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Water quality modeling

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From Wikipedia, the free encyclopedia Jump to navigationJump to search Water quality modeling involves water quality based data using mathematical simulation techniques. Water quality modeling helps people understand the eminence of water quality issues and models provide evidence for policy makers to make decisions in order to properly mitigate water[1]. Water quality modeling also helps determine correlations to constituent sources and water quality along with identifying information gaps[2]. Due to the increase in freshwater usage among people, water quality modeling is especially relevant[3] both in a local level and global level. In order to understand and predict the changes over time in water scarcity, climate change, and the economic factor of water resources[4], water quality models would need sufficient data by including water bodies from both local and global levels.

A typical water quality model consists of a collection of formulations representing physical mechanisms that determine position and momentum of pollutants in a water body[5]. Models are available for individual components of the hydrological system such as surface runoff[6]; there also exist basin wide models addressing hydrologic transport and for ocean and estuarine applications. Often finite difference methods are used to analyze these phenomena, and, almost always, large complex computer models are required[7].

Contents

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Building A Model

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Water quality models have different information, but generally have the same purpose, which is to provide evidentiary support of water issues. Models can be either deterministic or statistical depending on the scale with the base model,[2] which is dependent on if the area is on a local, regional, or a global scale. Another aspect to consider for a model is what needs to be understood or predicted about that research area along with setting up any parameters to define the research. Another aspect of building a water quality model is knowing the audience and the exact purpose for presenting data like to enhance water quality management[8] for water quality law makers for the best possible outcomes.

Formulations and associated Constants[edit]

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Water quality is modeled by one or more of the following formulations:

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  • Advective Transport formulation
  • Dispersive Transport formulation
  • Surface Heat Budget formulation
  • Dissolved Oxygen Saturation formulation
  • Reaeration formulation
  • Carbonaceous Deoxygenation formulation
  • Nitrogenous Biochemical Oxygen Demand formulation
  • Sediment oxygen demand formulation (SOD)
  • Photosynthesis and Respiration formulation
  • pH and Alkalinity formulation
  • Nutrients formulation (fertilizers)
  • Algae formulation
  • Zooplankton formulation
  • Coliform bacteria formulation (e.g. Escherichia coli)

SPARROW Models

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A SPARROW model is a SPAtially-Referenced Regression on Watershed attributes, which helps integrate water quality data with landscape information[2]. More specifically the USGS used this model to display long-term changes within watersheds to further explain in-stream water measurement in relation to upstream sources, water quality, and watershed properties. These models predict data for various spatial scales and integrate streamflow data with water quality at numerous locations across the US[2]. A SPARROW model used by the USGS focused on the nutrients in the Nation's major rivers and estuaries; this model helped create a better understanding of where nutrients come from, where they are transported to while in the water bodies, and where they end up (reservoirs, other estuaries, etc.)[2].

See also[edit]

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References[edit]

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  • U.S. Environmental Protection Agency (EPA). Environmental Research Laboratory, Athens, GA (1985). "Rates, Constants and Kinetics Formulations in Surface Water Quality Modeling." 2nd ed. Document no. EPA/600/3-85/040.
  • Bozorg-Haddad, O., Soleimani, S., & Loáiciga, H. A. (2017). Modeling water-quality parameters using genetic Algorithm–Least squares support vector regression and genetic programming. Journal of Environmental Engineering, 143(7), 04017021. doi:10.1061/(ASCE)EE.1943-7870.0001217
  • Tang, T., Strokal, M., van Vliet, M. T. H., Seuntjens, P., Burek, P., Kroeze, C., . . . Wada, Y. (2019). Bridging global, basin and local-scale water quality modeling towards enhancing water quality management worldwide. Current Opinion in Environmental Sustainability, 36, 39-48. doi:10.1016/j.cosust.2018.10.004
  • Preston, S. D., & Geological Survey (U.S.). (2009). SPARROW modeling: Enhancing understanding of the nation's water quality. ( No. 2009-3019.;2009-3019;). Reston, Va.: U.S. Dept. of the Interior, U.S. Geological Survey.
  • Zhang, W., Zhang, W., Wang, Y., Wang, Y., Peng, H., Peng, H., . . . Wu, K. B. (2010). A coupled water Quantity–Quality model for water allocation analysis. Water Resources Management, 24(3), 485-511. doi:10.1007/s11269-009-9456-8
  • Vallet, B., Muschalla, D., Lessard, P., & Vanrolleghem, P. A. (2014). A new dynamic water quality model for stormwater basins as a tool for urban runoff management: Concept and validation. Urban Water Journal, 11(3), 211-220. doi:10.1080/1573062X.2013.775313
  • Liu, Y., Li, S., Wallace, C. W., Chaubey, I., Flanagan, D. C., Theller, L. O., & Engel, B. A. (2017). Comparison of computer models for estimating hydrology and water quality in an agricultural watershed. Water Resources Management, 31(11), 3641-3665. doi:10.1007/s11269-017-1691-9

