DOI: 10.5194/hess-21-3231-2017
Scopus记录号: 2-s2.0-85022191679
论文题名: Climate and basin drivers of seasonal river water temperature dynamics
作者: Laizé C ; L ; R ; , Meredith C ; B ; , Dunbar M ; J ; , Hannah D ; M
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 6 起始页码: 3231
结束页码: 3247
语种: 英语
Scopus关键词: Analysis of variance (ANOVA)
; Atmospheric humidity
; Atmospheric temperature
; Process control
; Rivers
; Temperature
; Water resources
; Linear multiple regression
; Long-wave radiation
; Multi-model inference
; Random coefficients
; Short-wave radiation
; Spatial and temporal variability
; Spatiotemporal patterns
; Stream temperatures
; Climate change
; climate change
; climate effect
; data set
; permeability
; prediction
; river basin
; river water
; seasonal variation
; spatiotemporal analysis
; streamflow
; variance analysis
; water temperature
; United Kingdom
英文摘要: Stream water temperature is a key control of many river processes (e.g. ecology, biogeochemistry, hydraulics) and services (e.g. power plant cooling, recreational use). Consequently, the effect of climate change and variability on stream temperature is a major scientific and practical concern. This paper aims (1) to improve the understanding of large-scale spatial and temporal variability in climate- water temperature associations, and (2) to assess explicitly the influence of basin properties as modifiers of these relationships. A dataset was assembled including six distinct modelled climatic variables (air temperature, downward short-wave and long-wave radiation, wind speed, specific humidity, and precipitation) and observed stream temperatures for the period 1984-2007 at 35 sites located on 21 rivers within 16 basins (Great Britain geographical extent); the study focuses on broad spatio-temporal patterns, and hence was based on 3-month-averaged data (i.e. seasonal). A wide range of basin properties was derived. Five models were fitted (all seasons, winter, spring, summer, and autumn). Both site and national spatial scales were investigated at once by using multi-level modelling with linear multiple regressions. Model selection used multi-model inference, which provides more robust models, based on sets of good models, rather than a single best model. Broad climate-water temperature associations common to all sites were obtained from the analysis of the fixed coefficients, while site-specific responses, i.e. random coefficients, were assessed against basin properties with analysis of variance (ANOVA). All six climate predictors investigated play a role as a control of water temperature. Air temperature and short-wave radiation are important for all models/seasons, while the other predictors are important for some models/seasons only. The form and strength of the climate-stream temperature association vary depending on season and on water temperature. The dominating climate drivers and physical processes may change across seasons and across the stream temperature range. The role of basin permeability, size, and elevation as modifiers of the climate- water temperature associations was confirmed; permeability has the primary influence, followed by size and elevation. Smaller, upland, and/or impermeable basins are the most influenced by atmospheric heat exchanges, while larger, lowland and permeable basins are the least influenced. The study showed the importance of accounting properly for the spatial and temporal variability of climate-stream temperature associations and their modification by basin properties. © Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79133
Appears in Collections: 气候变化事实与影响
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作者单位: Centre for Ecology and Hydrology, Wallingford, United Kingdom; School of Geography, Earth, and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom; Scottish Environment Protection Agency, Arbroath, United Kingdom; Environmental Agency, Reading, United Kingdom
Recommended Citation:
Laizé C,L,R,et al. Climate and basin drivers of seasonal river water temperature dynamics[J]. Hydrology and Earth System Sciences,2017-01-01,21(6)