Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017WR021119 |
Prediction of Hydrologic Characteristics for Ungauged Catchments to Support Hydroecological Modeling | |
Bond, Nick R.1; Kennard, Mark J.2 | |
2017-11-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:11 |
文章类型 | Article |
语种 | 英语 |
国家 | Australia |
英文摘要 | Hydrologic variability is a fundamental driver of ecological processes and species distribution patterns within river systems, yet the paucity of gauges in many catchments means that streamflow data are often unavailable for ecological survey sites. Filling this data gap is an important challenge in hydroecological research. To address this gap, we first test the ability to spatially extrapolate hydrologic metrics calculated from gauged streamflow data to ungauged sites as a function of stream distance and catchment area. Second, we examine the ability of statistical models to predict flow regime metrics based on climate and catchment physiographic variables. Our assessment focused on Australia's largest catchment, the Murray-Darling Basin (MDB). We found that hydrologic metrics were predictable only between sites within similar to 25 km of one another. Beyond this, correlations between sites declined quickly. We found less than 40% of fish survey sites from a recent basin-wide monitoring program (n=777 sites) to fall within this 25 km range, thereby greatly limiting the ability to utilize gauge data for direct spatial transposition of hydrologic metrics to biological survey sites. In contrast, statistical model-based transposition proved effective in predicting ecologically relevant aspects of the flow regime (including metrics describing central tendency, high- and low-flows intermittency, seasonality, and variability) across the entire gauge network (median R-2 similar to 0.54, range 0.39-0.94). Modeled hydrologic metrics thus offer a useful alternative to empirical data when examining biological survey data from ungauged sites. More widespread use of these statistical tools and modeled metrics could expand our understanding of flow-ecology relationships. |
英文关键词 | ecology flow hydrology metrics prediction statistical model |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000418736700008 |
WOS关键词 | NATURAL FLOW REGIMES ; AUSTRALIA ; FISH ; FRAMEWORK ; RESPONSES ; STREAM |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/21574 |
专题 | 资源环境科学 |
作者单位 | 1.La Trobe Univ, Murray Darling Freshwater Res Ctr, Wodonga, Vic, Australia; 2.Griffith Univ, Australian Rivers Inst, Nathan, Qld, Australia |
推荐引用方式 GB/T 7714 | Bond, Nick R.,Kennard, Mark J.. Prediction of Hydrologic Characteristics for Ungauged Catchments to Support Hydroecological Modeling[J]. WATER RESOURCES RESEARCH,2017,53(11). |
APA | Bond, Nick R.,&Kennard, Mark J..(2017).Prediction of Hydrologic Characteristics for Ungauged Catchments to Support Hydroecological Modeling.WATER RESOURCES RESEARCH,53(11). |
MLA | Bond, Nick R.,et al."Prediction of Hydrologic Characteristics for Ungauged Catchments to Support Hydroecological Modeling".WATER RESOURCES RESEARCH 53.11(2017). |
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