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

Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 7885

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Special Issue Editors

Dr. Chi-Feng Chen

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Guest Editor

Department of Civil Engineering, National Taipei University of Technology, Taipei, Taiwan
Interests: water quality modeling; watershed management; urban stormwater management; nonpoint source pollution control; climate change adaptation

Prof. Dr. Chia-Ling Chang

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Guest Editor

Department of Water Resources Engineering and Conservation, Feng Chia University, Taichung‎, ‎Taiwan
Interests: environmental management; water science; watershed management; environmental modeling; hydrologic analysis

Special Issue Information

Dear Colleagues,

Water quality protection is always necessary and important. Massive efforts have made to improve water quality or to maintain its acceptable conditions. However, with more and more complex pollution emissions, the challenges become more severe. In addition, more uncertain weather systems strengthen the difficulties of water quality protection. This Special Issue seeks new water quality assessment and modelling methods to demonstrate water quality issues in watershed, rivers, reservoires, or urban drainage systems. It can be a focus on specific pollution sources or pollutants, which has been rarely discussed; an assessment of the effectiveness of customized water qauality control measures; or a historal data analysis to predict water quality trends or assess water quality under extreme weather conditions. New water quality model applications are welcome too. For example, the water quality assessement of natural-base solutions (NBS) or low impact development (LID), which includes the interactions between natural system. Total maximum daily loads (TMDLs), with the assimilative capacity of a waterbody, also represents a focal topic. Water quality is influenced by weather, external and internal pollution sources, and discharge conditions. Any contributions to the progress of water quality assessment and modeling are invited to submit to this Special Issue.

Dr. Chi-Feng Chen
Prof. Dr. Chia-Ling Chang
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.

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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 models
point and nonpoint source pollutions
SWMM
SWAT
WASP
LIDs
NBS

Published Papers (6 papers)

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Research

Open AccessArticle

Impact of Riparian Buffer Zone Design on Surface Water Quality at the Watershed Scale, a Case Study in the Jinghe Watershed in China

and

Water 2023, 15(15), 2696; https://doi.org/10.3390/w15152696 - 26 Jul 2023

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Abstract

This study was conducted to evaluate the impact of riparian buffer zones on water quality in the Jinghe watershed, China. To evaluate the effectiveness of riparian buffers in reducing sediments and nutrients in surface runoff, we employed two validated models: the agricultural non-point source pollution model (AnnAGNPS) and the riparian ecosystem management model (REMM). The AnnAGNPS was used to divide the catchment into homogeneous drainage areas and generate upland loadings for the REMM. The REMM model was then utilized to assess the impact of different riparian buffer designs on sediments and nutrient reduction in surface runoff. We tested five designs, including the recommended standard design by the United States Department of Agriculture (USDA). This design with 20 m herbaceous perennials next to the field (Zone 3), followed by a 20 m wide harvestable deciduous forest in the middle (Zone 2), and a 10 m wide non-harvestable deciduous forest adjacent to the river (Zone 1). We also evaluated alternative designs, such as removing Zone 3, removing Zone 2, and reducing the widths of the buffer zones further. For the entire Jinghe watershed, we calculated, compared, and analyzed the annual totals of water inflow, sediment yields, and dissolved nitrogen in surface runoff into and out of Zone 1, 2, and 3 for all the designs. The analysis indicated that the removal efficiency of sediments ranged from 85.7% to 90.8%, and the removal efficiency of dissolved nitrogen in surface runoff ranged from 85.4% to 91.9% for all the designs. It is also indicated that riparian buffer zones are highly effective in reducing sediments and nutrients in agricultural runoff, even with reduced buffer widths. This finding underscores the importance of implementing riparian buffer zones as a valuable approach in the agricultural intensive watershed with constraints for allocating for the creation of standard riparian buffers. Full article

(This article belongs to the Special Issue Water Quality Assessment and Modelling)

