Probabilistic eutrophication risk mapping in response to reservoir remediation DOI Creative Commons
Christina W. Tsai,

Chen-Hsin Chiang,

Stanley W. Shen

et al.

Journal of Hydrology Regional Studies, Journal Year: 2022, Volume and Issue: 44, P. 101213 - 101213

Published: Sept. 29, 2022

Reservoir eutrophication is a critical natural hazard in countries with rapid agricultural and industrial development. To simulate the of Fengshan Reservoir, algal bloom occurrence patterns reservoir were modeled using Environmental Fluid Dynamics Code (EFDC) for understanding dynamics. The calibration validation EFDC performed by comparing model results field data. was calibrated against hydrodynamic data, including water level temperature, quality data from four monitoring stations study area. Uncertainty analysis conducted perturbance moment method (PMM) model. Parameter uncertainty considered this study. order importance parameters terms their contribution to overall simulations obtained. validated then used investigate three contaminant remediation scenarios: (a) increasing level, (b) dilution, (c) reaeration. Operational also considered, as there exists variability effort project execution complex engineering system like reservoirs. Finally, probabilistic risk mapping established each facilitate decision-making assessment.

Language: Английский

Spatial and temporal variations in the relationship between lake water surface temperatures and water quality - A case study of Dianchi Lake DOI
Kun Yang, Zhenyu Yu, Yi Luo

et al.

The Science of The Total Environment, Journal Year: 2017, Volume and Issue: 624, P. 859 - 871

Published: Dec. 27, 2017

Language: Английский

Citations

237

An integrated approach to investigate the relationship of coupling coordination between social economy and water environment on urban scale - A case study of Kunming DOI

Dan Cui,

Xin Chen,

Yinglan Xue

et al.

Journal of Environmental Management, Journal Year: 2019, Volume and Issue: 234, P. 189 - 199

Published: Jan. 9, 2019

Language: Английский

Citations

194

Machine learning based marine water quality prediction for coastal hydro-environment management DOI
Tianan Deng, Kwok‐wing Chau, Huan‐Feng Duan

et al.

Journal of Environmental Management, Journal Year: 2021, Volume and Issue: 284, P. 112051 - 112051

Published: Jan. 27, 2021

Language: Английский

Citations

166

Impacts of a large river-to-lake water diversion project on lacustrine phytoplankton communities DOI
Jiangyu Dai,

Shiqiang Wu,

Xiufeng Wu

et al.

Journal of Hydrology, Journal Year: 2020, Volume and Issue: 587, P. 124938 - 124938

Published: April 11, 2020

Language: Английский

Citations

75

Assessment and a review of research on surface water quality modeling DOI
Jing Bai, Jian Zhao, Zhenyu Zhang

et al.

Ecological Modelling, Journal Year: 2022, Volume and Issue: 466, P. 109888 - 109888

Published: Feb. 3, 2022

Language: Английский

Citations

62

Integrated evaluation of the impact of water diversion on water quality index and phytoplankton assemblages of eutrophic lake: A case study of Yilong Lake DOI
Yundong Wu, Chengrong Peng, Genbao Li

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 357, P. 120707 - 120707

Published: March 29, 2024

Language: Английский

Citations

14

Spatiotemporal characterization and forecasting of coastal water quality in the semi-enclosed Tolo Harbour based on machine learning and EKC analysis DOI Creative Commons
Tianan Deng, Huan‐Feng Duan, Alireza Keramat

et al.

Engineering Applications of Computational Fluid Mechanics, Journal Year: 2022, Volume and Issue: 16(1), P. 694 - 712

Published: Feb. 27, 2022

Characterizing and forecasting coastal water quality spatiotemporal evolution should be significant to ecosystem management. However, high-quality modeling their evolutions is rather challenging due complex dynamic mechanisms especially in a spatially temporally heterogenous semi-enclosed bay. To this end, study develops framework incorporating machine learning (ML) algorithms the Environmental Kuznets Curves (EKC) analysis model, analyze forecast variations of indicators for different subzones seasons Tolo Harbour Hong Kong. The application results indicate that developed ML-based with an accuracy range 0.672 ∼ 0.998 well-suited understanding harbour compared conventional approach. Furthermore, characteristics bay are analyzed discussed hydro-environmental Moreover, EKC also performed determining essential variables under 95% confidence interval Kong PCGDP projection then implemented model future prediction.

Language: Английский

Citations

31

Bacterial community and eutrophic index analysis of the East Lake DOI
Bin Ji,

Jiechao Liang,

Yingqun Ma

et al.

Environmental Pollution, Journal Year: 2019, Volume and Issue: 252, P. 682 - 688

Published: May 29, 2019

Language: Английский

Citations

52

Lake surface water temperature prediction and changing characteristics analysis - A case study of 11 natural lakes in Yunnan-Guizhou Plateau DOI
Zhenyu Yu, Kun Yang, Yi Luo

et al.

Journal of Cleaner Production, Journal Year: 2020, Volume and Issue: 276, P. 122689 - 122689

Published: July 18, 2020

Language: Английский

Citations

49

Modelling impacts of water diversion on water quality in an urban artificial lake DOI
Haiyan Yang, Jiaqi Wang, Jiuhao Li

et al.

Environmental Pollution, Journal Year: 2021, Volume and Issue: 276, P. 116694 - 116694

Published: Feb. 11, 2021

Language: Английский

Citations

35