Developing a Bayesian network model for understanding river catchment resilience under future change scenarios
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
Developing a Bayesian network model for understanding river catchment resilience under future change scenarios ; day:21 ; month:07 ; year:2022 ; pages:1-35 ; extent:35
EGUsphere ; (21.07.2022), 1-35 (gesamt 35)
- Klassifikation
-
Natürliche Ressourcen, Energie und Umwelt
- Urheber
-
Adams, Kerr J.
Macleod, Christopher A. J.
Metzger, Marc J.
Melville, Nicola
Helliwell, Rachel C.
Pritchard, Jim
Glendell, Miriam
- DOI
-
10.5194/egusphere-2022-617
- URN
-
urn:nbn:de:101:1-2022072805245372240238
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:31 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Adams, Kerr J.
- Macleod, Christopher A. J.
- Metzger, Marc J.
- Melville, Nicola
- Helliwell, Rachel C.
- Pritchard, Jim
- Glendell, Miriam
Ähnliche Objekte (12)
Developing a Bayesian network model for understanding river catchment resilience under future change scenarios
Bayesian model evaluation for multiple scenarios
Identifying and testing adaptive management options to increase river catchment system resilience using a Bayesian Network model
Developing Resource use Scenarios for Europe
Designing multi-objective whole landscape scenarios at the catchment scale
Interactive elicitation of resilience scenarios in microservice architectures
Scenarios for Closed Basin Water Management in the Zayandeh Rud Catchment Area
Scenarios of developing private brands for food products
Developing and integrating scenarios in a virtual city
Drought adaptation and resilience in developing countries
Bayesian comparison of interacting modified holographic Ricci dark energy scenarios
Developing seasonal rainfall scenarios for food security early warning
Developing a Bayesian network model for understanding river catchment resilience under future change scenarios
Bayesian model evaluation for multiple scenarios
Identifying and testing adaptive management options to increase river catchment system resilience using a Bayesian Network model
Developing Resource use Scenarios for Europe
Designing multi-objective whole landscape scenarios at the catchment scale
Interactive elicitation of resilience scenarios in microservice architectures
Scenarios for Closed Basin Water Management in the Zayandeh Rud Catchment Area
Scenarios of developing private brands for food products
Developing and integrating scenarios in a virtual city
Drought adaptation and resilience in developing countries
Bayesian comparison of interacting modified holographic Ricci dark energy scenarios
Developing seasonal rainfall scenarios for food security early warning
Developing a Bayesian network model for understanding river catchment resilience under future change scenarios
Bayesian model evaluation for multiple scenarios
Identifying and testing adaptive management options to increase river catchment system resilience using a Bayesian Network model
Developing Resource use Scenarios for Europe
Designing multi-objective whole landscape scenarios at the catchment scale
Interactive elicitation of resilience scenarios in microservice architectures
Scenarios for Closed Basin Water Management in the Zayandeh Rud Catchment Area
Scenarios of developing private brands for food products
Developing and integrating scenarios in a virtual city
Drought adaptation and resilience in developing countries
Bayesian comparison of interacting modified holographic Ricci dark energy scenarios