globalchange  > 气候变化事实与影响
DOI: 10.5194/hess-21-4727-2017
Scopus记录号: 2-s2.0-85029932262
论文题名:
Can spatial statistical river temperature models be transferred between catchments?
作者: Jackson F; L; , Fryer R; J; , Hannah D; M; , Malcolm I; A
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期:9
起始页码: 4727
结束页码: 4745
语种: 英语
Scopus关键词: Forecasting ; Regression analysis ; Rivers ; Runoff ; Air temperature ; Catchment area ; New approaches ; Poor performance ; River catchment ; River temperature ; Spatial regression model ; Spatial structure ; Catchments ; air temperature ; catchment ; feasibility study ; hydrological modeling ; landscape ; performance assessment ; regression analysis ; river system ; spatial analysis
英文摘要: There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax / within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS-Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax . However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable.The LS-Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable.These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across multiple catchments and larger spatial scales. © Crown copyright 2017.
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79050
Appears in Collections:气候变化事实与影响

Files in This Item:

There are no files associated with this item.


作者单位: School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham, United Kingdom; Marine Scotland Science, Scottish Government, Freshwater Laboratory, Faskally, Pitlochry, United Kingdom; Marine Scotland, Marine Laboratory, 375 Victoria Road, Aberdeen, United Kingdom

Recommended Citation:
Jackson F,L,, Fryer R,et al. Can spatial statistical river temperature models be transferred between catchments?[J]. Hydrology and Earth System Sciences,2017-01-01,21(9)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Jackson F]'s Articles
[L]'s Articles
[, Fryer R]'s Articles
百度学术
Similar articles in Baidu Scholar
[Jackson F]'s Articles
[L]'s Articles
[, Fryer R]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Jackson F]‘s Articles
[L]‘s Articles
[, Fryer R]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.