Modified equilibrium temperature models for cold‐water streams

Herb, William R.; Stefan, Heinz G.

doi:10.1029/2010wr009586

Cited by 27 publications

(45 citation statements)

References 28 publications

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“…This fact is confirmed by other studies (e.g. Bogan et al, 2004;Herb and Stefan, 2011), but nonetheless fails to be accounted for in many stream temperature models (e.g. Caissie et al, 2005;Bustillo et al, 2014).…”

Section: Discussionsupporting

confidence: 77%

“…This conclusion is in agreement with the findings of Bogan et al (2004), who found that the precision of their stream temperature model was improved by including a term accounting for the lateral water inflow. Similarly, Herb and Stefan (2011) mention that the heat input associated with groundwater infiltration may be of the same order of magnitude as the heat flux due to atmospheric forcing in some cases. This effect seems to be largely underestimated in the literature, since the lateral inflow of water has often been neglected in previous stream temperature models (e.g.…”

Section: Discussionmentioning

confidence: 99%

“…Based on a formula similar to Eq. (4), Herb and Stefan (2011) have estimated L c to vary between 3 and 45 km for discharge values between 0.4 and 5.8 m 3 s −1 in the case of the Vermillion River in Minnesota. As most of the catchments considered in the present study have discharges contained within this range, we should expect a marked variation in the values of L c both during the course of the year and across catchments.…”

Section: Derivation Of the Analytical Solution To The Energy-balance mentioning

confidence: 99%

“…In addition, they all assumed the river width to remain constant along the stream so as to analytically solve the energy-balance equation. Very few studies accounted for the heat exchange with the stream bed or the heat advected by lateral inflow of water (Bogan et al, 2004;Herb and Stefan, 2011). Bogan et al (2003) were the only authors to evaluate their analytical expression over ungauged basins.…”

Section: Physics-inspired Statistical Modelmentioning

confidence: 99%

“…Although negligible in large catchments, they might be of the same order of magnitude as the heat exchange term in small watersheds. Only a few studies relying on an analytical expression for stream temperature modelling have considered the lateral inflow term to date (Bogan et al, 2004;Herb and Stefan, 2011), and none has retained the source term.…”

Section: Derivation Of the Analytical Solution To The Energy-balance mentioning

confidence: 99%

See 4 more Smart Citations

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Gallice

Schaefli

Lehning

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. The development of stream temperature regression models at regional scales has regained some popularity over the past years. These models are used to predict stream temperature in ungauged catchments to assess the impact of human activities or climate change on riverine fauna over large spatial areas. A comprehensive literature review presented in this study shows that the temperature metrics predicted by the majority of models correspond to yearly aggregates, such as the popular annual maximum weekly mean temperature (MWMT). As a consequence, current models are often unable to predict the annual cycle of stream temperature, nor can the majority of them forecast the inter-annual variation of stream temperature. This study presents a new statistical model to estimate the monthly mean stream temperature of ungauged rivers over multiple years in an Alpine country (Switzerland). Contrary to similar models developed to date, which are mostly based on standard regression approaches, this one attempts to incorporate physical aspects into its structure. It is based on the analytical solution to a simplified version of the energy-balance equation over an entire stream network. Some terms of this solution cannot be readily evaluated at the regional scale due to the lack of appropriate data, and are therefore approximated using classical statistical techniques. This physics-inspired approach presents some advantages: (1) the main model structure is directly obtained from first principles, (2) the spatial extent over which the predictor variables are averaged naturally arises during model development, and (3) most of the regression coefficients can be interpreted from a physical point of view -their values can therefore be constrained to remain within plausible bounds. The evaluation of the model over a new freely available data set shows that the monthly mean stream temperature curve can be reproduced with a rootmean-square error (RMSE) of ±1.3 • C, which is similar in precision to the predictions obtained with a multi-linear regression model. We illustrate through a simple example how the physical aspects contained in the model structure can be used to gain more insight into the stream temperature dynamics at regional scales.

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Section: Discussionsupporting

confidence: 77%

Section: Discussionmentioning

confidence: 99%

Section: Derivation Of the Analytical Solution To The Energy-balance mentioning

confidence: 99%

Section: Physics-inspired Statistical Modelmentioning

confidence: 99%

Section: Derivation Of the Analytical Solution To The Energy-balance mentioning

confidence: 99%

See 3 more Smart Citations

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Gallice

Schaefli

Lehning

et al. 2015

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

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

Laurel

Wohl

2017

Earth Surf Processes Landf

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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.

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Inter‐annual variability in the effects of riparian woodland on micro‐climate, energy exchanges and water temperature of an upland Scottish stream

Garner

Malcolm

Sadler

et al. 2014

Hydrological Processes

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Abstract:The influence of riparian woodland on stream temperature, micro-climate and energy exchange was investigated over seven calendar years. Continuous data were collected from two reaches of the Girnock Burn (a tributary of the Aberdeenshire Dee, Scotland) with contrasting land use characteristics: (1) semi-natural riparian forest and (2) open moorland. In the moorland reach, wind speed and energy fluxes (especially net radiation, latent heat and sensible heat) varied considerably between years because of variable riparian micro-climate coupled strongly to prevailing meteorological conditions. In the forested reach, riparian vegetation sheltered the stream from meteorological conditions that produced a moderated micro-climate and thus energy exchange conditions, which were relatively stable between years. Net energy gains (losses) in spring and summer (autumn and winter) were typically greater in the moorland than the forest. However, when particularly high latent heat loss or low net radiation gain occurred in the moorland, net energy gain (loss) was less than that in the forest during the spring and summer (autumn and winter) months. Spring and summer water temperature was typically cooler in the forest and characterised by less inter-annual variability due to reduced, more inter-annually stable energy gain in the forested reach. The effect of riparian vegetation on autumn and winter water temperature dynamics was less clear because of the confounding effects of reach-scale inflows of thermally stable groundwater in the moorland reach, which strongly influenced the local heat budget. These findings provide new insights as to the hydrometeorological conditions under which semi-natural riparian forest may be effective in mitigating river thermal variability, notably peaks, under present and future climates.

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Modified equilibrium temperature models for cold‐water streams

Cited by 27 publications

References 28 publications

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

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

Inter‐annual variability in the effects of riparian woodland on micro‐climate, energy exchanges and water temperature of an upland Scottish stream

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