Article
Engineering, Civil
Li Jing, Jun Kong, Jun Wang, Teng Xu, Mingjie Pan, Weilun Chen
Summary: This study proposes a new method, called RC-EnKF, based on EnKF to identify contaminant source information. The method uses the relation coefficient of concentration as a state variable in the assimilation process, which can decouple the release source mass from the parameter group of unknown contaminant information. This improves the assimilation speed and reduces interference with assimilation accuracy.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Civil
Valeria Todaro, Marco D'Oria, Maria Giovanna Tanda, J. Jaime Gomez-Hernandez
Summary: The article presents a new approach using ES-MDA method to determine the source location and time history of a pollutant in groundwater contamination events. Through two case studies, the method's application and impact in practice are demonstrated.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Arezou Dodangeh, Mohammad Mahdi Rajabi, Jesus Carrera, Marwan Fahs
Summary: Coastal aquifers, which are vital water sources for over one billion people, face the challenges of seawater intrusion and anthropogenic contamination. Identification and localization of contaminant source characteristics are needed to reduce contamination. However, most existing studies have focused on inland aquifers and have not addressed the complexities of coastal settings. This study presents an efficient methodology for identifying contaminant source characteristics and aquifer hydraulic conductivity in coastal aquifers. It uses numerical modeling and artificial neural network metamodels in the CRD-EnKF algorithm. The study successfully applies this approach to the complex setting of coastal aquifers and analyzes common issues in contaminant source identification monitoring.
JOURNAL OF CONTAMINANT HYDROLOGY
(2022)
Article
Engineering, Civil
Teng Xu, J. Jaime Gomez-Hernandez, Zi Chen, Chunhui Lu
Summary: Understanding a contaminant source is crucial for managing a polluted aquifer, but source information may be unavailable when pollutants are detected. The Ensemble Smoother with Multiple Data Assimilation (ES-MDA) is proposed as a more efficient solution than the restart Ensemble Kalman Filter (r-EnKF), but requires a large number of assimilations to achieve the same level of accuracy.
JOURNAL OF HYDROLOGY
(2021)
Article
Mathematics, Applied
Alexander Wikner, Jaideep Pathak, Brian R. Hunt, Istvan Szunyogh, Michelle Girvan, Edward Ott
Summary: This study discusses the forecasting of chaotic dynamical systems using noisy partial measurements data, with a focus on combining machine learning with knowledge-based models to improve predictions. By assimilating synthetic data and training machine learning models with partial measurements, it shows potential to correct imperfections in knowledge-based models and improve forecasting accuracy.
Article
Engineering, Civil
Zibo Wang, Wenxi Lu, Zhenbo Chang, Han Wang
Summary: The study combined EnKF and ASACO algorithms to construct an EnKF-ASACO algorithm for pollution source identification and model parameter optimization. The EnKF algorithm provided a good initial point, while the ASACO algorithm improved search efficiency using an adaptive step length search strategy.
JOURNAL OF HYDROLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Zidong Pan, Wenxi Lu, Han Wang, Yukun Bai
Summary: A novel ensemble learning search framework using auto extreme gradient boosting tree was proposed to solve groundwater contaminant source identification (GCSI) problem. The framework achieved improved search accuracy and efficiency by employing boosting strategy (BOS) and auto xgboost.
ENVIRONMENTAL MODELLING & SOFTWARE
(2023)
Article
Physics, Mathematical
Carlos A. Michelen Strofer, Xin-Lei Zhang, Heng Xiao
Summary: This paper introduces the DAFI code as a flexible framework for data assimilation and field inversion problems. The code utilizes ensemble Kalman filters to solve the problems and offers built-in uncertainty quantification with Bayesian methods. Additionally, it provides tools and I/O utilities for integration with OpenFOAM and showcases its capabilities through several test cases.
COMMUNICATIONS IN COMPUTATIONAL PHYSICS
(2021)
Article
Water Resources
Andrew Pensoneault, Witold F. Krajewski, Nicolas Velasquez, Xueyu Zhu, Ricardo Mantilla
Summary: This paper discusses the application of data assimilation techniques in hydrology, focusing on the potential of EnKF and its extensions in sequential state estimation and Bayesian inverse problems. The authors improve the streamflow in a virtual catchment using the EKI algorithm and demonstrate its favorable performance.
ADVANCES IN WATER RESOURCES
(2023)
Article
Engineering, Electrical & Electronic
M. A. Gonzalez-Cagigal, J. A. Rosendo-Macias, A. Gomez-Exposito
Summary: This research presents a state estimation approach using Kalman filtering to identify the phase to which single-phase customers are connected in three-phase distribution grids. The study compares different nonlinear formulations of the Kalman filter and shows that the ensemble Kalman filter provides better estimation results as the system size increases. The accuracy, robustness, and limitations of the estimator are also tested with consideration of measurement errors.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Meteorology & Atmospheric Sciences
Elias D. Nino-Ruiz, Randy S. Consuegra S. Ortega, Magdalena Lucini
Summary: This paper presents the efficient and practical implementation of sequential data assimilation methods for the SPEEDY Model into climate prediction. The computational implementation of SPEEDY blends the time integrator and the spatial discretization to accelerate algebraic computations. Augmented vector states are used to propagate analysis innovations from positions to velocities.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
(2023)
Article
Mechanics
Zhiwen Deng, Chuangxin He, Yingzheng Liu
Summary: This paper focuses on the optimal sensor placement strategy based on a deep neural network for turbulent flow recovery within the data assimilation framework of the ensemble Kalman filter. The results demonstrate the effectiveness and robustness of the proposed strategy, showing that RANS models with EnKF augmentation were substantially improved over their original counterparts. The study concludes that the DNN-based OSP with the selection of the five most sensitive sensors can efficiently reduce the number of sensors while achieving similar or better assimilated performance.
