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Woodrow, Rebecca (2021): Time series of water parameters, nutrient, and gas samples in the Coffs Creek estuary, March 2018 [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.937739, In: Woodrow, R (2021): Water parameters, nutrient, and gas samples in the Coffs Creek estuary, 2017-2018 [dataset bundled publication]. PANGAEA, https://doi.org/10.1594/PANGAEA.937740

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Published: 2021-11-02DOI registered: 2021-12-28

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Abstract:
Measurements of water parameters of temperature, dissolved oxygen, and salinity as well as nutrient samples of dissolved organic carbon, filtered and unfiltered nitrogen, and nitrous oxide were collected through time series apparatus, hourly and 3 hourly, over 185 hours and exclusively at one site in the lower estuary (Site 1). A calibrated Hydrolab MS5 sonde measured and logged water temperature (±0.02°C), DO (±0.2 mg/L), and salinity (±0.02) at 30 m intervals and a depth logger (CTD diver) measured water depth in 15-minute intervals. Nutrient samples (including duplicates), filtered and unfiltered, were collected with a sample-rinsed 60 mL polyethylene syringe. Samples for dissolved organic carbon (DOC) analysis were filtered using pre-combusted 0.7 µm GF/F filters (Whatman), into 40 mL borosilicate vials (USP Type I). Samples for nitrogen were immediately filtered using Satourious ™ 0.45μm cellulose acetate syringe filters into 10 mL polyethylene sample tubes. All samples were kept in a cold icebox, away from light, for less than 5 hours and then frozen until laboratory analysis. Nutrient analysis of DOC was performed with the 40 mL borosilicate vials (USP Type I) first treated with 30 µL of H3PO4 before analysis using an Aurora 1030W TOC Analyser (Thermo Fisher Scientific, ConFLo IV). Nutrient analysis of ammonium (NH4+), NOx (nitrate plus nitrite), and total dissolved nitrogen (TDN) was performed on the 10 mL polyethylene sample tubes colourimetrically using a Lachat Flow Injection Analyser. Total dissolved nitrogen and dissolved inorganic nitrogen were calculated from the nitrogen samples. N2O samples were collected from a time series gas equilibration device via a one-way valve into 150 mL syringes then transferred from the syringes into a Supelco company 1 L gasbag. A total of 800 mL of gas was taken per sample. The gasbags were analysed for N2O using cavity ringdown spectroscopy on a calibrated Picarro G2308.
Keyword(s):
Greenhouse gases; hydrology; porewater exchange; wetlands
Related to:
Woodrow, Rebecca; White, Shane A; Sanders, Christian J; Holloway, Ceylena J; Wadnerkar, Praktan D; Conrad, Stephen R; Tucker, James P; Davis, Kay L; Santos, Isaac R (2021): Nitrous oxide hot moments and cold spots in a subtropical estuary: Floods and mangroves. Estuarine, Coastal and Shelf Science, 107656, https://doi.org/10.1016/j.ecss.2021.107656
Coverage:
Latitude: -30.296390 * Longitude: 153.136670
Date/Time Start: 2018-03-06T02:00:00 * Date/Time End: 2018-03-13T14:00:00
Minimum DEPTH, water: m * Maximum DEPTH, water: m
Event(s):
Coffs_Creek_estuary_time-series * Latitude: -30.296390 * Longitude: 153.136670 * Location: Tasman Sea * Method/Device: Water sample (WS)
Status:
Curation Level: Enhanced curation (CurationLevelC) * Processing Level: PANGAEA data processing level 3 (ProcLevel3)
Size:
744 data points

Data

Download dataset as tab-delimited text — use the following character encoding:


Site

Depth water [m]

Date/Time

Temp [°C]

DO [%]

ASAL [g/kg]

DOC [µmol/l]

TDN [µmol/l]

