Alison Appling

United States Geological Survey — United States

Environmental Science · Physical Sciences

25h-index3.4kcitations94works32.72yr avg
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Research Topics

Hydrological Forecasting Using AI(43), Hydrology and Watershed Management Studies(40), Fish Ecology and Management Studies(23), Water Quality Monitoring Technologies(11), Flood Risk Assessment and Management(10)

Publications94 total

StreamPULSE Sensor Data and Metabolism Estimates for Rivers and Streams
HydroShare Resources·2025
Multi-Scale Graph Learning for Anti-Sparse Downscaling
Proceedings of the AAAI Conference on Artificial Intelligence·2025Open Access
Predictive Understanding of Stream Salinization in a Developed Watershed Using Machine Learning
Environmental Science & Technology·2024· 4 citedOpen Access
Stream Nitrate Dynamics Driven Primarily by Discharge and Watershed Physical and Soil Characteristics at Intensively Monitored Sites: Insights From Deep Learning
Water Resources Research·2024· 6 citedOpen Access
Deep learning of estuary salinity dynamics is physically accurate at a fraction of hydrodynamic model computational cost
Limnology and Oceanography·2024· 6 citedOpen Access
Deep learning for water quality
Nature Water·2024· 213 citedOpen Access
MULTISCALE DEEP-LEARNING MODELING METHODS FOR PREDICTING STREAM TEMPERATURE AT LOCAL SPATIAL RESOLUTIONS IN WELL-OBSERVED AND DATA-SPARSE BASINS
Abstracts with programs - Geological Society of America·2024
Train, Inform, Borrow, or Combine? Approaches to Process‐Guided Deep Learning for Groundwater‐Influenced Stream Temperature Prediction
Water Resources Research·2023· 9 citedOpen Access
Identifying Structural Priors in a Hybrid Differentiable Model for Stream Water Temperature Modeling
Water Resources Research·2023· 19 citedOpen Access
Differentiable modelling to unify machine learning and physical models for geosciences
Nature Reviews Earth & Environment·2023· 327 citedOpen Access
Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations
Frontiers in Water·2023· 9 citedOpen Access
Physics-guided machine learning from simulated data with different physical parameters
Knowledge and Information Systems·2023· 24 cited
Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture
Water Resources Research·2023· 30 citedOpen Access
Differentiable modeling to unify machine learning and physical models and advance Geosciences
2023· 19 citedOpen Access
Differentiable modeling to unify machine learning and physical models and advance Geosciences
arXiv (Cornell University)·2023· 2 citedOpen Access
Near‐term forecasts of stream temperature using deep learning and data assimilation in support of management decisions
JAWRA Journal of the American Water Resources Association·2022· 26 citedOpen Access
Machine learning for understanding inland water quantity, quality, and ecology
2022· 5 citedOpen Access
Physics-Guided Architecture (PGA) of LSTM Models for Uncertainty Quantification in Lake Temperature Modeling
2022· 1 cited
Long‐term change in metabolism phenology in north temperate lakes
Limnology and Oceanography·2022· 33 cited
Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?
Hydrological Processes·2022· 77 citedOpen Access
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Frequent Co-authors

Jordan S. Read(21), Samantha K. Oliver(21), Jeffrey M. Sadler(17), Xiaowei Jia(16), Jacob A. Zwart(16), Vipin Kumar(8), Chaopeng Shen(7), Emily S. Bernhardt(6), James B. Heffernan(6), Robert O. Hall(6), Kathryn Lawson(6), Jared Willard(5), Judson W. Harvey(5), Maite Arroita(5), Charles B. Yackulic(5), Farshid Rahmani(5), Emily H. Stanley(4), William H. McDowell(4), Edward G. Stets(4), Simon Topp(4)