Water quality assessment of the Karasu River (Turkey) using various indices, multivariate statistics and APCS-MLR model

Varol, Memet; Karakaya, Gökhan; Alpaslan, Kenan

doi:10.1016/j.chemosphere.2022.136415

Cited by 44 publications

(8 citation statements)

References 40 publications

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“…Since rivers are affected by the human activities carried out in their riverscape 38 , 39 , the aims of this research are (1) the assessment of the water quality of the Suquía River for the 2018–2019 period by implementing the WQI developed by Pesce and Wunderling 28 ; (2) the assessment of LULC change for the same period to analyze the riverscape dynamics at different spatial scales, and (3) the spatial analysis of the relation between LULC change, water quality parameters, and WQI by taking into consideration the seasonal variability. In this perspective, this research presents a novel spatial approach by integrating WQI and LULC dynamics.…”

Section: Introductionmentioning

confidence: 99%

The multiscale nexus among land use-land cover changes and water quality in the Suquía River Basin, a semi-arid region of Argentina

Paná,

Marinelli,

Bonansea

et al. 2024

Sci Rep

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Agricultural intensification and urban sprawl have led to significant alterations in riverscapes, and one of the critical consequences is the deterioration of water quality with significant implications for public health. Therefore, the objectives of this study were the assessment of the water quality of the Suquía River, the assessment of LULC change at different spatial scales, and the analysis of the potential seasonal correlation among LULC change and Water Quality Index (WQI). The Sample Sites (SS) 1 and 2 before Cordoba city had the highest WQI values while from SS3 the WQI decreased, with the lowest WQI close to the wastewater treatment plant (SS7) after Cordoba city. From SS8 in a agricultural context, the WQI increases but does not reach the original values. In light of analysis carried out, the correlation between water quality variables and the different LULC classes at the local and regional scales demonstrated that WQI is negatively affected by agricultural and urban activities, while natural classes impacted positively. The spatialization of the results can help strongly in assessing and managing the diffusion of point and non-point pollution along the riverscape. The knowledge gained from this research can play a crucial role in water resources management, which supports the provision of river ecosystem services essential for the well-being of local populations.

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Section: Introductionmentioning

confidence: 99%

The multiscale nexus among land use-land cover changes and water quality in the Suquía River Basin, a semi-arid region of Argentina

Paná,

Marinelli,

Bonansea

et al. 2024

Sci Rep

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show abstract

“…Because of the growing demand for fresh water and restricted access to water resources (Khataee et al, 2013), observation and control of river water quality have an incontrovertible role in environmental conservation and sustainable distribution of natural resources (Varol et al, 2022;Zhang et al, 2021;Deng et al, 2021;Jamei et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of total dissolved solids in rivers by improved neuro fuzzy approaches using metaheuristic algorithms

Jannatkhah,

Davarpanah,

Fakouri

et al. 2024

Earth Sci Inform

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Substantial deterioration of surface water quality, mainly caused by human activities and climate change, makes the assessment of water quality a global priority. Thus, in this study, four metaheuristic algorithms, namely the particle swarm optimization (PSO), differential evolution (DE), ant colony optimization algorithm (ACOR), and genetic algorithm (GA), were employed to improve the performance of the adaptive neuro-fuzzy inference system (ANFIS) in the evaluation of surface water total dissolved solids (TDS). Monthly and annual TDS were considered as target variables in the analysis. In order to evaluate and compare the authenticity of the models, an economic factor (execution time) and statistical indices of the coefficient of determination (R2), Kling Gupta efficiency (KGE), root mean squared error (RMSE), mean absolute error (MAE), and Nash-Sutcliff efficiency (NSE) were utilized. The results revealed that the hybrid methods used in this study could enhance the classical ANFIS performance in the analysis of monthly and annual TDS of both stations. For more clarification, the models were ranked using the TOPSIS approach by simultaneously applying the effects of statistical parameters, temporal and spatial change factors, and execution time. This approach significantly facilitated decision-making in ranking models. The ANFIS-ACOR annual model considering discharge had the best performance in the Vanyar Station; Furthermore, ANFIS-ACOR monthly model ignoring discharge was outstanding in the Gotvand Station. In total, after utilizing two defined and proposed temporal and spatial change factors, ANFIS-ACOR and ANFIS-DE hybrid models had the best and worst performance in TDS prediction, respectively.

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“…Moreover, it is crucial to determine heavy metal sources and conduct quantitative evaluations of the associated health risks. In recent years, receptor models, such as hierarchical cluster analysis (HCA) [31], factor analysis (FA) [32], principal component analysis (PCA) [33,34], absolute principal component score-multiple linear regression (APCS-MLR) [35], and positive matrix factorization (PMF) [36,37], have been used to determine the source and distribution of environmental contaminants. While receptor models have effectively examined pollution in soil, sediment, and air, there has been limited application of these methods in identifying the sources of pollution in groundwater.…”

Section: Introductionmentioning

confidence: 99%

Environmental Implications of the Soil-to-Groundwater Migration of Heavy Metals in Mining Area Hotspots

Vesković,

Onjia

2024

Metals

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Groundwater contamination was studied at several hotspot sites in the Majdanpek copper mining area (Serbia). These sites include a milling facility, a metallurgical wastewater treatment plant, a heavy vehicle service area, and a waste disposal site. In addition to Cu, high concentrations of As and heavy metals (Cd and Pb) were detected in groundwater and soil at the same sampling points. Mining operations and heavy vehicle transport activities have been identified as the main sources of pollution. The migration of metals from soil to groundwater, expressed as a concentration ratio, were the highest for Co and the lowest for Mn. The environmental implications of groundwater pollution were studied using the heavy metal pollution index (HPI), Nemerov pollution index (NPI), hazard index (HI), and incremental lifetime cancer risk (ILCR). HPI and NPI show the high potential of groundwater to have adverse environmental effects. HPI ranges in the following descending order of metals: Cd > Pb > As > Mn > Ni > Cr > Hg > Cu > Zn. NPI exceeds the threshold of 0.7 in 66.7% of the samples. Potential human exposure to the studied groundwater may cause severe health problems in adults, with HI ranging from 0.61 to 5.45 and ILCR from 1.72 × 10−4 to 1.27 × 10−3. Children were more susceptible to non-carcinogenic risk than adults, with HI ranging from 0.95 to 8.27. However, the results indicated that children were less prone to carcinogenic risks, with ILCR ranging from 5.35 × 10−5 to 3.98 × 10−4. Arsenic is the most contributing element to both risks. This research imposes the need for enhanced groundwater monitoring at hotspots in the mining area and the adoption of remediation plans and measures.

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Water quality assessment of the Karasu River (Turkey) using various indices, multivariate statistics and APCS-MLR model

Cited by 44 publications

References 40 publications

The multiscale nexus among land use-land cover changes and water quality in the Suquía River Basin, a semi-arid region of Argentina

The multiscale nexus among land use-land cover changes and water quality in the Suquía River Basin, a semi-arid region of Argentina

Evaluation of total dissolved solids in rivers by improved neuro fuzzy approaches using metaheuristic algorithms

Environmental Implications of the Soil-to-Groundwater Migration of Heavy Metals in Mining Area Hotspots

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