| Resource Name |
Mountain Pine Beetles, Salvage Logging, and Hydrologic Change: Predicting Wet Ground Areas |
| Unique File Number |
369 |
| Information Type |
applied Research |
| Surface Water |
A |
| Aquatic Ecosystem |
|
| Groundwater |
A |
| Groundwater & Surface Water |
A |
| Management for Natural & Industrial Hazards |
A |
| Strengths |
develops a tool to predict areas of wet ground following large scale disturbance. Likely applicable to low relief areas in NE BC. |
| Limitations |
not tested outside Vanderhoof area |
| Challenges |
|
| Outstanding Research Questions |
|
| Outstanding Research Questions |
|
| Information Subtype |
boreal hydrology |
| Organization |
FLNRO |
| Resource Name |
Rex, J.; Dubé, S.; Foord, V. Mountain Pine Beetles, Salvage Logging, and Hydrologic Change: Predicting Wet Ground Areas. Water 2013, 5, 443-461. |
| Resource Purpose |
The mountain pine beetle epidemic in British Columbia has covered 18.1 million hectares of forest land showing the potential for exceptionally large-scale disturbance to influence watershed hydrology. Pine stands killed by the epidemic can experience reduced levels of evapotranspiration and precipitation interception, which can translate into an increase in soil moisture as observed by some forest practitioners during salvage logging in the epicenter of the outbreak. They reported the replacement of summer ground, dry firm soil areas, with winter ground areas identified by having wetter, less firm soils upon which forestry equipment operation is difficult or impossible before winter freeze-up. To decrease the likelihood of soil disturbance from harvesting, a set of hazard indicators was developed to predict wet ground areas in areas heavily infested by the mountain pine beetle. Hazard indicators were based on available GIS data, aerial photographs, and local knowledge. Indicators were selected by an iterative process that began with office-based selection of potential indicators, model development and prediction, field verification, and model refinement to select those indicators that explained most field data variability. Findings indicate that the most effective indicators were lodgepole pine content, understory, drainage density, soil texture, and the topographic index. |
| Type of Information |
article |
| How does this help decision making? |
|
| Program Status |
complete |
| NE Coverage |
provincial |
| Drinking Water |
|
| Ecosystem |
|
| Fish |
|
| Groundwater |
y |
| Public Safety |
|
| SW Quality |
|
| SW Quantity |
y |
| Link |
http://www.mdpi.com/2073-4441/5/2/443 |
| Text Query |
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| Google Earth |
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| iMap Path Link |
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| Spatial Metadata |
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| Map |
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| Contact Email |
[email protected] |