DIN [µmol/l]
10 
N2O [nmol/l]
time-series observation 122018-03-06T02:00:0025.194.135.071.123.03.47.1
time-series observation 222018-03-06T05:00:0025.184.435.191.116.83.77.0
time-series observation 322018-03-06T07:00:0024.868.333.541.117.43.46.5
time-series observation 422018-03-06T09:00:0024.060.830.966.216.83.46.7
time-series observation 522018-03-06T11:00:0024.167.526.6106.522.84.67.3
time-series observation 622018-03-06T13:00:0024.494.634.1110.512.02.77.3
time-series observation 722018-03-06T14:00:0024.185.929.372.729.23.97.5
time-series observation 822018-03-06T15:00:0023.774.119.838.720.05.08.1
time-series observation 922018-03-06T16:00:0023.767.716.141.032.06.88.7
time-series observation 1022018-03-06T17:00:0023.470.39.861.428.610.710.0
time-series observation 1122018-03-06T18:00:0022.972.07.127.839.413.111.1
time-series observation 1222018-03-06T19:00:0022.771.04.825.326.014.211.8
time-series observation 1322018-03-06T20:00:0022.670.03.639.237.415.912.3
time-series observation 1422018-03-06T22:00:0021.670.13.156.342.216.813.8
time-series observation 1522018-03-07T00:00:0021.870.92.5111.859.421.111.6
time-series observation 1622018-03-07T02:00:0023.390.731.118.823.84.27.6
time-series observation 1722018-03-07T03:00:0022.478.510.549.639.018.39.3
time-series observation 1822018-03-07T04:00:0022.975.914.6102.544.620.812.5
time-series observation 1922018-03-07T05:00:0022.467.87.3137.661.430.420.3
time-series observation 2022018-03-07T06:00:0022.069.24.3174.255.832.123.3
time-series observation 2122018-03-07T07:00:0021.868.23.171.367.236.627.5
time-series observation 2222018-03-07T08:00:0027.767.02.4117.275.041.333.2
time-series observation 2322018-03-07T10:00:0022.066.72.1112.869.643.738.0
time-series observation 2422018-03-07T12:00:0025.298.031.5119.518.07.013.6
time-series observation 2522018-03-07T14:00:0025.896.832.6183.617.44.88.1
time-series observation 2622018-03-07T16:00:0025.597.134.418.014.93.17.7
time-series observation 2722018-03-07T18:00:0024.980.413.173.656.237.323.8
time-series observation 2822018-03-07T20:00:0024.173.86.862.267.844.345.2
time-series observation 2922018-03-07T22:00:0023.171.14.4101.375.449.947.4
time-series observation 3022018-03-07T23:55:0023.693.433.3131.518.06.222.5
time-series observation 3122018-03-08T02:00:0023.398.434.4159.812.72.67.9
time-series observation 3222018-03-08T04:00:0023.892.934.6177.915.92.97.1
time-series observation 3322018-03-08T06:00:0023.082.028.5188.349.215.210.9
time-series observation 3422018-03-08T08:00:0022.570.519.015.20.03.724.1
time-series observation 3522018-03-08T10:00:0022.165.413.07.871.244.337.9
time-series observation 3622018-03-08T12:00:0022.565.110.38.274.251.144.0
time-series observation 3722018-03-08T14:00:0024.795.934.272.117.02.19.6
time-series observation 3822018-03-08T16:00:0024.997.034.4108.215.02.67.4
time-series observation 3922018-03-08T18:00:0025.191.026.2119.543.017.913.2
time-series observation 4022018-03-08T20:00:0023.777.417.39.458.635.625.8
time-series observation 4122018-03-08T22:00:0023.171.212.432.567.842.926.4
time-series observation 4222018-03-09T00:00:0022.969.811.836.974.845.830.4
time-series observation 4322018-03-09T02:00:0024.594.334.796.415.02.07.9
time-series observation 4422018-03-09T04:00:0023.993.434.5166.716.22.37.0
time-series observation 4522018-03-09T06:00:0022.488.334.1223.716.32.87.1
time-series observation 4622018-03-09T08:00:0022.474.620.8242.849.424.613.1
