# Development of a Multi-Sensor GNSS-IoT System for Precise Water Surface Elevation Measurement
## 3 Field Experiment
### Reference Data  
To validate the experiment data, independent water height data collected at Googong reservoir by Icon Water Limited (IWL) were used. This reference dataset was provided in excel spreadsheets containing date, time, reservoir WSE and quality code (QC) in 10 min intervals. The time system of reference data is Australian Eastern Standard Time (AEST), and its datum is based on the AHD.  
The 10 min time-series original reference data and the 6 h and 24 h averages are depicted in Figure 8a. The 6 h data correspond to the period of the daily GNSS data collection session. Notably, there are three instances where the WSE rises more steeply than it declines. To further examine daily variations within 6 h and 24 h intervals, the WSE ranges are illustrated in Figure 8b. Typically, the daily WSE variation (24 h) is less than 2 cm, but during the three noted rising periods, variations exceed 4 cm, with the 24 h variation peaking at 0.156 m on 7 April 2024. As expected, the 6 h variation is smaller than the 24 h variation. The mean 6 h range is 3 mm, while the 24 h range is 11 mm, allowing us to approximate the ratio of 6 h to 24 h. To assess the accuracy of using the 6 h average as representative of the reference daily solution, the difference between the 24 h and 6 h averages is presented in Figure 8c. While differences are generally within 5 mm, several instances exceed 1 cm, with a maximum discrepancy of 5 cm on 7 April 2024. Therefore, for a more accurate evaluation of WSE estimation performance, it is necessary to generate and utilize 6 h reference average solutions, consistent with the GNSS data collection session.  
Figure 6: The experimental set-up on the CSIRO Dark-water Inland Observatory Network pontoon at Googong reservoir (photo credit: [PERSON] and [PERSON]).  
Figure 7: The two devices used in the experiment. (**a**) The F043 stable base station; (**b**) the F044 floating station.  
The descriptive statistics for the different reference data products and differences are summarised in Table 4. The mean WSE variation range over 24 h is 0.011 m, while the corresponding 6 h variation is only 0.003 m, which supports the assumption that water level changes are typically gradual over short intervals. This 3:1 ratio aligns with the time span difference, suggesting that averaging over 6 h intervals still captures the essential short-term variation. However, the STD values--0.018 m for 24 h and 0.006 m for 6 h--highlight occasional significant variations, especially during inflow events. The maximum WSE variation within a 24 h period is 0.156 m, which occurs during a major water rise event on 7 April 2024, indicating transient but impactful changes. Importantly, the difference between the 24 h and 6 h averages, though mostly negligible (mean = 0.000 m), can deviate by up to 5 cm. This finding confirms that using the 6 h average as a daily solution during validation may introduce substantial errors in specific cases.  
Consequently, these statistics justify the decision to use 6 h averaged data as the reference benchmark for evaluating GNSS-derived WSE estimates. The low mean and standard deviation of the 6 h WSE variation range (0.003 \(\pm\) 0.006 m) establish a performance target for the GNSS-based method: to reliably capture WSE fluctuations, it should achieve an accuracy better than \(\pm\)6 mm (1 \(\times\) STD). This aligns with the sensitivity needed to detect hydrologically meaningful signals within sub-daily observation windows.