Ten years of Lake Taupō surface height estimates using the GNSS interferometric reflectometry

Holden, Lucas; Larson, Kristine M.

doi:10.1007/s00190-021-01523-7

Cited by 13 publications

(8 citation statements)

References 38 publications

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“…Environmental forcing such as tides, tsunami and wind introduces surface deviations, both small‐scale random roughness and large‐scale systematic tilting. In their turn, roughness and tilting affect respectively the amplitude and frequency of SNR oscillation, thereby decreasing the accuracy of retrieved reflector height (e.g., Holden & Larson, 2021; Karegar & Kusche, 2020). In our study area, tides are absent.…”

Section: Water Level Results and Discussionmentioning

confidence: 99%

“…GNSS interferometric reflectometry (GNSS‐IR) is an emerging technique in geodesy that has shown remarkable contributions to ground‐based sea and lake level monitoring (Geremia‐Nievinski et al., 2020; Holden & Larson, 2021; Larson, Ray, et al., 2013; Roussel et al., 2015; Strandberg et al., 2016). Although the primary applications of GPS/GNSS are in Positioning, Navigation and Timing (PNT), the fast growth of GPS/GNSS base station networks has led to the emergence of GNSS‐IR for monitoring surface changes such as sea levels and river heights.…”

Section: Gnss Interferometric Reflectometry For Water Level Measurementsmentioning

confidence: 99%

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Raspberry Pi Reflector (RPR): A Low‐Cost Water‐Level Monitoring System Based on GNSS Interferometric Reflectometry

Karegar

Kusche

Geremia‐Nievinski

et al. 2022

Water Resources Research

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One of the challenges for hydrologists and environmental scientists is the need to obtain and sustain in situ water level measurements for calibrating and improving forecast models, validating satellite and airborne data products, and developing early-warning flood systems. Ground-based measurements are still scarce in many regions. In particular, stream flow monitoring gauges have been declining sharply since the mid 1980s due to high maintenance cost, funding shortfalls and (geo-) political constraints (Hannah et al., 2011;Reid et al., 2019;Ruhi et al., 2016Ruhi et al., , 2018. While satellite remote sensing techniques have been utilized to monitor oceanic and land surface water with unprecedented global coverage, their measurements are associated with moderate uncertainties and temporal resolution (>7-day return) (Escudier et al., 2017;Jarihani et al., 2013). The upcoming NASA's Surface Water Ocean Topography (SWOT) satellite mission will collect high-accuracy measurements of inland surface water elevation (10 cm error for 1 km 2 areas) at unprecedented scales (10-70 m resolution) using Ka-band interferometric synthetic aperture radar. SWOT will provide global maps of water surface elevation, slope and inundated areas for rivers wider than 100 m (Biancamaria et al., 2016). The SWOT interferometric swath will pass over a given location two or three times every 21-day orbital cycle (Tuozzolo et al., 2019). However, the coarse temporal resolution of satellite altimetry missions such as SWOT and the requirement for monitoring smaller rivers and tributaries underline the significance of in situ monitoring sites. Measurements of sea surface and river water level using ground-based sensors conventionally rely on contact methods, such as traditional float and stilling well gauges (Noye, 1974) and bubbler pressure gauges (Pugh, 1972), or proximal sensing gauges, such as acoustic (

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Section: Water Level Results and Discussionmentioning

confidence: 99%

Section: Gnss Interferometric Reflectometry For Water Level Measurementsmentioning

confidence: 99%

Raspberry Pi Reflector (RPR): A Low‐Cost Water‐Level Monitoring System Based on GNSS Interferometric Reflectometry

Karegar

Kusche

Geremia‐Nievinski

et al. 2022

Water Resources Research

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“…GNSS-IR operates at a moderate distance from the reflector surface, allowing the sensor to be protected from storms and flood events [5]. The advantage of using a GNSS receiver in this case is that it can simultaneously measure three-dimensional positions (using carrier phase data) and water level (using signal strength data), so that the results of observations of water level are at well-defined locations and terrestrial reference frames [8].…”

Section: Introductionmentioning

confidence: 99%

“…Several experiments and studies have been carried out regarding GNSS-IR observations with standard antenna configurations using geodetic devices [7][8][9][10][11][12]. There are several studies related to the comparison of GNSS-IR observations with conventional tide gauges.…”

