A synthetic study to assess the applicability of full-waveform inversion to infer snow stratigraphy from upward-looking ground-penetrating radar data

Abstract

Snow stratigraphy and liquid water content are key contributing factors to avalanche formation. Upward-looking groundpenetrating radar (upGPR) systems allow nondestructive monitoring of the snowpack, but deriving density and liquid water content profiles is not yet possible based on the direct analysis of the reflection response. We have investigated the feasibility of deducing these quantities using full-waveform inversion (FWI) techniques applied to upGPR data. For that purpose, we have developed a frequency-domain FWI algorithm in which we additionally took advantage of time-domain features such as the arrival times of reflected waves. Our results indicated that FWI applied to upGPR data is generally feasible. More specifically, we could show that in the case of a dry snowpack, it is possible to derive snow densities and layer thicknesses if sufficient a priori information is available. In case of a wet snowpack, in which it also needs to be inverted for the liquid water content, the algorithm might fail, even if sufficient a priori information is available, particularly in the presence of realistic noise. Finally, we have investigated the capability of FWI to resolve thin layers that play a key role in snow stability evaluation. Our simulations indicate that layers with thicknesses well below the GPR wavelengths can be identified, but in the presence of significant liquid water, the thin-layer properties may be prone to inaccuracies. These results are encouraging and motivate applications to field data, but significant issues remain to be resolved, such as the determination of the generally unknown upGPR source function and identifying the optimal number of layers in the inversion models. Furthermore, a relatively high level of prior knowledge is required to let the algorithm converge. However, we feel these are not insurmountable and the new technology has significant potential to improve field data analysis.

Determination of Snow Water Equivalent for Dry Snowpacks Using the Multipath Propagation of Ground-Based Radars

“…To solve this problem different techniques are employed. These include: i) a-priori hypothesis on the snow density; ii) the use of additional devices measuring either the snowpack depth or density; iii) approaches derived from ground penetrating radars (GPRs), for example based on the best fitting of the diffraction curve (common offset, common mid-point) or on the migration analysis [18][19][20][21][22][23][24][25][26]. However, these techniques have their own flaws.…”

Measurement of water equivalent, average density and height of layered snow cover using UWB electromagnetic pulses.

“…Подповерхностные радары широко используются для измерения одного или одновременного нескольких из следующих параметров снежного покрова: высота, плотность, водный эквивалент (ВЭСП) и влажность [1][2][3][4][5][6][7][8][9][10][11][12][13]. Толщина снежного покрова может быть измерена по времени задержки импульса t, отраженного от границы снег-почва относительно времени прихода опорного импульса.…”

“…Введенный автором дисперсионный параметр [9] пропорционален тангенсу угла потерь и позволяет оценить мнимую часть комплексной диэлектрической проницаемости, а, следовательно, на основе диэлектрической модели снега оценить и его влажность. Развиваются томографические методы, которые могут применяться для измерения перечисленных характеристик снежного покрова с пространственной привязкой к его объему [7,11,12,20]…”

Radius estimation of subsurface cylindrical objects from ground-penetrating-radar data using full-waveform inversion

“…Babcock and Bradford (2015) implemented the GPR waveform inversion for quantifying properties for nonaqueous phase liquid thin and ultrathin layers, and Bradford et al (2016) used a targeted GPR reflection-waveform inversion algorithm to quantify the geometry of oil spills under and within sea ice. Sassen and Everett (2009) combined the full-waveform inversion and the fully polarimetric GPR coherency technology to characterize the fractured rock, and Schmid et al (2016) studied the application of FWI to deduce the snow stratigraphy from the upward-looking GPR data. Recently, Feng et al…”