Diurnal timing of warmer air under climate change affects magnitude,timing and duration of stream temperature change

Stream temperature will be subject to changes because of atmospheric warming in the future. We investigated the effects of the diurnal timing of air temperature changes – daytime warming versus nighttime warming – on stream temperature. Using the physically based model, Heat Source, we performed a sensitivity analysis of summer stream temperatures to three diurnal air temperature distributions of +4 °C mean air temperature: i) uniform increase over the whole day, ii) warmer daytime and iii) warmer nighttime. The stream temperature model was applied to a 37‐km section of the Middle Fork John Day River in northeastern Oregon, USA. The three diurnal air temperature distributions generated 7‐day average daily maximum stream temperatures increases of approximately +1.8 °C ± 0.1 °C at the downstream end of the study section. The three air temperature distributions, with the same daily mean, generated different ranges of stream temperatures, different 7‐day average daily maximum temperatures, different durations of stream temperature changes and different average daily temperatures in most parts of the reach. The stream temperature changes were out of phase with air temperature changes, and therefore in many places, the greatest daytime increase in stream temperature was caused by nighttime warming of air temperatures. Stream temperature changes tended to be more extreme and of longer duration when driven by air temperatures concentrated in either daytime or nighttime instead of uniformly distributed across the diurnal cycle. Copyright © 2012 John Wiley & Sons, Ltd.     

Base flow‐driven shifts in tropical stream temperature regimes across a mean annual rainfall gradient

Climate change is expected to affect air temperature and watershed hydrology, but the degree to which these concurrent changes affect stream temperature is not well documented in the tropics. How stream temperature varies over time under changing hydrologic conditions is difficult to isolate from seasonal changes in air temperature. Groundwater and bank storage contributions to stream flow (i.e., base flow [BF]) buffer water temperatures against seasonal and daily fluctuations in solar radiation and air temperature, whereas rainfall‐driven runoff produces flooding events that also influence stream temperature. We used a space‐for‐time substitution to examine how shifts in BF and runoff alter thermal regimes in streams by analyzing hydrological and temperature data collected from similar elevations (400–510 m above sea level) across a 3,500‐mm mean annual rainfall gradient on Hawai'i Island. Sub‐daily water temperature and stream flow gathered for 3 years were analyzed for daily, monthly, and seasonal trends and compared with air temperature measured at multiple elevations. Results indicate that decreases in median BF increased mean, maximum, and minimum water temperatures as well as daily temperature range. Monthly and daily trends in stream temperature among watersheds were more pronounced than air temperature, driven by differences in groundwater inputs and runoff. Stream temperature was strongly negatively correlated to BF during the dry season but not during the wet season due to frequent wet season runoff events contributing to total flow. In addition to projected increases in global air temperature, climate driven shifts in rainfall and runoff are likely to affect stream flow and groundwater recharge, with concurrent influences on BF resulting in shifts in water temperature that are likely to affect aquatic ecosystems.     

Predicting river water temperatures using stochastic models: case study of the Moisie River (Québec,Canada)

Successful applications of stochastic models for simulating and predicting daily stream temperature have been reported in the literature. These stochastic models have been generally tested on small rivers and have used only air temperature as an exogenous variable. This study investigates the stochastic modelling of daily mean stream water temperatures on the Moisie River, a relatively large unregulated river located in Québec, Canada. The objective of the study is to compare different stochastic approaches previously used on small streams to relate mean daily water temperatures to air temperatures and streamflow indices. Various stochastic approaches are used to model the water temperature residuals, representing short‐term variations, which were obtained by subtracting the seasonal components from water temperature time‐series. The first three models, a multiple regression, a second‐order autoregressive model, and a Box and Jenkins model, used only lagged air temperature residuals as exogenous variables. The root‐mean‐square error (RMSE) for these models varied between 0·53 and 1·70 °C and the second‐order autoregressive model provided the best results. A statistical methodology using best subsets regression is proposed to model the combined effect of discharge and air temperature on stream temperatures. Various streamflow indices were considered as additional independent variables, and models with different number of variables were tested. The results indicated that the best model included relative change in flow as the most important streamflow index. The RMSE for this model was of the order of 0·51 °C, which shows a small improvement over the first three models that did not include streamflow indices. The ridge regression was applied to this model to alleviate the potential statistical inadequacies associated with multicollinearity. The amplitude and sign of the ridge regression coefficients seem to be more in agreement with prior expectations (e.g. positive correlation between water temperature residuals of different lags) and make more physical sense. Copyright © 2006 John Wiley & Sons, Ltd.     

