Comparing Alternative Budget Allocation Models to Support Strategic Wildland Fire Program Analysis Across Us National Parks

Comparing Alternative Budget Allocation Models to Support Strategic Wildland Fire Program Analysis Across Us National Parks

Yu Wei Douglas Rideout Andy Kirsch Niki Kernohan 

Colorado State University, USA

National Park Service, USA

Page: 
238-245
|
DOI: 
https://doi.org/10.2495/SAFE-V6-N2-238-245
Received: 
N/A
|
Accepted: 
N/A
|
Published: 
30 June 2016
| Citation

OPEN ACCESS

Abstract: 

Hazard fuel reduction and wildland fire preparedness programs are two important budgeting components in the US National Park Service strategic wildland fire planning. During the planning process, each national park independently conducts analysis to understand the benefits from investing in each program to mitigate fire risks and improve ecosystem benefits. The national program analysis imports the cost-effective frontiers of investment in both programs from each national park. The national pro- gram then allocates cost-effective funding to the parks and implements required national policies while minimizing disruption to current programs of work. In this study, we test and compare two alternative modeling methods for budget allocation between the fuel treatment and preparedness programs responding to changes in funding levels nationally. One approach uses a nonlinear programming model (NLP) to maximize the benefits of investments in both programs with a set of feasibility constraints. The other approach uses a simulation-based gradient method to manage program budget changes. Both approaches are designed to focus on national level program efficiency while mitigating potential program disruptions; however, different approaches suggest different budgeting allocation strategies. This study compares the trade-offs between efficiency and the level of disruption of different budget allocation methods. Discoveries could help managers to select and implement an efficient and viable analytical system to study the value of funding increases, the cost of budget reductions, and guide landscape allocations. It will also identify national impacts by accumulating allocations to individual units across the national parks in the United States.

Keywords: 

fuel treatment, gradient method, linear programming, preparedness

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