MODELS +
AI
= SOLUTIONS MADS is an open-source software framework providing cutting-edge methods and tools for data analyses and model diagnostics.
MADS can be coupled with any model. The analyzed models can represent any physics, including hydrological, environmental, and climate models. They can be numerical, analytical, or ML-developed models. Efficient parallel computing is supported for analyses of large-scale models.
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Model Diagnostics
Calibrate a model and identify influential, uncertain, or poorly constrained inputs.
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Contaminant Source Identification
Infer when and where a contaminant release may have entered groundwater.
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Contaminant Decision Support
Compare remediation choices while keeping cost, exposure, and uncertainty visible.
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Related publications
- Inverse Analysis with Variational Autoencoders: A Comparison of Shallow and Deep Networks (2022) — H. Wu et al. — Journal of Machine Learning for Modeling and Computing
- Learning to regularize with a variational autoencoder for hydrologic inverse analysis (2021) — D. O'Malley, J.K. Golden, V.V. Vesselinov — arXiv
- Characterizing the impact of model error in hydrologic time series recovery inverse problems (2018) — S.K. Hansen, J. He, V.V. Vesselinov — Advances in Water Resources
- Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices (2018) — E. Qian et al. — SIAM Journal on Uncertainty Quantification
- Randomization in Characterizing the Subsurface (2018) — Y. Lin et al. — SIAM News
- Agent-based Socio-hydrological Hybrid Modeling for Water Resource Management (2017) — J. Bakarji, V.V. Vesselinov, D. O’Malley — Water Resources Management
- Large-Scale Inverse Model Analyses Employing Fast Randomized Data Reduction (2017) — Y. Lin et al. — Water Resources Research
- A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses (2016) — Y. Lin, D. O'Malley, V.V. Vesselinov — Water Resources Research
- Contaminant point source localization error estimates as functions of data quantity and model quality (2016) — S.K. Hansen, V.V. Vesselinov — Journal of Contaminant Hydrology
- Decision Analysis for Robust CO2 Injection: Application of Bayesian-Information-Gap Decision Theory (2016) — M. Grasinger et al. — International Journal of Greenhouse Gas Control
- Analytical Sensitivity Analysis of Transient Groundwater Flow in a Bounded Model Domain using Adjoint Method (2015) — Z. Lu, V.V. Vesselinov — Water Resources Research
- Bayesian-Information-Gap Decision Theory (BIG-DT) with an application to CO2 sequestration (2015) — D. O’Malley, V.V. Vesselinov — Water Resources Research
- Linear Functional Minimization for Inverse Modeling (2015) — D. A. Barajas-Solano et al. — Water Resources Research
- Parameter estimation and prediction for groundwater contamination based on measure theory (2015) — S.A. Mattis et al. — Water Resources Research
- A combined probabilistic/non-probabilistic decision analysis for contaminant remediation (2014) — D. O’Malley, V.V. Vesselinov — Journal on Uncertainty Quantification, SIAM/ASA
- A high-performance workflow system for subsurface simulation (2014) — V.L. Freedman et al. — Environmental Modelling & Software
- Groundwater remediation using the information gap decision theory (2014) — D. O’Malley, V.V. Vesselinov — Water Resources Research
- Robust Decision Analysis for Environmental Management of Groundwater Contamination Sites (2014) — V.V. Vesselinov, D. O'Malley, D. Katzman — Vulnerability, Uncertainty, and Risk Quantification, Mitigation, and Management
- Data and Model-Driven Decision Support for Environmental Management of a Chromium Plume at Los Alamos National Laboratory (LANL) (2013) — V.V. Vesselinov et al. — Waste Management Symposium, Phoenix, AZ
- Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models (2012) — V.V. Vesselinov, D. Harp — Computers & Geosciences
- AGNI: Coupling Model Analysis Tools and High-Performance Subsurface Flow and Transport Simulators for Risk and Performance Assessments (2012) — V.V. Vesselinov, G. Pau, . Finsterle — Computational Methods in Water Resources (CMWR)
- An agent-based approach to global uncertainty and sensitivity analysis (2012) — D. Harp, V.V. Vesselinov — Computers & Geosciences
- Analysis of hydrogeological structure uncertainty by estimation of hydrogeological acceptance probability of geostatistical models (2012) — D. Harp, V.V. Vesselinov — Special issue of Uncertainty Quantification (invited), Advances in Water Resources
- Contaminant remediation decision analysis using information gap theory (2012) — D. Harp, V.V. Vesselinov — Stochastic Environmental Research and Risk Assessment (SERRA)
- Decision support based on uncertainty quantification of model predictions of contaminant transport (2010) — V.V. Vesselinov, D. Harp — Computational Methods in Water Resources (CMWR), Barcelona, Spain
- Maximum Likelihood Bayesian Averaging of air flow models in unsaturated fractured tuff using Occam and variance windows (2010) — E. Morales-Casique, S.P. Neuman, V.V. Vesselinov — Special issue of Stochastic Environmental Research and Risk Assessment (SERRA) Journal celebrating 70th anniversary of Shlomo P Neuman
