Surface Water Quality Modelling
Date
2023
Authors
Lindenschmidt, Karl-Erich
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MDPI
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Article
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Abstract
Surface water quality modelling has become an important means of better understanding aquatic and riparian ecosystem processes at all scales, from the micro-scale (e.g., bottom sediment dynamics), to the meso-scale (e.g., algal bloom growth) and the macro-scale (e.g., the role of cascading reservoirs in sediment transport). Increasingly, surface water quality models are being coupled to other models (e.g., hydrological models) to determine catchment area impacts on water quality. These impacts include future climate change and land-use developments. Coupling with water resource dynamics models also provides insight into changes in water supply and demand and flow regulation as they relate to surface water quality. Modelling the quality of surface waters under ice-covered conditions has also gained special attention due to the increased realization that a holistic all-year perspective is required to deepen our understanding of aquatic ecosystem functioning (e.g., the impact of lake ice phenology on spring succession of phytoplankton) (excerpts and adaptations from my Global Water Futures https://gwf.usask.ca/ (accessed on 16 February 2023) reporting and https://www.mdpi.com/journal/water/special_issues/surface_water (accessed on 16 February 2023) announcement).
Description
© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Keywords
Surface water quality, aquatic and riparian ecosystem processes, Surface water quality modelling, special issue
Citation
Lindenschmidt, K.-E. Surface Water Quality Modelling. Water 2023, 15, 828. https://doi.org/ 10.3390/w15040828
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Citation
Lindenschmidt, K.-E. Surface Water Quality Modelling. Water 2023, 15, 828. https://doi.org/ 10.3390/w15040828
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This article belongs to the Special Issue Surface Water Quality Modelling
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DOI
10.3390/w15040828