Modeling Livelihood Indicators and Household Resilience using Bayesian Networks

Wendy Merritt; Brendan Patch; V. Ratna Reddy; Sanjit Kumar Rout; Geoffrey J. Syme

doi:10.1016/B978-0-12-800067-0.00009-8

Modeling Livelihood Indicators and Household Resilience using Bayesian Networks

Wendy Merritt^*, Brendan Patch, V. Ratna Reddy, Sanjit Kumar Rout, Geoffrey J. Syme

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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Abstract

The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.

Original language	English
Title of host publication	Integrated Assessment of Scale Impacts of Watershed Intervention
Subtitle of host publication	Assessing Hydrogeological and Bio-Physical Influences on Livelihoods
Publisher	Elsevier Ltd.
Pages	287-316
Number of pages	30
ISBN (Electronic)	9780128008461
ISBN (Print)	9780128000670
DOIs	https://doi.org/10.1016/B978-0-12-800067-0.00009-8
Publication status	Published - 2015

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Merritt, W., Patch, B., Reddy, V. R., Rout, S. K., & Syme, G. J. (2015). Modeling Livelihood Indicators and Household Resilience using Bayesian Networks. In Integrated Assessment of Scale Impacts of Watershed Intervention: Assessing Hydrogeological and Bio-Physical Influences on Livelihoods (pp. 287-316). Elsevier Ltd.. https://doi.org/10.1016/B978-0-12-800067-0.00009-8

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abstract = "The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.",

keywords = "Bayesian network, Capital strength, Integrated modeling, Livelihood capitals, Resilience",

author = "Wendy Merritt and Brendan Patch and Reddy, {V. Ratna} and Rout, {Sanjit Kumar} and Syme, {Geoffrey J.}",

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Modeling Livelihood Indicators and Household Resilience using Bayesian Networks. / Merritt, Wendy; Patch, Brendan; Reddy, V. Ratna et al.
Integrated Assessment of Scale Impacts of Watershed Intervention: Assessing Hydrogeological and Bio-Physical Influences on Livelihoods. Elsevier Ltd., 2015. p. 287-316.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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Modeling Livelihood Indicators and Household Resilience using Bayesian Networks

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