Comprehensive Assessment of Water Quality and Pollution Source Apportionment in Wuliangsuhai Lake, Inner Mongolia, China

Shi, Rui; Zhao, Jixin; Shi, Wei; Shi, Song; Wang, Chenchen

doi:10.3390/ijerph17145054

Cited by 30 publications

(12 citation statements)

References 35 publications

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“…Several studies around the world have applied PCA to evaluate and classify water quality for irrigation purposes, including China [112], Turkey [113], Nigeria [114], and Brazil [115]. China applied PCA to the Tongjiyan irrigation area, and the given study indicated that the PCA classification had similar results with other methods such as fuzzy evaluation, the Nemerow index, and improved Nemerow index methods.…”

Section: Discussionmentioning

confidence: 90%

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

Abdel-Fattah

Abd-Elmabod

Aldosari

et al. 2020

Water

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Water scarcity and suitable irrigation water management in arid regions represent tangible challenges for sustainable agriculture. The current study aimed to apply multivariate analysis and to develop a simplified water quality assessment using principal component analysis (PCA) and the agglomerative hierarchical clustering (AHC) technique to assess the water quality of the Bahr Mouise canal in El-Sharkia Governorate, Egypt. The proposed methods depended on the monitored water chemical composition (e.g., pH, water electrical conductivity (ECiw), Ca2+, Mg2+, Na+, K+, HCO3−, Cl−, and SO42−) during 2019. Based on the supervised classification of satellite images (Landsat 8 Operational Land Imager (OLI)), the distinguished land use/land cover types around the Bahr Mouise canal were agriculture, urban, and water bodies, while the dominating land use was agriculture. The water quality of the Bahr Mouise canal was classified into two classes based on the application of the irrigation water quality index (IWQI), while the water quality was classified into three classes using the PCA and AHC methods. Temporal variations in water quality were investigated, where the water qualities in winter, autumn, and spring (January, February, March, April, November, and December) were classified as class I (no restrictions) based on IWQI application, and the water salinity, sodicity, and/or alkalinity did not represent limiting factors for irrigation water quality. On the other hand, in the summer season (May, June, July, August, and October), the irrigation water was classified as class II (low restrictions); therefore, irrigation processes during summer may lead to an increase in the alkalinity hazard. The PCA classifications were compared with the IWQI results; the PCA classifications had similar assessment results during the year, except in September, while the water quality was assigned to class II using the PCA method and class I by applying the IWQI. Furthermore, the normalized difference vegetation index (NDVI) around the Bahr Mouise canal over eight months and climatic data assisted in explaining the fluctuations in water quality during 2019 as a result of changing the crop season and agriculture management. Assessments of water quality help to conserve soil, reduce degradation risk, and support decision makers in order to obtain sustainable agriculture, especially under water irrigation scarcity and the limited agricultural land in such an arid region.

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Section: Discussionmentioning

confidence: 90%

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

Abdel-Fattah

Abd-Elmabod

Aldosari

et al. 2020

Water

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“…Despite this situation, the comprehensive pollution index values obtained in ALM were low in comparison to other studies such as the report by Tibebe et al [ 39 ], who obtained values from 0.68 to 0.98 for Lake Tana in Ethiopia. Using this index, Shi et al [ 40 ] and Zhao et al [ 41 ] demonstrated contamination of Lake Wuliangsuhai and Lake Baiyangdian, respectively. Shi et al [ 40 ] discovered that the drainage of agricultural lands was the main source of pollutants in Wuliangsuhai Lake, China.…”

Section: Resultsmentioning

confidence: 99%

“…Using this index, Shi et al [ 40 ] and Zhao et al [ 41 ] demonstrated contamination of Lake Wuliangsuhai and Lake Baiyangdian, respectively. Shi et al [ 40 ] discovered that the drainage of agricultural lands was the main source of pollutants in Wuliangsuhai Lake, China. They also report that the water quality is highly influenced by effluents from diffuse sources and by the many tourist attractions around the Lake.…”

