A regional-scale ecological risk framework for environmental flow evaluations

Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpo...
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Autor*in:	G. C. O'Brien [verfasserIn] C. Dickens [verfasserIn] E. Hines [verfasserIn] V. Wepener [verfasserIn] R. Stassen [verfasserIn] L. Quayle [verfasserIn] K. Fouchy [verfasserIn] J. MacKenzie [verfasserIn] P. M. Graham [verfasserIn] W. G. Landis [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Übergeordnetes Werk:	In: Hydrology and Earth System Sciences - Copernicus Publications, 2005, 22(2018), Seite 957-975
Übergeordnetes Werk:	volume:22 ; year:2018 ; pages:957-975

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.5194/hess-22-957-2018

Katalog-ID:	DOAJ075458306

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spelling	10.5194/hess-22-957-2018 doi (DE-627)DOAJ075458306 (DE-599)DOAJ84b6e6c4fe724be0983abdee5561045b DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 G. C. O'Brien verfasserin aut A regional-scale ecological risk framework for environmental flow evaluations 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements. Technology T Environmental technology. Sanitary engineering Geography. Anthropology. Recreation G Environmental sciences C. Dickens verfasserin aut E. Hines verfasserin aut V. Wepener verfasserin aut R. Stassen verfasserin aut L. Quayle verfasserin aut K. Fouchy verfasserin aut J. MacKenzie verfasserin aut P. M. Graham verfasserin aut W. G. Landis verfasserin aut In Hydrology and Earth System Sciences Copernicus Publications, 2005 22(2018), Seite 957-975 (DE-627)36277417X (DE-600)2100610-6 16077938 nnns volume:22 year:2018 pages:957-975 https://doi.org/10.5194/hess-22-957-2018 kostenfrei https://doaj.org/article/84b6e6c4fe724be0983abdee5561045b kostenfrei https://www.hydrol-earth-syst-sci.net/22/957/2018/hess-22-957-2018.pdf kostenfrei https://doaj.org/toc/1027-5606 Journal toc kostenfrei https://doaj.org/toc/1607-7938 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2018 957-975
allfields_unstemmed	10.5194/hess-22-957-2018 doi (DE-627)DOAJ075458306 (DE-599)DOAJ84b6e6c4fe724be0983abdee5561045b DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 G. C. O'Brien verfasserin aut A regional-scale ecological risk framework for environmental flow evaluations 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements. Technology T Environmental technology. Sanitary engineering Geography. Anthropology. Recreation G Environmental sciences C. Dickens verfasserin aut E. Hines verfasserin aut V. Wepener verfasserin aut R. Stassen verfasserin aut L. Quayle verfasserin aut K. Fouchy verfasserin aut J. MacKenzie verfasserin aut P. M. Graham verfasserin aut W. G. Landis verfasserin aut In Hydrology and Earth System Sciences Copernicus Publications, 2005 22(2018), Seite 957-975 (DE-627)36277417X (DE-600)2100610-6 16077938 nnns volume:22 year:2018 pages:957-975 https://doi.org/10.5194/hess-22-957-2018 kostenfrei https://doaj.org/article/84b6e6c4fe724be0983abdee5561045b kostenfrei https://www.hydrol-earth-syst-sci.net/22/957/2018/hess-22-957-2018.pdf kostenfrei https://doaj.org/toc/1027-5606 Journal toc kostenfrei https://doaj.org/toc/1607-7938 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2018 957-975
allfieldsGer	10.5194/hess-22-957-2018 doi (DE-627)DOAJ075458306 (DE-599)DOAJ84b6e6c4fe724be0983abdee5561045b DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 G. C. O'Brien verfasserin aut A regional-scale ecological risk framework for environmental flow evaluations 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements. Technology T Environmental technology. Sanitary engineering Geography. Anthropology. Recreation G Environmental sciences C. Dickens verfasserin aut E. Hines verfasserin aut V. Wepener verfasserin aut R. Stassen verfasserin aut L. Quayle verfasserin aut K. Fouchy verfasserin aut J. MacKenzie verfasserin aut P. M. Graham verfasserin aut W. G. Landis verfasserin aut In Hydrology and Earth System Sciences Copernicus Publications, 2005 22(2018), Seite 957-975 (DE-627)36277417X (DE-600)2100610-6 16077938 nnns volume:22 year:2018 pages:957-975 https://doi.org/10.5194/hess-22-957-2018 kostenfrei https://doaj.org/article/84b6e6c4fe724be0983abdee5561045b kostenfrei https://www.hydrol-earth-syst-sci.net/22/957/2018/hess-22-957-2018.pdf kostenfrei https://doaj.org/toc/1027-5606 Journal toc kostenfrei https://doaj.org/toc/1607-7938 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2018 957-975
allfieldsSound	10.5194/hess-22-957-2018 doi (DE-627)DOAJ075458306 (DE-599)DOAJ84b6e6c4fe724be0983abdee5561045b DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 G. C. O'Brien verfasserin aut A regional-scale ecological risk framework for environmental flow evaluations 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements. Technology T Environmental technology. Sanitary engineering Geography. Anthropology. Recreation G Environmental sciences C. Dickens verfasserin aut E. Hines verfasserin aut V. Wepener verfasserin aut R. Stassen verfasserin aut L. Quayle verfasserin aut K. Fouchy verfasserin aut J. MacKenzie verfasserin aut P. M. Graham verfasserin aut W. G. Landis verfasserin aut In Hydrology and Earth System Sciences Copernicus Publications, 2005 22(2018), Seite 957-975 (DE-627)36277417X (DE-600)2100610-6 16077938 nnns volume:22 year:2018 pages:957-975 https://doi.org/10.5194/hess-22-957-2018 kostenfrei https://doaj.org/article/84b6e6c4fe724be0983abdee5561045b kostenfrei https://www.hydrol-earth-syst-sci.net/22/957/2018/hess-22-957-2018.pdf kostenfrei https://doaj.org/toc/1027-5606 Journal toc kostenfrei https://doaj.org/toc/1607-7938 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2018 957-975
language	English
source	In Hydrology and Earth System Sciences 22(2018), Seite 957-975 volume:22 year:2018 pages:957-975
sourceStr	In Hydrology and Earth System Sciences 22(2018), Seite 957-975 volume:22 year:2018 pages:957-975
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Technology T Environmental technology. Sanitary engineering Geography. Anthropology. Recreation G Environmental sciences
isfreeaccess_bool	true
container_title	Hydrology and Earth System Sciences
authorswithroles_txt_mv	G. C. O'Brien @@aut@@ C. Dickens @@aut@@ E. Hines @@aut@@ V. Wepener @@aut@@ R. Stassen @@aut@@ L. Quayle @@aut@@ K. Fouchy @@aut@@ J. MacKenzie @@aut@@ P. M. Graham @@aut@@ W. G. Landis @@aut@@
publishDateDaySort_date	2018-01-01T00:00:00Z
hierarchy_top_id	36277417X
id	DOAJ075458306
language_de	englisch
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title	A regional-scale ecological risk framework for environmental flow evaluations
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title_sort	regional-scale ecological risk framework for environmental flow evaluations
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title_auth	A regional-scale ecological risk framework for environmental flow evaluations
abstract	Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements.
abstractGer	Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements.
abstract_unstemmed	Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements.
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title_short	A regional-scale ecological risk framework for environmental flow evaluations
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A regional-scale ecological risk framework for environmental flow evaluations

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Zugang & Verfügbarkeit

Vorhandene Bände

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