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Climate-informed statistical framework to estimate design floods across CONUS [Dataset]
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Created: Feb 02, 2026 at 11:54 p.m. (UTC)
Last updated: Oct 01, 2026 at 4:59 p.m. (UTC) (Metadata update)
Published date: Oct 01, 2026 at 4:59 p.m. (UTC)
DOI: 10.4211/hs.b1e843a8706245bcbca315b7b2b4091f
Citation: See how to cite this resource
Content types: CSV Content 
Sharing Status: Published
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Abstract

Reliable flood change projections under climate change are critical for water resources planning yet remain challenging due to uncertainty in climate-informed statistical models. Conventional approaches relate flood distribution parameters to climate variables using log-linear formulations, which can produce unrealistically large flood estimates. In this study, we develop a semi-parametric statistical framework that constrains flood variability using a bounded logistic link function and estimates parameters from hydroclimatically analogous samples. Using 548 natural basins across the coterminous United States, we evaluate the proposed approach against log-linear formulations from the entire sample. Model performances are assessed based on both the accuracy and sensitivity of flood quantiles to climate forcings. Results show that the proposed framework yields more stable and realistic flood quantile estimates, particularly under high precipitation conditions, and better preserves flood sensitivity. These findings highlight the value of bounded, locally informed statistical models for robust flood risk assessment under climate change.

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
North Latitude
50.0000°
East Longitude
-125.0000°
South Latitude
24.0000°
West Longitude
-67.0000°

Temporal

Start Date:
End Date:

Content

readme.txt 

Contents of shared files

1. nClimGrid_daily_basin_averaged.zip: Daily precipitation, average, maximum, and minimum temperature averaged over 704 Hydro-Climatic Data Network (HCDN) basins in the coterminous United States (CONUS) (Jan 1951 - Apr 2025).
Data sources: 
 1). nClimGrid-daily (https://www.ncei.noaa.gov/products/land-based-station/nclimgrid-daily)
 2). HCDN basins shape files (https://www.sciencebase.gov/catalog/item/631405bbd34e36012efa304a)

2. nClimGrid_monthly_aggregated_basin_averaged.zip: Monthly aggregated version of "nClimGrid_daily_basin_averaged.zip"

3. monthly_maximum_3-day_flows.zip: Monthly maximum 3-day flows (3-day moving window average) over 704 HCDN basins in the CONUS (~ Sep 2024) 
Data source: United States Geological Survey (USGS) website (https://waterdata.usgs.gov/nwis)

4. list_used_station_(548).csv: 548 HCDN stations used in the study
  
5. Source_codes_for_models.zip: Source codes for models used in the study

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How to Cite

Bae, K. (2026). Climate-informed statistical framework to estimate design floods across CONUS [Dataset], HydroShare, https://doi.org/10.4211/hs.b1e843a8706245bcbca315b7b2b4091f

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

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