From ad-hoc modelling to strategic infrastructure: A manifesto for model management

Arnold, Thorsten; Guillaume, Joseph H. A.; Lahtinen, Tuomas J.; Vervoort, W.

doi:10.1016/j.envsoft.2019.104563

Cited by 9 publications

(11 citation statements)

References 71 publications

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“…Although the number of steps and activities conducted may differ depending on purpose and Art. 9(1) page 18 of 28 Iwanaga et al: Treatment of scale in socio-environmental systems modeling conceptualization of the cycle (Boehm, 1986;Jakeman et al, 2006;Pianosi et al, 2016;Badham et al, 2019;Arnold et al, 2020;Zare et al, 2021), each step is intended to be revisited as often as needed to incorporate newly discovered or available knowledge, or ideas generated on deep reflection, as "[t]he first model is rarely the best model" (Sterling et al, 2019). It may at times be necessary to abandon an iteration and start over.…”

Section: Embrace Change and Reflect Throughout The Iterative Modeling Cyclementioning

confidence: 99%

Toward a complete interdisciplinary treatment of scale

Iwanaga

Wang

Koralewski

et al. 2021

Elementa: Science of the Anthropocene

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The pathways taken throughout any model-based process are undoubtedly influenced by the modeling team involved and the decision choices they make. For interconnected socioenvironmental systems (SES), such teams are increasingly interdisciplinary to enable a more expansive and holistic treatment that captures the purpose, the relevant disciplines and sectors, and other contextual settings. In practice, such interdisciplinarity increases the scope of what is considered, thereby increasing choices around model complexity and their effects on uncertainty. Nonetheless, the consideration of scale issues is one critical lens through which to view and question decision choices in the modeling cycle. But separation between team members, both geographically and by discipline, can make the scales involved more arduous to conceptualize, discuss, and treat. In this article, the practices, decisions, and workflow that influence the consideration of scale in SESs modeling are explored through reflexive accounts of two case studies. Through this process and an appreciation of past literature, we draw out several lessons under the following themes: (1) the fostering of collaborative learning and reflection, (2) documenting and justifying the rationale for modeling scale choices, some of which can be equally plausible (a perfect model is not possible), (3) acknowledging that causality is defined subjectively, (4) embracing change and reflection throughout the iterative modeling cycle, and (5) regularly testing the model integration to draw out issues that would otherwise be unnoticeable.

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Section: Embrace Change and Reflect Throughout The Iterative Modeling Cyclementioning

confidence: 99%

Toward a complete interdisciplinary treatment of scale

Iwanaga

Wang

Koralewski

et al. 2021

Elementa: Science of the Anthropocene

View full text Add to dashboard Cite

show abstract

Section: Cultivating and Applying Procedural Knowledge For Modeling Processesmentioning

confidence: 99%

“…Procedural knowledge encompasses operational guidelines that manage modeling workflows, as well as knowledge management strategies and supporting tools and cyberinfrastructure. It is an emerging issue related to how modeling processes can better be governed and supported within organizations ( Arnold, 2013 ; Arnold et al, 2020 ). Organizations and the water quality modeling community as a whole can focus on improving human capacity and the knowledge base, the operational framework surrounding modeling activities (e.g., guidelines, standards, model management, and technical support services), and the cyberinfrastructure and tools available for modeling (e.g., model codes, data management and analysis tools, workflow tools, and computational resources).…”

Section: Ways Forwardmentioning

confidence: 99%

“…Real-time monitoring and analysis frameworks ( Wong & Kerkez, 2016 ) and spatial workflow environments ( Nielsen et al, 2017 ; Zhang, Bu, et al, 2017 ) demonstrate technical innovations that still need to be operationalized by agencies. Yet, these innovations in software tools should not distract from the need to build rigorous operational protocols that simplify technical procedures and ensure access to relevant knowledge in a timely manner ( Argent et al, 2016 ; Arnold et al, 2020 ).…”

Section: Ways Forwardmentioning

confidence: 99%

“…To ensure access to knowledge, ensure transparency, and enhance reproducibility, intellectual property rights to software tools must be managed appropriately ( Arnold et al, 2020 ). Several open source codes are now available for water quality and aquatic ecosystem prediction ( Fu et al, 2019 ; Hipsey et al, 2015 ).…”

Section: Ways Forwardmentioning

confidence: 99%

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Modeling Water Quality in Watersheds: From Here to the Next Generation

Horsburgh

Jakeman

et al. 2020

Water Resources Research

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In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in-stream water quality and process interactions, soil health and land management, and (peri-)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches, and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

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An overview of groundwater response to a changing climate in the Murray-Darling Basin, Australia: potential implications for the basin system and opportunities for management

Doble,

Walker,

Crosbie

et al. 2023

Hydrogeol J

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The Murray-Darling Basin (MDB) is a highly allocated and regulated, mostly semiarid basin in south-eastern Australia, where groundwater is a significant water resource. Future climate predictions for the MDB include an expansion of arid and semiarid climate zones to replace temperate areas. The impacts of climate change are already evident in declining groundwater levels and changes in the connection status between rivers and groundwater, and modelling has predicted a further reduction in future groundwater recharge and ongoing declines in groundwater levels. This is predicted to further reduce river baseflow and negatively impact groundwater-dependent ecosystems (GDEs), and these system responses to a changing climate and extreme events are complex and not always well understood. This report provides an overview of the current state of knowledge of groundwater response to a changing climate for the MDB, and outlines challenges and opportunities for future groundwater research and management. Opportunities for the region include improving data systems and acquisition through automation and novel data sources, and growing capability in integrated, risk-based modelling. Quantification of the groundwater/surface-water connection response to declining groundwater levels, and assessing GDE water requirements and thresholds, would enable identification of vulnerable systems and inform the development of metrics for adaptive management, improving the ability to respond to climate extremes. There is potential to adapt policy to support active management of groundwater where required, including conjunctive use and water banking. Improving knowledge sharing and water literacy, including understanding community values of groundwater and GDEs, would support future decision-making.

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From ad-hoc modelling to strategic infrastructure: A manifesto for model management

Cited by 9 publications

References 71 publications

Toward a complete interdisciplinary treatment of scale

Toward a complete interdisciplinary treatment of scale

Modeling Water Quality in Watersheds: From Here to the Next Generation

An overview of groundwater response to a changing climate in the Murray-Darling Basin, Australia: potential implications for the basin system and opportunities for management

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