A framework for exploring environmental risk of the longest inter-basin water diversion project under the influence of multiple factors: A case study in China

Zhang, Chi; Nong, Xizhi; Zhong, Hua; Shao, Dongguo; Chen, Lihua; Ji, Liang

doi:10.1016/j.jenvman.2022.116036

Cited by 15 publications

(7 citation statements)

References 54 publications

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“…The proposed coupling method using the LHS and the Vine Copula model showed robustness and comparable ability. The simulation results were consistent with the Monte Carlo simulation by Zhang et al (2022). However, when analyzing the probability under special conditions such as the ACD > 0 cells/L (probability = 100%), the results of this study were more in line with the actual situation.…”

Section: Model Uncertaintysupporting

confidence: 83%

“…The data set of the Vine Copula model was simulated by the LHS, and the risk of ACD under different environmental conditions was analysed based on the Bayesian theory. Previous studies have reported that the limited influence of DO on algae proliferation in the MRSNWDPC, and the flow velocity has strong relationship with flow discharge (Zhang et al, 2022). Considering the actual project operation, this study will mainly explore the influence of WT and V on the ACD variations.…”

Section: Multivariate Risk Model Constructionmentioning

confidence: 99%

“…The early-warning thresholds of algal cell density in the upstream, midstream, and downstream sections of the MRSNWDPC were set to 300 × 10 4 cells/L, 500 × 10 4 cells/L, and 500 × 10 4 cells/L, respectively, according to the actual situation of the project and previous study (Zhang et al, 2022). The event in which the ACD has a 50% probability of exceeding the threshold was defined as "algal proliferation risk. "…”

Section: Algal-controlled Threshold For Different Sectionsmentioning

confidence: 99%

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Algal proliferation risk assessment using Vine Copula-based coupling methods in the South-to-North Water Diversion Project of China

Nong

Zeng

et al. 2023

Front. Ecol. Evol.

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The Middle Route of the South-to-North Water Diversion Project of China (MRSNWDPC), i.e., the longest inter-basin water diversion project (1,432 km) in the world, has delivered more than 60 billion m3 of water resources to North China and benefiting more than 100 million people since December 2014. However, the abnormal algal proliferation in the main canal under low nutrient background has seriously threatened the water quality safety of this mega project. In this research, 3 years of monitoring data matrix, including water temperature (WT), flow discharge (Q), flow velocity (V), dissolved oxygen (DO), and the algal cell density (ACD), from the main canal of the MRSNWDPC were analyzed. The nonlinear relationships were determined based on multiple regression models, and a composite risk analysis model was constructed by Latin hypercube sampling (LHS) method coupled with Vine Copula function. The impacts of different hydrological and environmental factors on algal proliferation were comprehensively analyzed by Bayesian theory. The results showed that the WT gradually decreased from upstream to downstream, with a narrow range of 16.6–17.4°C, and the annual average concentrations of DO showed a gradual increase from upstream to downstream. The flow velocity of MRSNWDPC had a tendency to increase year by year, and the maximum flow velocity exceeds 0.8 m/s upstream, midstream and downstream by 2018. The ACD accumulated along the main canal, and the annual average ACDs of downstream were the highest, ranging from 366.17 to 462.95 × 104 cells/L. The joint early-warning method considering both water temperature and flow velocity conditions is an effective way for algal proliferation risk warning management. When water temperatures of the upstream, midstream, and downstream were below 26, 26, and 23°C, respectively, the algal proliferation risk can be controlled under 50% by the flow velocity at 0.3 m/s; otherwise, the flow velocity needs to be regulated higher than 0.8 m/s. In order to keep the midstream and downstream avoid abnormal algal proliferation events (ACD ≥ 500 × 104 cells/L), the corresponding ACDs of the upstream and midstream need to be controlled lower than 319 × 104 cells/L and 470 × 104 cells/L, respectively. This study provides a scientific reference for the long-distance water diversion project’s algal control and environmental protection. The proposed coupling Vine Copula models can also be widely applied to multivariate risk analysis fields.

