| General Information: |
| Title: | Temporal changes in nitrate and DOC concentrations, and river volume transport |
| Identifier: | JaLTER-Akkeshi.1.2 |
| Abstract: |
In this study, nitrate nitrogen and dissolved organic carbon in river water were observed with high temporal resolution at 10-minute intervals using water quality sensors in the downstream wetland area of the Bekanbeushi River watershed in northern Japan. The river water flow was similarly measured to examine the relationship between water quality and riverine volume transport in downstream river water under the influence of tidal fluctuations.
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| Keywords: |
- Brackish water
- Biogeochemistry
- Water quality
- Riparian wetland
- Freshwater
- Tidal fluctuation
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Involved Parties
| Data Set Owners: |
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Individual: | Hideaki Shibata |
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Organization: | Hokkaido University |
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Position: | Professor |
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Individual: | Shiraiwa Takayuki |
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Organization: | Hokkaido University |
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Position: | Associate Professor |
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Email Address:
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| Data Set Contacts: |
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Individual: | Takayuki Shiraiwa |
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Organization: | Hokkaido University |
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Position: | Associate Professor |
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Email Address:
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Data Set Characteristics
| Geographic Region: |
| Geographic Description: | Observation point |
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Bounding Coordinates:
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| West: | 144.86274 degrees
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| East: | 144.86274 degrees
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| North: | 43.0941 degrees
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| South: | 43.0941 degrees
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Mimimum Altitude: | 2.0 meter |
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Maximum Altitude: | 2.0 meter |
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Sampling, Processing and Quality Control Methods
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Step by Step Procedures
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| Step 1: |
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Description:
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Monitoring of water quality
The NO3-N and DOC concentrations in river water were observed using a UV‒Vis spectrometer probe multi::lyser V2 (s::can Messtechnik GmbH, Vienna, Austria) at a point near the river bank where a stable water flow velocity was available. The absorbance measurements at wavelengths ranging from 220 to 720 nm were performed by a sensor at the tip of the probe, which outputs current values (mA). Measurements were taken at 10-min intervals, and the NO3-N and DOC current values were stored in a data logger. The power supply was provided by a lithium battery charged by a solar panel (when the charge capacity decreased during the observation, the battery was replaced with a charged lithium battery). Canoes were used to access the observation sites and to transport equipment.
To calibrate the sensor, river water near the sensor installation site was collected directly from the water surface into a polyethylene container several times, filtered through a 0.2-μm filter, brought back to the laboratory, and stored frozen until chemical analysis. The NO3-N concentration was analyzed using an autoanalyzer (AACS-4, BL Tech), and the DOC was analyzed using a total organic carbon analyzer (TOC-5000A, Shimadzu Corporation).
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Instrument(s):
| UV‒Vis spectrometer probe multi::lyser V2 (s::can Messtechnik GmbH, Vienna, Austria) |
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| Step 2: |
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Description:
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River water flow observation
An ultrasonic Doppler velocity profiler (SonTek-IQ Plus, Xylem Japan K.K., Kawasaki, Japan) was installed on the riverbed near the stream center at the observation site, and the water velocity and depth of the entire channel were observed at 5-min intervals (depth accuracy: 0.003 m, velocity accuracy: 0.0001 m/s). At the same location, the electrical conductivity (EC) and water temperature of the river water at the bottom of the channel were measured at the same intervals and used as indicators of saltwater mixing. In addition, observation lines were placed in the cross-sectional direction of the river, and flow rates were measured multiple times at regular intervals using a canoe. Flow rate was measured using an M9 RiverSurveyor (Xylem Japan K.K., Kawasaki, Japan) to simultaneously measure flow velocity and depth, and the observed values were used to correct the velocity profiler values to obtain the flow rate (river volume transport) for the entire river channel.
