This water quality time-series dataset was collected between late August 2017 and Mid March 2018 as the primary deliverable of a the Gold Coast Triathlon Monitoring Project between Gold Coast City Council and CSIRO. Data was collected by a suite of instruments deployed onto a CSIRO-owned buoy that was moored in the Broadwater lagoon in the planned location of the Triathlon event of the 2008 Commonwealth Games. The instrument output was sampled at 10 minute intervals by a Campbell Scientific data logger and stored in logger memory. CSIRO Coastal Monitoring sensor-data service polled the logger at regular intervals to fetch the latest data for visualisation and analysis. This dataset consists of the raw data accumulated by the CSIRO Coastal Monitoring sensor data service. It is raw data, and has not been cleaned of any glitches or adjusted to allow for calibration changes. This dataset contains time series data from the following instruments: ====================================================== EXO Sonde built-in data sources: ------------------------------------------ 1.a EXO_BatV => Battery voltage for the EXO Sonde power source. 1.b EXO_Depthm => Water depth in metres (m) Measured using a differential strain gauge transducer measures pressure with one side of the transducer exposed to the water and the other side exposed to a vacuum. Initially calibrated in Atmosphere: output can be affected by local barometric pressure, water density and temperature. EXO Wiped Conductivity and Temperature Sensor: ---------------------------------------------------------------- Ref: https://www.ysi.com/WipedCT 2.a EXO_TempC => Water Temperature in degrees celsius. Direct measurement using a thermistor-type sensor. 2.b EXO_SpCondmScm => Specific Conductance in milli-siemens per centimetre (ms/cm). Measured via a 4-electrode nickel-cell sensor, using a calibrated cell constance to convert absolute conductance to specific. Compensated to a 25 degree reference temperature. 2.c EXO_Salpsu => Salinity in Practical Salinity Units (PSU) Calculated from the conductivity and temperature readings according to algorithms found in Standard Methods for the Examination of Water and Wastewater (ed. 1989) PSU measurements are in reference to the conductivity of standard seawater at 15 °C. EXO Turbidity Smart Sensor ----------------------------------- Ref: https://www.ysi.com/Product/id-599101-01/EXO-Turbidity-Smart-Sensor 3.a EXO_TurbFNU => Turbidity in formazin nephelometric units (FNU) Measured by detection of scattering at 80 degrees of a near-infrared light source. 3.b EXO_TurbNTU => Turbitidy in nephelometric turbidity units (NTU) Calculated from the Turbidity FNU via a calibrated conversion factor. 3.c EXO_TSSmgL => Total Suspended Solids in milligrams per Litre (mg/L) Calculated from the Turbidity FNU value via a calibrated conversion factor. EXO pH and OPR Smart Sensor ---------------------------------------- Ref: https://www.ysi.com/Product/id-599706/EXO-pH--ORP-Smart-Sensor 4.a EXO_pHmV => Potential difference (in mV) across the pH sensor electrode. Measured using a glass combination electrode with a stable solution of known pH on the inside and the sample being measured on the outside. 4.b EXO_pH => pH in standard pH Units where 7.0 is neutral; < 7 is acidic; > 7 is alkaline. Calculated from the pHmV measurement. 4.c EXO_ORPmV => Oxidising-Reducing Potential of the water sample in millivolts (mV) Measured using a platinum button electrode. Detects high concentrations of redox-active species including metal salts, chlorine, sulfite ions etc. Refects all dissolved species in the medium: requires site-specific information to determine which are present. EXO Optical Dissolved Oxygen Smart Sensor --------------------------------------------------------- Ref: https://www.ysi.com/Product/id-599100-01/EXO-Optical-Dissolved-Oxygen-Smart-Sensor 5.a EXO_DOmgL => Dissolved Oxygen in milligrams per Litre Measured using an optical luminescence sensor 5.b EXO_DOPerSat => Dissolved Oxygen as % saturation. Calculated from the raw DO measurement, corrected for temperature and local barometric pressure at the time of callibration. ( local mmHg / 760 mmHg ) x 100 = %Sat EXO Total Algae PE Smart Sensor ------------------------------------------- Ref: https://www.ysi.com/Product/id-599103-01/EXO-Total-Algae-PE-Smart-Sensor Note: The Algal sensors have NOT been completely calibrated to local conditions. This data may be used as an estimate of comparative concentrations, but should not be relied on as a numerical value for testing against a threshold. 