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Water
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River Water Management and Water Quality
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River Water Management and Water Quality

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 18442

Special Issue Editor

Prof. Dr. Roko Andricevic

E-Mail Website
Guest Editor
Faculty of Civil Engineering, Architecture and Geodesy, University of Split, Croatia
Interests: surface and subsurface hydrology; water resources management and engineering; environmental monitoring; estuaries and coastal water quality; risk assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Many river basins around the world are facing frequent severe flood events due to continuous anthropogenic pressure, particularly from the strong climatic changes experienced in the last several decades, prompting further research into fluvial dynamics and river water quality and quantity. Many different forms of deterioration are affecting river dynamics and water quality, consequentially affecting coastlines through the river estuaries and deltas. Although this topic has been extensively studied for decades, recent advances in novel observational methods and technologies, together with improved modeling concepts, require re-visitation on the common topics of management and water quality.

The objective of this Special Issue is to provide the reader with recent advances in understanding complex phenomena in natural watercourses, especially in terms of the characterization, control, management, and environmental monitoring of flooding and pollution in river basins. Increased demand for and usage of water resources, along with the deterioration of natural conditions, quantitatively and qualitatively affect water resources negatively and continue to place pressure on them.

This Special Issue will collect contributions from different river management and water quality studies around the world, allowing scientists to compare different approaches in understanding natural watercourses and management practices.

Prof. Dr. Roko Andricevic
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 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

  • Fluvial dynamics
  • Flood risk management and forecasting
  • Hydrological modeling
  • Water quality in rivers and estuaries
  • River management and climate change
  • Environmental monitoring

Published Papers (6 papers)

