ABSTRACT:

This resource contains the active USGS stations measuring water temperature across the NOAA NWS 13 River Forecast Centers. It includes an educational Jupyter notebook designed to visualize the spatial distribution of these stations within each River Forecast Center (RFC). The notebook demonstrates the process of merging USGS station data with RFC boundaries and provides interactive visualizations to understand the geographic layout of these stations. By analyzing station distribution, this resource aids in evaluating the coverage and data collection capabilities across different RFCs.

ABSTRACT:

This resource contains performance metric data (R2, RMSE, NSE, MAE) compiled from published literature that used machine learning for stream water temperature modeling. The files in this resource were used to create the scatter plots and box plots for Figures 1 to 4 of the review paper, as well as data used to create Tables 3 and 4. We recommend the user reads the README file to understand organization of contents.

Finally, we note that these data and related items of information have not been formally disseminated by NOAA, and do not represent any agency determination, view, or policy.

ABSTRACT:

Extreme precipitation events (EPEs) will play a significant role in influencing soil–water and groundwater storage worldwide. We examined water-table depth (WTD) response to EPEs for 17 cases representative of soils and climate settings across the United States. Precipitation data from NOAA’s Precipitation Frequency Data Server were used for each case to characterize 1-day extreme precipitation events (EPEs) with annual exceedance probabilities of 0.1 % over an average baseline date range of 1981–2011. The inverse solution in the HYDRUS-1D modeling software was used to obtain the soil–water retention curve for each case. Non-EPE and EPE scenarios were modeled and compared to examine water-table displacement (ΔWTD) and recession time (trec). The ΔWTD ranged from 0.6 to 2.4 m across cases and were not directly controlled by EPE amount; instead, ΔWTD was inversely related to available …

Link to journal article: https://www.sciencedirect.com/science/article/pii/S0022169423000823

ABSTRACT:

North‐central Colorado experienced an extreme precipitation event (EPE) in September 2013, during which the equivalent of 80% of the region's annual average precipitation fell in a few days. Widespread flooding occurred above ground, but the short‐ and long‐term subsurface response remains unclear. The objective of the study is to better understand the dynamic subsurface response, namely how the water table and soil water storage responded to a large amount of infiltration in a short period of time and how the hydrologic properties of the subsurface influence the response. Better understanding of subsurface response to EPEs is expected to increase with the advent of more intense and frequent EPEs in the coming decades. A one‐dimensional subsurface flow model using HYDRUS‐1D, was built to simulate and examine infiltration of an EPE at a site in the Boulder Creek Watershed, Colorado. Model calibration was conducted with local field data to fit site observations over a 6-yr period. A rapid water table depth response in field observations was observed, with the modeled subsurface storing water for 18 months acting as a hydro-buffer during recovery. To examine influence on model results, a sensitivity study of soil hydraulic parameters was conducted. The sensitivity study found that changes in n, an empirical parameter related to pore-size distribution, most significantly affects water table depth. The implications are that one-dimensional models may provide useful estimates of water table fluctuations and subsurface hydro-buffer capacities in response to EPEs, which could be of use to regions preparing for EPE effect on water resources.

Link to journal article: https://acsess.onlinelibrary.wiley.com/doi/pdf/10.1002/vzj2.20189