Article
Engineering, Multidisciplinary
Jiannan Luo, Yong Liu, Xueli Li, Xin Xin, Wenxi Lu
Summary: In this study, a two-stage adaptive surrogate model-assisted trust region GA (TSASM-TRGA) framework was developed to improve the accuracy and stability of groundwater contamination source inversion. The results showed that the TSASM-TRGA framework outperformed other frameworks in terms of accuracy and stability.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Engineering, Civil
Mengtian Wu, Lingling Wang, Jin Xu, Zhe Wang, Pengjie Hu, Hongwu Tang
Summary: This paper proposes a multi-objective ensemble surrogate-based optimization algorithm named MESOA for groundwater optimization designs. By using surrogate models with various basis functions and an adaptive switching technique, MESOA can fully depict the outline of the true Pareto front with limited simulation invocations.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Zidong Pan, Wenxi Lu, Yue Fan, Jiuhui Li
Summary: A simulation-optimization method based on Bayesian regularization deep neural network (BRDNN) surrogate model was proposed to efficiently solve high-nonlinear inverse problem, identifying eight variables including locations and release intensities of pollution sources and hydraulic conductivities. The three hidden layers in the BRDNN surrogate model significantly improved the fitting capacity of nonlinear mapping relationship to the simulation model, while Bayesian regularization was applied to solve the overfitting problem.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Engineering, Civil
Zheng Han, Wenxi Lu, Yue Fan, Jianan Xu, Jin Lin
Summary: A new stochastic S/O framework is proposed and applied to a real-world case in China, overcoming limitations of traditional multi-objective evolutionary algorithms by introducing information entropy theory. Additionally, a surrogate model using MGGP method is developed, significantly reducing computational burden.
WATER RESOURCES MANAGEMENT
(2021)
Article
Computer Science, Artificial Intelligence
Kai Zhang, Chaonan Shen, Gary G. Yen, Zhiwei Xu, Juanjuan He
Summary: This article introduces a two-stage double niched evolution strategy, DN-MMOES, to effectively and efficiently search for global Pareto optimal solutions. The proposed algorithm employs niching strategy in the decision space in the first stage and double niching strategy in both decision and objective spaces in the second stage, as well as an effective decision density self-adaptive strategy to improve imbalanced decision space density. The experimental results demonstrate that DN-MMOES outperforms eight state-of-the-art MMOEAs in searching for complete Pareto subsets and Pareto front on IDMP and CEC 2019 MMOPs test suite.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Jing Liang, Leiyu Zhang, Kunjie Yu, Boyang Qu, Fuxing Shang, Kangjia Qiao
Summary: In this study, an interactive niching-based two-stage evolutionary algorithm for constrained multiobjective optimization (INCMO) is proposed. The algorithm uses two populations to optimize the multiobjective optimization problem and employs different niching mechanisms to maintain population diversity. The proposed method outperforms other methods in terms of performance on various test suites.
SWARM AND EVOLUTIONARY COMPUTATION
(2023)
Article
Automation & Control Systems
Anuj Pal, Ling Zhu, Yan Wang, Guoming G. Zhu
Summary: This article experimentally calibrates and optimizes the control parameters of an engine using a stochastic surrogate-assisted optimization method, and achieves good experimental results.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Geosciences, Multidisciplinary
Yongkai An, Xueman Yan, Wenxi Lu, Hui Qian, Zaiyong Zhang
Summary: The study developed an innovative framework that combined an improved MCMC approach with surrogate models to speed up convergence of posterior distribution and enhance identification accuracy of groundwater pollution source parameters. The KRG surrogate model showed higher accuracy compared to other surrogate models due to its linear unbiased estimation characteristic.
HYDROGEOLOGY JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Yi Zhao, Jian Zhao, Jianchao Zeng, Ying Tan
Summary: This paper proposes a two-stage infill strategy and surrogate-ensemble assisted optimization algorithm for solving expensive many-objective optimization problems. Experimental results demonstrate the superiority of this algorithm in solving computationally expensive many-objective optimization problems.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Tengfei Tang, Lei Lei, Li Xiao, Yili Peng, Hongjian Zhou
Summary: An optimization framework based on Optimized Latin Hypercube Sampling and Bayesian optimization is proposed for efficient design of throttle elements. The framework is validated through numerical cases and shows good performance in engineering problems, with computational fluid dynamics error less than 5% compared to experimental data.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Environmental Sciences
Jiuhui Li, Zhengfang Wu, Hongshi He, Wenxi Lu
Summary: The location and release history of groundwater contaminant sources (GCSs) are usually unknown, but previous studies have used prior information to identify GCSs. This study compared two methods for GCSs identification and found that the S/O method is more suitable for GCSs identification than the EnKF method.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Dan Wang, Peiyue Li, Ningning Yang, Chunliu Yang, Yuhan Zhou, Jiahui Li
Summary: This study used chemical indicators, dual isotopes of nitrate, random forest model, and Bayesian stable isotope mixing model to investigate the sources and destiny of nitrate in soil and groundwater within intensive agricultural areas. The results showed that nitrate accumulation in cropland and kiwifruit orchard led to subsequent leaching into deeper vadose zones and ultimately groundwater. The study also identified key variables influencing groundwater nitrate concentration and quantified the sources contribution at various depths.
ENVIRONMENTAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Xilu Wang, Yaochu Jin, Sebastian Schmitt, Markus Olhofer
Summary: A transfer learning scheme based on surrogate-assisted evolutionary algorithms is proposed to address the issue of non-uniform evaluation times in multi-objective optimization, demonstrating competitive performance in solving bi-objective optimization problems.
EVOLUTIONARY COMPUTATION
(2022)
Article
Engineering, Environmental
Jiuhui Li, Zhengfang Wu, Hongshi He, Wenxi Lu
Summary: The grey wolf optimization algorithm (GWO) has the disadvantage of premature convergence when solving the optimization model for groundwater contamination sources (IGCSs) due to its weak local search ability. To improve it, a hybrid grey wolf gradient optimization algorithm (HGWGO) was developed by integrating GWO with the gradient descent algorithm, which showed a strong local search ability and less dependence on the initial value. The HGWGO was applied to the optimization model to enhance the accuracy of IGCSs. Additionally, a surrogate model using a deep belief neural network (DBNN) was established to participate in the iterative calculation, reducing the computational load and time consumption.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Multidisciplinary Sciences
Rachida Bouhlila, Nejla T. Hariga
Summary: This paper applies the principle of reciprocity to flow and solute transport equations in porous media, achieving successful pollution sources identification and pollutant concentration recovery in aquifers. The proposed method demonstrates high efficiency in different levels of data availability and noisy data situations.
SCIENTIFIC REPORTS
(2022)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)