Synoptic Sampling to Determine Distributed Groundwater-Surface Water Nitrate Loading and Removal Potential Along a Lowland River. Pai, H., Villamizar, S. R., & Harmon, T. C. Water Resources Research, 53(11):9479–9495, November, 2017.
Synoptic Sampling to Determine Distributed Groundwater-Surface Water Nitrate Loading and Removal Potential Along a Lowland River [link]Paper  doi  abstract   bibtex   
Delineating pollutant reactive transport pathways that connect local land use patterns to surface water is an important goal. This work illustrates high-resolution river mapping of salinity or specific conductance (SC) and nitrate ( ) as a potential part of achieving this goal. We observed longitudinal river SC and nitrate distributions using high-resolution synoptic in situ sensing along the lower Merced River (38 river km) in Central California (USA) from 2010 to 2012. We calibrated a distributed groundwater-surface water (GW-SW) discharge model for a conservative solute using 13 synoptic SC sampling events at flows ranging from 1.3 to 31.6 m3 s−1. Nitrogen loads ranged from 0.3 to 1.6 kg N d−1 and were greater following an extended high flow period during a wet winter. Applying the distributed GW-SW discharge estimates to a simplistic reactive nitrate transport model, the model reproduced observed river nitrate distribution well (RRMSE = 5–21%), with dimensionless watershed-averaged nitrate removal (kt) ranging from 0 to 0.43. Estimates were uncertain due to GW nitrate data variability, but the resulting range was consistent with prior removal estimates. At the segment scale, estimated GW-SW nitrate loading ranged from 0 to 17 g s−1 km−1. Local loading peaked near the middle of the study reach, a location that coincides with a shallow clay lens and with confined animal feed operations in close proximity to the river. Overall, the results demonstrate the potential for high-resolution synoptic monitoring to support GW-SW modeling efforts aimed at understanding and managing nonpoint source pollution.
@article{pai_synoptic_2017,
	title = {Synoptic {Sampling} to {Determine} {Distributed} {Groundwater}-{Surface} {Water} {Nitrate} {Loading} and {Removal} {Potential} {Along} a {Lowland} {River}},
	volume = {53},
	copyright = {© 2017. American Geophysical Union. All Rights Reserved.},
	issn = {1944-7973},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017WR020677},
	doi = {10.1002/2017WR020677},
	abstract = {Delineating pollutant reactive transport pathways that connect local land use patterns to surface water is an important goal. This work illustrates high-resolution river mapping of salinity or specific conductance (SC) and nitrate ( ) as a potential part of achieving this goal. We observed longitudinal river SC and nitrate distributions using high-resolution synoptic in situ sensing along the lower Merced River (38 river km) in Central California (USA) from 2010 to 2012. We calibrated a distributed groundwater-surface water (GW-SW) discharge model for a conservative solute using 13 synoptic SC sampling events at flows ranging from 1.3 to 31.6 m3 s−1. Nitrogen loads ranged from 0.3 to 1.6 kg N d−1 and were greater following an extended high flow period during a wet winter. Applying the distributed GW-SW discharge estimates to a simplistic reactive nitrate transport model, the model reproduced observed river nitrate distribution well (RRMSE = 5–21\%), with dimensionless watershed-averaged nitrate removal (kt) ranging from 0 to 0.43. Estimates were uncertain due to GW nitrate data variability, but the resulting range was consistent with prior removal estimates. At the segment scale, estimated GW-SW nitrate loading ranged from 0 to 17 g s−1 km−1. Local loading peaked near the middle of the study reach, a location that coincides with a shallow clay lens and with confined animal feed operations in close proximity to the river. Overall, the results demonstrate the potential for high-resolution synoptic monitoring to support GW-SW modeling efforts aimed at understanding and managing nonpoint source pollution.},
	language = {en},
	number = {11},
	urldate = {2018-10-10},
	journal = {Water Resources Research},
	author = {Pai, Henry and Villamizar, Sandra R. and Harmon, Thomas C.},
	month = nov,
	year = {2017},
	keywords = {nitrate, river},
	pages = {9479--9495}
}

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