A case study of thermal and chemical stratification in a drinking water reservoir

Shi, Jianghong; Wang, Lianxiang; Yang, Yongrui

doi:10.1016/j.scitotenv.2022.157787

Cited by 23 publications

(5 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, changes in the proportion of hypoxia are consistent with changes in thermal stratification stability [100]. Thermal stratification leads to a decrease in both oxygen content and the volume of oxygen-rich zones [101], and the relationship between thermal stratification and density stratification, oxygen stratification, and other chemical stratifications is complex and close [84,[102][103][104]. Hypoxia caused by stratification promotes the release of substances such as methylmercury [105], phosphorus [106], and arsenic [107], leading to water acidification [108], while the disappearance of stratification resulting from mixing can redistribute substances such as polychlorinated biphenyls [109], resulting in complex environmental consequences.…”

Section: How Thermal Stratification Affects Lake Ecology 41 the Impac...mentioning

confidence: 75%

Challenge to Lake Ecosystems: Changes in Thermal Structure Triggered by Climate Change

Zhang,

Shen,

et al. 2024

Water

View full text Add to dashboard Cite

Human activities, global warming, frequent extreme weather events, and changes in atmospheric composition affect the solar radiation reaching the Earth’s surface, affect mass and heat transfer at the air–water interface, and induce oscillations in wind-driven internal waves. This leads to changes in the spatiotemporal characteristics of thermal stratification in lakes, altering lake circulation patterns and vertical mass transfer. However, thermal stratification structures are often overlooked. The intensification of lake thermal stratification due to warming may lead to increased release of bottom pollutants, spreading through the dynamic behavior of the thermocline to the epilimnion. Moreover, the increased heat storage is beneficial for the growth and development of certain phytoplankton, resulting in rapid transitions of the original steady state of lakes. Consequently, water quality deterioration, ecological degradation, and declining biodiversity may occur. Conventional surface water monitoring may not provide comprehensive, accurate, and timely assessments. Model simulations can better predict future thermal stratification behaviors, reducing financial burdens, providing more refined assessments, and thus preventing subsequent environmental issues.

show abstract

Section: How Thermal Stratification Affects Lake Ecology 41 the Impac...mentioning

confidence: 75%

Challenge to Lake Ecosystems: Changes in Thermal Structure Triggered by Climate Change

Zhang,

Shen,

et al. 2024

Water

View full text Add to dashboard Cite

show abstract

“…As a dimensionless parameter used to reflect the strength and hydrodynamic force of thermal stratification, RWCS is calculated as follows [19,20]:…”

Section: Relative Water Column Stability (Rwcs) Calculationmentioning

confidence: 99%

“…The lower the RWCS/H value, the lower the thermal stratification stability. Due to the low turbidity of Danjiangkou Reservoir, the water density was derived from the water temperature using the following formula [20]:…”

Section: Relative Water Column Stability (Rwcs) Calculationmentioning

confidence: 99%

Phytoplankton Communities’ Response to Thermal Stratification and Changing Environmental Conditions in a Deep-Water Reservoir: Stochastic and Deterministic Processes

Wang,

Li,

et al. 2024

Sustainability

View full text Add to dashboard Cite

Thermal stratification has become more extensive and prolonged because of global warming, and this change has had a significant impact on the distribution patterns of the phytoplankton communities. However, the response of phytoplankton community structures and assembly processes to thermal stratification is not fully understood. We predicted that the structure and assembly processes of phytoplankton communities would be affected by thermal stratification among water layers associated with environmental condition changes, reflecting certain patterns in temporal and spatial scales. Phytoplankton from Danjiangkou Reservoir were collected from October 2021 to July 2022 to verify this prediction. During the sampling period, Danjiangkou Reservoir remained thermally stratified with stability. The composition of the phytoplankton community in the surface layer significantly differed from that in both the thermocline and bottom layer. The phenomenon of thermal stratification affected the pattern of nitrogen and phosphorus distribution and, thus, the processes of the phytoplankton community structures. Deterministic processes had a greater influence on the assembly of the phytoplankton communities in the surface and bottom layers. In contrast, stochastic processes were more prevalent in the assembly of the thermocline phytoplankton community. The phytoplankton community within the thermocline layer exhibited a broader niche range than that in the surface and bottom layers, showing notable dissimilarity from that of the bottom layer. Canonical correspondence analysis (CCA) revealed that the vertical distributions of the phytoplankton communities were significantly correlated with NH4+-N, pH, and water temperature (WT). In summary, this study explained the distribution patterns of phytoplankton community structures and assembly processes in deep-water reservoirs during the stratification period. Additionally, the study explored the potential of using the distribution patterns of phytoplankton in stratified-state deep-water reservoirs under a subtropical–warm temperate climate as climate indicators in the context of global warming.

show abstract

“…Moreover, this study optimizes the selection of indicators and models to continuously improve the quality of the assessment. These improvements contribute to the theoretical foundation and application value compared to traditional methods [32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Improving Analytic Hierarchy Process inside the Analytic Group Decision-Making Approach Method with Two-Dimensional Cloud Model for Water Resource Pollution Risk Warning Evaluation: A Case Study in Shandong Province, China

Zhou,

Li,

Gao

et al. 2024

Water

View full text Add to dashboard Cite

This study proposes a water resource pollution risk warning evaluation method. Firstly, an evaluation system is constructed, consisting of 15 secondary indicators in four aspects: water quality, ecology, utilization protection, and water disasters. Then, an improved AGA-AHP method and coefficient of variation method are used to determine the weights of each indicator. Cloud models are employed to describe the characteristics of standard clouds and evaluation clouds, establishing a two-dimensional cloud model with risk probability and hazard level as variables. Taking a certain region in Shandong Province, China, as an example, the quantitative analysis results indicate that the water pollution risk level in the area is classified as Level IV, with particular attention needed for water quality and management indicators. Simultaneously, a series of measures such as source control, monitoring and early warning, emergency response, and public participation are proposed to further reduce the risk. The research findings demonstrate the following: (1) The establishment of a comprehensive indicator system for multidimensional assessment; (2) The combination of the AGA-AHP method and cloud model for quantitative analysis; (3) The practicality of the method validated through the case study; (4) Providing a basis for subsequent decision-making. This study provides new insights for water environmental risk management, but a further optimization of the model to enhance predictive capability is required when applied in practical scenarios. Nevertheless, the preliminary validation of this method’s application prospects in water resource risk monitoring has been achieved.

show abstract

A case study of thermal and chemical stratification in a drinking water reservoir

Cited by 23 publications

References 50 publications

Challenge to Lake Ecosystems: Changes in Thermal Structure Triggered by Climate Change

Challenge to Lake Ecosystems: Changes in Thermal Structure Triggered by Climate Change

Phytoplankton Communities’ Response to Thermal Stratification and Changing Environmental Conditions in a Deep-Water Reservoir: Stochastic and Deterministic Processes

Improving Analytic Hierarchy Process inside the Analytic Group Decision-Making Approach Method with Two-Dimensional Cloud Model for Water Resource Pollution Risk Warning Evaluation: A Case Study in Shandong Province, China

Contact Info

Product

Resources

About