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Open AccessArticle

Predictive Simulation Study on the Effect of Small and Medium River Basin Outfall Treatment Measures on Water Quality Improvement

and

Water 2023, 15(13), 2359; https://doi.org/10.3390/w15132359 - 26 Jun 2023

Viewed by 543

Abstract

In recent years, the problem of water pollution in middle and small river basins has become increasingly serious. In order to control the water pollution of small- and medium-sized rivers, based upon the hydrodynamic module and the water quality module in MIKE21, this paper established a numerical computing model for middle and small river basins by taking the Xiyong River Basin as a typical representative. The excessive levels of nitrogen in the Xiyong River have significantly impaired the quality of the water in terms of the river status, so seven different scenario hypotheses of treatment measures are proposed, based on which the hydrodynamic simulation on the total nitrogen (TN) concentration’s movement was implemented and the time of the nitrogen concentration to reach the standard was predicted. The results showed that the water quality of the Xiyong River improved significantly after the treatment measure, and the annual mean of the TN concentration will decrease by 0.496 mg/L. The results will help the government to control the pollution sources of small and medium river basins. The research of Xiyong River based on the MIKE21 model can be used as the basis for pollution reduction and water quality improvement, which provides an example for the ecological restoration of small and medium rivers. Full article

(This article belongs to the Special Issue Water Quality Assessment and Modelling)

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Open AccessArticle

Metal Transport in the Mixing Zone of an Estuarine River to the Northern Gulf of Mexico

Zhenwei Wu

Songjie He

and

Yi-Jun Xu

Water 2023, 15(12), 2229; https://doi.org/10.3390/w15122229 - 14 Jun 2023

Viewed by 640

Abstract

To better understand the pollution potential of metals in estuaries heavily concentrated with petrochemical industries, we measured concentrations of total recoverable metals in the lower Calcasieu River in southwestern Louisiana that flows into the northern Gulf of Mexico. Water samples were collected at six sites along the last 88 km reach of the river monthly between May 2013 and November 2015, during which salinity ranged from 0.02 to 29.5 ppt from upstream to downstream. The samples were analyzed for a series of total recoverable metals, including aluminum (Al), arsenic (As), boron (B), cadmium (Cd), calcium (Ca), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), lithium (Li), magnesium (Mg), manganese (Mn), nickel (Ni), silicon (Si), titanium (Ti), vanadium (V), and zinc (Zn), of which only Al, As, B, Ca, Fe, Li, Mg, Mn, Si, Ti, and Zn had a detection rate higher than 30% over the 31-month study period. In the freshwater portion of the river, Si, Ca, Al, Fe, and Mg showed the highest concentration (8, 5, 4, 2, and 2 mg/L, respectively), while Li, As, Zn, Ti, and B had the lowest concentration (6, 16, 27, 34 and 50 µg/L, respectively). The concentrations of Al and Si declined by more than 30% from the freshwater to the river mouth, but the concentrations of Li and B increased by 61 and 66 times, respectively. None of these metals’ concentrations were found to exceed US EPA standards, but the rapid increase in Li and B concentrations may indicate a potential anthropogenic influence. On average, the Calcasieu River discharged a total of 35,484 tons of the elements each year (or 8059 kg/km²/yr), of which Si, Al, Ca, Fe, and Mg contributed 98%. Three major components of factors were extracted explaining 34, 20, and 13% (cumulative 67%) of the total variation in the metal concentrations. Salinity and pH were the major (>0.3) parameters in component 1 explaining the variability of B and Li; TSS was the major (>0.3) parameter in component 2 explaining the variation of Al, Fe, and Ti concentration; and temperature and DO% were the major (>0.3) parameters in component 3 explaining the variation of Mn concentration. Further studies on riverbed sediment metals and their effect on metal concentrations in surface water can help understand the metal sources and their potential effects on coastal aquatic ecosystems. Full article

(This article belongs to the Special Issue Water Quality Assessment and Modelling)

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Open AccessArticle

Total Maximum Daily Load Application Using Biological Oxygen Demand, Chemical Oxygen Demand, and Ammoniacal Nitrogen: A Case Study for Water Quality Assessment in the Perai River Basin, Malaysia

Siti Multazimah Mohamad Faudzi

Danial Nakhaie Mohd Souhkri

Muhammad Fitri Mohd Akhir

Hamidi Abdul Aziz

Muhammad Zaki Mohd Kasim

Nor Azazi Zakaria

and

Noor Aida Saad

Water 2023, 15(6), 1227; https://doi.org/10.3390/w15061227 - 21 Mar 2023

Viewed by 1311

Abstract

Water shortage has been an issue for urbanized areas. For the Penang state in Malaysia, it is forecast that there will be a significant increase in water demand in the future. Penang authorities in Malaysia are trying to find an alternative water source to overcome the problem, with one of the options being the Perai River catchment. However, the river water quality was found to be polluted and not suitable to be used for water extraction for domestic consumption. This paper aims to study the pollution level variation due to changes in rainfall during the year in the Perai River Basin, and estimate the TMDL of the river in a particular case for BOD, COD, and NH₃N parameters. A water quality model was developed for the Perai River, Jarak River and Kulim River using InfoWorks ICM. The year 2016 was selected as a model event due to data availability. BOD, COD and NH₃N concentrations were used for TMDL calculation, and the load duration curve approach was used to estimate TMDL. The tidal effect at the downstream of the Perai River was found to impact the data analysis in the river stretch. It was found that pollutant load exceedance was the highest during the rainy season and the problematic pollutant was NH₃N. Thus, local authorities need to focus on tidal and seasonal change factors when developing action plans to manage water quality issues in this basin. Full article

