Introducing the Idea of Classifying Sets of Permanent GNSS Stations as Benchmarks for Hydrogeodesy

We propose a novel approach to classify sets of Global Navigation Satellite System (GNSS) permanent stations as benchmarks for hydrogeodesy. Benchmarks are trusted sets of GNSS stations whose displacements are classified as significantly and positively correlated with hydrospheric changes and identified in a three temporal-scales: short-term, seasonal and long-term. We use 63 vertical displacement time series processed at the Nevada Geodetic Laboratory for the period 1998-2021 from stations located within Amazon basin and show that estimates of trends and annual signals, including the annual phase maximum, are very coherent with water surface levels provided by altimetry missions. We compute vertical displacements from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On gravity missions and predict those also from Global Land Water Storage (GLWS) v2.0 data set which values are produced by assimilation of GRACE into WaterGAP Global Hydrological Model (WGHM). We divide vertical displacements from the three data sets into the pre-defined temporal-scales of short-term, seasonal and long-term, using non-parametric wavelet analysis. For each temporal-scale, correlation coefficients are computed between GNSS-measured and GRACE-derived/GLWS-predicted displacements. We present the benefits of applying high-resolution GRACE-assimilating hydrology model to benchmark GNSS stations, which are particularly evident when using spherical harmonic coefficients higher than 120. Their increase causes the number of stations included in the benchmarks to rise by up to 15% for short-term. Benchmarking allows hydrogeodesy to take advantage of a broader set of GNSS stations that were previously omitted, such as earthquake-affected sites and those where a possible poroelastic response is observed. Displacements of the Earth's crust measured by permanent Global Navigation Satellite System (GNSS) ground stations are used for many geophysical interpretations. However, it is common to omit the evaluation of the sensitivity of the system to the measurement of displacements from different sources, assuming in advance 100% sensitivity of the system to a given effect. Consequently, the fact that at a given station several effects can be recorded simultaneously is overlooked. This is particularly evident in earthquake-affected areas, where GNSS stations are excluded from most analyses of non-tectonic effects. We solve this problem and propose to divide GNSS stations into trusted sets, which we call benchmarks. Benchmarking is performed by indicating the stations that are certain to register a given effect in three pre-defined temporal-scales: short-term, seasonal and long-term. We present the analysis for the Amazon area, known for its large hydrosphere-related signal, and demonstrate that the benchmarking allows for the inclusion of GNSS stations that were previously omitted in analyses of this type. Displacements measured by Global Positioning System (GPS) correlate well with surface water levels derived from radar altimetry missionsTrusted sets of GPS stations are classified at the three pre-defined temporal-scales: short-term, seasonal and long-termBenchmarking allows to include more GPS stations in hydrogeodetic analyses