Foundations for Decision Making

Jones, Roger; Patwardhan, Anand; Cohen, Stewart; Dessai, Suraje; Lammel, Annamaria; Lempert, Robert J.; Mirza, M. Monirul Qader; Storch, Hans von; Krauß, Werner

doi:10.1017/cbo9781107415379.007

“…Technical aspects such as how the scenario is represented in the model are also strongly biased by the modeler's decision and represent an additional source of uncertainty (Mahmoud et al, 2009). The communication of the potential uncertainties inherent in the developed scenarios and the boundaries of the explanatory power of an scenario ensemble is essential for the integrity of any impact study (Mahmoud et al, 2009;Jones et al, 2014).…”

Section: How To Attribute Subjectivity Inherent In the Scenariosmentioning

confidence: 99%

A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions

Schürz

¹

,

Hollosi

²

,

Matulla

³

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. Environmental modeling studies aim to infer the impacts on environmental variables that are caused by natural and human-induced changes in environmental systems. Changes in environmental systems are typically implemented as discrete scenarios in environmental models to simulate environmental variables under changing conditions. The scenario development of a model input usually involves several data sources and perhaps other models, which are potential sources of uncertainty. The setup and the parametrization of the implemented environmental model are additional sources of uncertainty for the simulation of environmental variables. Yet to draw well-informed conclusions from the model simulations it is essential to identify the dominant sources of uncertainty. In impact studies in two Austrian catchments the eco-hydrological model Soil and Water Assessment Tool (SWAT) was applied to simulate discharge and nitrate-nitrogen (NO3--N) loads under future changing conditions. For both catchments the SWAT model was set up with different spatial aggregations. Non-unique model parameter sets were identified that adequately reproduced observations of discharge and NO3--N loads. We developed scenarios of future changes for land use, point source emissions, and climate and implemented the scenario realizations in the different SWAT model setups with different model parametrizations, which resulted in 7000 combinations of scenarios and model setups for both catchments. With all model combinations we simulated daily discharge and NO3--N loads at the catchment outlets. The analysis of the 7000 generated model combinations of both case studies had two main goals: (i) to identify the dominant controls on the simulation of discharge and NO3--N loads in the two case studies and (ii) to assess how the considered inputs control the simulation of discharge and NO3--N loads. To assess the impact of the input scenarios, the model setup, and the parametrization on the simulation of discharge and NO3--N loads, we employed methods of global sensitivity analysis (GSA). The uncertainties in the simulation of discharge and NO3--N loads that resulted from the 7000 SWAT model combinations were evaluated visually. We present approaches for the visualization of the simulation uncertainties that support the diagnosis of how the analyzed inputs affected the simulation of discharge and NO3--N loads. Based on the GSA we identified climate change and the model parametrization as being the most influential model inputs for the simulation of discharge and NO3--N loads in both case studies. In contrast, the impact of the model setup on the simulation of discharge and NO3--N loads was low, and the changes in land use and point source emissions were found to have the lowest impact on the simulated discharge and NO3--N loads. The visual analysis of the uncertainty bands illustrated that the deviations in precipitation of the different climate scenarios to historic records dominated the changes in simulation outputs, while the differences in air temperature showed no considerable impact.

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“…Moreover, because Indigenous knowledge systems and local knowledge systems are fundamentally shaped by different worldviews, cosmologies, and ontologies that posit distinct ways of relating with humanity and nature, these knowledge systems can play a fundamental role in providing alternatives for new forms of governance and more-than-human values (O’Brien and Sygna 2013 ; Lam et al 2020 ; Nightingale et al 2020 ; Chakraborty and Sherpa 2021 ; Vogel and O’Brien 2021 ). These alternatives can lead to just partnerships based on mutual recognition and respect between the peoples, communities, and societies of knowledge holders (Adger et al 2013 ; IPCC 2014 ; Jones et al 2014 ; Yeh 2016 ; Klenk et al 2017 ; Petzold et al 2020 ).…”

Section: Transformative Changementioning

confidence: 99%

Placing diverse knowledge systems at the core of transformative climate research

Orlove¹,

Sherpa²,

Dawson³

et al. 2023

Ambio

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We argue that solutions-based research must avoid treating climate change as a merely technical problem, recognizing instead that it is symptomatic of the history of European and North American colonialism. It must therefore be addressed by decolonizing the research process and transforming relations between scientific expertise and the knowledge systems of Indigenous Peoples and of local communities. Partnership across diverse knowledge systems can be a path to transformative change only if those systems are respected in their entirety, as indivisible cultural wholes of knowledge, practices, values, and worldviews. This argument grounds our specific recommendations for governance at the local, national, and international scales. As concrete mechanisms to guide collaboration across knowledge systems, we propose a set of instruments based on the principles of consent, intellectual and cultural autonomy, and justice. We recommend these instruments as tools to ensure that collaborations across knowledge systems embody just partnerships in support of a decolonial transformation of relations between human communities and between humanity and the more-than-human world.

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“…Technical aspects such as how the scenario is represented in the model are also strongly biased by the modelers decision and represent an additional source of uncertainty (Mahmoud et al, 2009). The communication of the potential uncertainties inherent in the developed scenarios and the boundaries of the explanatory power of an scenario ensemble is essential for the integrity of any impact study (Mahmoud et al, 2009;Jones et al, 2014).…”

Section: How To Attribute Subjectivity Inherent In the Scenariosmentioning

confidence: 99%

A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions

Schürz¹,

Hollosi²,

Matulla³

et al. 2018

Preprint

0

View full text Add to dashboard Cite

Abstract. Environmental modeling studies aim to infer the impacts on environmental variables that are caused by natural and human-induced changes in environmental systems. Changes in environmental systems are typically implemented as discrete scenarios in environmental models to simulate environmental variables under changing conditions. The scenario development of a model input usually involves several data sources and perhaps other models, that are potential sources of uncertainty. The setup and the parametrization of the implemented environmental model are additional sources of uncertainty for the simulation 5 of environmental variables. Yet, to draw well-informed conclusions from the model simulations it is essential to identify the dominant sources of uncertainty.In two Austrian impact studies the eco-hydrological model Soil and Water Assessment Tool (SWAT) was applied to simulate discharge and nitrate-nitrogen (NO In both case studies we employed global sensitivity analysis (GSA) to identify the impact of the scenario inputs, the model 15 setup and the parametrization on the simulation of discharge and NO − 3 -N loads. We accompanied the GSA with a visual analysis of the simulation outputs and their associated uncertainties that resulted from the simulations of the 7000 SWAT model combinations. We present visualizations of the results of the GSA and the simulation uncertainty bands that proved to be powerful diagnostic tools in this study. Based on the GSA we identified climate change and the model parametrization to be the most sensitive model inputs for the simulation of discharge and NO − 3 -N loads in both case studies. In contrast, the impact of the model setup on the simulation of discharge and NO − 3 -N loads was low and the changes in land use and point source emissions were found to have the least impact on the simulated discharge and NO − 3 -N loads. Additionally, the visual analysis of the uncertainty bands illustrated that the precipitation of the climate scenarios dominated the changes in simulation outputs, rather than changes in air temperature 5 in both case studies.

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Foundations for Decision Making

Cited by 13 publications

References 277 publications

A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions

A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions

Placing diverse knowledge systems at the core of transformative climate research

A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions

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