干旱区生态环境知识资源中心(Arid): Environmental predictors of stream flow in semi-arid watersheds for biological assessments

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DOI	10.1016/j.ecolind.2019.05.019
	Environmental predictors of stream flow in semi-arid watersheds for biological assessments
	Giraldo, Mario A.1; Dark, Shawna 2; Pendleton, Patricia 3; Stein, Eric D.; Mazor, Raphael 4; Andreas, Josh 5
通讯作者	Giraldo, Mario A.
来源期刊	ECOLOGICAL INDICATORS
ISSN	1470-160X
EISSN	1872-7034
出版年	2019
卷号	104 页码:429-438
英文摘要	The aim of this study is to test a spatially explicit statistical model to identify indicators of natural stream flow using readily available stream, climate and landscape data. Understanding flow behavior of unmonitored streams at different temporal scales using environmental indicators is of great interest considering the logistic constraints of providing comprehensive flow instrumentation for all stream reaches in a region. Our results have applications to assess human impact in watersheds, to study environmental changes in fresh water resources, and in the management of local ecosystem. This study uses classification and regression tree analysis to identify significant explanatory variables for a predictive model of stream flow in semi-arid watersheds of southern California, USA. The study collected 77 variables with 30 years record, for a set of 48 sites, interpolated to create raster files at 30m spatial resolution. After applying Pearson correlation analyses to eliminate redundant variables, nine variables were found to have strong positive predictive value for estimating stream flow at ungauged sites. Nine prediction rasters portraying spatial variation of stream flow for the study region at three key index months during wet, dry, and average rainfall conditions. The predictive power of the variables was tested and cross validated over a subset of data not included when building the model. Model validation by site at monthly temporal resolution showed mixed results. While some sites where accurately predicted others did not. The comparison of observed vs predicted values by month suggest that this statistically based approach is able to predict the general patterns of stream flow at the regional scale, however it may be inaccurate in estimating actual flow values by month since the models tends to under-predict monthly discharge.
英文关键词	Semi-arid landscapes Stream flow Bio-assessments Classification analysis
类型	Article
语种	英语
国家	USA
收录类别	SCI-E
WOS记录号	WOS:000470966000044
WOS关键词	CLASSIFICATION ; PERFORMANCE ; MODELS ; TREES
WOS类目	Biodiversity Conservation ; Environmental Sciences
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/215217
作者单位	1.Calif State Univ Northridge, Dept Geog, 18111 Nordhoff St, Northridge, CA 91330 USA; 2.Calif State Univ Long Beach, Off Provost, 1250 Bellflower Blvd, Long Beach, CA 90840 USA; 3.Land Informat Off, 1010 56th St, Kenosha, WI 53140 USA; 4.Southern Calif Coastal Water Res Project, 3535 Harbor Blvd 110, Costa Mesa, CA 92626 USA; 5.Ctr Geog Studies, 18111 Nordhoff St, Northridge, CA 91330 USA
推荐引用方式 GB/T 7714	Giraldo, Mario A.,Dark, Shawna,Pendleton, Patricia,et al. Environmental predictors of stream flow in semi-arid watersheds for biological assessments[J],2019,104:429-438.
APA	Giraldo, Mario A.,Dark, Shawna,Pendleton, Patricia,Stein, Eric D.,Mazor, Raphael,&Andreas, Josh.(2019).Environmental predictors of stream flow in semi-arid watersheds for biological assessments.ECOLOGICAL INDICATORS,104,429-438.
MLA	Giraldo, Mario A.,et al."Environmental predictors of stream flow in semi-arid watersheds for biological assessments".ECOLOGICAL INDICATORS 104(2019):429-438.