Article
Engineering, Civil
Aref Panjehfouladgaran, Mohammad Mahdi Rajabi
Summary: This study addresses the challenge of contaminant source characterization in complex transient velocity fields, specifically in coastal aquifers. The proposed methodology combines a numerical model of density-dependent flow and multiple-species solute transport, artificial neural networks, and a customized Kalman filtering technique. It provides an effective way to estimate the location and strength of contaminant sources.
JOURNAL OF HYDROLOGY
(2022)
Article
Engineering, Marine
Shaokun Deng, Zheqi Shen, Shengli Chen, Renxi Wang
Summary: The initial ensemble has an impact on the performance of ensemble-based assimilation techniques. The differences in the initial ensemble affect the convergence rate of assimilation, but all experiments eventually reach convergence. Sea surface height and sea surface salinity are more sensitive to the initial ensemble. The white-noise perturbation scheme has the largest effect, and the influence of different initial ensembles on sea surface height is concentrated in the region of the Antarctic Circumpolar Current.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Astronomy & Astrophysics
Michael R. Goodliff, Steven J. Fletcher, Anton J. Kliewer, Andrew S. Jones, John M. Forsythe
Summary: The Gaussian assumption is commonly used in data assimilation and numerical weather prediction systems, but combining lognormally distributed random variables with Gaussian distributions can better capture error interactions. Dynamically changing the formulation of the data assimilation system based on distribution changes allows for more accurate assimilation of observational data. Using machine learning techniques to detect and predict distribution changes can improve data assimilation analysis errors compared to using a single distribution type for the entire dataset.
EARTH AND SPACE SCIENCE
(2022)
Article
Geosciences, Multidisciplinary
Eduardo Cassiraga, J. Jaime Gomez-Hernandez, Marc Berenguer, Daniel Sempere-Torres, Javier Rodrigo-Ilarri
Summary: This study combines radar and rain gauge data for precipitation interpolation, considering temporal correlations using kriging with external drift. By tracking rainfall movement using a Lagrangian system of coordinates, the proposed approach outperforms radar estimation and other kriging methods in terms of rainfall estimation accuracy.
MATHEMATICAL GEOSCIENCES
(2021)
Article
Engineering, Civil
Teng Xu, J. Jaime Gomez-Hernandez, Zi Chen, Chunhui Lu
Summary: Understanding a contaminant source is crucial for managing a polluted aquifer, but source information may be unavailable when pollutants are detected. The Ensemble Smoother with Multiple Data Assimilation (ES-MDA) is proposed as a more efficient solution than the restart Ensemble Kalman Filter (r-EnKF), but requires a large number of assimilations to achieve the same level of accuracy.
JOURNAL OF HYDROLOGY
(2021)
Article
Geosciences, Multidisciplinary
J. Jaime Gomez-Hernandez, Teng Xu
Summary: Research on contaminant source identification has a long history, but there are still challenges in problem-solving and application. Researchers need to focus more on the practical application of source identification and consider other uncertain parameters in their studies.
MATHEMATICAL GEOSCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Vanessa A. Godoy, Gian F. Napa-Garcia, J. Jaime Gomez-Hernandez
Summary: In this study, the ensemble smoother with multiple data assimilation (ES-MDA) coupled with a normal-score transformation was used to fit a Langmuir isotherm curve and estimate its parameters and uncertainties. The results suggest that solute concentrations are more sensitive to the parameter S-m than to b, with a minimum of six samples needed to characterize the joint uncertainty.
MATHEMATICAL GEOSCIENCES
(2022)
Article
Geosciences, Multidisciplinary
J. Jaime Gomez-Hernandez
Summary: This research emphasizes the potential of using spreadsheets for numerical groundwater flow modeling in teaching, providing a step-by-step implementation of a two-dimensional groundwater flow model. It focuses on a confined irregular aquifer with boundary conditions, pumping, and recharge, enhancing the learning experience of students faced with the numerical solution of groundwater flow equations for the first time.