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Instrument(s):
| Ultrasonic Doppler velocity profiler (SonTek-IQ Plus, Xylem Japan K.K., Kawasaki, Japan)
M9 RiverSurveyor (Xylem Japan K.K., Kawasaki, Japan) |
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| Step 3: |
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Description:
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Data processing
Observations began on June 17, 2022, and were initially planned to continue for two weeks for both water quality and flow rate. However, due to intense rainfall during the early observation period, the flow sensor installed in the riverbed was buried by runoff sediment after the latter half of June 20, and data could not be obtained. The sensor was reinstalled, and observation resumed on June 23 but was terminated when the data logger placed on the riverbank was submerged and malfunctioned due to rainfall runoff starting on June 24. Therefore, in this study, only the period for which flow data were obtained was analyzed. In addition, because the DOC concentration in this river was relatively high, some of the observed data were found to have reached the upper detection limit, so such data were excluded from the analysis. Because DOC output data are necessary to obtain the NO3-N concentrations as described above, only the data for which both NO3-N and DOC sensor output values were obtained were available.
In analyzing the relationship between the NO3-N and DOC concentrations and water discharge, flow rate data were used every 10 minutes to match the measurement intervals of the water quality sensors. Due to the tidal influence (flood and ebb tides) of river water, there were cases where river water flowed out from upstream to downstream and cases where river water flowed back upstream from downstream. The flow rate from upstream to downstream was treated as a positive value (downward or ebb tide), and the flow rate from downstream to upstream was treated as a negative value (upward or flood tide).
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| Step 4: |
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Description:
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Calibration of sensors
For DOC concentration:
DOC (mgC/L) = -1.1879 x Sensor DOC (mA) + 0.3941
Adjusted R-squared: 0.9078
p-value < 0.001
For NO3 concentration:
NO3 (mg NO3/L) = 0.36304 x Sensor NO3 (mA) – 0.06885 x Sensor DOC (mA) + 0.11582
Adjusted R-squared: 0.5432
p-value: 0.04021
Please note the unit of the concentration.
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Sampling Area And Frequency:
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The study was conducted in the Bekanbeushi River watershed located in eastern Hokkaido, northern Japan. Most of the watershed is covered with cool-temperate mixed coniferous forest, secondary broadleaf forest, and forest plantation (Larix kaempferi, Abies sachalinensis, etc.), with dairy grasslands in the western part of the watershed and wide wetlands surrounding the riverbank in the middle and lower reaches. These wetlands are named Lake Akkeshi and Betkaneushi Marsh, 52.8 km2 of which is a Ramsar wetland, and they are recognized as an important habitat for migratory birds such as Japanese cranes and whooper swans. The marshland is mainly composed of lowland marshland with reeds and sedges, and highland marshland is distributed in the central part of the area. The watershed area of the Bekanbeushi River is 752 km2, with a gentle slope of 0 to 20 degrees (10 m mesh), which is especially flat in the riparian areas and wetlands, where the topography is less than 5 degrees. The lower reaches of the Bekanbeushi River are characterized by a tidal zone where the river level fluctuates under the influence of tides, and the Pacific coast of eastern Hokkaido, where this river is located, is characterized by greater tidal fluctuations than the Sea of Japan side in the west . The microtidal ranges during the spring and neap tides are approximately 1.2 and 0.7 m, respectively . The observation site is located in the lower reaches of the main river, where the river width is approximately 90 m and the depth at the river center varies in the range of approximately 1 to 2 m. Observations were made from mid- to late June 2022. During the observation period, there were intermittent, relatively intense rainfall events.
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Sampling Description:
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To calibrate the sensor, river water near the sensor installation site was collected directly from the water surface into a polyethylene container several times, filtered through a 0.2-μm filter, brought back to the laboratory, and stored frozen until chemical analysis. The NO3-N concentration was analyzed using an autoanalyzer (AACS-4, BL Tech), and the DOC was analyzed using a total organic carbon analyzer (TOC-5000A, Shimadzu Corporation).
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Data Set Usage Rights
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