Spatial and Temporal Variability of Water Quality in the Bystrzyca River Basin, Poland

Grzywna, Antoni; Bronowicka‐Mielniczuk, Urszula

doi:10.3390/w12010190

Cited by 20 publications

(10 citation statements)

References 57 publications

(46 reference statements)

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“…Thus, these three factors determine the complexity of the ecosystem with respect to water pollution in the watershed of Maros City. The spatial and temporal variability of human-induced hydrological changes in a river basin can affect the quality and quantity of water [54]. Therefore, in order, to assess the water quality indices in the watershed of Maros City, a water sampling location was determined, as shown in Figure 7 below.…”

Section: Determinants Of the Complexity Of The Maros City Watershed E...mentioning

confidence: 99%

Water Quality Pollution Control and Watershed Management Based on Community Participation in Maros City, South Sulawesi, Indonesia

et al. 2020

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Increases in the number of urban residents have significant impacts on spatial pressure, affecting the utilization of river basins. The purpose of this study is to analyze (1) the increase in population and changes in spatial use as determinants of the complexity of the watershed ecosystem; (2) the effect of housing development, urban activity systems, and land use changes on the degradation of the environmental quality of the watershed; and (3) the direct and indirect effects of changes in spatial use, land reclamation, and community behavior on water pollution and the sustainability of watershed management in Maros City. The research method used is a sequential explanatory design combining quantitative and qualitative research methods. Data were obtained through observation, in-depth interviews, surveys, and documentation. The study findings show that land use change, complexity of spatial use, and community behavior have a negative impact on the environmental quality of the watershed. Housing development, urban activity systems, and changes in land use had a significant effect on environmental quality degradation, with a coefficient of determination of 73.9%. Furthermore, the influence of spatial use, land reclamation, and community behavior on water pollution in the watershed was 72.82%. This study may serve to assist the decision-making of and policy formation by the Maros Regency Government in the framework of controlling the use of watersheds, working towards their social, economic, and environmental sustainability.

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Section: Determinants Of the Complexity Of The Maros City Watershed E...mentioning

confidence: 99%

Water Quality Pollution Control and Watershed Management Based on Community Participation in Maros City, South Sulawesi, Indonesia

et al. 2020

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“…The values of chemical parameters of water could vary depending on the temporal and spatial situation. The growth in phosphate concentration is correlated with non-scheduled waste disposal, agricultural runoff and the use of pesticides and fertilizers that cause surface water pollution (Mirzaei et al, 2016;Sun et al, 2016;Grzywna & Bronowicka-Mielniczuk, 2020). It has been found in the examined water of the current study that the concentrations of arsenic, barium, boron, zinc, copper, aluminium, molybdenum and selenium were less than 0.01 mg dm −3 .…”

Section: Discussionmentioning

confidence: 60%

The assessment of the amount of water pollution and its suitability for drinking of the Tyśmienica River Basin, Poland

Grzywna

Sender

2021

Environ Monit Assess

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The quality and potability of waters of the Tyśmienica River Basin were determined in 2017 at eight measuring stations. The paper presents analyses of the physical and chemical parameters of surface waters of the basin. With regard to suspended solids, pH value, electric conductivity, sulphates, ammonia, chlorides and phosphate, the water was classified as having a very good ecological status. In the case of Kjeldahl nitrogen, the waters were classified as having a good ecological status. In the case of the remaining parameters, i.e. BOD, DO, TOC and COD, the status varied among stations. The values of all the physical and chemical parameters complied with the values for undisturbed conditions. Only ammonia and COD showed significant differences among stations. The WPI values for each measuring point ranged from 0.90 to 1.56, what corresponds to the descriptive indicators of moderately polluted water. The high concentrations of COD and TOC indicate that high-performance treatment processes (category A3) must be used to ensure that the water is suitable for drinking.

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“…Cluster analysis uses distance matrix and the model intervals were calculated using squared Euclidean distance technique [63,73]. The method is regarded as the best option and most appropriate measure of distance in the physical world.…”

Section: Hierarchical Cluster Analysis (Hca)mentioning

confidence: 99%

Application of Multivariate Statistical Analysis in the Development of a Surrogate Water Quality Index (WQI) for South African Watersheds

Banda

Kumarasamy

2020

Water

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Water quality indices (WQIs) are customarily associated with heavy data input demand, making them more rigorous and bulky. Such burdensome attributes are too taxing, time-consuming, and command a significant amount of resources to implement, which discourages their application and directly influences water resource monitoring. It is then imperative to focus on developing compatible, simpler, and less-demanding WQI tools, but with equally matching computational ability. Surrogate models are the best fitting, conforming to the prescribed features and scope. Therefore, this study attempts to provide a surrogate WQI as an alternative water quality monitoring tool that requires fewer inputs, minimal effort, and marginal resources to function. Accordingly, multivariate statistical techniques which include principal component analysis (PCA), hierarchical clustering analysis (HCA) and multiple linear regression (MLR) are applied primarily to determine four proxy variables and establish relevant model coefficients. As a result, chlorophyll-a, electrical conductivity, pondus Hydrogenium and turbidity are the final four proxy variables retained. A vital feature of the proposed surrogate index is that the input parameters qualify for inclusion into remote monitoring systems; henceforth, the model can be applied in remote monitoring programs. Reflecting on the model validation results, the proposed surrogate WQI is considered scientifically stable, with a minimum magnitude of divergence from the ideal water quality values. More importantly, the model displayed a predictive pattern identical to the ideal graph, matching on both index scores and classification values. The established surrogate model is an important milestone with the potential of promoting water resource monitoring and assisting in capturing of spatial and temporal changes in South African river catchments. This paper aims at outlining the methods used in developing the surrogate water quality index and document the results achieved.

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Spatial and Temporal Variability of Water Quality in the Bystrzyca River Basin, Poland

Cited by 20 publications

References 57 publications

Water Quality Pollution Control and Watershed Management Based on Community Participation in Maros City, South Sulawesi, Indonesia

Water Quality Pollution Control and Watershed Management Based on Community Participation in Maros City, South Sulawesi, Indonesia

The assessment of the amount of water pollution and its suitability for drinking of the Tyśmienica River Basin, Poland

Application of Multivariate Statistical Analysis in the Development of a Surrogate Water Quality Index (WQI) for South African Watersheds

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