Trends in the seasonal cycle of modelled streamflow across Australia, 1980–2018

Author:

Coleman Rachel Lauren1ORCID,Jain Shaleen1ORCID

Affiliation:

1. a University of Maine, Orono, ME, USA

Abstract

AbstractAustralian seasonal streamflow cycles represent diverse weather and climate variations and distinctive influences from coupled ocean-atmospheric phenomena, including monsoons, frontal systems, and El Nino-Southern Oscillation. Streamflow strongly modulates the health of ecosystems and is inextricably linked to communities through consumptive use and cultural and spiritual practices. To better understand the potential impacts of a changing climate, a comprehensive trend analysis of streamflow variability resolved at daily scales is pursued for 35 rivers across Australia using a serially complete modelled streamflow dataset (1979–2018) from the GloFAS-ERA5 operational global river discharge reanalysis. Analysis consisted of quantile regression to identify direction and significances of trends in low, median, and high flows, K-means clustering to identify grouping of data with similar features, and Poisson regressions to identify rainfall changes during low and high rainfall seasons. Results present comprehensive decreases at low, median, and high flows in southern continental river streamflow. Northern continental streamflows display increases and decreases throughout the year across flows, with increases more prevalent. Trends within upper and lower portions of the flow distributions reveal unique sub-seasonal time windows in the extremes, thus underscoring that trends across the full distribution of streamflow are necessary to understand vulnerability to human and environmental systems.

Publisher

IWA Publishing

Subject

Management, Monitoring, Policy and Law,Atmospheric Science,Water Science and Technology,Global and Planetary Change

Reference26 articles.

1. A global streamflow reanalysis for 1980–2018;Journal of Hydrology X,2020

2. Development of a regional gridded runoff dataset using long short-term memory (LSTM) networks;Hydrology,2021

3. Non-crossing quantile regression curve estimation;Biometrika,2010

4. Bureau of Meteorology 2022 Climate Data Online. Australian Government: Bureau of Meteorology. Available from: http://www.bom.gov.au/climate/data/

5. Coleman R. L. 2022 Overlapping Scales of Place Based Indigenous Knowledge and Hydroclimate in Australia . Electronic Theses and Dissertations, p. 3570. Available from: https://digitalcommons.library.umaine.edu/etd/3570

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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