Surface Deformation and Seismicity Linked to Fluid Injection in the Raton Basin.

It is suggested that in addition to seismicity deep fluid injection may cause surface uplift and subsidence in oil and gas-producing regions. This study uses the Raton Basin as an example to investigate the hydromechanical processes of surface uplift and subsidence during wastewater injection. The Raton Basin, in southern central Colorado and northern central New Mexico, has experienced wastewater injection related to coalbed methane and gas production starting in 1994. In this study, we estimate the extent and magnitude of total vertical deformation in the Raton Basin from 1994 to 2020 and incremental deformation between the years 2017 to 2020. Results indicate a modeled uplift as much as 15 cm occurring between 1994 and 2020. Between 2017 and 2020, up to 3 cm of uplift occurred, largely near the northwestern injection wells. Most modeled uplift between 1994 and 2020 occurred near the southern wells, where the greatest cumulative volume of wastewater was injected. However, modeled subsidence occurred around the southern and eastern wells between 2017 and 2020, after the rate of injection decreased. Modeling indicates that while the magnitude of modeled uplift corresponds to cumulative injection volume and maximum rate in the long-term, short-term incremental deformation (uplift or subsidence) is controlled by changes in the rate of injection. The number of yearly earthquake events follows periods of rapid modeled uplifting throughout the Basin, suggesting that measurable surface deformation may be caused by the same injection-induced pore pressure perturbations that initiate seismicity.

Tidal modulation of the seismic activity related to the 2021 La Palma volcanic eruption.

The volcanic eruption at La Palma started on September 19, 2021. The eruption was preceded by a seismic swarm that began on September 11, although anomalous seismicity has been observed on the island since 2017. During the co-eruptive phase of the seismic activity, hypocenters depth was generally less than 15 km, save for the period between November 10 and November 27, when hypocenters ranged in the depth from 15 to 40 km. The eruption ended on December 13, 2021. We compute tidal stress for each earthquake at the hypocenter depth and find statistically significant correlations between the occurrence times of the earthquakes and the confining tidal stress values and stress rates. The correlation is depth-dependent, and ocean-loading tides have a stronger effect than body tides. We find that tidal stress variations contribute to the eruption onset and that certain explosive events, typical in Strombolian type volcanoes, seem to occur preferentially when the tidal stress rate is high. Our analysis supports the hypothesis that tides may modulate earthquake activity in volcanic areas, specifically during magma migration at shallow depths. A conceptual model is proposed, which could have a general application in the Canary Islands archipelago and other volcanic islands.

Shallow magmatic intrusion evolution below La Palma before and during the 2021 eruption.

La Palma, Canary Islands, underwent volcanic unrest which culminated in its largest historical eruption. We study this unrest along 2021 using Interferometric Synthetic Aperture Radar (InSAR) and a new improved interpretation methodology, comparing achieved results with the crustal structure. We reproduce the final phase of La Palma volcanic unrest, highligthing a shallow magma accumulation which begins about 3.5 months before the eruption in a crustal volume charactherized by low density and fractured rocks. Our modeling, together with our improved pictures of the crustal structure, allows us to explain the location and characteristics of the eruption and to detect failed eruption paths. These can be used to explain post-eruptive phenomena and hazards to the local population, such as detected gases anomalies in La Bombilla and Puerto Naos. Our results have implications for understanding volcanic activity in the Canaries and volcano monitoring elsewhere, helping to support decision-making and providing significant insights into urban and infrastructure planning in volcanic areas.

A multi-sensor evaluation of precipitation uncertainty for landslide-triggering storm events.

Extreme precipitation can have profound consequences for communities, resulting in natural hazards such as rainfall-triggered landslides that cause casualties and extensive property damage. A key challenge to understanding and predicting rainfall-triggered landslides comes from observational uncertainties in the depth and intensity of precipitation preceding the event. Practitioners and researchers must select from a wide range of precipitation products, often with little guidance. Here we evaluate the degree of precipitation uncertainty across multiple precipitation products for a large set of landslide-triggering storm events and investigate the impact of these uncertainties on predicted landslide probability using published intensity-duration thresholds. The average intensity, peak intensity, duration, and NOAA-Atlas return periods are compared ahead of 177 reported landslides across the continental United States and Canada. Precipitation data are taken from four products that cover disparate measurement methods: near real-time and post-processed satellite (IMERG), radar (MRMS), and gauge-based (NLDAS-2). Landslide-triggering precipitation was found to vary widely across precipitation products with the depth of individual storm events diverging by as much as 296 mm with an average range of 51 mm. Peak intensity measurements, which are typically influential in triggering landslides, were also highly variable with an average range of 7.8 mm/h and as much as 57 mm/h. The two products more reliant upon ground-based observations (MRMS and NLDAS-2) performed better at identifying landslides according to published intensity-duration storm thresholds, but all products exhibited hit ratios of greater than 0.56. A greater proportion of landslides were predicted when including only manually verified landslide locations. We recommend practitioners consider low-latency products like MRMS for investigating landslides, given their near-real time data availability and good performance in detecting landslides. Practitioners would be well-served considering more than one product as a way to confirm intense storm signals and minimize the influence of noise and false alarms.

Detection of volcanic unrest onset in La Palma, Canary Islands, evolution and implications.

