Next-Generation Intensity-Duration-Frequency Curves for Diverse Land across the Continental United States.

Hongxiang Yan, Zhuoran Duan, Mark S Wigmosta, Ning Sun, Ethan D Gutmann, Bert Kruyt, Jeffrey R Arnold
Author Information
  1. Hongxiang Yan: Earth Systems Science Division, Pacific Northwest National Laboratory, Richland, WA, USA. hongxiang.yan@pnnl.gov. ORCID
  2. Zhuoran Duan: Earth Systems Science Division, Pacific Northwest National Laboratory, Richland, WA, USA.
  3. Mark S Wigmosta: Earth Systems Science Division, Pacific Northwest National Laboratory, Richland, WA, USA.
  4. Ning Sun: Earth Systems Science Division, Pacific Northwest National Laboratory, Richland, WA, USA. ORCID
  5. Ethan D Gutmann: National Center for Atmospheric Research, Boulder, CO, USA.
  6. Bert Kruyt: National Center for Atmospheric Research, Boulder, CO, USA.
  7. Jeffrey R Arnold: MITRE Corporation, McLean, VA, USA.

Abstract

The current methods for designing hydrological infrastructure rely on precipitation-based intensity-duration-frequency curves. However, they cannot accurately predict flooding caused by snowmelt or rain-on-snow events, potentially leading to underdesigned infrastructure and property damage. To address these issues, next-generation intensity-duration-frequency (NG-IDF) curves have been developed for the open condition, characterizing water available for runoff from rainfall, snowmelt, and rain-on-snow. However, they lack consideration of land use land cover (LULC) factors, which can significantly affect runoff processes. We address this limitation by expanding open area NG-IDF dataset to include eight vegetated LULCs over the continental United States, including forest (deciduous, evergreen, mixed), shrub, grass, pasture, crop, and wetland. This NG-IDF 2.0 dataset offers a comprehensive analysis of hydrological extreme events and their associated drivers under different LULCs at a continental scale. It will serve as a useful resource for improving standard design practices and aiding in the assessment of infrastructure design risks. Additionally, it provides useful insights into how changes in LULC impact flooding magnitude, mechanisms, timing, and snow water supply.

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Word Cloud

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