Return to search

Toward verification of a natural resource uncertainty model

Natural resource management models simplify reality for the purpose of planning or management.
In much the same way, an uncertainty model simplifies the many uncertainties that
pervade the natural resource management model. However, though a number of uncertainty
models have been developed, there has been little work on verifying such models against the
uncertainty they purport to represent. The central research question addressed by this work is
'can a natural resource management uncertainty model be verified in order to evaluate its
utility in real-world management?' Methods to verity uncertainty models are developed in two
areas: uncertainty data models, and uncertainty propagation through process models. General
methods are developed, and then applied to a specific case study: slope stability uncertainty in
the southern Queen Charlotte Islands. Verification of two typical uncertainty data models (of
classified soils and continuous slope) demonstrates that (in this case) both expert opinion
inputs and published error statistics underestimate the level of uncertainty that exists in
reality. Methods are developed to recalibrate the data models, and the recalibrated data are
used as input to an uncertainty propagation model. Exploratory analysis methods are then
used to verify the output of this model, comparing it with a high-resolution mass wastage
database—itself developed using a new set of tools incorporating uncertainty visualisation.
Exploratory data analysis and statistical analysis of the verification shows that, given the
nature of slope stability modelling, it is not possible to directly verify variability in the model
outputs due to the existing distribution of slope variability (based on the nature of slope modelling).
However, the verification work indicates that the information retained in uncertaintybased
process models allows increased predictive accuracy—in this case of slope failure. It is
noted that these verified models and their data increase real-world management and planning
options at all levels of resource management. Operational utility is demonstrated throughout
this work. Increased strategic planning utility is discussed, and a call is made for integrative
studies of uncertainty model verification at this level.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVAU.2429/9958
Date11 1900
CreatorsDavis, Trevor John
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
RelationUBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]

Page generated in 0.0022 seconds