(This article belongs to the Special Issue Water Quality Assessment and Modelling)

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Open AccessArticle

Water Quality Analysis of a Tropical Reservoir Based on Temperature and Dissolved Oxygen Modeling by CE-QUAL-W2

Humberto Tavera-Quiroz

and

Water 2023, 15(6), 1013; https://doi.org/10.3390/w15061013 - 07 Mar 2023

Viewed by 1352

Abstract

Water quality impacts on water bodies such as reservoirs are strongly influenced by the hydrodynamics of the system. Although multiple models might be applied, they are limited by the simplification of the variables. In this study, a two-dimensional public domain model, CE-QUAL-W2, was adapted to test whether it would generate an accurate hydrodynamic simulation of the URRÁ Reservoir in Córdoba, Colombia, to understand water quality. The variables to be modeled were temperature and dissolved oxygen due to their importance in ecological terms. Thus, trial and error techniques were used to calibrate and validate the model, varying different parameters such as the wind shelter coefficient (WSC). Although the model accurately predicted the hydrodynamic part by having daily flow information, significant modifications to the eddy diffusivity coefficient were required to simulate acceptable longitudinal currents. This research shows that the CE-QUAL-W2 model fits adequately to tropical lentic systems. However, it is recommended that, for future studies, the modeling be adjusted using hourly data, especially in areas where inflow and boundary conditions are unstable. Full article

(This article belongs to the Special Issue Water Quality Assessment and Modelling)

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Open AccessArticle

A Machine Learning Approach to Predict Watershed Health Indices for Sediments and Nutrients at Ungauged Basins

Ganeshchandra Mallya

Mohamed M. Hantush

and

Rao S. Govindaraju

Water 2023, 15(3), 586; https://doi.org/10.3390/w15030586 - 02 Feb 2023

Viewed by 2919

Abstract

Effective water quality management and reliable environmental modeling depend on the availability, size, and quality of water quality (WQ) data. Observed stream water quality data are usually sparse in both time and space. Reconstruction of water quality time series using surrogate variables such as streamflow have been used to evaluate risk metrics such as reliability, resilience, vulnerability, and watershed health (WH) but only at gauged locations. Estimating these indices for ungauged watersheds has not been attempted because of the high-dimensional nature of the potential predictor space. In this study, machine learning (ML) models, namely random forest regression, AdaBoost, gradient boosting machines, and Bayesian ridge regression (along with an ensemble model), were evaluated to predict watershed health and other risk metrics at ungauged hydrologic unit code 10 (HUC-10) basins using watershed attributes, long-term climate data, soil data, land use and land cover data, fertilizer sales data, and geographic information as predictor variables. These ML models were tested over the Upper Mississippi River Basin, the Ohio River Basin, and the Maumee River Basin for water quality constituents such as suspended sediment concentration, nitrogen, and phosphorus. Random forest, AdaBoost, and gradient boosting regressors typically showed a coefficient of determination

R^{2} > 0.8

for suspended sediment concentration and nitrogen during the testing stage, while the ensemble model exhibited

R^{2} > 0.95

. Watershed health values with respect to suspended sediments and nitrogen predicted by all ML models including the ensemble model were lower for areas with larger agricultural land use, moderate for areas with predominant urban land use, and higher for forested areas; the trained ML models adequately predicted WH in ungauged basins. However, low WH values (with respect to phosphorus) were predicted at some basins in the Upper Mississippi River Basin that had dominant forest land use. Results suggest that the proposed ML models provide robust estimates at ungauged locations when sufficient training data are available for a WQ constituent. ML models may be used as quick screening tools by decision makers and water quality monitoring agencies for identifying critical source areas or hotspots with respect to different water quality constituents, even for ungauged watersheds. Full article

(This article belongs to the Special Issue Water Quality Assessment and Modelling)

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