6.a EXO_ChlRFU => Chlorophyll concentration in Relative Fluorescence Units (RFU) Measured using an optical fluorescence sensor with a blue excitation beam that excites the chlorophyll molecure present in all photosynthetic cells. Calibrated relative to a stable secondary standard, such as Rhodamine WT dye. 6.b EXO_ChlugL => Chlorophyll concentration in micro-grams per Litre (µg/L) Calculated estimate of chlorophyll pigment concentration. Not correlated to local conditions: use for comparison purposes only. 6.c EXO_BGAPERFU => Phycoetherin Concentration in Relative Fluorescence Units Measured using an optical fluorescence sensor with an orange excitation beam that excites the phycoetherin accessory pigment found in saltwater blue-green algae (cyanobacteria). Calibrated relative to a stable secondary standard, such as Rhodamine WT dye. 6.d EXO_BGAPEugL => Phycoetherin Concentration in micro-grams per Litre (µg/L) Calculated estimate of phycoetherin pigment concentration. Not correlated to local conditions: use for comparison purposes only. EXO fDOM Sensor ----------------------- Ref: https://www.ysi.com/Product/id-599104-01/EXO-fDOM-Smart-Sensor 7.a EXO_fDOMRFU => Fluorescent Dissolved Organic Matter concentration in Relative Fluorescence Units (RFU) Measured using an optical fluorescence sensor which detects fluorescence associated with dissolved organic matter exposed to near-ultraviolet light. Measurement is relative to the fluorescence of quinine sulfate, which, in acid solution, fluoresces similarly to dissolved organic matter 7.b EXO_fDOMQSU => Fluorescent Dissolved Organic Matter concentration in Quinine Sulfate Units (1 QSU => 1 part-per-billion Qunine Sulfate) Calculated from the EXO_fDOMRFU Measurement Flow / Current Meter -------------------------- Data values are the average value over the previous sample interval, unless indicated otherwise. 8.a ABSSpd_Avg => Absolute current speed in meters per second (m/s) 8.b NorthCur_Avg => Northward current velocity in meters per second (m/s) 8.c EastCur_Avg => Eastward current velocity in meters per second (m/s) 8.d Heading_Avg => Current meter heading in compass degrees 8.e Direction_Avg => Current direction in compass degrees 8.f AbsTilt_Avg => Absolute tilt in degrees from the horizontal 8.g TiltX_Avg => Tilt in the X-plane (across the current) in degrees from the horizontal 8.h TiltY_Avg => Tilt in the Y-plane (aligned with current) in degrees from the horizontal 8.i MaxTilt_Avg => Maximum absolute tilt during the sample interval, in degrees from the horizontal 8.j StdTilt_Avg => Standard deviation of absolute tilt during the sample interval, in degrees from the horizontal 8.k SPstd_Avg 8.l SigStrength_Avg 8.m PingCnt_Avg GillMX10 Weather Station -------------------------------- 9.a Gill_Ws_Mean => Mean wind speed during the previous sample interval, in meters per second (m/s) 9.b Gill_Wd_MeanUnitVector => Mean wind direction during the previous sample interval, in compass degrees 9.c Gill_Wd_StdDev => Standard deviation of wind direction during the previous sample interval, in compass degrees 9.d Gill_WindSpd_Max => Maximum wind speed during the previous sample interval, in meters per second (m/s) 9.e Gill_Temperature_Avg => Average air temperature during the previous sample interval, in degrees Celcius 9.f Gill_RH => Relative Humidity at the sample time, in % 9.g Gill_Pressure => Atmospheric pressure at the sample time, in hecto-pascals (hPa) 9.h Gill_Rain_mm_Tot => Cumulative rainfall during the previous sample interval (mm) 9.i Gill_TotalRain_mm => Cumulative rainfall in millimetres (mm) for the 24 hours to 10 AM AEST ( => 9AM AEDT to match the BOM cutoff) 9.j Gill_TotalDailyRain_mm => Cumulative rainfall in millimetres (mm) for the 24 hours to midnight AEST 9.k Gill_DewPoint_Avg => Average dewpoint during the previous sample interval, in degrees Celcius 9.l Gill_SRad_Avg => Average solar radiance during the previous sample interval watts per square meter 9.m Gill_SunHours_Avg => Average hours of sunlight during the previous sample interval in hours 9.n Gill_Latitude => Latitude of the weather station, in decimal degrees 9.o Gill_Longitude => Longitude of the weather station, in decimal degrees 9.p Gill_Time => ISO Day of the month The following known events may have caused shifts in sensor calibration: ========================================================== Note: The CWQM buoy was used as an anchor for the SAFA instrument that was involved in collecting microbial monitoring data for a seperate deliverable of this project. Retrieving and deploying the SAFA instrument required the CWQM buoy to be tilted, which may have briefly disrupted the CWQM Sensors. CWQM Instruments were checked and cleaned during the SAFA collection trips. All times are AEST (+10:00) 2017-08-03 15:00 => Initial deployment of CWQM buoy and instruments: lon=153.4139, lat=-27.9573 2017-10-05 08:20 => Recalibration & restart 2017-10-12 22:10 => Power interruption (reason unknown) 2017-11-02 12:10 => SAFA instrument removal 2017-11-29 07:50 => SAFA instrument redeployed 2017-12-01 12:00 => SAFA samples collected, instrument redeployed 2017-12-11 15:30 => SAFA samples collected, instrument redeployed 2017-12-15 19:53 => SAFA samples collected, instrument redeployed 2017-12-21 13:10 => SAFA samples collected, instrument redeployed 2018-01-02 16:40 => GillMX10 Weather Station Damaged (suspected lightening or hail strike) 2018-01-03 11:00 => SAFA samples collected, instrument redeployed, instrument removed 2018-01-08 07:30 => SAFA instrument redeployed 2018-01-10 07:50 => SAFA samples collected, instrument removed. 