ABSTRACT:

This dataset contains hand-labeled classifications of baseflow-dominant (BFD) periods from 182 USGS stream gages across the continental United States, representing the first systematically developed ground-truth dataset for baseflow period identification. The dataset encompasses daily streamflow records spanning from 1890-2024, with each record classified as either baseflow-dominant (BFD=1) or non-baseflow-dominant (BFD=0) based on expert hydrological analysis using graphical hydrograph separation principles. BFD periods were identified as flow conditions occurring without quickflow contributions, focusing on streamflow magnitude relative to long-term averages, hydrograph stability during recession periods, and characteristic slope patterns of baseflow behavior. Quality assurance included independent labeling by multiple experts to ensure consistency and reliability. This benchmark dataset enables systematic evaluation of automated BFD identification algorithms, supports machine learning model development, and facilitates continental-scale hydrological research for improved low-flow forecasting and groundwater-surface water interaction assessments.

ABSTRACT:

This repository contains CSV files of selected gauges, evenly distributed across different geological sections according to USGS divisions. Each data point has been manually labeled to indicate whether baseflow is the only source of the streamflow.

ABSTRACT:

In this repository, 178 streamflow data from several gauges are gathered and for each of them, the baseflow value, based on the Chapman's model is calculated.

ABSTRACT:

This resource contains a series of Python-based Jupyter Notebooks used to evaluate the performance of short-range flood forecasts from the National Water Model (NWM) across 17 major U.S. flood events between 2021 and 2022. The workflows include gage selection, watershed delineation, land cover and topographic analysis, NWM forecast retrieval via API, and forecast performance evaluation using peak flow, timing, volume, and Kling-Gupta Efficiency metrics. These notebooks support the analyses presented in the mansucript "Comprehensive Evaluation of Short-Range Flood Forecasts in the U.S. National Water Model: A Multi-Region Analysis of Flood Timing, Magnitude, and Basin Influences" submitted to the journal and are intended to promote reproducibility and transparency in large-scale hydrologic model evaluation.

Note: The resource is currently discoverable only. Upon publication of the manuscript, the full dataset will be made accessible and the resource will be published with a DOI.