Modelling temperature change downstream of forest harvest using Newton's law of cooling

We adapted Newton's law of cooling to model downstream water temperature change in response to stream‐adjacent forest harvest on small and medium streams (average 327 ha in size) throughout the Oregon Coast Range, USA. The model requires measured stream gradient, width, depth and upstream control reach temperatures as inputs and contains two free parameters, which were determined by fitting the model to measured stream temperature data. This model reproduces the measured downstream temperature responses to within 0.4 °C for 15 of the 16 streams studied and provides insight into the physical sources of site‐to‐site variation among those responses. We also use the model to examine how the pre‐harvest to post‐harvest change in daily maximum stream temperature depends on distance from the harvest reach. The model suggests that the pre‐harvest to post‐harvest temperature change approximately 300 m downstream of the harvest will range from roughly 82% to less than 1% of that temperature change that occurred within the harvest reach, depending primarily on the downstream width, depth and gradient. Using study‐averaged values for these channel characteristics, the model suggests that for a stream representative of those in the study, the temperature change approximately 300 m downstream of the harvest will be 56% of the temperature change that occurred within the harvest reach. This adapted Newton's law of cooling procedure represents a highly practical means for predicting stream temperature behaviour downstream of timber harvests relative to conventional heat budget approaches and is informative of the dominant processes affecting stream temperature. Copyright © 2015 John Wiley & Sons, Ltd.     

Examining the effect of geomorphic characteristics on pool temperatures for native fish habitat management in mountainous stream networks

Stream temperature is a critical habitat parameter for cold‐water fish, many species of which now exist in geographically fragmented populations within the western United States. To assist managers in identifying thermally suitable fish habitat, we used data from 31 pools on streams of the White River National Forest in Colorado, USA to create multiple regression models to predict summer pool temperature metrics related to lethal and sublethal thermal tolerances of fish. We modeled the 7‐day mean of daily maximum pool temperature for the warmest 7 days and the mean temperature of the warmest month, using air temperature and several geomorphic parameters. The strongest predictor variables of these temperature metrics were drainage area, discharge, and residual pool volume. Most previous studies found air temperature to be the strongest predictor variable for pool temperature, but for the mountain streams in this study, variables related to stream flow volume and stream morphology had better predictive power. The models, created from and tested against field data, were able to explain 66% and 51% of the variability in monthly mean and 7‐day mean pool temperatures, respectively, and had prediction errors of less than 2°C. The reach‐scale approach developed here, which includes geomorphically relevant predictors of pool temperature, should be applicable to other mountainous river networks. Copyright © 2016 John Wiley & Sons, Ltd.     

Stream temperature modelling using artificial neural networks: application on Catamaran Brook,New Brunswick,Canada

Fish habitat and aquatic life in rivers are highly dependent on water temperature. Therefore, it is important to understand andto be able to predict river water temperatures using models. Such models can increase our knowledge of river thermal regimes as well as provide tools for environmental impact assessments. In this study, artificial neural networks (ANNs) will be used to develop models for predicting both the mean and maximum daily water temperature. The study was conducted within Catamaran Brook, a small drainage basin tributary to the Miramichi River (New Brunswick, Canada). In total, eight ANN models were investigated using a variety of input parameters. Of these models, four predicted mean daily water temperature and four predicted maximum daily water temperature. The best model for mean daily temperature had eight input parameters: minimum, maximum and mean air temperatures of the current day and those of the preceding day, the day of year and the water level. This model had an overall root‐mean‐square error (RMSE) of 0·96 °C, a bias of 0·26 °C and a coefficient of determination R² = 0·971. The model that best predicted maximum daily water temperature was similar to the first model but excluded mean daily air temperature. Good results were obtained for maximum water temperatures with an overall RMSE of 1·18 °C, a bias of 0·15 °C and R² = 0·961. The results of ANN models were similar to and/or better than those observed from the literature. The advantages of artificial neural networks models in modelling river water temperature lie in their simplicity of use, their low data requirement and their good performance, as well as their flexibility in allowing many input and output parameters. Copyright © 2008 Crown in the right of Canada and John Wiley & Sons, Ltd.     