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Research

12 pages, 2519 KiB  
Article
Water Quality Predictive Analytics Using an Artificial Neural Network with a Graphical User Interface
by Nur Najwa Mohd Rizal, Gasim Hayder and Khairul Adib Yusof
Water 2022, 14(8), 1221; https://doi.org/10.3390/w14081221 - 11 Apr 2022
Cited by 10 | Viewed by 2442
Abstract
Since clean water is well known as one of the crucial sources that all living things need in their daily lives, the demand for clean freshwater nowadays has increased. However, water quality is slowly deteriorating due to anthropogenic and natural sources of pollution [...] Read more.
Since clean water is well known as one of the crucial sources that all living things need in their daily lives, the demand for clean freshwater nowadays has increased. However, water quality is slowly deteriorating due to anthropogenic and natural sources of pollution and contamination. Therefore, this study aims to develop artificial neural network (ANN) models to predict six different water quality parameters in the Langat River, Malaysia. Moreover, an application (app) equipped with a graphical user interface (GUI) was designed and developed to conduct real-time prediction of the water quality parameters by using real-time data as inputs together with the ANN models. As for the results, all of the ANN models achieved high coefficients of determination (R2), which were between 0.9906 and 0.9998, as well as between 0.8797 and 0.9972 for training and testing datasets, respectively. The developed app successfully predicted the outcome based on the run models. The implementation of a GUI-based app in this study enables a simpler and more trouble-free workflow in predicting water quality parameters. By eliminating sophisticated programming subroutines, the prediction process becomes accessible to more people, especially on-site operators and trainees. Full article
(This article belongs to the Special Issue River Water Management and Water Quality)
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16 pages, 7456 KiB  
Article
Spatial-Temporal Change of Land Use and Its Impact on Water Quality of East-Liao River Basin from 2000 to 2020
by Mingxi Zhang, Guangzhi Rong, Aru Han, Dao Riao, Xingpeng Liu, Jiquan Zhang and Zhijun Tong
Water 2021, 13(14), 1955; https://doi.org/10.3390/w13141955 - 16 Jul 2021
Cited by 5 | Viewed by 2521
Abstract
Land use change is an important driving force factor affecting the river water environment and directly affecting water quality. To analyze the impact of land use change on water quality change, this study first analyzed the land use change index of the study [...] Read more.
Land use change is an important driving force factor affecting the river water environment and directly affecting water quality. To analyze the impact of land use change on water quality change, this study first analyzed the land use change index of the study area. Then, the study area was divided into three subzones based on surface runoff. The relationship between the characteristics of land use change and the water quality grade was obtained by grey correlation analysis. The results showed that the land use types changed significantly in the study area since 2000, and water body and forest land were the two land types with the most significant changes. The transfer rate is cultivated field > forest land > construction land > grassland > unused land > water body. The entropy value of land use information is represented as Area I > Area III > Area II. The shift range of gravity center is forest land > grassland > water body > unused land > construction land > cultivated field. There is a strong correlation between land use change index and water quality, which can be improved and managed by changing the land use type. It is necessary to establish ecological protection areas or functional areas in Area I, artificial lawns or plantations shall be built in the river around the water body to intercept pollutants from non-point source pollution in Area II, and scientific and rational farming in the lower reaches of rivers can reduce non-point source pollution caused by farming. Full article
(This article belongs to the Special Issue River Water Management and Water Quality)
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20 pages, 3742 KiB  
Article
Spatial–Temporal Variations of Total Nitrogen and Phosphorus in Poyang, Dongting and Taihu Lakes from Landsat-8 Data
by Wei Shang, Shuanggen Jin, Yang He, Yuanyuan Zhang and Jian Li
Water 2021, 13(12), 1704; https://doi.org/10.3390/w13121704 - 20 Jun 2021
Cited by 28 | Viewed by 3968
Abstract
Poyang Lake, Dongting Lake, and Taihu Lake are the largest freshwater lakes in the middle and lower reaches of the Yangtze River, China. In recent years, the eutrophication level of lakes has increased with the development of the social economy and caused many [...] Read more.
Poyang Lake, Dongting Lake, and Taihu Lake are the largest freshwater lakes in the middle and lower reaches of the Yangtze River, China. In recent years, the eutrophication level of lakes has increased with the development of the social economy and caused many environmental and social problems. The concentrations of total nitrogen (TN) and total phosphorus (TP) are the key indicators of the degree of eutrophication, but the traditional ground monitoring methods are not capable of capturing such parameters in whole lakes with high spatial-temporal resolution. In this paper, empirical models are established and evaluated between the TN and TP and remote sensing spectral factors in the three lakes using Landsat 8 Operational Land Imager (OLI) satellite data and in-situ data. The results show that the inversion accuracy is higher than 75%. The TN and TP concentrations in the three lakes are inversed based on the Google Earth Engine (GEE) platform from 2014 to 2020 and their spatial-temporal variations are analyzed. The results show that the concentrations of TN and TP in Poyang Lake were decreased by 5.99% and 7.13% over 7 years, respectively, and the TN in Dongting Lake was decreased by 5.25% while the TP remained stable. The temporal changes in TN and TP concentrations displayed seasonal variations. A low concentration was observed in summer and high concentrations were in spring and winter. The average concentrations of TN and TP in Taihu Lake were higher than that of the other two lakes. The TP concentration was increased by 17.3% over 7 years, while the TN concentration remained almost stable. The variation in TN in Taihu Lake was the same as the growth cycle of algae, with higher value in spring and winter and lower value in summer, while the concentration of TP was lower in spring and winter and higher in summer. The spatial distribution of TN and TP concentrations in the three major lakes was significantly affected by human activities, and the concentrations of TN and TP were higher in areas near cities and agricultural activities. Full article
