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Research on Nutrient Dynamics in Surface Water Using Water Quality Models and State-of-the-Art Monitoring

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".

Deadline for manuscript submissions: closed (20 June 2024) | Viewed by 3781

Special Issue Editors


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Guest Editor
Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK S7N 3H5, Canada
Interests: surface water quality modelling; CE-QUAL-W2; limnology; water security

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Guest Editor
Global Institute for Water Security, School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK S7N 3H5, Canada
Interests: surface water quality modelling; ice-jam flood hazard mapping; ice-jam flood risk assessment; remote sensing of river ice covers; river ice hydraulic modelling
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Special Issue Information

Dear Colleagues,

Nutrient processes are intrinsically connected to the global health of freshwater and coastal marine environments. Water quality models are increasingly being used as research tools for understanding complex nutrient dynamics in surface water bodies. Models can approximate processes that cannot be directly measured and inform future planning through scenarios of environmental change. Water quality models are increasingly coupled with hydrological models and can assess large-scale climate and operational management impacts on nutrient transport from catchment areas to oceans. Supporting these models are new advancements in data collection and innovative modelling tools. Sensor-based monitoring systems (such as deployable lakes and ocean buoys) provide the opportunity to observe nutrient transformations during short timescales or in real-time. New modules and subroutines are expanding the capabilities of packaged water-quality models to study in-depth nutrient processes (such as sediment diagenesis). New integrated methods of monitoring, analysis, and modelling will continue to advance our knowledge of nutrient processes, and, in this context, we invite you to submit a contribution to this Special Issue entitled “Research on Nutrient Dynamics in Surface Water Using Water Quality Models and State-of-the-Art Monitoring”.

Dr. Julie Terry
Prof. Dr. Karl-Erich Lindenschmidt
Guest Editors

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Keywords

  • water quality modelling
  • surface water modelling
  • nutrient dynamics
  • water quality monitoring
  • eutrophication
  • buoys
  • lakes
  • rivers
  • estuaries
  • ocean

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Published Papers (2 papers)

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Research

12 pages, 12892 KiB  
Article
Evaluating Surface Water Nitrogen Pollution via Visual Clustering in Megacity Chengdu
by Yao Ding, Yin Wang, Shuming Yang, Xiaolong Zhao, Lili Ouyang and Chengyue Lai
Water 2023, 15(11), 2113; https://doi.org/10.3390/w15112113 - 2 Jun 2023
Cited by 2 | Viewed by 1737
Abstract
The current standards used for nitrogen pollution evaluation are lacking, and scientific classification methods are needed for nitrogen pollution to improve water quality management capabilities. This study addresses the important issue of assessing surface water nitrogen pollution by utilizing two advanced multivariate statistical [...] Read more.
The current standards used for nitrogen pollution evaluation are lacking, and scientific classification methods are needed for nitrogen pollution to improve water quality management capabilities. This study addresses the important issue of assessing surface water nitrogen pollution by utilizing two advanced multivariate statistical techniques: self-organizing maps (SOMs) obtained using the K-means algorithm and the Hasse diagram technique (HDT). The research targets of this study are the rivers of the megacity Chengdu, China. Samples were collected on a monthly basis in 2017–2020 from different sites along the rivers, and their nitrogen pollution parameters were determined. The grouping of nitrogen pollution parameters and the clustering of sampling events using SOMs facilitate the preprocessing required for the HDT, wherein clusters are ordered according to the pre-clustered water sampling events. The results indicate that nitrogen pollution in the Chengdu River Basin, which is prominent and mainly driven by nitrate nitrogen, can be categorized into five levels. The nitrogen pollution in Tuo River is serious. Although the degree of ammonia nitrogen pollution in Jin River is higher, the pollution range is smaller. Furthermore, these results were evaluated by the SOMs and HDT to be clear and reliable. Overall, these findings can provide a basis for local environmental legislation. Full article
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15 pages, 2307 KiB  
Article
Water Quality and Flow Management Scenarios in the Qu’Appelle River–Reservoir System Using Loosely Coupled WASP and CE-QUAL-W2 Models
by Julie Terry and Karl-Erich Lindenschmidt
Water 2023, 15(11), 2005; https://doi.org/10.3390/w15112005 - 25 May 2023
Cited by 4 | Viewed by 1611
Abstract
The water bodies of the Saskatchewan Prairies suffer multiple stressors, and demand for water is expected to increase. Water quality models can help evaluate water management strategies and risks such as climate change. This study assesses the impact of interbasin water transfers on [...] Read more.
The water bodies of the Saskatchewan Prairies suffer multiple stressors, and demand for water is expected to increase. Water quality models can help evaluate water management strategies and risks such as climate change. This study assesses the impact of interbasin water transfers on the water quality of a strategic, eutrophic prairie reservoir that receives poor-quality watershed run-off. A one-dimensional WASP model was used to estimate nutrient transformations in the transfers along a 97 km river channel. The WASP model was then loosely coupled to a two-dimensional CE-QUAL-W2 model of the downstream receiving reservoir. Output from the WASP model was manually transformed into boundary conditions for the CE-QUAL-W2 reservoir model. This method improves on an earlier attempt to estimate nutrient transformations in the transfers using linear regression. Results from the loosely coupled models suggest Buffalo Pound Lake would respond well to the interbasin transfers. The number of threshold exceedances decreased for all modeled water quality variables. Nutrient concentrations were most influenced in the open water season following spring freshet. Any additional reduction of threshold exceedances during winter was minimal in comparison. These results are interesting from a management perspective as increased transfers under winter operations risk ice damage to the river channel. Full article
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