- Stochastic inverse method for estimation of geostatistical representation of hydrogeologic stratigraphy using borehole logs and pressure (2010) — D. Harp, V.V. Vesselinov — Special issue of Stochastic Environmental Research and Risk Assessment (SERRA) Journal celebrating 70th anniversary of Shlomo P Neuman
- Uncertainties in Transient Capture-Zone Estimates of Groundwater Supply Wells (2007) — V.V. Vesselinov — Journal of Contemporary Water Research & Education
- Uncertainties In Transient Capture-Zone Estimates (2006) — V.V. Vesselinov — Computational Methods in Water Resources (CMWR) — ISBN 90-5809-124-4
- Improved Inverse Modeling in Geophysics: Combined Parameter and State Estimation (2005) — J.A. Vrugt, B.A. Robinson, V.V. Vesselinov — Geophysical Research Letters
- Estimation of parameter uncertainty using inverse model sensitivities (2004) — V.V. Vesselinov — Computational Methods in Water Resources (CMWR), Elsevier — ISBN 0-444-51839-8
Related presentations
- Machine Learning for Small, Uncertain, and Sparse Data Sets (2022) — M. Ahmmed, V.V. Vesselinov — AGU Fall Meeting
- Toward Automated Data-Model Calibration for the Arctic Terrestrial Ecosystem Model (2022) — E. Jafarov et al. — AGU Fall Meeting
- Site-Scale and Regional-Scale Modeling for Geothermal Resource Analysis and Exploration (2020) — M. Mudunuru, V.V. Vesselinov, et al. — Geothermal Workshop, Stanford, CA
- Physics-Informed Machine Learning Methods for Data Analytics and Model Diagnostics (2019) — V.V. Vesselinov — M3 NASA DRIVE Workshop, Los Alamos
- Decision Analyses for Groundwater Remediation (2017) — V.V. Vesselinov, D. O'Malley, D. Katzman — Waste Management Symposium
- Hydraulic Inverse Modeling using Total-Variation Regularization with Relaxed Variable-Splitting (2017) — Y. Lin et al. — SIAM Conference on Computational Science and Engineering
- Quo vadis: Hydrologic inverse analyses using high-performance computing and a D-Wave quantum annealer (2017) — D. O'Malley, V.V. Vesselinov — AGU Fall Meeting
- Uncertainty quantification and experimental design based on unsupervised machine learning identification of contaminant sources and groundwater types using hydrogeochemical data (2017) — V.V. Vesselinov, D. O'Malley, B. Alexandrov — AGU Fall Meeting
- Analysis of Hydrologic Time Series Reconstruction Uncertainty due to Inverse Model Inadequacy (2016) — J. He, S. Hansen, V.V. Vesselinov — AGU Fall Meeting
- Groundwater Remediation using Bayesian Information-Gap Decision Theory (2016) — D. O'Malley, V.V. Vesselinov — AGU Fall Meeting
- Hydraulic Inverse Modeling using Total-Variation Regularization with Relaxed Variable-Splitting (2016) — Y. Lin et al. — AGU Fall Meeting
- Identifying Aquifer Heterogeneities using the Level Set Method (2016) — Z. Lu, V.V. Vesselinov, H. Lei — AGU Fall Meeting
- Model Analyses of Complex Systems Behavior using MADS (2016) — V.V. Vesselinov, D. O'Malley — AGU Fall Meeting
- Reduced Order Models for Decision Analysis and Upscaling of Aquifer Heterogeneity (2016) — V.V. Vesselinov, D. O'Malley, B. Alexandrov — AGU Fall Meeting (invited)
- ZEM: Integrated Framework for Real-Time Data and Model Analyses for Robust Environmental Management Decision Making (2016) — V.V. Vesselinov, D. O'Malley, D. Katzman — Waste Management Symposium
- Model-Assisted Decision Analyses Related to a Chromium Plume at Los Alamos National Laboratory (2015) — V.V. Vesselinov, D. O'Malley, D. Katzman — Waste Management Symposium
- Bayesian Information-Gap Decision Analysis Applied to a Geologic CO2 Sequestration Problem (2014) — D. O'Malley, V.V. Vesselinov — AGU Fall Meeting
- Random dispersion coefficients and Tsallis entropy (2014) — J. Cushman, V.V. Vesselinov, D. O'Malley — AGU Fall Meeting
- Data and Model-Driven Decision Support for Environmental Management of a Chromium Plume at Los Alamos National Laboratory (LANL) (2013) — V.V. Vesselinov et al. — Waste Management Symposium
- What Matters When and Where For Anomalous Dispersion/Diffusion (2013) — D. O'Malley, V.V. Vesselinov — AGU Fall Meeting
- AGNI: Coupling Model Analysis Tools and High-Performance Subsurface Flow and Transport Simulators for Risk and Performance Assessments (2012) — V.V. Vesselinov, et al. — XIX International Conference on Computational Methods in Water Resources (CMWR 2012)
- MADS & ASCEM (2012) — V.V. Vesselinov — AGU Fall Meeting
- Model-driven decision support for monitoring network design based on analysis of data and model uncertainties: methods and applications (2012) — V.V. Vesselinov, D. Harp, D. Katzman — AGU Fall meeting (invited)
- Numerical Optimization using the Levenberg-Marquardt Algorithm (2011) — L. Leif Zinn-Bjorkman, V.V. Vesselinov — DOE LANL Presentations
- Recent developments in MADS algorithms: ABAGUS and Squads (2011) — D. Harp, V.V. Vesselinov — DOE LANL Presentations
- Environmental Management Modeling Activities at Los Alamos National Laboratory (LANL) (2010) — V.V. Vesselinov, et al. — Department of Energy Technical Exchange Meeting, Performance Assessment Community of Practice, Hanford
- Tomographic inverse estimation of aquifer properties based on pressure variations caused by transient water-supply pumping (2008) — V.V. Vesselinov et al. — AGU Meeting
- Uncertainties in Transient Capture-Zone Estimates (2006) — V.V. Vesselinov — Conference on Computational Methods in Water Resources (CMWR), Copenhagen, Denmark