Temperature in lowland Danish streams: contemporary patterns,empirical models and future scenarios

Continuous temperature measurements at 11 stream sites in small lowland streams of North Zealand, Denmark over a year showed much higher summer temperatures and lower winter temperatures along the course of the stream with artificial lakes than in the stream without lakes. The influence of lakes was even more prominent in the comparisons of colder lake inlets and warmer outlets and led to the decline of cold‐water and oxygen‐demanding brown trout. Seasonal and daily temperature variations were, as anticipated, dampened by forest cover, groundwater input, input from sewage plants and high downstream discharges. Seasonal variations in daily water temperature could be predicted with high accuracy at all sites by a linear air‐water regression model (r²: 0·903–0·947). The predictions improved in all instances (r²: 0·927–0·964) by a non‐linear logistic regression according to which water temperatures do not fall below freezing and they increase less steeply than air temperatures at high temperatures because of enhanced heat loss from the stream by evaporation and back radiation. The predictions improved slightly (r²: 0·933–0·969) by a multiple regression model which, in addition to air temperature as the main predictor, included solar radiation at un‐shaded sites, relative humidity, precipitation and discharge. Application of the non‐linear logistic model for a warming scenario of 4–5 °C higher air temperatures in Denmark in 2070‐2100 yielded predictions of temperatures rising 1·6–3·0 °C during winter and summer and 4·4–6·0 °C during spring in un‐shaded streams with low groundwater input. Groundwater‐fed springs are expected to follow the increase of mean air temperatures for the region. Great caution should be exercised in these temperature projections because global and regional climate scenarios remain open to discussion. Copyright © 2006 John Wiley & Sons, Ltd.     

Thermal regime of a headwater stream within a clear‐cut,coastal British Columbia,Canada

This study examined the thermal regime of a headwater stream within a clear‐cut. The stream had a complex morphology dominated by step–pool features, many formed by sediment accumulation upstream of woody debris. Maximum daily temperatures increased up to 5 °C after logging, and were positively associated with maximum daily air temperature and negatively with discharge. Maximum daily temperatures generally increased with downstream distance through the cut block, but decreased with distance in two segments over distances of tens of metres, where the topography indicated relatively concentrated lateral inflow. Localized cool areas within a step–pool unit were associated with zones of concentrated upwelling. Bed temperatures tended to be higher and have greater ranges in areas of downwelling flow into the bed. Heat budget estimates were made using meteorological measurements over the water surface and a model of net radiation using canopy characteristics derived from fisheye photography. Heat exchange driven by hyporheic flow through the channel step was a cooling effect during daytime, with a magnitude up to approximately 25% that of net radiation during the period of maximum daytime warming. Heat budget calculations in these headwater streams are complicated by the heterogeneity of incident solar radiation and channel geometry, as well as uncertainty in estimating heat and water exchanges between the stream and the subsurface via hyporheic exchange and heat conduction. Copyright © 2005 John Wiley & Sons, Ltd.     

A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

Stream temperatures in urban watersheds are influenced to a high degree by changes in landscape and climate, which can occur at small temporal and spatial scales. Here, we describe a modelling system that integrates the distributed hydrologic soil vegetation model with the semi‐Lagrangian stream temperature model RBM. It has the capability to simulate spatially distributed hydrology and water temperature over the entire network at high time and space resolutions, as well as to represent riparian shading effects on stream temperatures. We demonstrate the modelling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model was able to produce realistic streamflow and water temperature predictions that are consistent with observations. We use the modelling construct to characterize impacts of land use change and near‐stream vegetation change on stream temperatures and explore the sensitivity of stream temperature to changes in land use and riparian vegetation. The results suggest that, notwithstanding general warming as a result of climate change over the last century, there have been concurrent increases in low flows as a result of urbanization and deforestation, which more or less offset the effects of a warmer climate on stream temperatures. On the other hand, loss of riparian vegetation plays a more important role in modulating water temperatures, in particular, on annual maximum temperature (around 4 °C), which could be mostly reversed by restoring riparian vegetation in a fairly narrow corridor – a finding that has important implications for management of the riparian corridor. Copyright © 2014 John Wiley & Sons, Ltd.     

