Publications by authors named "H W Golden"

Connections between agricultural runoff and excess nitrogen in the Upper Mississippi River Basin are well-documented, as is the potential role of constructed wetlands in mitigating this surplus nitrogen. However, limited knowledge exists about the "best" placement of these wetlands for downstream nitrogen reductions within a whole watershed context as well as how far downstream these benefits are realized. In this study, we simulate the cumulative impacts of diverse wetland restoration scenarios on downstream nitrate reductions in different subbasins of the Raccoon River Watershed, Iowa, USA, and spatially trace their relative effects downstream.

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Article Synopsis
  • Understanding water quality in inland waters is challenging due to complex processes, expensive data collection, and limitations of traditional modeling methods.
  • Deep learning offers a promising solution by analyzing high-dimensional data, bridging gaps caused by data scarcity, and identifying key factors influencing water quality.
  • This Review discusses the strengths and weaknesses of deep learning compared to traditional methods, highlighting its potential for advancing knowledge in water-quality science and addressing future challenges.
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Continued large-scale public investment in declining ecosystems depends on demonstrations of "success". While the public conception of "success" often focuses on restoration to a pre-disturbance condition, the scientific community is more likely to measure success in terms of improved ecosystem health. Using a combination of literature review, workshops and expert solicitation we propose a generalized framework to improve ecosystem health in highly altered river basins by reducing ecosystem stressors, enhancing ecosystem processes and increasing ecosystem resilience.

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Climate change is projected to impact river, lake, and wetland hydrology, with global implications for the condition and productivity of aquatic ecosystems. We integrated Sentinel-1 and Sentinel-2 based algorithms to track monthly surface water extent (2017-2021) for 32 sites across the central United States (U.S.

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