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Stream Temperature Data and Modeling Meeting Notes
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NALCC Aquatic Technical Team Meeting, 2012
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Resource Materials: Previous Workshops
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2012 Stream Temperature Data and Modeling (Meeting I)
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A regional neural network ensemble for predicting mean daily river water temperature
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Abstract: Water temperature is a fundamental property of river habitat and often a key aspect of river resource
management, but measurements to characterize thermal regimes are not available for most streams
and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean
daily water temperature in 197,402 individual stream reaches during the warm season (May–October)
throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four
models with different groups of predictors to determine how well water temperature could be predicted
by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100
ANNs as our final prediction for each model. The final model included air temperature, landform attributes
and forested land cover and predicted mean daily water temperatures with moderate accuracy
as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009
(RMSE = 1.91 C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010
(RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream
reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air
temperature, and network catchment area according to sensitivity analyses. Forest land cover at both
riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature
averaged for the month of July matched expected spatial trends with cooler temperatures in
headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures
throughout a large region, while other regional efforts have predicted at relatively coarse time
steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled
rivers under current conditions and future projections of climate and land use changes, thereby providing
information that is valuable to management of river ecosystems and biota such as brook trout.
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Brook Trout and Stream Temperature Workshop Information
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Resource Materials: Reprints
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Predicting Brook Trout Occurrence in Stream Reaches throughout their Native Range in the Eastern United States
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Abstract
The Brook Trout Salvelinus fontinalis is an important species of conservation concern in the eastern USA. We
developed a model to predict Brook Trout population status within individual stream reaches throughout the
species’ native range in the eastern USA. We utilized hierarchical logistic regression with Bayesian estimation to
predict Brook Trout occurrence probability, and we allowed slopes and intercepts to vary among ecological
drainage units (EDUs). Model performance was similar for 7,327 training samples and 1,832 validation samples
based on the area under the receiver operating curve (»0.78) and Cohen’s kappa statistic (0.44). Predicted water
temperature had a strong negative effect on Brook Trout occurrence probability at the stream reach scale and was
also negatively associated with the EDU average probability of Brook Trout occurrence (i.e., EDU-specific
intercepts). The effect of soil permeability was positive but decreased as EDU mean soil permeability increased.
Brook Trout were less likely to occur in stream reaches surrounded by agricultural or developed land cover, and an
interaction suggested that agricultural land cover also resulted in an increased sensitivity to water temperature.
Our model provides a further understanding of how Brook Trout are shaped by habitat characteristics in the
region and yields maps of stream-reach-scale predictions, which together can be used to support ongoing
conservation and management efforts. These decision support tools can be used to identify the extent of potentially
suitable habitat, estimate historic habitat losses, and prioritize conservation efforts by selecting suitable stream
reaches for a given action. Future work could extend the model to account for additional landscape or habitat
characteristics, include biotic interactions, or estimate potential Brook Trout responses to climate and land use
changes.
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Brook Trout and Stream Temperature Workshop Information
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Resource Materials: Reprints
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Paired stream-air temperature measurements reveal fine-scale thermal heterogeneity within headwater brook trout stream networks.
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Authors:
Y. Kanno,J. C. Vokoun and B. H. Letcher
Keywords:
climate change;fish conservation;groundwater;Salmonidae;stream discharge;water temperature
ABSTRACT
Previous studies of climate change impacts on stream fish distributions commonly project the potential patterns of habitat loss and fragmentation due to elevated stream temperatures at a broad spatial scale (e.g. across regions or an entire species range). However, these studies may overlook potential heterogeneity in climate change vulnerability within local stream networks. We examined fine-scale stream temperature patterns in two headwater brook trout Salvelinus fontinalis stream networks (7.7 and 4.4 km) in Connecticut, USA, by placing a combined total of 36 pairs of stream and air temperature loggers that were approximately 300 m apart from each other. Data were collected hourly from March to October 2010. The summer of 2010 was hot (the second hottest on record) and had well below average precipitation, but stream temperature was comparable with those of previous 2 years because streamflow was dominated by groundwater during base-flow conditions. Nonlinear regression models revealed stream temperature variation within local stream networks, particularly during warmest hours of the day (i.e. late afternoon to evening) during summer. Thermal variability was primarily observed between stream segments, versus within a stream segment (i.e. from confluence to confluence). Several cold tributaries were identified in which stream temperature was much less responsive to air temperature. Our findings suggested that regional models of stream temperature would not fully capture thermal variation at the local scale and may misrepresent thermal resilience of stream networks. Groundwater appeared to play a major role in creating the fine-scale spatial thermal variation, and characterizing this thermal variation is needed for assessing climate change impacts on headwater species accurately.
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Brook Trout and Stream Temperature Workshop Information
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Resource Materials: Reprints
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Forecasting changes in stream flow, temperature, and salmonid populations in Eastern U.S. as a result of climate change
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Presentation by Ben Letcher. One of the slides near the end is entitled: Papers where he lists many relevant publications
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Brook Trout and Stream Temperature Workshop Information
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Resource Materials: Reprints
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2014 Lecture: Forecasting changes in stream flow, temperature, and salmonid populations in Eastern U.S. as a result of climate change
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Ben Letcher
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Brook Trout and Stream Temperature Workshop Information
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Resource Materials: Presentations
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Relevant reprints
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As referenced in Ben Letcher's 2014 Presentation Slides (partial list)
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Brook Trout and Stream Temperature Workshop Information
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Current Research (2015)
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Links to relevant conservation research:
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Brook Trout and Stream Temperature Workshop Information
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SIAS - 2014
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Climate and Nat'l Adaptation Reporting
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