Spatially prioritizing fuel treatments to manage wildfire risks to municipal watersheds

Transcription

1 Spatially prioritizing fuel treatments to manage wildfire risks to municipal watersheds Benjamin Gannon 1,2, Yu Wei 2, Stephanie Kampf 3, Lee MacDonald 3, Jeff Cannon 1, Brett Wolk 1, Tony Cheng 1,2, Kelly Jones 4, Heather Schinkel 5, Rob Addington 6, Matt Thompson 7 1 Colorado Forest Restoration Institute, Colorado State University; 2 Forest and Rangeland Stewardship, Colorado State University; 3 Ecosystem Science and Sustainability, Colorado State University; 4 Human Dimensions of Natural Resources, Colorado State University; 5 Colorado Conservation Exchange and Peaks to People Water Fund, Colorado State University; 6 Colorado Chapter, The Nature Conservancy; 7 Rocky Mountain Research Station, USDA Forest Service

2 Recent Front Range Wildfires High Park 2012 Crystal 2011 Hewlett Gulch 2012 Big Elk 2000 Overland 2003 Black Tiger 1989 Picnic Rock 2004 Galena 2013 Bobcat Gulch 2000 Four Mile 2010 Hi Meadow 2000 Lower North Fork 2012 Buffalo Creek 1996 Hayman 2002 Black Forest 2013 Waldo Canyon 2012

3 Study Area: Cache la Poudre and Big Thompson Our Solution Area: 4,660 km 2 Elevation: 1,499-4,344 m Vegetation: Ponderosa pine 16.7% Lodgepole pine 16.6% Mixed conifer 11.3% Ownership: Federal 52.3% Private 37.4% State 7.4% Local 2.9% Water Stakeholders: Fort Collins Greeley Loveland Northern Water (Fort Collins, Greeley, Loveland, Longmont, Boulder, Louisville, Lafayette, Broomfield, and smaller communities) Agricultural Users Water Resources and Assets: 22 Reservoirs 5 Municipal diversions 4 Agricultural diversions Additional downstream infrastructure

4 Tools to support complex watershed management objectives Fire Wildfire Risk Likelihood Fire Behavior Resource Exposure and Susceptibility

5 Basic Risk Assessment Math Finney 2005 Fire Likelihood Wildfire Risk i spatial units Catchments from NHD+ Fire Behavior Resource Exposure and Susceptibility Burn Probability from FSim Short et al Net Value Change is a function of fire effects on erosion, sediment transport to infrastructure, and infrastructure sediment impact costs Fire behavior modeling (FlamMap) Quantify erosion response (RUSLE) Map and value infrastructure Quantify exposure (NHD+, sediment transport models)

6 Watershed Topology Finney 2005 i catchments Infrastructure has value

7 Burn Probability Finney 2005 Why do we use Burn Probability? When benefits are framed as avoiding wildfire impacts, benefit is only achieved when treatments interact with fire. Some benefits of forest restoration are achieved independent of fire, e.g. improved wildlife habitat, increased understory plant diversity, and increased resistance to insects, disease, and drought.

8 Fire Effects on Erosion Finney 2005

9 Fuel Treatment Effects on Fire and Erosion Mechanical Rx Fire Benefits can then be measured as: Avoided Erosion = Untreated Treated for the feasible acres for each treatment type in each catchment

10 Bringing it all together for planning Fire Wildfire Risk Likelihood Fire Behavior Resource Exposure and Susceptibility

11 Bringing it all together for planning BCR Lower Higher Mechanical Only Mechanical & Rx Fire Rx Fire Only We can then sort the treatment-catchment decision units and build an optimal treatment plan under total budget and catchment-level feasibility constraints.

12 Bringing it all together for planning

13 Valuing Infrastructure Infrastructure sediment costs are specified as tabular input. The location and value of infrastructure drive the benefit of fuel treatment, so we built a tool to help stakeholders visualize how the model translates these costs into the value of retaining sediment in the watershed. Infrastructure Feature $ per Mg Finney 2005 BARNES DITCH 8 LOVELAND PIPELINE 8 GEORGE RIST DITCH 4 DILLE TUNNEL 8 MARY'S LAKE AT ESTES PARK EAST PORTAL RES PINEWOOD RES LAKE ESTES CARTER LAKE RES POUDRE VALLEY CANAL 4 GREELEY FILTERS PIPELINE 8 JOE WRIGHT RES BARNES MEADOW RES PETERSON LAKE RES NOTE: these values are for illustration purposes only. Actual stakeholder values are being collected and revised through an iterative process.

14 Optimal treatment plan for set budget(s) NOTE: this treatment plan is presented for illustration purposes only. It may change with further stakeholder feedback on values.

15 Summary 1) Models aren t perfect but we can do a pretty good job estimating risk of wildfire impacts to water infrastructure. Finney ) We can use the ratio of risk reduction to treatment cost to prioritize restoration investments. 3) A decision support system can facilitate a range of complex analyses for assessment and planning.