Quantifying watershed-scale groundwater loading and in-stream fate of nitrate using high-frequency water quality data

被引:66
|
作者
Miller, Matthew P. [1 ]
Tesoriero, Anthony J. [2 ]
Capel, Paul D. [3 ]
Pellerin, Brian A. [4 ]
Hyer, Kenneth E. [5 ]
Burns, Douglas A. [6 ]
机构
[1] US Geol Survey, Salt Lake City, UT USA
[2] US Geol Survey, Portland, OR USA
[3] US Geol Survey, Minneapolis, MN USA
[4] US Geol Survey, Sacramento, CA USA
[5] US Geol Survey, Richmond, VA USA
[6] US Geol Survey, Troy, NY USA
关键词
CONTERMINOUS UNITED-STATES; CHESAPEAKE BAY; BASE-FLOW; NITROGEN-CYCLE; ORGANIC-CARBON; PHOSPHORUS; DENITRIFICATION; ECOSYSTEMS; TRANSPORT; RIVERS;
D O I
10.1002/2015WR017753
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We describe a new approach that couples hydrograph separation with high-frequency nitrate data to quantify time-variable groundwater and runoff loading of nitrate to streams, and the net in-stream fate of nitrate at the watershed scale. The approach was applied at three sites spanning gradients in watershed size and land use in the Chesapeake Bay watershed. Results indicate that 58-73% of the annual nitrate load to the streams was groundwater-discharged nitrate. Average annual first-order nitrate loss rate constants (k) were similar to those reported in both modeling and in-stream process-based studies, and were greater at the small streams (0.06 and 0.22 day(-1)) than at the large river (0.05 day(-1)), but 11% of the annual loads were retained/lost in the small streams, compared with 23% in the large river. Larger streambed area to water volume ratios in small streams results in greater loss rates, but shorter residence times in small streams result in a smaller fraction of nitrate loads being removed than in larger streams. A seasonal evaluation of k values suggests that nitrate was retained/lost at varying rates during the growing season. Consistent with previous studies, streamflow and nitrate concentrations were inversely related to k. This new approach for interpreting high-frequency nitrate data and the associated findings furthers our ability to understand, predict, and mitigate nitrate impacts on streams and receiving waters by providing insights into temporal nitrate dynamics that would be difficult to obtain using traditional field-based studies.
引用
收藏
页码:330 / 347
页数:18
相关论文
共 50 条
  • [31] Predicting sediment and nutrient concentrations from high-frequency water-quality data
    Leigh, Catherine
    Kandanaarachchi, Sevvandi
    McGree, James M.
    Hyndman, Rob J.
    Alsibai, Omar
    Mengersen, Kerrie
    Peterson, Erin E.
    PLOS ONE, 2019, 14 (08):
  • [32] High-frequency precipitation and stream water quality time series from Plynlimon, Wales: an openly accessible data resource spanning the periodic table
    Neal, Colin
    Reynolds, Brian
    Kirchner, James W.
    Rowland, Phil
    Norris, Dave
    Sleep, Darren
    Lawlor, Alan
    Woods, Clive
    Thacker, Sarah
    Guyatt, Hayley
    Vincent, Colin
    Lehto, Kathryn
    Grant, Simon
    Williams, Jeremy
    Neal, Margaret
    Wickham, Heather
    Harman, Sarah
    Armstrong, Linda
    HYDROLOGICAL PROCESSES, 2013, 27 (17) : 2531 - 2539
  • [33] Identifying multiple stressor controls on phytoplankton dynamics in the River Thames (UK) using high-frequency water quality data
    Bowes, M. J.
    Loewenthal, M.
    Read, D. S.
    Hutchins, M. G.
    Prudhomme, C.
    Armstrong, L. K.
    Harman, S. A.
    Wickham, H. D.
    Gozzard, E.
    Carvalho, L.
    SCIENCE OF THE TOTAL ENVIRONMENT, 2016, 569 : 1489 - 1499
  • [34] The effect of sampling frequency and strategy on water quality modelling driven by high-frequency monitoring data in a boreal catchment
    Piniewski, Mikolaj
    Marcinkowski, Pawel
    Koskiaho, Jari
    Tattari, Sirkka
    JOURNAL OF HYDROLOGY, 2019, 579
  • [35] Understanding links between water-quality variables and nitrate concentration in freshwater streams using high frequency sensor data
    Kermorvant, Claire
    Liquet, Benoit
    Litt, Guy
    Mengersen, Kerrie
    Peterson, Erin E.
    Hyndman, Rob J.
    Jones Jr, Jeremy B.
    Leigh, Catherine
    PLOS ONE, 2023, 18 (06):
  • [36] Processes and mechanisms controlling nitrate dynamics in an artificially drained field: Insights from high-frequency water quality measurements
    Liu, Wenlong
    Youssef, Mohamed A.
    Birgand, Francois P.
    Chescheir, George M.
    Tian, Shiying
    Maxwell, Bryan M.
    AGRICULTURAL WATER MANAGEMENT, 2020, 232 (232)
  • [37] Evaluation of Chemcatcher? passive samplers for pesticide monitoring using high-frequency catchment scale data
    Farrow, Luke G.
    Morton, Phoebe A.
    Cassidy, Rachel
    Floyd, Stewart
    McRoberts, W. Colin
    Doody, Donnacha G.
    Jordan, Philip
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2022, 324
  • [38] Identifying the impact of Energy Base Water Project on groundwater using high-frequency monitoring data in the Subei Lake basin, Ordos, Northwestern China
    Liu, Fei
    Song, Xianfang
    Yang, Lihu
    Han, Dongmei
    Zhang, Yinghua
    Ma, Ying
    Bu, Hongmei
    HYDROLOGY RESEARCH, 2017, 48 (01): : 160 - 176
  • [39] Quantifying hydrological responses to monsoon-controlled precipitation across the soil-groundwater-stream continuum with long-term high-frequency hydrometric monitoring
    Dai, Xin
    Xie, Yueqing
    Liao, Aimin
    Wang, Chuan
    Lin, Jin
    Wu, Jichun
    HYDROLOGICAL PROCESSES, 2024, 38 (02)
  • [40] Assessment of catchment response and calibration of a hydrological model using high-frequency discharge-nitrate concentration data
    Shrestha, Rajesh R.
    Osenbrueck, Karsten
    Rode, Michael
    HYDROLOGY RESEARCH, 2013, 44 (06): : 995 - 1012