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Abstract. Progressive fracturing contributes to structural degradation of natural rock arches and other freestanding rock landforms. However, methods to detect structural changes arising from fracturing are limited, particularly at sites with difficult access and high cultural value, where non-invasive approaches are essential. This study aims to determine how fractures affect the dynamic properties of rock arches, focusing on resonance modes as indicators of structural health conditions. We hypothesize that damage resulting from fracture propagation may influence specific resonance modes that can be identified through ambient vibration modal analysis. We characterized the dynamic properties (i.e., resonance frequencies, damping ratios, and mode shapes) of Hunter Canyon Arch, Utah (USA), using spectral and cross-correlation analyses of data generated from an array of nodal geophones. Results revealed properties of nine resonance modes with frequencies between 1 and 12 Hz. Experimental data were then compared to numerical models with homogeneous and heterogeneous compositions, the latter implementing weak mechanical zones in areas of mapped fractures. All numerical solutions replicated the first two resonance modes of the arch, indicating these modes are insensitive to structural complexity derived from fractures. Meanwhile, heterogenous models with discrete fracture zones succeeded in matching the frequency and shape of one additional higher mode, indicating this mode is sensitive to the presence of fractures and thus most likely to respond to structural change from fracture propagation. An evolutionary crack damage model was then applied to simulate fracture propagation, confirming that only this higher mode is sensitive to structural damage resulting from fracture growth. While examination of fundamental modes is common practice in structural health monitoring studies, our results suggest that analysis of higher-order resonance modes can be more informative for characterizing fracture-driven structural damage. 

Resonance frequency monitoring can detect structural changes during progressive rock slope failure; however, reversible environmentally-driven frequency drifts may inhibit identification of permanent changes. Frequency drifts are commonly correlated with air temperature, lagging temperature changes by zero to 35–60 days. Here we report observations from two years of monitoring at a rock tower in Utah, USA where annual resonance frequency changes appear to precede air temperature cycles by ~35 days. Using correlations with meteorological data supplemented by numerical modeling, we identify changes in insolation as the primary driver of annual frequency drifts, giving rise to the negative lag time. Sparse in-situ insolation data show that the daily frequency increase lags sunrise by several hours, while frequencies decrease at sunset, responses we attribute to the west facing aspect of the tower. Modeled daily insolation patterns match frequency data for months when in-situ measurements are not available. Numerical models offer the advantage of predicting insolation patterns for different aspects of the rock tower, such as the west facing cliff where measurements would be challenging. Our study highlights the value of long-term datasets in identifying mechanisms driving environmentally associated frequency drifts, understanding that is crucial to facilitate detection of permanent changes during progressive failure.