Scale dependence of controls on groundwater vulnerability in the water–energy–food nexus, California Coastal Basin aquifer system. Gurdak, J. J., Geyer, G. E., Nanus, L., Taniguchi, M., & Corona, C. R. Journal of Hydrology: Regional Studies, 11:126–138, June, 2017. Paper doi abstract bibtex The Coastal California basin aquifer system (CCB), USA. Understanding the controls on nonpoint source (NPS) nitrate (NO3−) contamination in groundwater is motivated by the widespread detection of NO3−, implications for human health and aquatic ecosystems, groundwater sustainability, and a growing realization that such understanding across spatial scales promotes management and policy choices that optimize the Water–Energy–Food (WEF) Nexus. In the CCB, the conflicts in the WEF Nexus are apparent because of intensive agricultural practices that have contributed to chronic NO3− loading to groundwater. We evaluate the scale-dependent relations among source, transport, and attenuation (STA) factors that control NPS NO3− contamination in recently recharged CCB groundwater. Logistic regression models are presented for sub-regional and regional model domains. Dissolved oxygen (DO) (attenuation) in groundwater is often the most significant STA factor in all model domains, indicating that DO is an important, scale-invariant factor controlling NPS NO3− contamination. Farm fertilizer (source) is also a significant scale-invariant factor, while many of the transport factors are scale-dependent factors. We present vulnerability maps that illustrate the spatial patterns of predicted probability of detected elevated NO3−. Findings here improve knowledge about the scale dependence of STA factors, which help decision makers develop best management strategies and policies that advances groundwater sustainability and optimizes the WEF Nexus.
@article{gurdak_scale_2017,
series = {Water, energy, and food nexus in the {Asia}-{Pacific} region},
title = {Scale dependence of controls on groundwater vulnerability in the water–energy–food nexus, {California} {Coastal} {Basin} aquifer system},
volume = {11},
issn = {2214-5818},
url = {http://www.sciencedirect.com/science/article/pii/S2214581816000057},
doi = {10.1016/j.ejrh.2016.01.002},
abstract = {The Coastal California basin aquifer system (CCB), USA. Understanding the controls on nonpoint source (NPS) nitrate (NO3−) contamination in groundwater is motivated by the widespread detection of NO3−, implications for human health and aquatic ecosystems, groundwater sustainability, and a growing realization that such understanding across spatial scales promotes management and policy choices that optimize the Water–Energy–Food (WEF) Nexus. In the CCB, the conflicts in the WEF Nexus are apparent because of intensive agricultural practices that have contributed to chronic NO3− loading to groundwater. We evaluate the scale-dependent relations among source, transport, and attenuation (STA) factors that control NPS NO3− contamination in recently recharged CCB groundwater. Logistic regression models are presented for sub-regional and regional model domains. Dissolved oxygen (DO) (attenuation) in groundwater is often the most significant STA factor in all model domains, indicating that DO is an important, scale-invariant factor controlling NPS NO3− contamination. Farm fertilizer (source) is also a significant scale-invariant factor, while many of the transport factors are scale-dependent factors. We present vulnerability maps that illustrate the spatial patterns of predicted probability of detected elevated NO3−. Findings here improve knowledge about the scale dependence of STA factors, which help decision makers develop best management strategies and policies that advances groundwater sustainability and optimizes the WEF Nexus.},
urldate = {2017-08-11TZ},
journal = {Journal of Hydrology: Regional Studies},
author = {Gurdak, Jason J. and Geyer, Gabriela E. and Nanus, Leora and Taniguchi, Makoto and Corona, Claudia R.},
month = jun,
year = {2017},
keywords = {Contamination, Groundwater, Nitrate, Water–energy–food nexus},
pages = {126--138}
}
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