Special Issue "Diffuse Water Pollution Modeling, Monitoring and Mitigation 2020"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: closed (31 January 2021).

Special Issue Editor

Dr. Marina Cabral Pinto
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Guest Editor
Investigator GeoBioTec Research, Invited Professor, Department of Geosciences, University of Aveiro, 3810-193 Aveiro, Portugal
Interests: forest; land use planning; agriculture; plant sciences, vegetation; soil; rocks; geomedicine; water quality; mineral exploration; dust; industrial pollution; geochemical mineral; mineralogy; environmental regulation
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Special Issue Information

Dear Colleagues,

The urbanization process generates impacts on water resources and is directly involved in the alteration of the natural conditions and, consequently, reduction of groundwater recharge and increase of runoff and pollutant loads. In the modern era, diffuse water pollution from rural and urban sources has continuously and negatively impacted water resources, irrespective of the efforts made to the contrary. In order to minimize the problem and further improve the overall water quality of surface- and groundwater, long-term monitoring and further modeling are required. However, several research gaps still exist and need proper attention: What effective mitigation measures are there for rural and urban sources? What are the existing modeling and monitoring methods for long-term prediction of water resource quality and quantity to achieve our goals? What is the time gap needed to see the effects of implemented mitigation measures? Are natural-based solutions sufficient in reducing pollution load? Do different climatic drives influence the effects of diffuse pollution and of mitigation measures?

Model use has become more widespread due to scientific and technological developments, which today give easy access to a relatively high level of sophistication. Hydrological and water quality (WQ) models are also effective tools to predict environmental impacts and to set WQ objectives, because receiving water bodies in developing countries are often highly polluted due to combined sewer overflows, wrong connections of sewers to the drainage system, and uncontrolled industrial discharges.

Diffuse water pollution modeling, monitoring, and mitigation is acknowledged to be an important area of research worldwide; nevertheless, it has received little attention from scientists, administrators, policy makers, water resource planners, and managers. The aim of this Special Issue is (a) to focus on a selection of current challenges and research opportunities in mitigating diffuse water pollution and (b) existing and suitability of models to predict medium and long term sources of water, and (c) to encourage knowledge transfer between environmentalists and policymakers whose work concerns ecological and health risk problems.

Dr. Marina Marques da Silva Cabral Pinto
Guest Editor

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 papers will be 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. International Journal of Environmental Research and Public Health 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 2300 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

  • Modeling
  • Pollution sources
  • Freshwater bodies
  • Groundwater
  • Surface water
  • Water quality
  • Ecological and human risk
  • Eco-hydrology

Published Papers (1 paper)

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Research

Open AccessArticle
Identification Framework of Contaminant Spill in Rivers Using Machine Learning with Breakthrough Curve Analysis
Int. J. Environ. Res. Public Health 2021, 18(3), 1023; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18031023 - 24 Jan 2021
Abstract
To minimize the damage from contaminant accidents in rivers, early identification of the contaminant source is crucial. Thus, in this study, a framework combining Machine Learning (ML) and the Transient Storage zone Model (TSM) was developed to predict the spill location and mass [...] Read more.
To minimize the damage from contaminant accidents in rivers, early identification of the contaminant source is crucial. Thus, in this study, a framework combining Machine Learning (ML) and the Transient Storage zone Model (TSM) was developed to predict the spill location and mass of a contaminant source. The TSM model was employed to simulate non-Fickian Breakthrough Curves (BTCs), which entails relevant information of the contaminant source. Then, the ML models were used to identify the BTC features, characterized by 21 variables, to predict the spill location and mass. The proposed framework was applied to the Gam Creek, South Korea, in which two tracer tests were conducted. In this study, six ML methods were applied for the prediction of spill location and mass, while the most relevant BTC features were selected by Recursive Feature Elimination Cross-Validation (RFECV). Model applications to field data showed that the ensemble Decision tree models, Random Forest (RF) and Xgboost (XGB), were the most efficient and feasible in predicting the contaminant source. Full article
(This article belongs to the Special Issue Diffuse Water Pollution Modeling, Monitoring and Mitigation 2020)
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