JOURNAL ARTICLE
Hydrologic Mechanisms for 2022 Yellowstone River Flood and Comparisons to Recent Historic Floods.
Published In: Hydrological Processes, 2025, v. 39, n. 3. P. 1 1 of 3
Database: Environment Complete 2 of 3
Authored By: Giovando, Jeremy; Reis, Wyatt; Zhang, Wei; Barth, Nancy A. 3 of 3
Abstract
In June 2022, a historic flood event occurred in the headwaters of the Yellowstone River Basin. The flood resulted in millions of dollars in damages and substantial interruptions to Yellowstone National Park. The 2022 flood event was substantially higher in magnitude than other high‐peak flow events over the last 30 years. The high discharge was primarily due to the combination of hydrologic mechanisms initiated by rain‐on‐snow, including a high‐elevation snowpack that peaked later than average. However, the contributions of each hydrologic driver, rain and snow, have not been quantified and could be important for understanding future flood events in the region. The contribution of snowmelt to the total terrestrial water input (TWI) varied throughout the area, yet was concentrated in the headwaters of the Yellowstone, Stillwater, and Boulder rivers, along with the headwaters of Rock Creek in Wyoming and Montana. The primary atmospheric contributions to the TWI during the 2022 event were precipitation from moisture transported from the Pacific Ocean that converged over the Greater Yellowstone Area (GYA) and snowmelt from residual snowpack in the northeast part of Yellowstone National Park. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Hydrological Processes. 2025/03, Vol. 39, Issue 3, p1
- Document Type:Article
- Subject Area:Environmental Sciences
- Publication Date:2025
- ISSN:0885-6087
- DOI:10.1002/hyp.70099
- Accession Number:183988599
- Copyright Statement:Copyright of Hydrological Processes is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.