Characterizing Antecedent Conditions Prior to Annual Maximum Flood Events in a High-Elevation Watershed Using Self-Organizing Maps

Author:

Holman Kathleen D.1

Affiliation:

1. Bureau of Reclamation, Department of the Interior, Denver, Colorado

Abstract

Abstract Flood frequency estimates are required for many water management and design engineering projects, including dam safety risk management activities. Most studies assume that annual or peak-over-threshold flood events are sampled from a single homogeneous population, an assumption that is sometimes invalid. In this study, we characterize conditions prior to annual maximum flood events in the Taylor Park watershed between water years 1981 and 2016 using historical observations and the self-organizing maps (SOM) algorithm. Inputs to the SOM algorithm include annual maximum daily reservoir inflow, annual maximum snow water equivalent (SWE), SWE melt length, and 4-day antecedent precipitation. Four-day antecedent precipitation is defined as the precipitation accumulated over the 3 days prior to and on the day of the annual maximum event. Results based on a 2 × 2 SOM output map, which represents four flood categories, suggest that 58% of events are the result of snowmelt with a near-negligible contribution from antecedent precipitation, 17% of events are the result of snowmelt combined with large antecedent precipitation, and the remaining 25% of events are the result of snowmelt with no contribution from antecedent precipitation. These results, which highlight the existence of more than one flood mechanism, may have implications for future flood frequency analyses in this watershed and other watersheds within the region.

Funder

Bureau of Reclamation Dam Safety Technology Development Program

Publisher

American Meteorological Society

Subject

Atmospheric Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3