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Enabling Advanced Snow Physics within Land Surface Models Through an Interoperable Model-Physics Coupling Framework
Enabling Advanced Snow Physics within Land Surface Models Through an Interoperable Model-Physics Coupling Framework
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Enabling Advanced Snow Physics within Land Surface Models Through an Interoperable Model-Physics Coupling Framework

Navari, Mahdi ; Kumar, Sujay ; Wang, Shugong ; Geiger, James ; Mocko, David M ; Arsenault, Kristi R ; Kemp, Eric M

Journal of advances in modeling earth systems, 2024-04, Vol.16 (4), p.n/a [Periódico revisado por pares]

Goddard Space Flight Center: American Geophysical Union

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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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3
The Bias‐Detecting Ensemble: A New and Efficient Technique for Dynamically Incorporating Observations Into Physics‐Based, Multilayer Snow Models
The Bias‐Detecting Ensemble: A New and Efficient Technique for Dynamically Incorporating Observations Into Physics‐Based, Multilayer Snow Models
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The Bias‐Detecting Ensemble: A New and Efficient Technique for Dynamically Incorporating Observations Into Physics‐Based, Multilayer Snow Models

Winstral, A. ; Magnusson, J. ; Schirmer, M. ; Jonas, T.

Water resources research, 2019-01, Vol.55 (1), p.613-631 [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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4
Development of a Distributed Physics‐Informed Deep Learning Hydrological Model for Data‐Scarce Regions
Development of a Distributed Physics‐Informed Deep Learning Hydrological Model for Data‐Scarce Regions
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Development of a Distributed Physics‐Informed Deep Learning Hydrological Model for Data‐Scarce Regions

Zhong, Liangjin ; Lei, Huimin ; Yang, Jingjing

Water resources research, 2024-06, Vol.60 (6), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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5
Developing a Physics‐Informed Deep Learning Model to Simulate Runoff Response to Climate Change in Alpine Catchments
Developing a Physics‐Informed Deep Learning Model to Simulate Runoff Response to Climate Change in Alpine Catchments
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Developing a Physics‐Informed Deep Learning Model to Simulate Runoff Response to Climate Change in Alpine Catchments

Zhong, Liangjin ; Lei, Huimin ; Gao, Bing

Water resources research, 2023-06, Vol.59 (6), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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6
Impacts of Noah model physics on catchment‐scale runoff simulations
Impacts of Noah model physics on catchment‐scale runoff simulations
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Impacts of Noah model physics on catchment‐scale runoff simulations

Zheng, Donghai ; Van der Velde, Rogier ; Su, Zhongbo ; Wen, Jun ; Wang, Xin ; Booij, Martijn J. ; Hoekstra, Arjen Y. ; Lv, Shihua ; Zhang, Yu ; Ek, Michael B.

Journal of geophysical research. Atmospheres, 2016-01, Vol.121 (2), p.807-832 [Periódico revisado por pares]

Washington: Blackwell Publishing Ltd

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7
Improved Near‐Surface Continental Climate in IPSL‐CM6A‐LR by Combined Evolutions of Atmospheric and Land Surface Physics
Improved Near‐Surface Continental Climate in IPSL‐CM6A‐LR by Combined Evolutions of Atmospheric and Land Surface Physics
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Improved Near‐Surface Continental Climate in IPSL‐CM6A‐LR by Combined Evolutions of Atmospheric and Land Surface Physics

Cheruy, Frédérique ; Ducharne, Agnès ; Hourdin, Frédéric ; Musat, Ionela ; Vignon, Étienne ; Gastineau, Guillaume ; Bastrikov, Vladislav ; Vuichard, Nicolas ; Diallo, Binta ; Dufresne, Jean‐Louis ; Ghattas, Josefine ; Grandpeix, Jean‐Yves ; Idelkadi, Abderrahmane ; Mellul, Lidia ; Maignan, Fabienne ; Ménégoz, Martin ; Ottlé, Catherine ; Peylin, Philippe ; Servonnat, Jérôme ; Wang, Fuxing ; Zhao, Yanfeng

Journal of advances in modeling earth systems, 2020-10, Vol.12 (10), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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8
Ensemble Skill Gains Obtained From the Multi‐Physics Versus Multi‐Model Approaches for Continental‐Scale Hydrological Simulations
Ensemble Skill Gains Obtained From the Multi‐Physics Versus Multi‐Model Approaches for Continental‐Scale Hydrological Simulations
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Ensemble Skill Gains Obtained From the Multi‐Physics Versus Multi‐Model Approaches for Continental‐Scale Hydrological Simulations

Fei, Wenli ; Zheng, Hui ; Xu, Zhongfeng ; Wu, Wen‐Ying ; Lin, Peirong ; Tian, Ye ; Guo, Mengyao ; She, Dunxian ; Li, Lingcheng ; Li, Kai ; Yang, Zong‐Liang

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

Washington: John Wiley & Sons, Inc

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9
A comparison of two physics-based numerical models for simulating surface water–groundwater interactions
A comparison of two physics-based numerical models for simulating surface water–groundwater interactions
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A comparison of two physics-based numerical models for simulating surface water–groundwater interactions

Sulis, Mauro ; Meyerhoff, Steven B. ; Paniconi, Claudio ; Maxwell, Reed M. ; Putti, Mario ; Kollet, Stefan J.

Advances in water resources, 2010-04, Vol.33 (4), p.456-467 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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10
A physics based distributed integrated hydrological model in prediction of water balance of a semi-arid catchment in India
A physics based distributed integrated hydrological model in prediction of water balance of a semi-arid catchment in India
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A physics based distributed integrated hydrological model in prediction of water balance of a semi-arid catchment in India

Loliyana, V.D. ; Patel, P.L.

Environmental modelling & software : with environment data news, 2020-05, Vol.127, p.104677, Article 104677 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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