Arid
DOI10.3390/w9120946
A Statistical Method to Predict Flow Permanence in Dryland Streams from Time Series of Stream Temperature
Arismendi, Ivan1; Dunham, Jason B.2; Heck, Michael P.2; Schultz, Luke D.2,3; Hockman-Wert, David2
通讯作者Arismendi, Ivan
来源期刊WATER
ISSN2073-4441
出版年2017
卷号9期号:12
英文摘要

Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015-2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.


英文关键词flow permanence stream drying Hidden Markov Models stream networks
类型Article
语种英语
国家USA
收录类别SCI-E
WOS记录号WOS:000419225500040
WOS关键词HIDDEN MARKOV-MODELS ; HEADWATER STREAMS ; DURATION ; LOGGERS ; DROUGHT
WOS类目Water Resources
WOS研究方向Water Resources
来源机构United States Geological Survey
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/202850
作者单位1.Oregon State Univ, Dept Fisheries & Wildlife, 104 Nash Hall, Corvallis, OR 97331 USA;
2.US Geol Survey, Forest & Rangeland Ecosyst Sci Ctr, 3200 SW Jefferson Way, Corvallis, OR 97331 USA;
3.Wyoming Game & Fish Dept, POB 850, Pinedale, WY 82941 USA
推荐引用方式
GB/T 7714
Arismendi, Ivan,Dunham, Jason B.,Heck, Michael P.,et al. A Statistical Method to Predict Flow Permanence in Dryland Streams from Time Series of Stream Temperature[J]. United States Geological Survey,2017,9(12).
APA Arismendi, Ivan,Dunham, Jason B.,Heck, Michael P.,Schultz, Luke D.,&Hockman-Wert, David.(2017).A Statistical Method to Predict Flow Permanence in Dryland Streams from Time Series of Stream Temperature.WATER,9(12).
MLA Arismendi, Ivan,et al."A Statistical Method to Predict Flow Permanence in Dryland Streams from Time Series of Stream Temperature".WATER 9.12(2017).
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Arismendi, Ivan]的文章
[Dunham, Jason B.]的文章
[Heck, Michael P.]的文章
百度学术
百度学术中相似的文章
[Arismendi, Ivan]的文章
[Dunham, Jason B.]的文章
[Heck, Michael P.]的文章
必应学术
必应学术中相似的文章
[Arismendi, Ivan]的文章
[Dunham, Jason B.]的文章
[Heck, Michael P.]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。