Section: Introductionmentioning

confidence: 99%

“…Song et al [13] evaluated the performance of GNSS-IR against tide gauges in Shuangwangcheng Reservoir (China) for 8 months using geodetic GNSS observation data. The resulting accuracy is satisfactory at the daily average RMS of 0.05 m. Larson et al [8] have compared the performance of GNSS-IR against tide gauges for longterm water level observations in Lake Taupo (New Zealand). Hu et al [14] made observations of sea level height using the GNSS-IR method and obtained very good accuracy results with a correlation of 0.97 cm to the tide gauge.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Water Level Monitoring using GNSS Interferometric Reflectometry in River Waters

Cahyadi,

Bawasir,

Susilo

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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GNSS Interferometric Reflectometry (GNSS-IR) is one of the newest explorations of Global Navigation Satellite System (GNSS) signals which utilizes multipath signals to calculate the vertical distance from the reflecting surface to the geodetic antenna/receiver. However, scientific-grade or geodetic GNSS instruments are expensive, which is a limiting factor for their prompt and more widespread deployment as a dedicated environmental sensor. Hence, in this study, low-cost GNSS receiver devices were used to monitor the surface level of PT Garam River in Pamekasan Regency using the GNSS-IR method. The study location of PT Garam River which is quite close to the sea causes the water level to vary following the tides at the sea. This is because there are needs for advanced methodologies to limit GNSS observations in a much narrower area. The river in this case is a more challenging study location in terms of monitoring the water level. Calculation of river water level height with GNSS-IR observations is based on determining the peak frequency on the periodogram resulting from signal-to-noise ratio (SNR) data extraction. The two-weeks GNSS-IR observation in this study were applied by installing sideway orientation of GNSS antenna towards the river. This will be done to see how effective the strength of the reflected signal received by the low-cost GNSS devices are in narrow footprint area. Conventional tide gauge near the GNSS-IR site was used to evaluate the accuracy of GNSS-IR in river water level monitoring. Tide analysis is carried out to obtain tidal constituents and tide predictions using least square harmonics estimation (LSE). The resulting accuracy of the validation data is at an RMSE of 15.35 cm, with the correlation value of 0.94. The type of river tides in the study location based on the calculation results is mixed tide prevailing semidiurnal. Tide prediction for 20 days gives promising results with an RMSE of 16 cm. These results indicate that low-cost GNSS device has a promising capability for water level monitoring using GNSS-IR method in a narrow reflector area.

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Multi-constellation GNSS interferometric reflectometry for tidal analysis: mitigations for K1 and K2 biases due to GPS geometrical errors

Peng,

Lin,

Lee

et al. 2024

J Geod

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It has been observed that when using sea levels derived from GPS (Global Positioning System) signal-to-noise ratio (SNR) data to perform tidal analysis, the luni-solar semidiurnal (K2) and the luni-solar diurnal (K1) constituents are biased due to geometrical errors in the reflection data, which result from their periods coinciding with the GPS orbital period and revisit period. In this work, we use 18 months of GNSS SNR data from multiple frequencies and multiple constellations at three sites to further investigate the biases and how to mitigate them. We first estimate sea levels using SNR data from the GPS, GLONASS, and Galileo signals, both individually and by combination. Secondly, we conduct tidal harmonic analysis using these sea-level estimates. By comparing the eight major tidal constituents estimated from SNR data with those estimated from the co-located tide-gauge records, we find that the biases in the K1 and K2 amplitudes from GPS S1C, S2X and S5X SNR data can reach 5 cm, and they can be mitigated by supplementing GLONASS- and Galileo-based sea-level estimates. With a proper combination of sea-level estimates from GPS, GLONASS, and Galileo, SNR-based tidal constituents can reach agreement at the millimeter level with those from tide gauges.

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Ten years of Lake Taupō surface height estimates using the GNSS interferometric reflectometry

Cited by 13 publications

References 38 publications

Raspberry Pi Reflector (RPR): A Low‐Cost Water‐Level Monitoring System Based on GNSS Interferometric Reflectometry

Raspberry Pi Reflector (RPR): A Low‐Cost Water‐Level Monitoring System Based on GNSS Interferometric Reflectometry

Analysis of Water Level Monitoring using GNSS Interferometric Reflectometry in River Waters

Multi-constellation GNSS interferometric reflectometry for tidal analysis: mitigations for K1 and K2 biases due to GPS geometrical errors

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