Stream and bed temperature variability in a coastal headwater catchment: influences of surface‐subsurface interactions and partial‐retention forest harvesting

Stream temperature was recorded between 2002 and 2005 at four sites in a coastal headwater catchment in British Columbia, Canada. Shallow groundwater temperatures, along with bed temperature profiles at depths of 1 to 30 cm, were recorded at 10‐min intervals in two hydrologically distinct reaches beginning in 2003 or 2004, depending on the site. The lower reach had smaller discharge contributions via lateral inflow from the hillslopes and fewer areas with upwelling (UW) and/or neutral flow across the stream bed compared to the middle reach. Bed temperatures were greater than those of shallow groundwater during summer, with higher temperatures in areas of downwelling (DW) flow compared to areas of neutral and UW flow. A paired‐catchment analysis revealed that partial‐retention forest harvesting in autumn 2004 resulted in higher daily maximum stream and bed temperatures but smaller changes in daily minima. Changes in daily maximum stream temperature, averaged over July and August of the post‐harvest year, ranged from 1.6 to 3 °C at different locations within the cut block. Post‐harvest changes in bed temperature in the lower reach were smaller than the changes in stream temperature, greater at sites with DW flow, and decreased with depth at both UW and DW sites, dropping to about 1 °C at a depth of 30 cm. In the middle reach, changes in daily maximum bed temperature, averaged over July and August, were generally about 1 °C and did not vary significantly with depth. The pre‐harvest regression models for shallow groundwater were not suitable for applying the paired‐catchment analysis to estimate the effects of harvesting. However, shallow groundwater was warmer at the lower reach following harvesting, despite generally cooler weather compared to the pre‐harvest year. Copyright © 2012 John Wiley & Sons, Ltd.     

Urban stream temperature patterns: Spatial and temporal heterogeneity in the Philadelphia region,Pennsylvania, USA

Stream temperature is a critical water quality parameter that is not fully understood, particularly in urban areas. This study explores drivers contributing to stream temperature variability within an urban system, at 21 sites within the Philadelphia region, Pennsylvania, USA. A comprehensive set of temperature metrics were evaluated, including temperature sensitivity, daily maximum temperatures, time >20°C, and temperature surges during storms. Wastewater treatment plants (WWTPs) were the strongest driver of downstream temperature variability along 32 km in Wissahickon Creek. WWTP effluent temperature controlled local (1–3 km downstream) temperatures year-round, but the impacts varied seasonally: during winter, local warming of 2–7°C was consistently observed, while local cooling up to 1°C occurred during summer. Summer cooling and winter warming were detected up to 12 km downstream of a WWTP. Comparing effects from different WWTPs provided guidelines for mitigating their thermal impact; WWTPs that discharged into larger streams, had cooler effluent, or had lower discharge had less effect on stream temperatures. Comparing thermal regimes in four urban headwater streams, sites with more local riparian canopy had cooler maximum temperatures by up to 1.5°C, had lower temperature sensitivity, and spent less time at high temperatures, although mean temperatures were unaffected. Watershed-scale impervious area was associated with increased surge frequency and magnitude at headwater sites, but most storms did not result in a surge and most surges had a low magnitude. These results suggest that maintaining or restoring riparian canopy in urban settings will have a larger impact on stream temperatures than stormwater management that treats impervious area. Mitigation efforts may be most impactful at urban headwater sites, which are particularly vulnerable to stream temperature disruptions. It is vital that stream temperature impacts are considered when planning stormwater management or stream restoration projects, and the appropriate metrics need to be considered when assessing impacts.     

