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Stream Temperature Modeling and Monitoring > Spatial Statistical Stream Temperature Model
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Spatial Statistical Stream Temperature Model
Spatial Statistical Stream
Many natural resource agencies routinely collect digital stream
temperature data. However, a lack of coordinated sampling efforts typically
results in temperature observations within a stream network that are spatially
clustered, non-random, and autocorrelated. Recently, a
new class of spatial statistical models that account for network topology (i.e.,
flow direction and volume) has been developed to address these issues (Ver Hoef
et al. 2006).
the application of these models, we
assembled a large stream temperature database (n = 780 records) spanning a 14-year period from 1993 – 2006 for the 6,900 km2 Boise River basin in
central Idaho. Predictor variables that potentially affected stream temperature
were quantified using automated GIS routines to obtain measurements of
geomorphic features (e.g., elevation, channel slope, and valley confinement),
imagery to estimate solar radiation changes from wildfire, and climate stations
to provide information on stream flow and air temperatures. Spatial models with
four fixed-effect predictors and a mixed model spatial error structure accounted
for 93% and 86% of the variation in summer mean and maximum stream temperatures,
respectively, during the 14-year study period.
models yield more accurate parameter estimates than traditional,
non-spatial models and offer much improved predictive ability.
These models are
being used to map past and future thermal conditions and suitable habitat
distributions for native salmonid species in this basin, but could also be used
to better understand factors that affect stream temperature, determine
compliance with water quality standards, or optimize temperature sampling
designs. Preliminary results from this project have been presented at several
scientific meetings and a peer-reviewed manuscript has been drafted for
Ver Hoef, J.M., E. Peterson, and D. Theobald. 2006.
Spatial statistical models that use flow and stream distance. Environmental
and Ecological Statistics 13:449-464.