dc.contributor.author |
Scharler, UM
|
|
dc.contributor.author |
Gerber, G
|
|
dc.contributor.author |
Taljaard, Susan
|
|
dc.contributor.author |
Mackay, F
|
|
dc.date.accessioned |
2024-07-22T06:39:50Z |
|
dc.date.available |
2024-07-22T06:39:50Z |
|
dc.date.issued |
2024-03 |
|
dc.identifier.citation |
Scharler, U., Gerber, G., Taljaard, S. & Mackay, F. 2024. 5.9 - Modelling estuaries in data-Poor environments. In <i>Treatise on Estuarine and Coastal Science. 2nd Edition</i>. S.l.: Elsevier. http://hdl.handle.net/10204/13725 . |
en_ZA |
dc.identifier.isbn |
978-0-08-087885-0 |
|
dc.identifier.uri |
https://doi.org/10.1016/B978-0-323-90798-9.00100-1
|
|
dc.identifier.uri |
http://hdl.handle.net/10204/13725
|
|
dc.description.abstract |
Models are inherently data-hungry for the construction, calibration, validation and predictive capacity that is demanded of models. In data-poor environments, a severe challenge to modelling is the lack of historic data, and present lack of sufficient monitoring programmes of important variables and number of estuarine ecosystems. This is largely due to lack of infrastructure, skills, political will, and monetary support. However, environmental challenges do not wait for adequate datasets to arrive to inform decision-making, and therefore different pathways to modelling that inform both research and management are needed. We present approaches to water quality, ecosystem modelling and climate change research in South African estuaries, as a representative of a data-poor environment. Such approaches aim to use available data in novel ways to inform research and decision-making, and identify data and information gaps. We propose that such methods be used in other data-poor areas with similar types of estuaries as South Africa and we provide recommendations how to construct, validate and use models and their outcomes. The communication of model uncertainty for research purposes and to decision-makers takes an important place in such endeavours. |
en_US |
dc.format |
Abstract |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Elsevier |
en_US |
dc.relation.uri |
https://www.sciencedirect.com/science/article/abs/pii/B9780323907989001001?via%3Dihub |
en_US |
dc.relation.uri |
https://www.sciencedirect.com/referencework/9780323910422/treatise-on-estuarine-and-coastal-science |
en_US |
dc.source |
Treatise on Estuarine and Coastal Science. 2nd Edition |
en_US |
dc.subject |
Estuarine science |
en_US |
dc.subject |
Coastal science |
en_US |
dc.subject |
Data-poor environments |
en_US |
dc.title |
5.9 - Modelling estuaries in data-poor environments |
en_US |
dc.type |
Book Chapter |
en_US |
dc.description.pages |
192-212 |
en_US |
dc.description.placeofpublication |
N/A |
en_US |
dc.description.note |
Copyright © 2024 Elsevier Inc. All rights reserved. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website: https://www.sciencedirect.com/referencework/9780323910422/treatise-on-estuarine-and-coastal-science |
en_US |
dc.description.cluster |
Smart Places |
en_US |
dc.description.impactarea |
Coastal Systems |
en_US |
dc.identifier.apacitation |
Scharler, U., Gerber, G., Taljaard, S., & Mackay, F. (2024). 5.9 - Modelling estuaries in data-Poor environments., <i>Treatise on Estuarine and Coastal Science. 2nd Edition</i> Elsevier. http://hdl.handle.net/10204/13725 |
en_ZA |
dc.identifier.chicagocitation |
Scharler, UM, G Gerber, Susan Taljaard, and F Mackay. "5.9 - Modelling estuaries in data-poor environments" In <i>TREATISE ON ESTUARINE AND COASTAL SCIENCE. 2ND EDITION</i>, n.p.: Elsevier. 2024. http://hdl.handle.net/10204/13725. |
en_ZA |
dc.identifier.vancouvercitation |
Scharler U, Gerber G, Taljaard S, Mackay F. 5.9 - Modelling estuaries in data-poor environments.. Treatise on Estuarine and Coastal Science. 2nd Edition. [place unknown]: Elsevier; 2024. [cited yyyy month dd]. http://hdl.handle.net/10204/13725. |
en_ZA |
dc.identifier.ris |
TY - Book Chapter
AU - Scharler, UM
AU - Gerber, G
AU - Taljaard, Susan
AU - Mackay, F
AB - Models are inherently data-hungry for the construction, calibration, validation and predictive capacity that is demanded of models. In data-poor environments, a severe challenge to modelling is the lack of historic data, and present lack of sufficient monitoring programmes of important variables and number of estuarine ecosystems. This is largely due to lack of infrastructure, skills, political will, and monetary support. However, environmental challenges do not wait for adequate datasets to arrive to inform decision-making, and therefore different pathways to modelling that inform both research and management are needed. We present approaches to water quality, ecosystem modelling and climate change research in South African estuaries, as a representative of a data-poor environment. Such approaches aim to use available data in novel ways to inform research and decision-making, and identify data and information gaps. We propose that such methods be used in other data-poor areas with similar types of estuaries as South Africa and we provide recommendations how to construct, validate and use models and their outcomes. The communication of model uncertainty for research purposes and to decision-makers takes an important place in such endeavours.
DA - 2024-03
DB - ResearchSpace
DP - CSIR
J1 - Treatise on Estuarine and Coastal Science. 2nd Edition
KW - Estuarine science
KW - Coastal science
KW - Data-poor environments
LK - https://researchspace.csir.co.za
PY - 2024
SM - 978-0-08-087885-0
T1 - 5.9 - Modelling estuaries in data-poor environments
TI - 5.9 - Modelling estuaries in data-poor environments
UR - http://hdl.handle.net/10204/13725
ER -
|
en_ZA |
dc.identifier.worklist |
27880 |
en_US |