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Advances in soil evaporation physics; a review
Advances in soil evaporation physics; a review
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Advances in soil evaporation physics; a review

Or, Dani ; Lehmann, Peter ; Shahraeeni, Ebrahim ; Shokri, Nima

Vadose zone journal, 2013-11, Vol.12 (4), p.1-16 [Periódico revisado por pares]

Soil Science Society of America

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2
Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems
Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems
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Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

Tartakovsky, A. M. ; Marrero, C. Ortiz ; Perdikaris, Paris ; Tartakovsky, G. D. ; Barajas‐Solano, D.

Water resources research, 2020-05, Vol.56 (5), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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3
Physics‐Informed Neural Network Method for Forward and Backward Advection‐Dispersion Equations
Physics‐Informed Neural Network Method for Forward and Backward Advection‐Dispersion Equations
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Physics‐Informed Neural Network Method for Forward and Backward Advection‐Dispersion Equations

He, QiZhi ; Tartakovsky, Alexandre M.

Water resources research, 2021-07, Vol.57 (7), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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4
Training Machine Learning Surrogate Models From a High‐Fidelity Physics‐Based Model: Application for Real‐Time Street‐Scale Flood Prediction in an Urban Coastal Community
Training Machine Learning Surrogate Models From a High‐Fidelity Physics‐Based Model: Application for Real‐Time Street‐Scale Flood Prediction in an Urban Coastal Community
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Training Machine Learning Surrogate Models From a High‐Fidelity Physics‐Based Model: Application for Real‐Time Street‐Scale Flood Prediction in an Urban Coastal Community

Zahura, Faria T. ; Goodall, Jonathan L. ; Sadler, Jeffrey M. ; Shen, Yawen ; Morsy, Mohamed M. ; Behl, Madhur

Water resources research, 2020-10, Vol.56 (10), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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5
Physics‐Informed Neural Networks With Monotonicity Constraints for Richardson‐Richards Equation: Estimation of Constitutive Relationships and Soil Water Flux Density From Volumetric Water Content Measurements
Physics‐Informed Neural Networks With Monotonicity Constraints for Richardson‐Richards Equation: Estimation of Constitutive Relationships and Soil Water Flux Density From Volumetric Water Content Measurements
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Physics‐Informed Neural Networks With Monotonicity Constraints for Richardson‐Richards Equation: Estimation of Constitutive Relationships and Soil Water Flux Density From Volumetric Water Content Measurements

Bandai, Toshiyuki ; Ghezzehei, Teamrat A.

Water resources research, 2021-02, Vol.57 (2), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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6
Urban Flood Modeling: Uncertainty Quantification and Physics‐Informed Gaussian Processes Regression Forecasting
Urban Flood Modeling: Uncertainty Quantification and Physics‐Informed Gaussian Processes Regression Forecasting
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Urban Flood Modeling: Uncertainty Quantification and Physics‐Informed Gaussian Processes Regression Forecasting

Kohanpur, Amir H. ; Saksena, Siddharth ; Dey, Sayan ; Johnson, J. Michael ; Riasi, M. Sadegh ; Yeghiazarian, Lilit ; Tartakovsky, Alexandre M.

Water resources research, 2023-03, Vol.59 (3), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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7
Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport
Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport
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Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport

He, QiZhi ; Barajas-Solano, David ; Tartakovsky, Guzel ; Tartakovsky, Alexandre M.

Advances in water resources, 2020-07, Vol.141, p.103610, Article 103610 [Periódico revisado por pares]

Elsevier Ltd

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8
Imaging and computational considerations for image computed permeability: Operating envelope of Digital Rock Physics
Imaging and computational considerations for image computed permeability: Operating envelope of Digital Rock Physics
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Imaging and computational considerations for image computed permeability: Operating envelope of Digital Rock Physics

Saxena, Nishank ; Hows, Amie ; Hofmann, Ronny ; O. Alpak, Faruk ; Freeman, Justin ; Hunter, Sander ; Appel, Matthias

Advances in water resources, 2018-06, Vol.116, p.127-144 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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9
Reconstructing the Unsaturated Flow Equation From Sparse and Noisy Data: Leveraging the Synergy of Group Sparsity and Physics‐Informed Deep Learning
Reconstructing the Unsaturated Flow Equation From Sparse and Noisy Data: Leveraging the Synergy of Group Sparsity and Physics‐Informed Deep Learning
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Reconstructing the Unsaturated Flow Equation From Sparse and Noisy Data: Leveraging the Synergy of Group Sparsity and Physics‐Informed Deep Learning

Song, Wenxiang ; Shi, Liangsheng ; Hu, Xiaolong ; Wang, Yanling ; Wang, Lijun

Water resources research, 2023-05, Vol.59 (5), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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10
Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning
Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning
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Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning

Bindas, Tadd ; Tsai, Wen‐Ping ; Liu, Jiangtao ; Rahmani, Farshid ; Feng, Dapeng ; Bian, Yuchen ; Lawson, Kathryn ; Shen, Chaopeng

Water resources research, 2024-01, Vol.60 (1), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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