2018-01-10 08:45 => GillMX10 Weather station replaced 2018-02-01 10:30 => Cleaning and Calibration 2018-02-23 08:30 => Relocate to Coast Guard Pontoon for Luke Harrop Memorial Triathlon: lon=153.4101,lat=-27.9557 2018-02-25 16:30 => Relocate back in position: lon=153.4139, lat=-27.9573 2018-03-14 09:00 => CWQM Buoy Removed

Presentation Abstract: Submerged sand banks in the northwest of Torres Strait typically have smaller dunes superimposed upon them. Survey work undertaken as part of the Torres Strait CRC measured the rates of sand dune migration on these banks in an effort to gauge their potential impact on local seagrass communities. Marine surveys at the end of the monsoon and trade wind seasons measured very similar hydrodynamic conditions but substantially different patterns of dune migration. At the end of the monsoon season migration rates of up to 17 meters were measured over a 14 day period, at the end of the trade wind season migration rates of up to 4 meters were measured over a similar time period. Wind data acquired for the two weeks before and during the monsoon season survey indicated the onset of the trade wind season during this time. As a result, the elevated levels of dune migration observed at the end monsoon season are probably the result of wind driven-currents, changing from predominantly eastwards during the monsoon season to predominantly westwards with the onset of the trade wind season. Dunes that were influenced by wind-driven currents during the monsoon season were east facing at the start of the trade wind season but these dunes then became hydrodynamically unstable under the influence of the westward-directed wind-driven currents and experienced accelerated levels of migration to the west. By comparison, the lower rates of sand dune migration observed during the trade wind season survey are considered to be representative of dunes that are hydrodynamically stable. The main conclusions from this research are that the dunes in the study area have been observed to move rapidly in response to seasonal changes in hydrodynamics however the typical rates of dune migration suggest that only seagrass communities in close proximity to the sandbanks are likely to be threatened by dune migration.

These data are the result of Geoscience Australia survey 266 to the central Torres Strait region, with the survey being the first of two by Geoscience Australia carried out in 2004. They form part of a larger field-based program managed by the Torres Strait CRC aimed at identifying and quantifying the principal physical and biological processes operating in Torres Strait. The impetus for the program is the threat of widespread seagrass dieback and its effects on local dugong and turtle populations and the implications for indigenous islander communities. The principal aim of the survey was to investigate the seabed geomorphology and sedimentary processes in the vicinity of Turnagain Island and to infer the possible effects (if any) on the distribution, abundance and survival of seagrasses. The Turnagain Island region was chosen because it is a known site of recent widespread seagrass dieback. The survey consisted of a detailed geophysical survey using swath (multi-beam) sonar and shallow seismic equipment that was supplemented with a detailed sampling program consisting of 301 near-bed water samples, 54 seabed grabs, 5 vibrocores and 69 camera stations. Four oceanographic moorings were also deployed for the duration of the survey to measure the local tide, wave and wind-driven currents. A regional survey was initially undertaken, followed by a detailed study of two areas: Area A - located approximately 2.5 km SW of Turnagain Island which contained sand ridges and seagrass beds, and Area B - located approximately 2.0 km SE of Turnagain Island which contained sandwaves and no seagrass beds. In a new application of the swath (multi-beam) data, the total volume of sediment transported during the survey was estimated from changes in the high-resolution seabed bathymetry collected during the repeat surveys. Preliminary results of the study found that seagrasses in the region are subject to frequent and significant changes in environmental conditions, with implications for limited dispersal and survival. A follow-up survey was undertaken in October 2004.