/10.1007/s11192-016-2014-2 CrossRefGoogle Scholar
  145. Whittaker G, Färe R, Srinivasan R, Scott DW (2003) Spatial evaluation of alternative nonpoint nutrient regulatory instruments. Water Resour Res 39(4).  https://doi.org/10.1029/2001WR001119
  146. Williams JR, Arnold JG, Kiniry JR, Gassman PW, Green CH (2008) History of model development at Temple, Texas. Hydrol Sci J 53(5):948–960.  https://doi.org/10.1623/hysj.53.5.948 CrossRefGoogle Scholar
  147. Wu Y, Chen J (2009) Simulation of nitrogen and phosphorus loads in the Dongjiang River basin in South China using SWAT. Front Earth Sci China 3(3):273–278 https://link.springer.com/article/10.1007/s11707-009-0032-6 CrossRefGoogle Scholar
  148. Wu G, Xu Z (2011) Prediction of algal blooming using EFDC model: case study in the Daoxiang Lake. Ecol Model 222(6):1245–1252.  https://doi.org/10.1016/j.ecolmodel.2010.12.021 CrossRefGoogle Scholar
  149. Wu Y, Liu S, Abdul-Aziz OI (2012) Hydrological effects of the increased CO 2 and climate change in the Upper Mississippi River Basin using a modified SWAT. Clim Chang 110(3-4):977–1003.  https://doi.org/10.1007/s10584-011-0087-8 CrossRefGoogle Scholar
  150. Yang MD, Merry CJ, Sykes RM (1999) Integration of water quality modeling, remote sensing, and GIS 1. JAWRA Journal of the American Water Resources Association 35(2):253–263.  https://doi.org/10.1111/j.1752-1688.1999.tb03587.x CrossRefGoogle Scholar
  151. Yang W, Wang X, Liu Y, Gabor S, Boychuk L, Badiou P (2010) Simulated environmental effects of wetland restoration scenarios in a typical Canadian prairie watershed. Wetl Ecol Manag 18(3):269–279 https://link.springer.com/article/10.1007/s11273-009-9168-0 CrossRefGoogle Scholar
  152. Yazdi J, Moridi A (2017) Interactive Reservoir-Watershed Modeling Framework for Integrated Water Quality Management. Water Resour Manag 31(7):2105–2125CrossRefGoogle Scholar
  153. Zhai X, Zhang Y, Wang X, Xia J, Liang T (2014) Non-point source pollution modelling using Soil and Water Assessment Tool and its parameter sensitivity analysis in Xin’anjiang catchment, China. Hydrol Process 28(4):1627–1640.  https://doi.org/10.1002/hyp.9688 CrossRefGoogle Scholar
  154. Zhang W, Rao YR (2012) Application of a eutrophication model for assessing water quality in Lake Winnipeg. J Great Lakes Res 38:158–173.  https://doi.org/10.1016/j.jglr.2011.01.003 CrossRefGoogle Scholar
  155. Zhang XS, Hao FH, Cheng HG, Li DF (2003) Application of SWAT model in the upstream watershed of the Luohe River. Chin Geogr Sci 13(4):334–339 https://link.springer.com/article/10.1007/s11769-003-0039-y CrossRefGoogle Scholar
  156. Zhang ML, Shen YM, Guo Y (2008) Development and application of a eutrophication water quality model for river networks. J Hydrodyn 20(6):719–726 https://link.springer.com/article/10.1016/S1001-6058(09)60007-X CrossRefGoogle Scholar
  157. Zhang L, Lu W, An Y, Li D, Gong L (2012a) Response of non-point source pollutant loads to climate change in the Shitoukoumen reservoir catchment. Environ Monit Assess 184(1):581–594 https://link.springer.com/article/10.1007/s10661-011-2353-7 CrossRefGoogle Scholar
  158. Zhang R, Qian X, Li H, Yuan X, Ye R (2012b) Selection of optimal river water quality improvement programs using QUAL2K: a case study of Taihu Lake Basin, China. Sci Total Environ 431:278–285.  https://doi.org/10.1016/j.scitotenv.2012.05.063 CrossRefGoogle Scholar
  159. Zhang Z, Sun B, Johnson BE (2015) Integration of a benthic sediment diagenesis module into the two dimensional hydrodynamic and water quality model–CE-QUAL-W2. Ecol Model 297:213–231.  https://doi.org/10.1016/j.ecolmodel.2014.10.025 CrossRefGoogle Scholar
  160. Zhang D, Chen X, Yao H (2016) SWAT-CSenm: enhancing SWAT nitrate module for a Canadian Shield catchment. Sci Total Environ 550:598–610.  https://doi.org/10.1016/j.scitotenv.2016.01.109 CrossRefGoogle Scholar
  161. Zhao L, Delatolla R, Mohammadian A (2013) Nitrification kinetics and modified model for the Rideau River, Canada. Water Quality Research Journal 48(2):192–201.  https://doi.org/10.2166/wqrjc.2013.023 CrossRefGoogle Scholar
  162. Zhu L, Li HE, Li JK, Wu XJ (2012) Connecting hydrological and water quality models for prediction research of reservoir water quality. China Environ Sci 32(3):571–576Google Scholar
  163. Zhu Z, Oberg N, Morales VM, Quijano JC, Landry BJ, Garcia MH (2016) Integrated urban hydrologic and hydraulic modelling in Chicago, Illinois. Environ Model Softw 77:63–70.  https://doi.org/10.1016/j.envsoft.2015.11.014 CrossRefGoogle Scholar
  164. Zhu S, Zhang Z, Liu X (2017) Enhanced two dimensional hydrodynamic and water quality model (CE-QUAL-W2) for simulating mercury transport and cycling in water bodies. Water 9(9):643.  https://doi.org/10.3390/w9090643 CrossRefGoogle Scholar
  165. Zinia NJ, Kroeze C (2015) Future trends in urbanization and coastal water pollution in the Bay of Bengal: the lived experience. Environ Dev Sustain 17(3):531–546 https://link.springer.com/article/10.1007/s10668-014-9558-1 CrossRefGoogle Scholar

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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Engineering, Architecture and Urbanism and GeographyFederal University of Mato Grosso do SulCampo GrandeBrazil

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