Environmental decision support systems (EDSS) development – Challenges and best practices

McIntosh, Brian S.; Ascough, J. C.; Twery, Mark J.; Chew, Jimmie D.; Elmahdi, Amgad; Haase, Dagmar; Harou, Julien J.; Hepting, Daryl H.; Cuddy, Susan M.; Jakeman, Anthony J.; Chen, S.; Kassahun, Ayalew; Lautenbach, Sven; Matthews, Keith; Merritt, Wendy; Quinn, Nigel W.T.; Rodríguez-Roda, Ignasi; Sieber, Stefan; Stavenga, M.; Sulis, Andrea; Ticehurst, Jenifer Lyn; Völk, Martin; Wrobel, Markus; Delden, Hedwig van; Elsawah, Sondoss; Rizzoli, Andrea Emilio; Voinov, Alexey

doi:10.1016/j.envsoft.2011.09.009

Cited by 261 publications

(155 citation statements)

References 54 publications

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“…A more fundamental way to enhance citizens' participation to the science production process is through joint analysis of the obtained data, which requires platforms for visualization and communication of results, joint scenario and hypothesis formulation, as well as data processing and hypothesis testing. Many relevant concepts and technologies have recently been developed in the context of science-supported decision support mechanisms (e.g., Olsson and Andersson, 2007;McIntosh et al, 2011). Visualization and communication ensures that scientific content is comprehensible for the layperson, so that citizen scientists can directly gain from participation, which will also incentivise them for further engagement.…”

Section: Communication Of Results Scenario Building and Participatomentioning

confidence: 99%

Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development

et al. 2014

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The participation of the general public in the research design, data collection and interpretation process together with scientists is often referred to as citizen science. While citizen science itself has existed since the start of scientific practice, developments in sensing technology, data processing and visualization, and communication of ideas and results, are creating a wide range of new opportunities for public participation in scientific research. This paper reviews the state of citizen science in a hydrological context and explores the potential of citizen science to complement more traditional ways of scientific data collection and knowledge generation for hydrological sciences and water resources management. Although hydrological data collection often involves advanced technology, the advent of robust, cheap, and low-maintenance sensing equipment provides unprecedented opportunities for data collection in a citizen science context. These data have a significant potential to create new hydrological knowledge, especially in relation to the characterization of process heterogeneity, remote regions, and human impacts on the water cycle. However, the nature and quality of data collected in citizen science experiments is potentially very different from those of traditional monitoring networks. This poses challenges in terms of their processing, interpretation, and use, especially with regard to assimilation of traditional knowledge, the quantification of uncertainties, and their role in decision support. It also requires care in designing citizen science projects such that the generated data complement optimally other available knowledge. Lastly, using 4 case studies from remote mountain regions we reflect on the challenges and opportunities in the integration of hydrologically-oriented citizen science in water resources management, the role of scientific knowledge in the decision-making process, and the potential contestation to established community institutions posed by co-generation of new knowledge.

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Section: Communication Of Results Scenario Building and Participatomentioning

confidence: 99%

Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development

et al. 2014

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“…In response to these challenges, decision-support systems (DSS) informed by environmental flows science offer a range of potential benefits to water-resource management-such as by improving the transparency, objectivity, and efficiency of the decision-making process-but are currently not widely applied [17][18][19][20]. In practice, many water-resource decisions are made in an ad hoc fashion, using experience-based rather than evidence-based approaches [21,22].…”

Section: Needs and Challenges Of Decision-support Systems For Water-rmentioning

confidence: 99%

Putting Flow–Ecology Relationships into Practice: A Decision-Support System to Assess Fish Community Response to Water-Management Scenarios

Cartwright

Caldwell

Nebiker

et al. 2017

Water

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This paper presents a conceptual framework to operationalize flow-ecology relationships into decision-support systems of practical use to water-resource managers, who are commonly tasked with balancing multiple competing socioeconomic and environmental priorities. We illustrate this framework with a case study, whereby fish community responses to various water-management scenarios were predicted in a partially regulated river system at a local watershed scale. This case study simulates management scenarios based on interactive effects of dam operation protocols, withdrawals for municipal water supply, effluent discharges from wastewater treatment, and inter-basin water transfers. Modeled streamflow was integrated with flow-ecology relationships relating hydrologic departure from reference conditions to fish species richness, stratified by trophic, reproductive, and habitat characteristics. Adding a hypothetical new water-withdrawal site was predicted to increase the frequency of low-flow conditions with adverse effects for several fish groups. Imposition of new reservoir release requirements was predicted to enhance flow and fish species richness immediately downstream of the reservoir, but these effects were dissipated further downstream. The framework presented here can be used to translate flow-ecology relationships into evidence-based management by developing decision-support systems for conservation of riverine biodiversity while optimizing water availability for human use.

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“…Overall, the climatic changes that could be observed over the last decades had no significant negative impact yet on water resources management (Barthel 2011;Barthel et al 2011aBarthel et al , b, 2012. Mauser and Prasch (2016) compiled a comprehensive description of the study area, models, scenarios, and results.…”

Section: Modeling Framework and Study Areamentioning

confidence: 99%

“…It consists of 18 separate model components and a central framework that controls data exchange and temporal sequences (Barth et al 2004;Hennicker et al 2010). Please see Mauser and Prasch (2016) for a complete description of the framework and all models (Fig. 2).…”

Section: Modeling Framework and Study Areamentioning

confidence: 99%

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Global change impacts on the Upper Danube Catchment (Central Europe): a study of participatory modeling

et al. 2015

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Participatory modeling (PM) has become an essential concept in environmental impact assessment and planning in the field of water resources. In this paper, we focus on the use of PM to support the development of the integrated regional modeling system DANUBIA as a scientific concept to analyze the previously unknown impacts of global change, i.e., the combined effects of climate, demographic, economic, social and ecological change, on the Upper Danube Catchment (Germany). We use this case study to examine the specific conditions for PM in the field of complex integrated models on a regional scale. We describe the stepwise PM process and discuss the respective results, focusing on (1) the stakeholder dialogue's contribution in supporting the development of new, complex modeling systems, particularly on a regional scale, (2) conditions of stakeholder involvement in issues related to the distant future, such as climate change impacts on regional water availability, and (3) limitations of PM and scientists' motivation to carry out participatory research at all. We conclude that the PM process was not entirely successful in improving the scientific quality and practical applicability of the developed models because the process goals were manifold and overambitious, and the definition of the problem of ''global change impacts on a regional scale'' was too weak and uncertain to allow for a clear common objective of modelers and stakeholders. We claim that there is a lack of incentives for scientists, particularly natural scientists, to commit to PM activities.

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Environmental decision support systems (EDSS) development – Challenges and best practices

Cited by 261 publications

References 54 publications

Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development

Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development

Putting Flow–Ecology Relationships into Practice: A Decision-Support System to Assess Fish Community Response to Water-Management Scenarios

Global change impacts on the Upper Danube Catchment (Central Europe): a study of participatory modeling

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