Section: Resultsmentioning

confidence: 99%

“…The comprehensive pollution index was applied to qualitatively assess the surface water quality in the ALM reservoir. Furthermore, this index has been applied to assess water quality in many studies [ 39 , 40 , 41 , 42 , 43 ]. The comprehensive pollution index was determined by Equation (3):

where P is the comprehensive pollution index, C i is the concentration of the measured water quality parameter (mg/L), S i represents the guideline value of water quality (this reference was taken from the National Water Commission in Mexico for agricultural use) and n is the number of selected pollutants (BOD, COD, NO 2 , NO 3 , TN, and TP).…”

Section: Methodsmentioning

confidence: 99%

“…Finally, the value of P was used to classify the level of quality of the ALM reservoir [ 44 ]. The comprehensive pollution index classifies a waterbody as follows: for level I (≤0.20) the classification is “Cleanness”; level II (0.21-0.40) is “Sub-cleanness”; level III (0.41-1.00) is “Slight pollution”; level IV (1.01-2.0) is “Moderate pollution” and level V (≥2.01) is “Severe pollution” [ 40 ]. This index is a simplified contamination index, which is also known as the Raw contamination index [ 6 ].…”

Section: Methodsmentioning

confidence: 99%

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Assessment of Water Quality in A Tropical Reservoir in Mexico: Seasonal, Spatial and Multivariable Analysis

Loaiza

Rangel‐Peraza

Sanhouse-García

et al. 2021

IJERPH

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Agricultural activities are highly related to the reduction of the availability of water resources due to the consumption of freshwater for crop irrigation, the use of fertilizers and pesticides. In this study, the water quality of the Adolfo López Mateos (ALM) reservoir was evaluated. This is one of the most important reservoirs in Mexico since the water stored is used mainly for crop irrigation in the most productive agricultural region. A comprehensive evaluation of water quality was carried out by analyzing the behavior of 23 parameters at four sampling points in the period of 2012-2019. The analysis of the spatial behavior of the water quality parameters was studied by spatial distribution graphs using the Inverse Distance Weighting interpolation. Pearson correlation was performed to better describe the behavior of all water quality parameters. This analysis revealed that many of these parameters were significantly correlated. The Principal Components Analysis (PCA) was carried out and showed the importance of water quality parameters. Ten principal components were obtained, which explained almost 90% of the total variation of the data. Additionally, the comprehensive pollution index showed a slight water quality variation in the ALM reservoir. This study also demonstrated that the main source of contamination in this reservoir occurs near sampling point one. Finally, the results obtained indicated that a contamination risk in the waterbody and further severe ecosystem degradations may occur if appropriate management is not taken.

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Study of biological quality of lake waters based on phycocyanin using tree‐based methodologies

Kheimi,

Almadani,

Ramezani‐Charmahineh

et al. 2024

Ecohydrology

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The provision of drinking water, agricultural, and industrial applications by reservoirs has made lake exploration and monitoring unavoidable. The features of the ecosystem, particularly physical and chemical elements, influence the evaluation of the quality of water resources. Lakes undergo extensive qualitative changes due to their vast amount of water. In general, these bodies of water represent geological conditions as well as water contamination produced by natural and human activities. In the present research, the prediction of the amount of phycocyanin (fPC) in the water of Lake Michigan has been implemented employing four tree‐based machine learning techniques based on seasonality factors. Phycocyanin has significant effects on quality parameters such as turbidity, chlorophyll concentration, algal bloom, and dissolved oxygen in water by affecting the photosynthesis process of algae. Therefore, in this study, the prediction of the amount of phycocyanin dissolved in the lake water using the mentioned variables, along with the temperature of the water, specific conductance, and pH, has been able to interpret the quality of the water and the occurrence of phenomena such as algal blooms. The results of the models in predicting fPCs equal to 0.44 and 0.55 μg/L were consistent with the natural conditions of the lake, and it seems that ensemble tree–based models, along with the biological index of fPC, formed the right combination of input and output parameters in modeling and obtained the lowest prediction error (root‐mean‐square error [RMSE] boosted trees = 0.0140 and RMSE random forests = 0.0141 μg/L).

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Comprehensive Assessment of Water Quality and Pollution Source Apportionment in Wuliangsuhai Lake, Inner Mongolia, China

Cited by 30 publications

References 35 publications

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

Assessment of Water Quality in A Tropical Reservoir in Mexico: Seasonal, Spatial and Multivariable Analysis

Study of biological quality of lake waters based on phycocyanin using tree‐based methodologies

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