Kathryn Lawson

Differentiable, Learnable, Regionalized Process‐Based Models With Multiphysical Outputs can Approach State‐Of‐The‐Art Hydrologic Prediction Accuracy

Dapeng Feng, Jiangtao Liu, Kathryn Lawson et al. · Water Resources Research · 2022 · 240 citations · Full text

Hydrological Science, Hydrological Prediction, Engineering +17

Transferring Hydrologic Data Across Continents – Leveraging Data‐Rich Regions to Improve Hydrologic Prediction in Data‐Sparse Regions

Kai Ma, Dapeng Feng, Kathryn Lawson et al. · Water Resources Research · 2021 · 216 citations

Hydrological Prediction, Engineering, Machine Learning +17

The Data Synergy Effects of Time‐Series Deep Learning Models in Hydrology

Kuai Fang, Daniel Kifer, Kathryn Lawson et al. · Water Resources Research · 2022 · 173 citations · Full text

Hydrological Science, Engineering, Data Science +14

Mitigating Prediction Error of Deep Learning Streamflow Models in Large Data‐Sparse Regions With Ensemble Modeling and Soft Data

Dapeng Feng, Kathryn Lawson, Chaopeng Shen · Geophysical Research Letters · 2021 · 158 citations

Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data

Farshid Rahmani, Kathryn Lawson, Wenyu Ouyang et al. · Environmental Research Letters · 2020 · 134 citations · Full text