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Water-Quality Modeling, Volume II
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Water-Quality Modeling, Volume II

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 December 2023) | Viewed by 5231

Special Issue Editors

Prof. Dr. Steven Chapra

E-Mail Website
Guest Editor
Civil and Environmental Engineering Department, Tufts University, Medford, MA 02155, USA
Interests: water quality modeling; advanced decision support; eutrophication; environmental engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Luis Alejandro Camacho Botero

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Los Andes University, Bogotá 111711, Colombia
Interests: water quality modeling; environmental hydraulics; advanced decision support
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The field of surface water-quality model started in 1925, with the classic Streeter and Phelps model to simulate dissolved oxygen on the Ohio River. In the almost 100 years since that seminal contribution, the field has expanded to encompass a myriad of pollutants beyond oxygen-demanding wastes. These include plant nutrients, toxic organic compounds, heavy metals, pathogens, as well as emerging contaminants such as human and animal pharmaceuticals, endocrine-disrupting compounds, microfibers, plastic waste, personal care products, and nanoparticles. Further, models have been developed and applied for all of the major natural waters and their sediments, including deep rivers, shallow streams, natural lakes, artificial impoundments, tidal rivers, estuaries, and the coastal zones of oceans and large lakes.

This Special Issue brings together emerging approaches, kinetic and computational challenges, and research frontiers related to water-quality modeling, with the ultimate aim of providing direction and concepts to carry the field into its next stages of evolution. Along with addressing new areas, approaches, and emerging pollutants, the Issue is also designed to explore the coupling and integration of water-quality modeling with other facets of the natural aqueous environment, including the biosphere, subsurface, and atmosphere, as well as interfaces with socioeconomic models and systems for decision support. In particular, water quality model frameworks addressing future problems such as climate change and mega-urbanization would be of particular interest.

Prof. Dr. Steven Chapra
Dr. Luis Alejandro Camacho Botero
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • water quality
  • modeling
  • oxygen
  • eutrophication
  • metals
  • nutrients
  • emerging contaminants
  • decision support

Published Papers (3 papers)

