(Near) Real-Time Snow Water Equivalent Observation Using GNSS Refractometry and RTKLIB

Global navigation satellite system (GNSS) refractometry enables automated and continuous in situ snow water equivalent (SWE) observations. Such accurate and reliable in situ data are needed for calibration and validation of remote sensing data and could enhance snow hydrological monitoring and modeling. In contrast to previous studies which relied on post-processing with the highly sophisticated Bernese GNSS processing software, the feasibility of in situ SWE determination in post-processing and (near) real time using the open-source GNSS processing software RTKLIB and GNSS refractometry based on the biased coordinate Up component is investigated here. Available GNSS observations from a fixed, high-end GNSS refractometry snow monitoring setup in the Swiss Alps are reprocessed for the season 2016/17 to investigate the applicability of RTKLIB in post-processing. A fixed, low-cost setup provides continuous SWE estimates in near real time at a low cost for the complete 2021/22 season. Additionally, a mobile, (near) real-time and low-cost setup was designed and evaluated in March 2020. The fixed and mobile multi-frequency GNSS setups demonstrate the feasibility of (near) real-time SWE estimation using GNSS refractometry. Compared to state-of-the-art manual SWE observations, a mean relative bias below 5% is achieved for (near) real-time and post-processed SWE estimation using RTKLIB

Characteristics and limitations of GPS L1 observations from submerged antennas

Observations from a submerged GNSS antenna underneath a snowpack need to be analyzed to investigate its potential for snowpack characterization. The magnitude of the main interaction processes involved in the GPS L1 signal propagation through different layers of snow, ice, or freshwater is examined theoretically in the present paper. For this purpose, the GPS signal penetration depth, attenuation, reflection, refraction as well as the excess path length are theoretically investigated. Liquid water exerts the largest influence on GPS signal propagation through a snowpack. An experiment is thus set up with a submerged geodetic GPS antenna to investigate the influence of liquid water on the GPS observations. The experimental results correspond well with theory and show that the GPS signal penetrates the liquid water up to three centimeters. The error in the height component due to the signal propagation delay in water can be corrected with a newly derived model. The water level above the submerged antenna could also be estimated.ISSN:0949-7714ISSN:1432-139

Radioglaciological studies on Hurd Peninsula glaciers, Livingston Island, Antarctica

We present the results of several radio-echo sounding surveys carried out on Johnsons and Hurd Glaciers, Livingston Island, Antarctica, between the 1999/2000 and 2004/05 austral summer campaigns, which included both radar profiling and common-midpoint measurements with low (20- 25 MHz)- and high (200MHz)-frequency radars. The latter have allowed us to estimate the radio-wave velocity in ice and firn and the corresponding water contents in temperate ice, which vary between 0 and 1.6% depending on the zone. Maximum ice thickness is ~200 m, with a mean value of 93.6 ± 2.5 m. Total ice volume is 0.968 ± 0.026 km3, for an area of 10.34 ± 0.03 km2. The subglacial relief of Johnsons Glacier is quite smooth, while that of Hurd Glacier shows numerous overdeepenings and peaks. The radar records suggest that Hurd Glacier has a polythermal structure, contrary to the usual assumption that glaciers in Livingston Island are temperate. This is also supported by other dynamical and geomorphological evidence

An autonomous navigational system using GPS and computer vision for futuristic road traffic

Navigational service is one of the most essential dependency towards any transport system and at present, there are various revolutionary approaches that has contributed towards its improvement. This paper has reviewed the global positioning system (GPS) and computer vision based navigational system and found that there is a large gap between the actual demand of navigation and what currently exists. Therefore, the proposed study discusses about a novel framework of an autonomous navigation system that uses GPS as well as computer vision considering the case study of futuristic road traffic system. An analytical model is built up where the geo-referenced data from GPS is integrated with the signals captured from the visual sensors are considered to implement this concept. The simulated outcome of the study shows that proposed study offers enhanced accuracy as well as faster processing in contrast to existing approaches

Advancements in Measuring and Modeling the Mechanical and Hydrological Properties of Snow and Firn: Multi-sensor Analysis, Integration, and Algorithm Development

