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Modeling Landscape Change Effects on Stream Temperature Using the Soil and Water Assessment Tool
Article

Improved Soil Temperature Modeling Using Spatially Explicit Solar Energy Drivers

1
Western Ecology Division, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Corvallis, OR 97330, USA
2
College of Earth and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA
3
Environmental Science & Management, Humboldt State University, Arcata, CA 95521, USA
4
Inoventures (LLC), Western Ecology Division, National Health and Environmental Effects Research Laboratory, c/o U.S. Environmental Protection Agency, Corvallis, OR 97330, USA
*
Author to whom correspondence should be addressed.
Water 2018, 10(10), 1398; https://doi.org/10.3390/w10101398
Received: 31 August 2018 / Revised: 27 September 2018 / Accepted: 4 October 2018 / Published: 9 October 2018
(This article belongs to the Special Issue Impacts of Landscape Change on Water Resources)
Modeling the spatial and temporal dynamics of soil temperature is deterministically complex due to the wide variability of several influential environmental variables, including soil column composition, soil moisture, air temperature, and solar energy. Landscape incident solar radiation is a significant environmental driver that affects both air temperature and ground-level soil energy loading; therefore, inclusion of solar energy is important for generating accurate representations of soil temperature. We used the U.S. Environmental Protection Agency’s Oregon Crest-to-Coast (O’CCMoN) Environmental Monitoring Transect dataset to develop and test the inclusion of ground-level solar energy driver data within an existing soil temperature model currently utilized within an ecohydrology model called Visualizing Ecosystem Land Management Assessments (VELMA). The O’CCMoN site data elucidate how localized ground-level solar energy between open and forested landscapes greatly influence the resulting soil temperature. We demonstrate how the inclusion of local ground-level solar energy significantly improves the ability to deterministically model soil temperature at two depths. These results suggest that landscape and watershed-scale models should incorporate spatially distributed solar energy to improve spatial and temporal simulations of soil temperature. View Full-Text
Keywords: soil temperature; solar energy; watershed model; landscape scale; VELMA soil temperature; solar energy; watershed model; landscape scale; VELMA
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MDPI and ACS Style

Halama, J.J.; Barnhart, B.L.; Kennedy, R.E.; McKane, R.B.; Graham, J.J.; Pettus, P.P.; Brookes, A.F.; Djang, K.S.; Waschmann, R.S. Improved Soil Temperature Modeling Using Spatially Explicit Solar Energy Drivers. Water 2018, 10, 1398. https://doi.org/10.3390/w10101398

AMA Style

Halama JJ, Barnhart BL, Kennedy RE, McKane RB, Graham JJ, Pettus PP, Brookes AF, Djang KS, Waschmann RS. Improved Soil Temperature Modeling Using Spatially Explicit Solar Energy Drivers. Water. 2018; 10(10):1398. https://doi.org/10.3390/w10101398

Chicago/Turabian Style

Halama, Jonathan J., Bradley L. Barnhart, Robert E. Kennedy, Robert B. McKane, James J. Graham, Paul P. Pettus, Allen F. Brookes, Kevin S. Djang, and Ronald S. Waschmann 2018. "Improved Soil Temperature Modeling Using Spatially Explicit Solar Energy Drivers" Water 10, no. 10: 1398. https://doi.org/10.3390/w10101398

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