Development and Applications of GNSS Drifters with Water Quality - PowerPoint PPT Presentation

Development and Applications of GNSS Drifters with Water Quality Measurements in Shallow Rivers and Estuaries Charles Wang Richard Brown Kabir Suara Yanming Feng 1

Background Why studying shallow water bodies? • about 60% of global population live along coast • more than 8 in 10 Australians (85%) lived within 50 km of the coastline of Australia (ABS, 2001 population estimate) Photo credit: Visit Brisbane: http://www.visitbrisbane.com.au/

Environmental Flow WATER EVENTS • Natural • Man Made POLLUTION • Urban • Industrial • Agricultural 3

1. Drifter design and calibration Advances in real ‐ time 2. Integration of water and air quality sensors Design satellite monitoring of flow in rivers and 3. Deployment of the real time data acquisition, processing and management estuaries (RTFLOW) • ARC Linkage 2016 ‐ 2019 • QUT and USC research 4. Field deployment collaboration with Sunshine Application Coast Council 5. Assimilation of Lagrangian data into Eulerian based models 6. Hydrodynamic and transport modelling Management of estuarine systems

Overview of drifter fleet capability Scales of Drifter capabilities interest in estuary High Medium Low. Res resolution resolution (Off ‐ the ‐ shelf) O [1 m] Position error ~ 2 cm* ~ 20 cm* ~ 3 m* * Position error O [0.01 Hz] Frequency 10 Hz 1 Hz 1 Hz Cut ‐ off freq 1 Hz ‐ 0.01 Hz RT ‐ Flow o Preliminary challenges o Waterproofing, post ‐ processing and noise removal o Choice of coordinate and extraction of Lagrangian time and length scales

• Operation in shallow rivers and estuaries • Simplicity and affordable Single frequency • Raspberry Pi 3 High positioning • Ublox M8T receiver and antenna RTK solution • 4G wifi hotspot accuracy • 20000mAh power bank (10 cm) Continuous WQ • Atlas Scientific sensors: pH, Dissolve oxygen Water quality and Conductivity measurement • Turbidity and temperature sensor measurements • Voltage isolation boards (0.5 Hz) Real ‐ time • NeCTAR cloud server Tracking and • Thingsboard IoT platform visualization and monitoring management 6

Sensor Integration 7

WQ Sensor Calibrations Water Quality Sensor Comparison QUT Sensor (Multi 3430) 12 • Computer Integrated Tracking 11 • pH, Conductivity, DO and 10 Temperature Sensor 9 • Approx $3500 AUD Measured pH Value (pH) 8 • Developed by WTW a Xylem Brand 7 6 5 4 3 2 1 0 4 7 8.012 8.421 10 Calibration Solution (pH) QUT Waspmote Atlas 8

WQ Sensor Calibrations Water Quality Sensor Noise Comparison Water Quality Sensor Response Time Comparison 0.35 90 80 0.3 Measured pH Value Change (pH) 70 0.25 60 Time (seconds) 0.2 50 40 0.15 30 0.1 20 0.05 10 0 0 4 7 8.012 8.421 10 4 7 8.012 8.421 10 Calibration Solution (pH) Calibration Solution (pH) QUT Waspmote Atlas QUT Waspmote Atlas 9

Turbidity Sensors • Amount of cloudiness in water SOLUTION caused by sand, salt, bacteria and • Washing machines! chemical precipitates, etc METHODOLOGY • Commercial turbidity sensors are • Turbidimetric relatively large and expensive (> $3000) BENEFITS • Cheap ($20 ‐ $30) • Operating Range (0 ‐ 4000 NTU) CHALLENGES • Calibration • Operating conditions • Water quality relationships 10

Circuit evolution • Drifter project microcontroller: • Connection: Through the General Purpose Input Output (GPIO) • Analog to Digital Converter (ADC): 16 ‐ bit • Stable power: Step ‐ up/Step ‐ down DC voltage converter 11

Calibration 12

Cloud Tracking and Monitoring Server • Nectar Cloud facility • Thingsboard IoT platform – open source • Data collection • MQTT, CoAP, HTTP • Data visualization • Real ‐ time charts and maps • Data processing • Define processing rules • Device management • Event trigger and alarm • Horizontal scalability 13

Field Trips • http://203.101.225.66:8080/home Currimundi Lake Epapah Creek 14

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Proof of concept for drifters with water quality sensor pH 16

Proof of concept for drifter with water quality sensor 50 minutes deployment of RT ‐ Flow at Currimundi Lake during opening Dissolve oxygen (mg/L) 17

Application 1: height with HR ‐ drifter  GPS drifter vertical 1 Fixed local station position component Drifter measured elevation 0.5 validated using fixed Local Tidal Elevation (m AHD) location tidal height 0 measurements. -0.5  This shows that the -1 GPS drifter data is 0 0.5 1 1.5 2 2.5 sensitive to height 5 x 10 measurement and thus 1 could be used to Drifter measured elevation monitor both both Fixed local station 0.5 velocity change and height during flood . 0 -0.5 -1 1.34 1.36 1.38 1.4 1.42 1.44 1.46 18 Time from 00:00 on 29/09/2013(sec) 5 x 10

Application 2: Streamwise velocity estimates o Quality controlled o DOF > 5. o Run test : passed o Max time = 100 s o Max distance = 60 m Very good correlation (R 2 > 0.9) in streamwise direction o Correlation reduces with distance from the surface o Poor correlation (R 2 < 0.2) in cross stream direction o Cause by quick change in direction of flow within the chosen radius o 19

Application 3: Mixing and Water quality Effect of mouth conditions and opening operation on dynamics of Currimundi Lake Baseline experiment 1: open inlet (April) o Tide, rivers, wind and run ‐ offs o Tide dominated o Baseline experiment 2: closed inlet (September) o Wind, river and run ‐ offs o Questions are: Limited tidal influence o What is mixing quality? o Mouth opening operation Magnitude of diffusivity? o o (October) What are the dominant o mechanisms governing dispersion in the system?

Results : Flow velocity variability (u) North Open inlet experiment containing Closed inlet condition, drifters travelled in ebb ‐ ward direction about 20 o aligned trajectories driven by for both ebb and flood tides with dominant surface wind direction

Mixing parameter: Dispersion coefficients (K) 10 1 Open inlet ( Ebb) Open inlet ( Flood) Closed inlet Mean dispersion coefficient (m 2 /s) Open inlet- Ebb dispersion 10 0 Closed inlet dispersion 10 -1 Open inlet - Flood dispersion 10 -2 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1 Mean horizontal velocity magnitude (m/s)

Evolution • Custom PCB to reduce electronic footprint • Additional sensors (Temperature, Nitrate, etc) • Simplified operation for field staff with provision of operation manual • Event trigger and alarm • Configuration options for different application • Lora & Lorawan gateway, zigbee • Low ‐ power module for up to a month operation • Solar power for permanent placement 23

Capabilities • Solution is extendable to include additional sensor • Can provide valuable tool to locate source of pollutants into waterways • Lower cost compared to fixed instruments for equivalent area coverage • Better spatial coverage • Adaptability to individual need • The GNSS monitoring system offers a flexible and low maintenance alternative to current fixed station • RTK solution provides Lagrangian measurement which may be useful to improve water modelling in the case of climate changes and flood events. 24