Browsing by Author "Gardner, John"

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    Estimating the Value of Public Water Data
    (2017-06-22) Gardner, John; Doyle, Martin; Patterson, Lauren
    Public water data, such as river flow from stream gauges or precipitation from weather satellites, produce broad benefits at a cost to the general public. This paper presents a review of the academic literature on the costs and benefits of government investments in public water data. On the basis of 21 studies quantifying the costs and benefits of public water quantity data, it appears that the median benefit-cost ratio across different economic sectors and geographic regions is 4:1. But a great deal of uncertainty attends this number; very few studies empirically quantify or monetize the costs, the benefits, or both of water information with sound economic methods, and no studies have quantified the value of water quality information. This review is part of an ongoing effort by the Nicholas Institute of Environmental Policy Solutions at Duke University and the Aspen Institute to develop the foundations of an Internet of Water by quantifying the potential value of open and integrated public water data.
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    Rethinking Rivers: How Light, Lakes, and Sediment Vary Along the River Continuum
    (2018) Gardner, John

    This dissertation focuses on the riverine water column and the lentic (i.e. lake like) nature of rivers in the context of predominant themes in river science: spatial heterogeneity and scale. River science has developed many concepts to describe and understand the hydrologic, geomorphic, and ecological structure and function of rivers. While these core concepts largely grapple with spatial heterogeneity and scale, they have generally not conceptualized the water column as unit of study nor have they integrated lakes and rivers as one hydrologic system. Understanding the spatial heterogeneity and scaling patterns within the water column itself and how lakes fit into river networks will advance our understanding of geomorphic and ecological processes of entire networks.

    The study approach includes field campaigns using in-situ sensors, analysis of large data sets, and conceptual modeling. Chapter 2 develops an analytical model implemented with empirical data to find the location along a river where there is more sediment surface area in the water column than the benthic zone. Chapter 3 integrates flowpath and fixed-site measurement approaches to characterize the spatial and temporal scales of variability in water column light regimes. Chapter 4 analyzes large datasets to understand the scaling patterns of lake abundance, lake size, and lake spacing with river size across the conterminous US.

    Conclusions from this research have theoretical and practical implications. First, rivers larger than ~5th order had more sediment surface area in the water column than the benthic zone. This suggests material processing may occur largely within the water column in large rivers. Studying large rivers may therefore require different conceptual and methodological approaches, and it may be inappropriate to scale up measurements from small streams. Second, large rivers had an expanding and contracting photic volume over multiple temporal and spatial scales. Photo-reactive processes in the water column are therefore limited by the size of these light and dark zones and turbulent fluctuations along flowpaths through the river. Third, river networks are, in-fact, river-lake networks that have characteristic scaling patterns that describe lake abundance, size, and spacing. This suggests the default conceptual model of river networks should be river-lake networks.