Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...

Ranking forest effects on snow storage: a decision tool for forest management

Owners: This resource does not have an owner who is an active HydroShare user. Contact CUAHSI ( for information on this resource.
Type: Resource
Storage: The size of this resource is 214.5 MB
Created: Oct 07, 2019 at 1:51 p.m.
Last updated: Sep 28, 2021 at 11:24 p.m.
DOI: 10.4211/hs.76e60d8b9ead4c33898c14dd677c6e06
Citation: See how to cite this resource
Sharing Status: Published
Views: 535
Downloads: 33
+1 Votes: Be the first one to 
Comments: No comments (yet)


Forests modify snow accumulation and ablation rates, and overall snow storage amounts and durations, with multiple processes acting simultaneously and often in different directions. To synthesize complex forest-snow relations and help guide near-term management decisions, we present a decision tree model based on a hypothesized hierarchy of processes and associated variables that predict forest effects on snow storage. In locations with high wind speeds, forests enhance snow storage magnitude and duration relative to open areas. Where wind speeds are low, and winter and spring air temperatures are colder, forests diminish snow storage magnitude but enhance duration. Where air temperatures are warmer, forests diminish both magnitude and duration. Forest structure and aspect are secondary influences that shift the net effect of forest on snow storage. We apply the model to map the influence of forests on snow storage under historic and warming climate conditions across the western United States, but this model is applicable in any region with forests and snow. The decision tree model provides practitioners a first-step evaluation to guide management decisions that consider where and how forests can be managed to optimize in-situ water storage alongside other objectives, such as reducing wildfire fuels. This framework also articulates geospatial hypotheses, in order of anticipated importance, to be tested in future investigations of forest-snow-climate relations.

The data and code included herein are described in Dickerson-Lange, et al. 2021, Ranking forest effects on snow storage: a decision tool for forest management, Water Resources Research. The repository contains all input data, model code, and results.

Subject Keywords



Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
North Latitude
East Longitude
South Latitude
West Longitude


Start Date:
End Date:


Related Resources

The content of this resource is derived from PRISM 800m DEM and Climate Normals (
This resource is referenced by Dickerson-Lange, S. E., J. A. Vano, R. Gersonde, and J. D. Lundquist (2021), Ranking forest effects on snow storage: a decision tool for forest management, Water Resources Research, 57, e2020WR027926.
The content of this resource is derived from National Landcover Dataset, 2011 (


Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
Department of the Interior Northwest Climate Science Center Cooperative Agreement GS297A
National Science Foundation (NSF) CBET‐1703663, EAR‐1250087

How to Cite

Dickerson-Lange, S., J. Lundquist, J. Vano, R. Gersonde (2021). Ranking forest effects on snow storage: a decision tool for forest management, HydroShare,

Select a license CC-BY-NC


There are currently no comments

New Comment