time-series observation 4722018-03-09T10:00:0021.867.916.828.526.428.718.4
time-series observation 4822018-03-09T12:00:0021.969.712.824.656.429.220.3
time-series observation 4922018-03-09T14:00:0022.974.813.4116.060.226.317.6
time-series observation 5022018-03-09T16:00:0025.996.234.7162.114.92.07.5
time-series observation 5122018-03-09T18:00:0025.496.927.0192.926.69.38.4
time-series observation 5222018-03-09T20:00:0024.086.620.8211.253.415.413.8
time-series observation 5322018-03-09T22:00:0023.373.314.225.253.820.117.4
time-series observation 5422018-03-10T00:00:0022.774.011.037.060.821.619.5
time-series observation 5522018-03-10T02:00:0022.892.933.732.716.82.59.8
time-series observation 5622018-03-10T00:04:0023.594.434.6106.822.22.07.1
time-series observation 5722018-03-10T06:00:0023.090.634.6135.020.02.66.9
time-series observation 5822018-03-10T08:00:0022.382.128.7163.227.26.27.2
time-series observation 5922018-03-10T10:00:0022.272.022.4100.436.69.110.2
time-series observation 6022018-03-10T12:00:0022.568.017.1190.039.611.512.8
time-series observation 6122018-03-10T14:00:0024.375.614.137.746.612.015.8
time-series observation 6222018-03-10T16:00:0025.997.834.471.116.51.79.2
time-series observation 6322018-03-10T18:00:0026.198.935.098.115.11.67.6
time-series observation 6422018-03-10T20:00:0025.696.324.7137.528.23.18.9
time-series observation 6522018-03-10T22:00:0024.485.619.2155.340.819.111.4
time-series observation 6622018-03-11T00:00:0023.678.014.033.441.20.014.0
time-series observation 6722018-03-11T03:00:0022.774.212.042.941.624.114.6
time-series observation 6822018-03-11T06:00:0022.994.534.936.117.82.07.1
time-series observation 6922018-03-11T08:00:0023.290.931.061.730.82.16.9
time-series observation 7022018-03-11T22:00:0022.776.025.590.632.610.86.9
time-series observation 7122018-03-11T12:00:0023.272.521.2119.335.014.28.1
time-series observation 7222018-03-11T14:00:0024.076.718.6137.235.416.010.3
time-series observation 7322018-03-11T16:00:0024.786.017.031.413.516.012.0
time-series observation 7422018-03-11T18:00:0025.996.934.034.918.82.213.6
time-series observation 7522018-03-11T20:00:0025.495.434.280.519.82.17.7
time-series observation 7622018-03-11T22:00:0024.590.428.2115.430.65.87.4
time-series observation 7722018-03-12T00:00:0023.779.019.7143.638.412.09.5
time-series observation 7822018-03-12T06:00:0022.876.215.9162.820.814.412.2
time-series observation 7922018-03-12T08:00:0022.592.434.927.630.42.213.5
time-series observation 8022018-03-12T10:00:0022.688.632.423.229.04.17.0
time-series observation 8122018-03-12T12:00:0024.278.827.273.534.67.87.1
time-series observation 8222018-03-12T14:00:0025.882.223.695.632.07.98.8
time-series observation 8322018-03-12T14:00:0027.092.221.7115.622.68.011.9
time-series observation 8422018-03-12T16:00:0026.898.433.6123.123.63.212.8
time-series observation 8522018-03-12T18:00:0025.894.735.325.021.41.58.8
time-series observation 8622018-03-12T20:00:0024.989.735.224.523.41.97.7
time-series observation 8722018-03-12T22:00:0025.181.125.757.928.86.37.4
time-series observation 8822018-03-13T00:00:0024.275.621.7100.417.28.78.9
time-series observation 8922018-03-13T06:00:0023.392.135.0123.913.41.611.0
time-series observation 9022018-03-13T08:00:0023.791.735.144.920.01.77.2
time-series observation 9122018-03-13T10:00:0025.284.030.858.728.23.97.5
time-series observation 9222018-03-13T12:00:0026.685.228.082.223.65.38.1
time-series observation 9322018-03-13T14:00:0027.892.425.5135.543.45.510.5