TY - JOUR
T1 - Next-Generation Intensity-Duration-Frequency Curves for Diverse Land across the Continental United States
AU - Yan, Hongxiang
AU - Duan, Zhuoran
AU - Wigmosta, Mark S.
AU - Sun, Ning
AU - Gutmann, Ethan D.
AU - Kruyt, Bert
AU - Arnold, Jeffrey R.
N1 - Publisher Copyright:
© 2023, Battelle Memorial Institute, NCAR, MITRE Corp.
PY - 2023/12
Y1 - 2023/12
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85178490031
U2 - 10.1038/s41597-023-02680-4
DO - 10.1038/s41597-023-02680-4
M3 - Article
C2 - 38049456
AN - SCOPUS:85178490031
SN - 2052-4463
VL - 10
JO - Scientific data
JF - Scientific data
IS - 1
M1 - 863
ER -