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Research

24 pages, 7337 KiB  
Article
One- and Three-Dimensional Hydrodynamic, Water Temperature, and Dissolved Oxygen Modeling Comparison
by Bushra Tasnim, Xing Fang and Joel S. Hayworth
Water 2024, 16(2), 317; https://doi.org/10.3390/w16020317 - 17 Jan 2024
Viewed by 837
Abstract
Understanding and modeling water quality in a lake/reservoir is important to the effective management of aquatic ecosystems. The advantages and disadvantages of different water quality models make it challenging to choose the most suitable model; however, direct comparison of 1-D and 3-D models [...] Read more.
Understanding and modeling water quality in a lake/reservoir is important to the effective management of aquatic ecosystems. The advantages and disadvantages of different water quality models make it challenging to choose the most suitable model; however, direct comparison of 1-D and 3-D models for lake water quality modeling can reveal their relative performance and enable modelers and lake managers to make informed decisions. In this study, we compared the 1-D model MINLAKE and the 3-D model EFDC+ for water temperature, ice cover, and dissolved oxygen (DO) simulation in three Minnesota lakes (50-m Carlos Lake, 23.5-m Trout Lake, and 5.6-m Pearl Lake). EFDC+ performed well for water temperature and DO simulation in the open water seasons with an average root mean square error (RMSE) of 1.32 °C and 1.48 mg/L, respectively. After analyzing the ice thickness with relevant data, it was found that EFDC+ calculates a shorter ice cover period and smaller ice thickness. EFDC+ does not consider snowfall for ice thickness simulation. The results also revealed that EFDC+ considers spatial variance and allows the user to select inflow/outflow locations precisely. This is important for large lakes with complex bathymetry or lakes having multiple inlets and outlets. MINLAKE is computationally less intensive than EFDC+, allowing rapid simulation of water quality parameters over many years under a variety of climate scenarios. Full article
(This article belongs to the Special Issue Water-Quality Modeling, Volume II)
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15 pages, 4927 KiB  
Article
Spatio-Temporal Dynamics of Non-Point Source Pollution in Jiulong River Basin (China) Using the Soil & Water Assessment Tool Model in Combination with the GeoSOS-FLUS Model
by Zheng Li, Wenchao Xue, Ekbordin Winijkul and Sangam Shrestha
Water 2023, 15(15), 2763; https://doi.org/10.3390/w15152763 - 30 Jul 2023
Cited by 2 | Viewed by 1645
Abstract
Water pollution, particularly non-point source pollution, poses a significant environmental challenge in river basins around the world. This complex and dynamic process is influenced by both human activities and natural processes. In this study, a quantitative analysis of ammonia-N and total phosphorus (TP) [...] Read more.
Water pollution, particularly non-point source pollution, poses a significant environmental challenge in river basins around the world. This complex and dynamic process is influenced by both human activities and natural processes. In this study, a quantitative analysis of ammonia-N and total phosphorus (TP) levels in the North Stream of the Jiulong River basin, China from 2010 to 2018 was conducted using the Soil & Water Assessment Tool (SWAT) model. The model was able to facilitate the simulation of spatio-temporal dynamics of concerned pollutants. Additionally, the GeoSOS-FLUS model was integrated with SWAT to predict land use patterns in 2040 and assess their impact on pollutant dynamics. The results demonstrated that the SWAT model effectively simulated the spatial and temporal dynamics of concerned pollutants in the study area, with satisfactory R2 and NS values for river discharges and pollutant loads. Notably, 2016 exhibited significant pollution levels, particularly in March. The study revealed distinct sources of ammonia-N and TP, originating from aquatic animal breeding areas and industrial wastewater discharge, respectively. Moreover, land use patterns influenced the spatial distribution of pollutants. These findings serve as a crucial data foundation for future endeavors in controlling and mitigating non-point source pollution in the Jiulong River basin. Full article
(This article belongs to the Special Issue Water-Quality Modeling, Volume II)
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29 pages, 9439 KiB  
Article
Water Quality Modeling in Headwater Catchments: Comprehensive Data Assessment, Model Development and Simulation of Scenarios
by Nicolas Fernandez and Luis A. Camacho
Water 2023, 15(5), 868; https://doi.org/10.3390/w15050868 - 23 Feb 2023
Viewed by 2281
Abstract
Water quality is a major concern globally and in headwater catchments of developing countries it is often poorly managed. In these catchments, having scarce and heterogeneous information hinders the development of water quality assessments and predictive models to support management. To address this [...] Read more.
Water quality is a major concern globally and in headwater catchments of developing countries it is often poorly managed. In these catchments, having scarce and heterogeneous information hinders the development of water quality assessments and predictive models to support management. To address this issue, the authors propose a framework of three stages that allows for: (i) conducting a comprehensive assessment of water quality; (ii) the development of a mountain stream water quality model based on said assessment; and (iii) the simulation of scenarios with the model to resolve conflicts between uses and quality of water. The framework involves multivariate analyses of principal components and clusters and follows a novel modeling protocol mainly designed for mountainous streams in developing countries. Applied to an Andean catchment in Colombia, the first stage of the framework revealed the catchment’s most significant water quality constituents and the most polluted season. The problematic constituents in this catchment include pathogens, nutrients, organic matter, and metals such as the highly toxic Cr and Pb, while water pollution is the highest during the driest months of the year (i.e., January to March). In the second stage, the model was calibrated reproducing the concentrations of pathogens, organic matter, and most nutrients, and showed a predictive capacity. This capacity was measured with an objective function to be minimized based on a normalized root mean square error. It increased only 14% when verified with a different dataset. In addition, during the third stage of the proposed framework, the simulation of alternative scenarios showed that centralized treatment is not sufficient to make water safe for potabilization and agriculture in the catchment. For this reason, improving water quality in the sub-basins at the highest altitudes is required. The proposed framework can be applied in other headwater catchments where information is limited, and where an improved management of water quality is needed. Full article
(This article belongs to the Special Issue Water-Quality Modeling, Volume II)
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