Post‐processing the national water model with long short‐term memory networks for streamflow predictions and model diagnostics
We build three long short‐term memory (LSTM) daily streamflow prediction models (deep
learning networks) for 531 basins across the contiguous United States (CONUS), and …
learning networks) for 531 basins across the contiguous United States (CONUS), and …
Restructuring and serving web-accessible streamflow data from the NOAA National Water Model historic simulations
Abstract In 2016, the National Oceanic and Atmospheric Administration deployed the first
iteration of an operational National Water Model (NWM) to forecast the water cycle in the …
iteration of an operational National Water Model (NWM) to forecast the water cycle in the …
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential …
Deep learning (DL) rainfall–runoff models outperform conceptual, process-based models in
a range of applications. However, it remains unclear whether DL models can produce …
a range of applications. However, it remains unclear whether DL models can produce …
Near‐term forecasts of stream temperature using deep learning and data assimilation in support of management decisions
Deep learning (DL) models are increasingly used to make accurate hindcasts of
management‐relevant variables, but they are less commonly used in forecasting …
management‐relevant variables, but they are less commonly used in forecasting …
Insights from Dayflow: A historical streamflow reanalysis dataset for the conterminous United States
Reconstructed historical streamflow time series can supplement limited streamflow gauge
observations. However, there are common challenges of typical modeling approaches …
observations. However, there are common challenges of typical modeling approaches …
Incorporating physically-based water temperature predictions into the National water model framework
While river water temperatures are a strong control on instream processes and aquatic
ecosystems, monitoring networks for river water temperatures are often sparse. Despite …
ecosystems, monitoring networks for river water temperatures are often sparse. Despite …
Identifying spatial patterns of hydrologic drought over the southeast US using retrospective national water model simulations
J Dyer, A Mercer, K Raczyński - Water, 2022 - mdpi.com
Given the sensitivity of natural environments to freshwater availability in the Southeast US,
as well as the reliance of many municipal and commercial water consumers on surface …
as well as the reliance of many municipal and commercial water consumers on surface …
[HTML][HTML] Evaluating Hydrologic Model Performance for Characterizing Streamflow Drought in the Conterminous United States
Hydrologic models are the primary tools that are used to simulate streamflow drought and
assess impacts. However, there is little consensus about how to evaluate the performance of …
assess impacts. However, there is little consensus about how to evaluate the performance of …
Comprehensive analysis of the NOAA National Water Model: A call for heterogeneous formulations and diagnostic model selection
With an increasing number of continental‐scale hydrologic models, the ability to evaluate
performance is key to understanding uncertainty and making improvements to the model (s) …
performance is key to understanding uncertainty and making improvements to the model (s) …
Map** Heat Wave Hazard in Urban Areas: A Novel Multi-Criteria Decision Making Approach
Global population is experiencing more frequent, longer, and more severe heat waves due
to global warming and urbanization. Episodic heat waves increase mortality and morbidity …
to global warming and urbanization. Episodic heat waves increase mortality and morbidity …