Air/water/sediment temperature contrasts in small streams to identify groundwater seepage locations

The need to identify groundwater seepage locations is of great importance for managing both stream water quality and groundwater sourced ecosystems due to their dependency on groundwater‐borne nutrients and temperatures. Although several reconnaissance methods using temperature as tracer exist, these are subjected to limitations related to mainly the spatial and temporal resolution and/or mixing of groundwater and surface water leading to dilution of the temperature differences. Further, some methods, for example, thermal imagery and fiber optic distributed temperature sensing, although relative efficient in detecting temperature differences over larger distances, these are labor‐intensive and costly. Therefore, there is a need for additional cost‐effective methods identifying substantial groundwater seepage locations. We present a method expanding the linear regression of air and stream temperatures by measuring the temperatures in dual‐depth; in the stream column and at the streambed‐water interface (SWI). By doing so, we apply metrics from linear regression analysis of temperatures between air/stream and air/SWI (linear regression slope, intercept, and coefficient of determination), and the daily water temperature cycle (daily mean temperatures, temperature variance, and the mean diel temperature fluctuation). We show that using metrics from only single‐depth stream temperature measurements are insufficient to identify substantial groundwater seepage locations in a head‐water stream. Conversely, comparing the metrics from dual‐depth temperatures show significant differences; at groundwater seepage locations, temperatures at the SWI merely explain 43–75% of the variation opposed to ? 91% at the corresponding stream column temperatures. In general, at these locations at the SWI, the slopes ( < 0.25) and intercepts ( > 6.5 °C) are substantially lower and higher, respectively, while the mean diel temperature fluctuations ( < 0.98 °C) are decreased compared to remaining locations. The dual‐depth approach was applied in a post‐glacial fluvial setting, where metrics analyses overall corroborated with field measurements of groundwater fluxes and stream flow accretions. Thus, we propose a method reliably identifying groundwater seepage locations along streambeds in such settings.     

Influence of a rock glacier spring on the stream energy budget and cold‐water refuge in an alpine stream

The thermal regimes of alpine streams remain understudied and have important implications for cold‐water fish habitat, which is expected to decline due to climatic warming. Previous research has focused on the effects of distributed energy fluxes and meltwater from snowpacks and glaciers on the temperature of mountain streams. This study presents the effects of the groundwater spring discharge from an inactive rock glacier containing little ground ice on the temperature of an alpine stream. Rock glaciers are coarse blocky landforms that are ubiquitous in alpine environments and typically exhibit low groundwater discharge temperatures and resilience to climatic warming. Water temperature data indicate that the rock glacier spring cools the stream by an average of 3 °C during July and August and reduces maximum daily temperatures by an average of 5 °C during the peak temperature period of the first two weeks in August, producing a cold‐water refuge downstream of the spring. The distributed stream surface and streambed energy fluxes are calculated for the reach along the toe of the rock glacier, and solar radiation dominates the distributed stream energy budget. The lateral advective heat flux generated by the rock glacier spring is compared to the distributed energy fluxes over the study reach, and the spring advective heat flux is the dominant control on stream temperature at the reach scale. This study highlights the potential for coarse blocky landforms to generate climatically resilient cold‐water refuges in alpine streams.     

Insights on stream temperature processes through development of a coupled hydrologic and stream temperature model for forested coastal headwater catchments

Stream temperature controls a number of biological, chemical, and physical processes occurring in aquatic environments. Transient snow cover and advection associated with lateral throughflow inputs can have a dominant influence on stream thermal regimes for headwater catchments in the rain‐on‐snow zone. Most existing stream temperature models lack the ability to properly simulate these processes. We developed and evaluated a conceptual‐parametric catchment‐scale stream temperature model that includes the role of transient snow cover and lateral advection associated with throughflow. The model consists of routines for simulating canopy interception, snow accumulation and melt, hillslope throughflow runoff and temperature, and stream channel energy exchange processes. The model was used to predict discharge and stream temperature for a small forested headwater catchment near Vancouver, Canada, using long‐term (1963–2013) weather data to compute model forcing variables. The model was evaluated against 4 years of observed stream temperature. The model generally predicted daily mean stream temperature accurately (annual RMSE between 0.57 and 1.24 °C) although it overpredicted daily summer stream temperatures by up to 3 °C during extended low streamflow conditions. Model development and testing provided insights on the roles of advection associated with lateral throughflow, channel interception of snow, and surface–subsurface water interactions on stream thermal regimes. This study shows that a relatively simple but process‐based model can provide reasonable stream temperature predictions for forested headwater catchments located in the rain‐on‐snow zone.     

