Water quality modelling

Water quality modeling involves water quality based data using mathematical simulation techniques. Modeling helps people understand the importance of water quality issues and provides evidence for policy makers to make decisions in order to properly mitigate water pollution.^[1] Water quality modeling also helps determine correlations to constituent sources and water quality along with identifying information gaps.^[2] Due to increases in human use of fresh water, water quality modeling is especially relevant^[3] at both the local 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,^[1] water quality models depend on 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.^[4] Models are available for individual components of the hydrological system such as surface runoff.^[5] Basin-wide models address hydrologic transport aspects and are used for ocean and estuarine applications. Finite difference methods are often used to analyze these phenomena, and, almost always, large complex computer models are required.^[6]

Building a model

Various water quality models utilize 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, which is dependent on whether the modeled area is on a local, regional, or a global scale.^[2] 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, such as to enhance water quality management for water quality law makers for the best possible outcomes.^[7]

Formulations and associated constants

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

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

A SPARROW model ("SPAtially-Referenced Regression on Watershed" attributes) helps integrate water quality data with landscape information. More specifically the United States Geological Survey (USGS) uses 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. One SPARROW model used by the USGS focused on the nutrients in major US rivers and estuaries. This model improved 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]

References

^ ^a ^b Tang, Ting; Strokal, Maryna; van Vliet, Michelle T.H.; Seuntjens, Piet; Burek, Peter; Kroeze, Carolien; Langan, Simon; Wada, Yoshihide (February 2019). "Bridging global, basin and local-scale water quality modeling towards enhancing water quality management worldwide". Current Opinion in Environmental Sustainability. 36: 39–48. Bibcode:2019COES...36...39T. doi:10.1016/j.cosust.2018.10.004. hdl:10067/1586430151162165141.
^ ^a ^b ^c Preston, Stephen D.; Alexander, Richard B.; Woodside, Michael D.; Hamilton, Pixie A. (2009). SPARROW Modeling—Enhancing Understanding of the Nation's Water Quality (Report). Reston, VA: US Geological Survey. doi:10.3133/fs20093019. Fact Sheet 2009-3019.
^ Bozorg-Haddad, Omid; Soleimani, Shima; Loáiciga, Hugo A. (July 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. ISSN 0733-9372.
^ Zhang, Wanshun; Wang, Yan; Peng, Hong; Li, Yiting; Tang, Jushan; Wu, K. Benjamin (February 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. ISSN 0920-4741. S2CID 153922326.
^ 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. S2CID 111045671.
^ Liu, Yaoze; Li, Sisi; Wallace, Carlington W.; Chaubey, Indrajeet; Flanagan, Dennis C.; Theller, Lawrence O.; Engel, Bernard A. (September 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. ISSN 0920-4741. S2CID 158035959.
^ Tang, Ting; Strokal, Maryna; Van Vliet, Michelle T.H.; Seuntjens, Piet; Burek, Peter; Kroeze, Carolien; Langan, Simon; Wada, Yoshihide (2019-02-01). "Bridging global, basin and local-scale water quality modeling towards enhancing water quality management worldwide". Current Opinion in Environmental Sustainability. 36: 39–48. Bibcode:2019COES...36...39T. doi:10.1016/j.cosust.2018.10.004. hdl:10067/1586430151162165141. ISSN 1877-3435.

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.

External links

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

[Tang_39–48-1] Tang, Ting; Strokal, Maryna; van Vliet, Michelle T.H.; Seuntjens, Piet; Burek, Peter; Kroeze, Carolien; Langan, Simon; Wada, Yoshihide (February 2019). "Bridging global, basin and local-scale water quality modeling towards enhancing water quality management worldwide". Current Opinion in Environmental Sustainability. 36: 39–48. Bibcode:2019COES...36...39T. doi:10.1016/j.cosust.2018.10.004. hdl:10067/1586430151162165141.

[USGS_2009-2] Preston, Stephen D.; Alexander, Richard B.; Woodside, Michael D.; Hamilton, Pixie A. (2009). SPARROW Modeling—Enhancing Understanding of the Nation's Water Quality (Report). Reston, VA: US Geological Survey. doi:10.3133/fs20093019. Fact Sheet 2009-3019.

[3] Bozorg-Haddad, Omid; Soleimani, Shima; Loáiciga, Hugo A. (July 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. ISSN 0733-9372.

[4] Zhang, Wanshun; Wang, Yan; Peng, Hong; Li, Yiting; Tang, Jushan; Wu, K. Benjamin (February 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. ISSN 0920-4741. S2CID 153922326.

[5] 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. S2CID 111045671.

[6] Liu, Yaoze; Li, Sisi; Wallace, Carlington W.; Chaubey, Indrajeet; Flanagan, Dennis C.; Theller, Lawrence O.; Engel, Bernard A. (September 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. ISSN 0920-4741. S2CID 158035959.

[7] Tang, Ting; Strokal, Maryna; Van Vliet, Michelle T.H.; Seuntjens, Piet; Burek, Peter; Kroeze, Carolien; Langan, Simon; Wada, Yoshihide (2019-02-01). "Bridging global, basin and local-scale water quality modeling towards enhancing water quality management worldwide". Current Opinion in Environmental Sustainability. 36: 39–48. Bibcode:2019COES...36...39T. doi:10.1016/j.cosust.2018.10.004. hdl:10067/1586430151162165141. ISSN 1877-3435.

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