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River water quality modelling in South Africa: Considerations, sourcing and accessing of input data

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dc.contributor.author Mahlathi, Christopher D
dc.contributor.author Brink, IC
dc.contributor.author Wilms, JM
dc.date.accessioned 2024-06-11T09:16:14Z
dc.date.available 2024-06-11T09:16:14Z
dc.date.issued 2024-03
dc.identifier.citation Mahlathi, C.D., Brink, I. & Wilms, J. 2024. River water quality modelling in South Africa: Considerations, sourcing and accessing of input data. <i>Journal of the South African Institution of Civil Engineering, 66(1).</i> http://hdl.handle.net/10204/13698 en_ZA
dc.identifier.issn 1021-2019
dc.identifier.issn 2309-8775
dc.identifier.uri http://hdl.handle.net/10204/13698
dc.description.abstract River water quality modelling relies on a good dataset for model input, calibration and validation to develop a reliable model. Determination of data requirements, and data sourcing towards this purpose in South Africa, are not elementary. Data availability is key throughout the modelling processes, making the sourcing of good data equally imperative. This paper provides starting considerations, and compiles a list of available data sources applicable to river water quality modelling in South Africa. It also provides a background on the included data sources and a general overview of the extent of the databases. en_US
dc.format Fulltext en_US
dc.language.iso en en_US
dc.relation.uri http://www.scielo.org.za/scielo.php?script=sci_arttext&pid=S1021-20192024000100001&lng=en&nrm=iso&tlng=en en_US
dc.source Journal of the South African Institution of Civil Engineering, 66(1) en_US
dc.subject Calibration en_US
dc.subject Validation en_US
dc.subject Water quality data en_US
dc.subject Hydrodynamic data en_US
dc.title River water quality modelling in South Africa: Considerations, sourcing and accessing of input data en_US
dc.type Article en_US
dc.description.pages 2-11 en_US
dc.description.note Licensed under a Creative Commons Attribution Licence (CC BY-NC-ND). Readers may therefore freely use and share the content as long as they credit the original creator and publisher, do not change the material in any way, and do not use it commercially. Copyright of this article remains with the authors. en_US
dc.description.cluster Next Generation Enterprises & Institutions en_US
dc.description.impactarea Geospatial Modelling Analysis en_US
dc.identifier.apacitation Mahlathi, C. D., Brink, I., & Wilms, J. (2024). River water quality modelling in South Africa: Considerations, sourcing and accessing of input data. <i>Journal of the South African Institution of Civil Engineering, 66(1)</i>, http://hdl.handle.net/10204/13698 en_ZA
dc.identifier.chicagocitation Mahlathi, Christopher D, IC Brink, and JM Wilms "River water quality modelling in South Africa: Considerations, sourcing and accessing of input data." <i>Journal of the South African Institution of Civil Engineering, 66(1)</i> (2024) http://hdl.handle.net/10204/13698 en_ZA
dc.identifier.vancouvercitation Mahlathi CD, Brink I, Wilms J. River water quality modelling in South Africa: Considerations, sourcing and accessing of input data. Journal of the South African Institution of Civil Engineering, 66(1). 2024; http://hdl.handle.net/10204/13698. en_ZA
dc.identifier.ris TY - Article AU - Mahlathi, Christopher D AU - Brink, IC AU - Wilms, JM AB - River water quality modelling relies on a good dataset for model input, calibration and validation to develop a reliable model. Determination of data requirements, and data sourcing towards this purpose in South Africa, are not elementary. Data availability is key throughout the modelling processes, making the sourcing of good data equally imperative. This paper provides starting considerations, and compiles a list of available data sources applicable to river water quality modelling in South Africa. It also provides a background on the included data sources and a general overview of the extent of the databases. DA - 2024-03 DB - ResearchSpace DP - CSIR J1 - Journal of the South African Institution of Civil Engineering, 66(1) KW - Calibration KW - Validation KW - Water quality data KW - Hydrodynamic data LK - https://researchspace.csir.co.za PY - 2024 SM - 1021-2019 SM - 2309-8775 T1 - River water quality modelling in South Africa: Considerations, sourcing and accessing of input data TI - River water quality modelling in South Africa: Considerations, sourcing and accessing of input data UR - http://hdl.handle.net/10204/13698 ER - en_ZA
dc.identifier.worklist 26650 en_US


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