An economic analysis and operations research of wildfire management - Donovan, Geoffrey H., author (Colorado State University. Libraries, 2001)
PART ONE: The Cost plus Net Value Change (C+NVC) model provides the theoretical foundation for wildland fire economics, and provides the basis for the National Fire Management Analysis System (NFMAS). The C+NVC model is based upon the earlier least Cost plus Loss model (LC+L) expressed by Sparhawk (1925). Mathematical and graphical analysis of the LC+L model illustrates three errors in model formulation. First, suppression is incorrectly modeled as a model output. Second, suppression and loss are incorrectly illustrated as positively correlated. Third, suppression and primary protection are incorrectly modeled as negatively correlated. These errors are shown to be perpetuated by the contemporary C+NVC model, and to have serious implications for the model's capacity to correctly identify the most efficient level of fire management expenditure. A corrected graphical representation of the C+NVC model is presented, which allows the most efficient level of fire management expenditure to be correctly identified. PART TWO: The economic efficiency of the National Fire Management Analysis System (NFMAS) and FIREPRO is examined. A brief history of the two programs is provided, as well as recent improvements to the contemporary theory of C+NVC. The NFMAS process is reviewed in relation to the theory of C+NVC with particular focus on its ability to reliably locate the Most Efficient Level of preparedness/presuppression (MEL). FIREPRO is reviewed with regard to its ability to ensure cost effective resource allocations. Improvements and alternative approaches for both systems are suggested. PART THREE: Determining the specific mix of fire-fighting resources for a given fire, is a necessary condition for identifying the minimum of the C+NVC function. Current wildland fire management models do not reliably do so. The optimal mix problem is characterized mathematically using integer-programming techniques. This mathematical exposition is then solved using the LINGO optimization language. Sensitivity analysis is conducted on model inputs to demonstrate the flexibility of the model architecture. Further, the model is used to accommodate budget constraints commonly faced by fire managers.
Keywords: forestry; forest and brush fires; studies; identification; values; expenditures; efficiency; forest management; sensitivity analysis; planning; variables; copyright; reference materials; national parks; fire protection