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Solander, Kurt C.

Publications and source records attributed to Solander, Kurt C..

Advancing the Limits of InSAR to Detect Crustal Displacement from Low-Magnitude Earthquakes through Deep Learning

Detecting surface deformation associated with low-magnitude (M w ≤ 5) seismicity using interferometric synthetic aperture radar (InSAR) is challenging due to the subtlety of the signal and the often challenging imaging environments. However, low-magnitude earthquakes are potential precursors to larger seismic events, and thus characterizing the crustal displacement associated with them is crucial for regional seismic hazard assessment. We combine InSAR time-series techniques with a Deep Learning (DL) autoencoder denoiser to detect the magnitude and extent of crustal deformation from the M w = 3.4 Gallina, New Mexico earthquake that occurred on 30 July 2020. Although InSAR alone cannot detect event-related deformation from such a low-magnitude seismic event, application of the DL method reveals maximum displacements as small as (±2.5 mm) in the vicinity of both the fault and earthquake epicenter without prior knowledge of the fault system. This finding improves small-scale displacement discernment with InSAR by an order of magnitude relative to previous studies. We additionally estimate best-fitting fault parameters associated with the observed deformation. The application of the DL technique unlocks the potential for low-magnitude earthquake studies, providing new insights into local fault geometries and potential risks from higher-magnitude earthquakes. This technique also permits low-magnitude event monitoring in areas where seismic networks are sparse, allowing for the possibility of global fault deformation monitoring.

58 GEOSCIENCES↗

Soil water percolation and nutrient fluxes as a function of topographical, seasonal and soil texture variation in Central Amazonia, Brazil

Abstract Understanding soil water dynamics and transport of nutrients is challenging in tropical rainforests due to the uniqueness of several properties related to soils, vegetation and seasonality that make relating patterns found in temperate environments to tropical sites difficult. We address the need for better edaphic characterization in tropical environments by investigating soil water percolation rates and chemistry across topographic, soil texture and seasonal gradients in a mature tropical rainforest in Central Amazonia, Brazil. We utilized a passive wick flux meter (e.g., drainage lysimeter) to directly measure real‐time percolation fluxes at 60‐cm depth, and to sample a suite of chemical species across plateau, slope and valley topographic positions. We found percolation flux volume and chemical exports generally increase with decreasing elevation and clay content, which was lowest in the valley. Daily percolation flux was observed to be 2.39 ± 0.44 in plateau, 3.01 ± 0.50 in slope and 6.16 ± 0.83 mm in valley. Most solutes were present in small amounts of <1 mg L −1 , such as PO₄ 3− , Fe 2+ /Fe 3+ and Mn 2+ ; however, NO 3 − concentrations were >20 mg L −1 , even exceeding 100 mg L −1 in the valley. Based on additional isotopic analysis, we speculate high NO 3 − concentrations are partially an artefact of root decomposition following installation of the flux meters. The empirical relationships we show among percolation volume and nutrient exports under varying topographies and soil textures can improve Earth System Model performance by better constraining ecohydrological relationships to nutrient fluxes, which can in‐turn better illuminate the important factors that govern their behaviour.

54 ENVIRONMENTAL SCIENCES↗