Modeling the Model: Adapting to Data Uncertainties in Watershed Management

Authors: Jeremy Trombley*,
Topics: Water Resources and Hydrology
Keywords: Computer modeling, data uncertainty, Chesapeake Bay
Session Type: Paper
Day: 4/7/2019
Start / End Time: 3:55 PM / 5:35 PM
Room: Marshall West, Marriott, Mezzanine Level
Presentation File: No File Uploaded

Environmental management staff must often navigate a complex set of hierarchies, funding structures, and public interests. In some cases, access to and engagement with data infrastructures, despite being offered as “decision support tools,” can add a layer of uncertainty to these navigations. In these situations, management staff must find ways to make sense of data tools that can, themselves, be complex and opaque. In this presentation, I draw upon ethnographic research to examine the ways that management staff in the Chesapeake Bay watershed have adapted to the uncertainties produced by a complex computational model that is used to identify, track, and predict the effects of nutrient management on the landscape. Management staff must conform to the logic of the model and develop nutrient reduction plans that demonstrate effectiveness within it. But the effects of different management practices in the model can be as unpredictable as their effects on the actual watershed. As a result, a suite of tools, known as the Assessment Scenario Tools or AST suite, was created to simulate the model itself in order to assist management staff in the planning process. Eventually, the AST models were folded into the original model to provide a guaranteed agreement between the two. Here, I explore the history behind the development of the AST suite, and discuss some implications for watershed management. Furthermore, I seek to outline a framework for understanding how management staff adapt to data uncertainties and the effects of these adaptation strategies on the management process.

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