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Section: Model Uncertaintysupporting

confidence: 83%

Section: Multivariate Risk Model Constructionmentioning

confidence: 99%

Section: Algal-controlled Threshold For Different Sectionsmentioning

confidence: 99%

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Algal proliferation risk assessment using Vine Copula-based coupling methods in the South-to-North Water Diversion Project of China

Nong

Zeng

et al. 2023

Front. Ecol. Evol.

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“…The application of machine learning algorithms also holds promise in accurately forecasting the performance of adsorption packages, further enhancing the precision and efficiency of water purification processes. Furthermore, developing comprehensive management frameworks for water quality forecasting can also be helpful for detecting such contamination in the first place in water systems [20].…”

Section: Discussionmentioning

confidence: 99%

Dynamic Modelling, Simulation, and Sensitive Analysis of Lead Removal in a Fixed-Bed Adsorption Column using Waste-Based Materials

Gheibi,

Wacławek,

Leo

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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This study focuses on dynamic modelling and numerical simulation of lead removal from contaminated water using a fixed-bed adsorption column packed with waste-based adsorbents. The pressing need for efficient and sustainable water treatment methods, particularly for heavy metal removal, underscores the significance of this research. Lead contamination in water sources poses severe health risks, necessitating the development of effective removal strategies. The present investigation centres on a comprehensive mathematical model that considers critical parameters, including the column’s physical dimensions, flow rate, initial lead concentration, adsorption rate constant, and adsorbent density. This model is expressed as a partial differential equation (PDE) describing the temporal and spatial evolution of lead concentration along the fixed-bed column. To solve the PDE, the method of lines, a powerful numerical technique that discretises the spatial domain and handles the resulting system of ordinary differential equations (ODEs) using an adaptive solver, is employed. Following that, the effect factors of the simulation process are evaluated by sensitive analysis approach. Simulations are conducted to elucidate the intricate dynamics of lead removal over time and column height. The numerical approach enables the prediction of lead concentration profiles within the column at various time intervals, providing crucial insights into the behavior of the adsorption process.

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“…In water-related engineering, there is significant focus on risk assessment studies pertaining to sizeable water diversion projects [45] and water resource management [46]. Nevertheless, in contrast to these investigations, this research prioritized the evaluation process for leakage risk in small-scale water distribution networks.…”

Section: Discussionmentioning

confidence: 99%

Leakage Risk Assessment of Urban Water Distribution Network Based on Unascertained Measure Theory and Game Theory Weighting Method

Xiong,

Wang,

Gao

et al. 2023

Water

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Assessing the risk of water leakage within urban water distribution networks (UWDN) is crucial prior to implementing any control measures. Conducting a risk assessment facilitates the development of effective water leakage management plans. By comprehensively analyzing the probability and loss factors that contribute to the risk of leakage in UWDN, this paper presents an evaluation index system for pipeline leakage risk. This index system utilized both quantitative and qualitative data on influencing factors derived from an actual pipeline network. In order to determine the precise level of pipeline leakage risk, an index theory-based pipeline leakage risk evaluation model was established. This model consisted of a single-index measure function and a multi-index comprehensive measure vector. The combined weight of evaluation indices through game theory was used to determine the weight of each index, thereby minimizing the negative effects of a single weight determination method. A risk assessment model that evaluated the leakage risk of specific pipelines was constructed based on actual data from the water distribution network in a certain area of China. The analysis showed that the risk of pipeline leakage in this area was mainly classified as a third-level risk, which is consistent with the actual evaluation results obtained from field visits.

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A framework for exploring environmental risk of the longest inter-basin water diversion project under the influence of multiple factors: A case study in China

Cited by 15 publications

References 54 publications

Algal proliferation risk assessment using Vine Copula-based coupling methods in the South-to-North Water Diversion Project of China

Algal proliferation risk assessment using Vine Copula-based coupling methods in the South-to-North Water Diversion Project of China

Dynamic Modelling, Simulation, and Sensitive Analysis of Lead Removal in a Fixed-Bed Adsorption Column using Waste-Based Materials

Leakage Risk Assessment of Urban Water Distribution Network Based on Unascertained Measure Theory and Game Theory Weighting Method

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