Estimating snow mechanical properties – such as elastic modulus, stiffness, and strength – is important for understanding how effectively a vehicle can travel over snow-covered terrain. Vehicle instrumentation data and observations of the snowpack are valuable for improving the estimates of winter vehicle performance. Combining in-situ and remotely-sensed snow observations, driver input, and vehicle performance sensors requires several techniques of data integration. I explored correlations between measurements spanning from millimeter to meter scales, beginning with the SnowMicroPenetrometer (SMP) and instruments applied to snow that were designed for measuring the load bearing capacity and the compressive and shear strengths of roads and soils. The spatial distribution of snow’s mechanical properties is still largely unknown. From this initial work, I determined that snow density remains a useful proxy for snowpack strength. To measure snow density, I applied multi-sensor electromagnetic methods. Using spatially distributed snowpack, terrain, and vegetation information developed in the subsequent chapters, I developed an over-snow vehicle performance model. To measure the vehicle performance, I joined driver and vehicle data in the coined Normalized Difference Mobility Index (NDMI). Then, I applied regression methods to distribute NDMI from spatial snow, terrain, and vegetation properties. Mobility prediction is useful for the strategic advancement of warfighting in cold regions. The security of water resources is climatologically inequitable and water stress causes international conflict. Water resources derived from snow are essential for modern societies in climates where snow is the predominant source of precipitation, such as the western United States. Snow water equivalent (SWE) is a critical parameter for yearly water supply forecasting and can be calculated by multiplying the snow depth by the snow density. In this work, I combined high-spatial resolution light detection and ranging (LiDAR) measured snow depths with ground-penetrating radar (GPR) measurements of two-way travel-time (TWT) to solve for snow density. Then using LiDAR derived terrain and vegetation features as predictors in a multiple linear regression, the density observations are distributed across the SnowEx 2020 study area at Grand Mesa, Colorado. The modeled density resolved detailed patterns that agree with the known interactions of snow with wind, terrain, and vegetation. The integration of radar and LiDAR sensors shows promise as a technique for estimating SWE across entire river basins and evaluating observational- or physics-based snow-density models. Accurate estimation of SWE is a means of water security. In our changing climate, snow and ice mass are being permanently lost from the cryosphere. Mass balance is an indicator of the (in)stability of glaciers and ice sheets. Surface mass balance (SMB) may be estimated by multiplying the thickness of any annual snowpack layer by its density. Though, unlike applications in seasonal snowpack, the ages of annual firn layers are unknown. To estimate SMB, I modeled the firn depth, density, and age using empirical and numerical approaches. The annual SMB history shows cyclical patterns representing the combination of atmospheric, oceanic, and anthropogenic climate forcing, which may serve as evaluation or assimilation data in climate model retrievals of SMB. The advancements made using the SMP, multi-channel GPR arrays, and airborne LiDAR and radar within this dissertation have made it possible to spatially estimate the snow depth, density, and water equivalent in seasonal snow, glaciers, and ice sheets. Open access, process automation, repeatability, and accuracy were key design parameters of the analyses and algorithms developed within this work. The many different campaigns, objectives, and outcomes composing this research documented the successes and limitations of multi-sensor estimation techniques for a broad range of cryosphere applications

Investigations of Crustal Loading Effects on Vertical GPS Time Series in the Hardangervidda Region: A Comparative Analysis

This master's thesis seeks to ascertain if the vertical seasonal variations observed at permanent GPS stations (PGS) can be attributed to mass load deformations. The study focuses on seven PGSs in or around a highland region in south Norway. The mass loads examined include hydrological loads in the region and those related to water level fluctuations in nearby reservoirs. The study compares and corrects the vertical positions of a PGS against modelled vertical deformation resulting from mass displacement. Common mode filtering is employed on the GPS time series to minimise network errors. The findings reveal no direct connection between vertical displacements and the modelled hydrological mass load, as they exhibit phase shifts. Adjusting the observed PGSs' time series for the local effect and implementing a common mode filtering will significantly diminish the seasonal signal, although not entirely. This implies that either an unmodelled deformation signal influences certain PGSs in the study area or that these PGSs are subject to a similar error. Additionally, the study demonstrates that nearby water reservoirs contribute to the seasonal variation to a limited extent and do not cause substantial deformation at an adjacent PGS, particularly in comparison with other hydrological deformations