Bayesian Network Applications for Sustainable Holistic Water Resources Management : Modeling Opportunities for South Africa
(2022) In Risk Analysis 42(6). p.1346-1364- Abstract
Anthropogenic transformation of land globally is threatening water resources in terms of quality and availability. Managing water resources to ensure sustainable utilization is important for a semiarid country such as South Africa. Bayesian networks (BNs) are probabilistic graphical models that have been applied globally to a range of water resources management studies; however, there has been very limited application of BNs to similar studies in South Africa. This article explores the benefits and challenges of BN application in the context of water resources management, specifically in relation to South Africa. A brief overview describes BNs, followed by details of some of the possible opportunities for BNs to benefit water resources... (More)
Anthropogenic transformation of land globally is threatening water resources in terms of quality and availability. Managing water resources to ensure sustainable utilization is important for a semiarid country such as South Africa. Bayesian networks (BNs) are probabilistic graphical models that have been applied globally to a range of water resources management studies; however, there has been very limited application of BNs to similar studies in South Africa. This article explores the benefits and challenges of BN application in the context of water resources management, specifically in relation to South Africa. A brief overview describes BNs, followed by details of some of the possible opportunities for BNs to benefit water resources management. These include the ability to use quantitative and qualitative information, data, and expert knowledge. BN models can be integrated into geographic information systems and predict impact of ecosystem services and sustainability indicators. With additional data and information, BNs can be updated, allowing for integration into an adaptive management process. Challenges in the application of BNs include oversimplification of complex systems, constraints of BNs with categorical nodes for continuous variables, unclear use of expert knowledge, and treatment of uncertainty. BNs have tremendous potential to guide decision making by providing a holistic approach to water resources management.
(Less)
- author
- Govender, Indrani Hazel ; Sahlin, Ullrika LU and O'Brien, Gordon C.
- organization
- publishing date
- 2022
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Bayesian networks, South Africa, water resources
- in
- Risk Analysis
- volume
- 42
- issue
- 6
- pages
- 19 pages
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- scopus:85111888599
- pmid:34342043
- ISSN
- 0272-4332
- DOI
- 10.1111/risa.13798
- language
- English
- LU publication?
- yes
- additional info
- Funding Information: This work was funded by a grant from the National Research Foundation (grant number 116760), South Africa. The views in this article are those of the authors and do not represent those of the National Research Foundation. U.S. was supported by the Swedish Research Council FORMAS through the strategic research environment Biodiversity and Ecosystem Services in Changing Climate (BECC). The authors would like to thank the reviewers for their constructive comments that helped with a marked improvement in this publication. Publisher Copyright: © 2020 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
- id
- 5cdaf911-75b9-4e8a-bc88-131c590f1a84
- date added to LUP
- 2021-08-19 15:31:10
- date last changed
- 2024-04-20 09:43:57
@article{5cdaf911-75b9-4e8a-bc88-131c590f1a84,
abstract = {{<p>Anthropogenic transformation of land globally is threatening water resources in terms of quality and availability. Managing water resources to ensure sustainable utilization is important for a semiarid country such as South Africa. Bayesian networks (BNs) are probabilistic graphical models that have been applied globally to a range of water resources management studies; however, there has been very limited application of BNs to similar studies in South Africa. This article explores the benefits and challenges of BN application in the context of water resources management, specifically in relation to South Africa. A brief overview describes BNs, followed by details of some of the possible opportunities for BNs to benefit water resources management. These include the ability to use quantitative and qualitative information, data, and expert knowledge. BN models can be integrated into geographic information systems and predict impact of ecosystem services and sustainability indicators. With additional data and information, BNs can be updated, allowing for integration into an adaptive management process. Challenges in the application of BNs include oversimplification of complex systems, constraints of BNs with categorical nodes for continuous variables, unclear use of expert knowledge, and treatment of uncertainty. BNs have tremendous potential to guide decision making by providing a holistic approach to water resources management.</p>}},
author = {{Govender, Indrani Hazel and Sahlin, Ullrika and O'Brien, Gordon C.}},
issn = {{0272-4332}},
keywords = {{Bayesian networks; South Africa; water resources}},
language = {{eng}},
number = {{6}},
pages = {{1346--1364}},
publisher = {{John Wiley & Sons Inc.}},
series = {{Risk Analysis}},
title = {{Bayesian Network Applications for Sustainable Holistic Water Resources Management : Modeling Opportunities for South Africa}},
url = {{http://dx.doi.org/10.1111/risa.13798}},
doi = {{10.1111/risa.13798}},
volume = {{42}},
year = {{2022}},
}