Author

K. Lawson

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Preprint Sep 2026

Hourly U.S.-wide flood simulation beyond the limits of traditional and data-driven models

As increasingly-damaging floods can strike within hours of a storm and in ungauged reaches, hourly network-wide simulation has become critical societal infrastructure. Here we demonstrate a multi-timescale physics-embedded learning model which outperforms the United States'operational system and surpasses AI-based syst...

Wencong Yang, Leo Lonzarich, Ya-Lan Song et al. · 0 citations

Open access Aug 2026

Geospatial Foundation Embeddings as Transferable Catchment Descriptors

Deep learning hydrological models rely on static catchment attributes to characterize basin heterogeneity, but these traditional descriptors suffer from regional inconsistency and limited temporal representativeness. This study evaluates geospatial foundation model embeddings (from AlphaEarth and StefaLand) as transfer...

Jiangtao Liu, Chaopeng Shen, Yuan Yang et al. · Geophysical Research Letters · 0 citations

#machine learning Preprint Aug 2026

Sensitivity-Constrained Neural Operators for Data-Efficient Forward and Inverse Modeling of Partial Differential Equation Systems

Results support sampled sensitivity supervision as a practical way to improve neural PDE surrogates when forward accuracy, inverse stability, robustness, and computational cost must be considered together.

Abdolmehdi Behroozi, Chao-Peng Shen, Daniel Kifer et al. · 0 citations