Describing alpine lake influence on stream network temperatures: A statistical modelling approach

Systematic variations in atmospheric heat exchange, surface residence time, and groundwater influx across montane stream networks commonly produce an increasing stream temperature trend with decreasing elevation. However, complex stream temperature profiles that differ from this common longitudinal trend also exist, suggesting that stream temperatures may be influenced by complex interactions among hydrologic and atmospheric processes. Lakes within stream networks form one potential source of temperature profile complexity due to the spatially variable contribution of lake-sourced water to stream flow. We investigated temperature profile complexity in a multi-season stream temperature dataset collected across a montane stream network containing many alpine lakes. This investigation was performed by making comparisons between multiple statistical models that used different combinations of stream and lake characteristics to represent specific hypotheses for the controls on stream temperature. The compared models included a set of models which used a topographically derived estimate of the hydrologic influence of lakes to separate and quantify the effects of stream elevation and lake source-water contributions to longitudinal stream temperature patterns. This source-water mixing model provided a parsimonious explanation for complex stream-network temperature patterns in the summer and autumn, and this approach may be further applicable to other systems where stream temperatures are influenced by multiple water sources. Simpler models that discounted lake effects were more optimal during the winter and spring, suggesting that complex patterns in stream temperature profiles may emerge and subside temporally, across seasons, in response to diversity of water temperatures from different sources.     

Comparison of non-parametric and parametric water temperature models on the Nivelle River,France

Abstract

Water temperature is an important abiotic variable in aquatic habitat studies and may be one of the factors limiting the potential fish habitat (e.g. salmonids) in a stream. Stream water temperatures are modelled using statistical approaches with air temperature and streamflow as exogenous variables in the Nivelle River, southern France. Two different models are used to model mean weekly maximum temperature data: a non-parametric approach, the k-nearest neighbours method (k-NN) and a parametric approach, the periodic autoregressive model with exogenous variables (PARX). The k-NN is a data-driven method, which consists of finding, at each point of interest, a small number of neighbours nearest to this value, and the prediction is estimated based on these neighbours. The PARX model is an extension of commonly-used autoregressive models in which parameters are estimated for each period within the years. Different variants of air temperature and flow are used in the model development. In order to test the performance of these models, a jack-knife technique is used, whereby model goodness of fit is assessed separately for each year. The results indicate that both models give good performances, but the PARX model should be preferred, because of its good estimation of the individual weekly temperatures and its ability to explicitly predict water temperature using exogenous variables.     

SESTET: A spatially explicit stream temperature model based on equilibrium temperature

Stream-water temperature is a key variable controlling chemical, biological, and ecological processes in freshwater environments. Most models focus on a single river cross-section; however, temperature gradients along stretches and tributaries of a river network are crucial to assess ecohydrological features such as aquatic species suitability, growth and feeding rates, or disease transmission. We propose SESTET, a deterministic, spatially explicit stream temperature model for a whole river network, based on water and energy budgets at a reach scale and requiring only commonly available spatially distributed datasets, such as morphology and air temperature, as input. Heat exchange processes at the air–water interface are modelled via the widely used equilibrium temperature concept, whereas the effects of network structure are accounted for through advective heat fluxes. A case study was conducted on the prealpine Wigger river (Switzerland), where water temperatures have been measured in the period 2014–2018 at 11 spatially distributed locations. The results show the advantages of accounting for water and energy budgets at the reach scale for the entire river network, compared with simpler, lumped formulations. Because our approach fundamentally relies on spatially distributed air temperature fields, adequate spatial interpolation techniques that account for the effects of both elevation and thermal inversion in air temperature are key to a successful application of the model. SESTET allows the assessment of the magnitude of the various components of the heat budget at the reach scale and the derivation of reliable estimates of spatial gradients of mean daily stream temperatures for the whole catchment based on a limited number of conveniently located (viz., spanning the largest possible elevation range) measuring stations. Moreover, accounting for mixing processes and advective fluxes through the river network allows one to trust regionalized values of the parameters controlling the relationship between equilibrium and air temperature, a key feature to generalize the model to data-scarce catchments.     

