Climatic Change

, Volume 116, Issue 1, pp 133–148 | Cite as

Connecting physical watershed characteristics to climate sensitivity for California mountain streams

  • Iris T. Stewart


California mountain streams provide critical water resources for human supplies and aquatic ecosystems, and have been affected by climatic changes to varying degrees, often within close proximity. The objective of this study is to examine stream flow timing changes and their climatic drivers through 2009, identify sub-regional patterns in response and sensitivity, and explore whether the differences in the sensitivity of a stream to climatic changes can be partially explained through the physical characteristics of a watershed. To this end, changes in streamflow timing for each watershed were assessed through several runoff timing measures, and overall sensitivity to historic climatic changes through a composite sensitivity index. Elevation, aspect, slope, geology, and landcover distributions, as well as climate information were assembled for each watershed; and were analyzed in conjunction with the sensitivity index. Results showed that the basins most sensitive to climatic changes are on the western Sierra Nevada slopes, while eastern and southern Sierra Nevada, as well as Klamath mountain watersheds exhibit little or no response to climatic shifts to date. Basin sensitivity was not found to be connected to any individual physical watershed characteristic other than elevation. However, it is suggested that basin-to-basin differences in sensitivity, observed in spite of regional-scale warming and similar watershed elevations, can be explained by differences in elevation ranges and combinations of physical watershed characteristics. Results about stream differences in climate sensitivity could aid in prioritizing stream preservation efforts.


Streamflow Pacific Decadal Oscillation Climate Sensitivity Precipitation Index Basaltic Rock 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The author would like to thank the Clare Booth Luce Foundation for its support of this work.

Supplementary material

10584_2012_567_MOESM1_ESM.doc (187 kb)
ESM 1 (DOC 187 kb)
10584_2012_567_MOESM2_ESM.doc (270 kb)
ESM 2 (DOC 270 kb)
10584_2012_567_MOESM3_ESM.doc (122 kb)
ESM 3 (DOC 122 kb)


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Environmental Studies and SciencesSanta Clara UniversitySanta ClaraUSA

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