MATHEMATICAL GEOSCIENCES
(2022)
Article
Engineering, Environmental
Alessandro Pansa, Ilaria Butera, J. Jaime Gomez-Hernandez, Bartolomeo Vigna
Summary: The ensemble smoother with multiple data assimilation can be used to predict discharge in an Alpine karst aquifer, specifically the Bossea aquifer. This method effectively fits a unit hydrograph along with other parameters in a hydrologic model, using observed discharge flow rates, daily precipitation, and temperatures. By analyzing multiple events, average models are defined for predicting flow discharge during spring and autumn, with acceptable results for the fall rainfall events. However, further exploration is needed for refining the snow melting approximation and the parameterization of the infiltration coefficient. Overall, the study concludes that the ensemble smoother can be used to characterize a karst aquifer for forecast analyses.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Environmental Sciences
Andres Sahuquillo, Eduardo Cassiraga, J. Jaime Gomez-Hernandez, Joaquin Andreu, Manuel Pulido-Velazquez, David Pulido-Velazquez, Oscar D. Alvarez-Villa, Teodoro Estrela
Summary: Aquifers are widely available and easy to access, but their overexploitation can lead to significant issues such as declining water levels, reduced river flows, seawater intrusion, and wetland degradation. The conjunctive use of surface and subsurface waters through strategies like artificial recharge and alternate conjunctive use can help mitigate these problems and provide economic and environmental benefits.
Article
Computer Science, Interdisciplinary Applications
Valeria Todaro, Marco Doria, Maria Giovanna Tanda, J. Jaime Gomez-Hernandez
Summary: In this paper, a new generic software package called genES-MDA is introduced for solving inverse problems and implementing ensemble Kalman filter methods. It provides a flexible workflow and various programming tools, making it suitable for different types of inverse problems. Through testing with three synthetic case studies, the flexibility and efficiency of genES-MDA have been demonstrated.
COMPUTERS & GEOSCIENCES
(2022)
Article
Environmental Sciences
Zi Chen, Teng Xu, J. Jaim Gomez-Hernandez, Andrea Zanini, Quanping Zhou
Summary: This study employs the ensemble smoother with multiple data assimilation (ES-MDA) method to tackle groundwater contamination issues. Results show that ES-MDA performs well in recovering the release history, especially with higher observation data frequency. However, more detailed uncertainties and parameterization of the time functions are needed to move towards field cases.
JOURNAL OF CONTAMINANT HYDROLOGY
(2023)
Article
Engineering, Civil
Vanessa A. Godoy, Gian F. Napa-Garcia, J. Jaime Gomez-Hernandez
Summary: The ensemble random forest filter (ERFF) is proposed as an alternative to the ensemble Kalman filter (EnKF) for inverse modeling. By using a non-linear function represented by a random forest, the ERFF is able to capture the non-linear relationships between parameters and observations, resulting in better updates. The ERFF is demonstrated to effectively reconstruct spatial heterogeneity and match observed data in various scenarios.
JOURNAL OF HYDROLOGY
(2022)
Article
Geosciences, Multidisciplinary
Valeria Todaro, Marco D'Oria, Andrea Zanini, J. Jaime Gomez-Hernandez, Maria Giovanna Tanda
Summary: Estimating aquifer properties and their spatial variability is a challenging task in groundwater flow and transport simulations. This study applies the ensemble smoother with multiple data assimilation method to infer the characteristics of a binary field using tracer test data. Two different approaches are compared, with the second one performing better by coupling the ensemble smoother with a truncated Gaussian model. Synthetic experiments are conducted to find the optimal configurations for real cases, and the results show that both the fully parameterized approach and the pilot point approach yield comparable solutions.
HYDROGEOLOGY JOURNAL
(2023)
Article
Geosciences, Multidisciplinary
Joao Lino Pereira, J. Jaime Gomez-Hernandez, Andrea Zanini, Emmanouil A. Varouchakis, Leonardo Azevedo
Summary: Electrical resistivity tomography (ERT) is a geophysical method used to create an image of the subsurface. This study proposes an iterative geostatistical resistivity inversion method using stochastic sequential simulation and co-simulation to generate electrical resistivity models and predict subsurface properties. The method is validated using synthetic and real ERT data sets, showing its ability to model small-scale variability and assess spatial uncertainty.
HYDROGEOLOGY JOURNAL
(2023)
Editorial Material
Geosciences, Multidisciplinary
Philippe Renard, J. Jaime Gomez-Hernandez, Maria-Theresia Schafmeister, Emmanouil A. Varouchakis
HYDROGEOLOGY JOURNAL
(2023)
Article
Geosciences, Multidisciplinary
J. Jaime Gomez-Hernandez, Daniele Secci
Summary: The use of spreadsheets in numerical groundwater flow modeling has not been fully utilized in educational settings. This article introduces a teaching aid that expands the scope of a previous publication, covering various types of groundwater flow situations and incorporating new features, making the spreadsheet model a versatile tool. Students can use this user-friendly platform for experimentation and research to gain a better understanding of groundwater flow modeling and related numerical codes.
MATHEMATICAL GEOSCIENCES
(2023)
Article
Mechanics
Pablo Moreno-Navarro, Jose L. Perez-Aparicio, J. J. Gomez-Hernandez
Summary: The current article proposes closed-form and semianalytical solutions to improve the temperature distribution of Bi2Te3 thermoelements, aiming to maximize cooling. By studying different geometries of thermoelements, optimal electric intensity is determined and the accuracy of the analytical solutions is validated through numerical simulations.
COUPLED SYSTEMS MECHANICS
(2022)