Thermal regimes in a large upland salmon river: a simple model to identify the influence of landscape controls and climate change on maximum temperatures

Temperature observations at 25 sites in the 2000 km² Dee catchment in NE Scotland were used, in conjunction with geographic information system (GIS) analysis, to identify dominant landscape controls on mean monthly maximum stream temperatures. Maximum winter stream temperatures are mainly controlled by elevation, catchment area and hill shading, whereas the maximum temperatures in summer are driven by more complex interactions, which include the influence of riparian forest cover and distance to coast. Multiple linear regression was used to estimate the catchment‐wide distribution of mean weekly maximum stream temperatures for the hottest week of the 2‐year observation period. The results suggested the streams most sensitive to high temperatures are small upland streams at exposed locations without any forest cover and relatively far inland, while lowland streams with riparian forest cover at locations closer to the coast exhibit a moderated thermal regime. Under current conditions, all streams provide a suitable thermal habitat for both, Atlantic salmon and brown trout. Using two climate change scenarios assuming 2·5 and 4 °C air temperature increases, respectively, temperature‐sensitive zones of the stream network were identified, which could potentially have an adverse effect on the thermal habitat of Atlantic salmon and brown trout. Analysis showed that the extension of riparian forests into headwater streams has the potential to moderate changes in temperature under climate change. Copyright © 2010 John Wiley & Sons, Ltd.     

Landscape influence on small‐scale water temperature variations in a moorland catchment

We monitored temperatures in stream water, groundwater and riparian wetland surface water over 18 months in a 3.2‐km² moorland catchment in the Scottish Highlands. The stream occupies a glaciated valley, aligned east–west. It has three main headwater tributaries with a large north facing catchment, a south facing catchment and the smallest east facing headwater. The lower catchment sampling locations begin after the convalescence of all three headwaters. Much of the stream network is fringed by riparian peatlands. Stream temperatures are mainly regulated by energy exchanges at the air–water interface. However, they are also influenced by inflows from the saturated riparian zone, where surface water source areas are strongly connected with the stream network. Consequently, the spatial distribution of stream temperatures exhibits limited variability. Nevertheless, there are significant summer differences between the headwaters, despite their close proximity to each other. This is consistent with aspect (and incident radiation), given the south and east facing headwaters having higher temperatures. The largest, north‐facing sub‐catchment shows lower summer diurnal temperature variability, suggesting that lower radiation inputs dampen temperature extremes. Whilst stream water temperature regimes in the lower catchment exhibit little change along a 1‐km reach, they are similar to those in the largest headwater; probably reflecting size and comparable catchment aspect and hydrological flow paths. Our results suggest that different parts of the channel network and its connected wetlands have contrasting sensitivity to higher summer temperatures. This may be important in land management strategies designed to mitigate the impacts of projected climatic warming. Copyright © 2015 John Wiley & Sons, Ltd.     

A multicatchment analysis of headwater and downstream temperature effects from contemporary forest harvesting

Stream temperature is a key physical water‐quality parameter, controlling many biological, chemical, and physical processes in aquatic ecosystems. Maintenance of cool stream temperatures during summer is critical for high‐quality aquatic habitat. As such, transmission of warm water from small, nonfish‐bearing headwater streams after forest harvesting could cause warming in downstream fish‐bearing stream reaches with negative consequences. In this study, we evaluate (a) the effects of contemporary forest management practices on stream temperature in small, headwater streams, (b) the transmission of thermal signals from headwater reaches after harvesting to downstream fish‐bearing reaches, and (c) the relative role of lithology and forest management practices in influencing differential thermal responses in both the headwater and downstream reaches. We measured summer stream temperatures both preharvest and postharvest at 29 sites—12 upstream sites (4 reference, 8 harvested) and 17 downstream sites (5 reference, 12 harvested)—across 3 paired watershed studies in western Oregon. The 7‐day moving average of daily maximum stream temperature (T_7DAYMAX) was greater during the postharvest period relative to the preharvest period at 7 of the 8 harvested upstream sites. Although the T_7DAYMAX was generally warmer in the downstream direction at most of the stream reaches during both the preharvest and postharvest period, there was no evidence for additional downstream warming related to the harvesting activity. Rather, the T_7DAYMAX cooled rapidly as stream water flowed into forested reaches ~370–1,420 m downstream of harvested areas. Finally, the magnitude of effects of contemporary forest management practices on stream temperature increased with the proportion of catchment underlain by more resistant lithology at both the headwater and downstream sites, reducing the potential for the cooling influence of groundwater.