External Resources[edit]

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  • SPARROW Water-Quality Modeling - US Geological Survey
  • BASINS - EPA environmental analysis system integrating GIS, national watershed data, environmental assessment and modeling tools
  • Water Quality Models and Tools - EPA
  • Models for Total Maximum Daily Load Studies - Washington State Department of Ecology
  • Catchment Modelling Toolkit - eWater Cooperative Research Centre, Australia
  • Water Evaluation And Planning (WEAP), an integrated water resources planning model, including water quality - Stockholm Environmental Institute (US)
  • Stochastic Empirical Loading and Dilution Model (SELDM) - US Geological Survey stormwater quality model
  • U.S. Army Corps of Engineers Water Quality - New water quality modeling software developed by the U.S. Army Corps of Engineers
  1. ^ Tang, Ting; Strokal, Maryna; van Vliet, Michelle T.H.; Seuntjens, Piet; Burek, Peter; Kroeze, Carolien; Langan, Simon; Wada, Yoshihide (2019-02). "Bridging global, basin and local-scale water quality modeling towards enhancing water quality management worldwide". Current Opinion in Environmental Sustainability. 36: 39–48. doi:10.1016/j.cosust.2018.10.004. {{cite journal}}: Check date values in: |date= (help)
  2. ^ a b c d e Preston, S.D. "SPARROW MODELING—Enhancing Understanding of the Nation's Water Quality". USGS – via US Dep of Interior.
  3. ^ Bozorg-Haddad, Omid; Soleimani, Shima; Loáiciga, Hugo A. (2017-07). "Modeling Water-Quality Parameters Using Genetic Algorithm–Least Squares Support Vector Regression and Genetic Programming". Journal of Environmental Engineering. 143 (7): 04017021. doi:10.1061/(ASCE)EE.1943-7870.0001217. ISSN 0733-9372. {{cite journal}}: Check date values in: |date= (help)
  4. ^ Tang, Ting; Strokal, Maryna; van Vliet, Michelle T.H.; Seuntjens, Piet; Burek, Peter; Kroeze, Carolien; Langan, Simon; Wada, Yoshihide (2019-02). "Bridging global, basin and local-scale water quality modeling towards enhancing water quality management worldwide". Current Opinion in Environmental Sustainability. 36: 39–48. doi:10.1016/j.cosust.2018.10.004. {{cite journal}}: Check date values in: |date= (help)
  5. ^ Zhang, Wanshun; Wang, Yan; Peng, Hong; Li, Yiting; Tang, Jushan; Wu, K. Benjamin (2010-02). "A Coupled Water Quantity–Quality Model for Water Allocation Analysis". Water Resources Management. 24 (3): 485–511. doi:10.1007/s11269-009-9456-8. ISSN 0920-4741. {{cite journal}}: Check date values in: |date= (help)
  6. ^ Vallet, B.; Muschalla, D.; Lessard, P.; Vanrolleghem, P.A. (2014-04-03). "A new dynamic water quality model for stormwater basins as a tool for urban runoff management: Concept and validation". Urban Water Journal. 11 (3): 211–220. doi:10.1080/1573062X.2013.775313. ISSN 1573-062X.
  7. ^ Liu, Yaoze; Li, Sisi; Wallace, Carlington W.; Chaubey, Indrajeet; Flanagan, Dennis C.; Theller, Lawrence O.; Engel, Bernard A. (2017-09). "Comparison of Computer Models for Estimating Hydrology and Water Quality in an Agricultural Watershed". Water Resources Management. 31 (11): 3641–3665. doi:10.1007/s11269-017-1691-9. ISSN 0920-4741. {{cite journal}}: Check date values in: |date= (help)
  8. ^ "Bridging global, basin and local-scale water quality modeling towards enhancing water quality management worldwide". Current Opinion in Environmental Sustainability. 36: 39–48. 2019-02-01. doi:10.1016/j.cosust.2018.10.004. ISSN 1877-3435.