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Linking the Scales of Scientific inquiry and Watershed Management: A Focus on Green Infrastructure
Citation:
Golden, H. AND N. Hoghooghi. Linking the Scales of Scientific inquiry and Watershed Management: A Focus on Green Infrastructure. 2017 AGU Fall Meeting, New Orleans, LA, December 11 - 15, 2017.
Impact/Purpose:
2017 AGU Fall meeting presentation at Advances in Green Infrastructure Development: Benefits from Point to Watershed Scale.
Description:
Urbanization modifies the hydrologic cycle, resulting in potentially deleterious downstream water quality and quantity effects. However, the cumulative interacting effects of water storage, transport, and biogeochemical processes occurring within other land cover and use types of the same watershed can render management explicitly targeted to limit the negative outcomes from urbanization ineffective. For example, evidence indicates that green infrastructure, or low impact development (LID), practices can attenuate the adverse water quality and quantity effects of urbanizing systems. However, the research providing this evidence has been conducted at local scales (e.g., plots, small homogeneous urban catchments) that isolate the measurable effects of such approaches. Hence, a distinct disconnect exists between the scale of scientific inquiry and the scale of management and decision-making practices. Here we explore the oft-discussed yet rarely directly addressed scientific and management conundrum: How do we scale our well-documented scientific knowledge of the water quantity and quality responses to LID practices measured and modeled at local scales to that of “actual” management scales? We begin by focusing on LID practices in mixed land cover watersheds. We present key concepts that have emerged from LID research at the local scale, considerations for scaling this research to watersheds, recent advances and findings in scaling the effects of LID practices on water quality and quantity at watershed scales, and the use of combined novel measurements and models for these scaling efforts. We underscore these concepts with a case study that evaluates the effects of three LID practices using simulation modeling across a mixed land cover watershed. This synthesis and case study highlight that scientists are making progress toward successfully tailoring fundamental research questions with decision-making goals in mind, yet we still have a long road ahead.