(This article belongs to the Special Issue River Water Management and Water Quality)
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19 pages, 3333 KiB  
Article
Analysis of the Water Quality of the Ishim River within the Akmola Region (Kazakhstan) Using Hydrochemical Indicators
by Natalya S. Salikova, Javier Rodrigo-Ilarri, Kulyash K. Alimova and María-Elena Rodrigo-Clavero
Water 2021, 13(9), 1243; https://doi.org/10.3390/w13091243 - 29 Apr 2021
Cited by 11 | Viewed by 3133
Abstract
For the first time in scientific literature, this work addresses the current situation of the Ishim River water quality in the Akmola Region (Northern Kazakhstan). This work uses environmental monitoring techniques to analyze the current state of surface waters in the river. The [...] Read more.
For the first time in scientific literature, this work addresses the current situation of the Ishim River water quality in the Akmola Region (Northern Kazakhstan). This work uses environmental monitoring techniques to analyze the current state of surface waters in the river. The content of main ions, biogenic and inorganic ions, heavy metals, organic impurities in seasonal and annual dynamics have been studied. Results show that, despite the tightening of requirements for wastewater discharge into the Ishim River basin, a number of water quality indicators did not fulfill the regulatory requirements for surface water bodies during 2013–2019. It has been identified that the greatest pollution in the Ishim River is brought by enterprises of the Karaganda-Temirtau technogenic region, located in the upper reaches of the river. Future water quality monitoring is needed and should include increasing the number of sampling locations and the sampling frequency in order to characterize the spatial and temporal variability of hydrochemical parameters and allow a comprehensive monitoring of legally fixed water quality parameters/indicators. Full article
(This article belongs to the Special Issue River Water Management and Water Quality)
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16 pages, 3931 KiB  
Article
Major Elements in the Upstream of Three Gorges Reservoir: An Investigation of Chemical Weathering and Water Quality during Flood Events
by Di Wang, Guilin Han, Mingming Hu, Yuchun Wang, Jinke Liu, Jie Zeng and Xiaoqiang Li
Water 2021, 13(4), 454; https://doi.org/10.3390/w13040454 - 09 Feb 2021
Cited by 7 | Viewed by 2578
Abstract
Rivers transport terrestrial matter into the ocean, constituting a fundamental channel between inland and oceanic ecosystem and affect global climate change. To reveal chemical weathering processes and environmental health risks during flood periods, water samples were collected in the upper reaches of Three [...] Read more.
Rivers transport terrestrial matter into the ocean, constituting a fundamental channel between inland and oceanic ecosystem and affect global climate change. To reveal chemical weathering processes and environmental health risks during flood periods, water samples were collected in the upper reaches of Three Gorges Reservoir (TGR) in 2020. HCO3− and Ca2+ were the most abundant anions and cations of the river water, respectively. The range of HCO3− concentration was between 1.81 and 3.02 mmol/L, while the mean content of Ca2+ was 1.03 mmol/L. The results of the Piper diagram and element ratios revealed that the river solutes were mainly contributed by carbonate weathering and gypsum-rich evaporite dissolution. A mass balance model indicated that the contribution order of sources to cations in the main channel (Yibin-Luzhou) was evaporites > carbonates > atmospheric input > silicates. The order in the Chongqing—Three Gorges Dam was carbonates > atmospheric input > evaporites > silicates. These results showed a lithologic control on hydrochemical characteristics. Most sampling sites were suitable for agricultural irrigation according to the water quality assessment. However, indexes sodium adsorption ratio (SAR) and soluble sodium percentage (Na%) were higher than 1.0 in Yibin-Luzhou and 30% in Yibin–Chongqing, respectively, suggesting a potential sodium hazard. In addition, except Tuojiang River and Shennong River, the risk of sodium hazard in tributaries was relatively low. High Na+ concentration in irrigation water can damage soil structure and function and ultimately affect agricultural production. Water quality in the upstream of a Piper diagram should attract enough attention. Full article
(This article belongs to the Special Issue River Water Management and Water Quality)
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26 pages, 7176 KiB  
Article
Incorporating Uncertainty of the System Behavior in Flood Risk Assessment—Sava River Case Study
by Toni Kekez, Snježana Knezić and Roko Andričević
Water 2020, 12(10), 2676; https://doi.org/10.3390/w12102676 - 24 Sep 2020
Cited by 4 | Viewed by 2580
Abstract
This paper proposes a framework for evaluation of the sources of uncertainty that can disrupt the flood emergency response process. During the flood response, flood emergency managers usually choose between several decision options under limited available lead-time, but they are often compelled with [...] Read more.
This paper proposes a framework for evaluation of the sources of uncertainty that can disrupt the flood emergency response process. During the flood response, flood emergency managers usually choose between several decision options under limited available lead-time, but they are often compelled with different sources of uncertainty. These sources can significantly affect the quality of decisions related to adequate response and rapid recovery of the affected system. The proposed framework considers efficient identification, integration, and quantification of system uncertainties related to the flood risk. Uncertainty analysis is performed from a decision-maker’s perspective and focused on the time period near and during the flood event. The major scope of proposed framework is to recognize and characterize sources of uncertainty which can potentially appear within the behavior of the observed system. Using a Bayesian network approach, a model is developed capable for quantification of different sources uncertainty in respect to their particular type. The proposed approach is validated on the Sava River case study, in the area of the city of Slavonski Brod, following the destructive 2014 flood event. The results indicate that, despite improvements of structural measures, the weir failure can still cause flooding of the approximately 1 km2 of otherwise safe area, resulting in the increased flood risk. Full article
(This article belongs to the Special Issue River Water Management and Water Quality)
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