High frequency data provide new insights into evaluating and modeling nitrogen retention in reservoirs

Xiangshen Kong (Co-auteur), Qing Zhan, Bertram Boehrer, Karsten Rinke

Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgave › Artikel › Wetenschappelijk › peer review

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@article{5f2fa0af257f4d51b0be60e299b8b734,

title = "High frequency data provide new insights into evaluating and modeling nitrogen retention in reservoirs",

keywords = "international",

author = "Xiangshen Kong and Qing Zhan and Bertram Boehrer and Karsten Rinke",

note = "6787, AqE, AKW; Data Archiving: data archived at The Rappbode Reservoir Observatory (not NIOO data)",

year = "2019",

doi = "10.1016/j.watres.2019.115017",

language = "English",

volume = "166",

journal = "Water Research",

issn = "0043-1354",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - High frequency data provide new insights into evaluating and modeling nitrogen retention in reservoirs

AU - Kong, Xiangshen

AU - Zhan, Qing

AU - Boehrer, Bertram

AU - Rinke, Karsten

N1 - 6787, AqE, AKW; Data Archiving: data archived at The Rappbode Reservoir Observatory (not NIOO data)

PY - 2019

Y1 - 2019

KW - international

U2 - 10.1016/j.watres.2019.115017

DO - 10.1016/j.watres.2019.115017

M3 - Article

SN - 0043-1354

VL - 166

JO - Water Research

JF - Water Research

M1 - 115017

ER -