La Palma island is one of the highest potential risks in the volcanic archipelago of the Canaries and therefore it is important to carry out an in-depth study to define its state of unrest. This has been accomplished through the use of satellite radar observations and an original state-of-the-art interpretation technique. Here we show the detection of the onset of volcanic unrest on La Palma island, most likely decades before a potential eruption. We study its current evolution seeing the spatial and temporal changing nature of activity at this potentially dangerous volcano at unprecedented spatial resolutions and long time scales, providing insights into the dynamic nature of the associated volcanic hazard. The geodetic techniques employed here allow tracking of the fluid migration induced by magma injection at depth and identifying the existence of dislocation sources below Cumbre Vieja volcano which could be associated with a future flank failure. Therefore they should continue being monitored using these and other techniques. The results have implications for the monitoring of steep-sided volcanoes at oceanic islands.

Modeling the two- and three-dimensional displacement field in Lorca, Spain, subsidence and the global implications.

Land subsidence associated with overexploitation of aquifers is a hazard that commonly affects large areas worldwide. The Lorca area, located in southeast Spain, has undergone one of the highest subsidence rates in Europe as a direct consequence of long-term aquifer exploitation. Previous studies carried out on the region assumed that the ground deformation retrieved from satellite radar interferometry corresponds only to vertical displacement. Here we report, for the first time, the two- and three-dimensional displacement field over the study area using synthetic aperture radar (SAR) data from Sentinel-1A images and Global Navigation Satellite System (GNSS) observations. By modeling this displacement, we provide new insights on the spatial and temporal evolution of the subsidence processes and on the main governing mechanisms. Additionally, we also demonstrate the importance of knowing both the vertical and horizontal components of the displacement to properly characterize similar hazards. Based on these results, we propose some general guidelines for the sustainable management and monitoring of land subsidence related to anthropogenic activities.

Surface uplift and time-dependent seismic hazard due to fluid injection in eastern Texas.

Observations that unequivocally link seismicity and wastewater injection are scarce. Here we show that wastewater injection in eastern Texas causes uplift, detectable in radar interferometric data up to >8 kilometers from the wells. Using measurements of uplift, reported injection data, and a poroelastic model, we computed the crustal strain and pore pressure. We infer that an increase of >1 megapascal in pore pressure in rocks with low compressibility triggers earthquakes, including the 4.8-moment magnitude event that occurred on 17 May 2012, the largest earthquake recorded in eastern Texas. Seismic activity increased even while injection rates declined, owing to diffusion of pore pressure from earlier periods with higher injection rates. Induced seismicity potential is suppressed where tight confining formations prevent pore pressure from propagating into crystalline basement rocks.

Record-breaking avalanches in driven threshold systems.

Record-breaking avalanches generated by the dynamics of several driven nonlinear threshold models are studied. Such systems are characterized by intermittent behavior, where a slow buildup of energy is punctuated by an abrupt release of energy through avalanche events, which usually follow scale-invariant statistics. From the simulations of these systems it is possible to extract sequences of record-breaking avalanches, where each subsequent record-breaking event is larger in magnitude than all previous events. In the present work, several cellular automata are analyzed, among them the sandpile model, the Manna model, the Olami-Feder-Christensen (OFC) model, and the forest-fire model to investigate the record-breaking statistics of model avalanches that exhibit temporal and spatial correlations. Several statistical measures of record-breaking events are derived analytically and confirmed through numerical simulations. The statistics of record-breaking avalanches for the four models are compared to those of record-breaking events extracted from the sequences of independent and identically distributed (i.i.d.) random variables. It is found that the statistics of record-breaking avalanches for the above cellular automata exhibit behavior different from that observed for i.i.d. random variables, which in turn can be used to characterize complex spatiotemporal dynamics. The most pronounced deviations are observed in the case of the OFC model with a strong dependence on the conservation parameter of the model. This indicates that avalanches in the OFC model are not independent and exhibit spatiotemporal correlations.

Probabilities for large events in driven threshold systems.

Many driven threshold systems display a spectrum of avalanche event sizes, often characterized by power-law scaling. An important problem is to compute probabilities of the largest events ("Black Swans"). We develop a data-driven approach to the problem by transforming to the event index frame, and relating this to Shannon information. For earthquakes, we find the 12-month probability for magnitude m>6 earthquakes in California increases from about 30% after the last event, to 40%-50% prior to the next one.

Results of the Regional Earthquake Likelihood Models (RELM) test of earthquake forecasts in California.

The Regional Earthquake Likelihood Models (RELM) test of earthquake forecasts in California was the first competitive evaluation of forecasts of future earthquake occurrence. Participants submitted expected probabilities of occurrence of M ≥ 4.95 earthquakes in 0.1° × 0.1° cells for the period 1 January 1, 2006, to December 31, 2010. Probabilities were submitted for 7,682 cells in California and adjacent regions. During this period, 31 M ≥ 4.95 earthquakes occurred in the test region. These earthquakes occurred in 22 test cells. This seismic activity was dominated by earthquakes associated with the M = 7.2, April 4, 2010, El Mayor-Cucapah earthquake in northern Mexico. This earthquake occurred in the test region, and 16 of the other 30 earthquakes in the test region could be associated with it. Nine complete forecasts were submitted by six participants. In this paper, we present the forecasts in a way that allows the reader to evaluate which forecast is the most "successful" in terms of the locations of future earthquakes. We conclude that the RELM test was a success and suggest ways in which the results can be used to improve future forecasts.

Space-time clustering and correlations of major earthquakes.

Earthquake occurrence in nature is thought to result from correlated elastic stresses, leading to clustering in space and time. We show that the occurrence of major earthquakes in California correlates with time intervals when fluctuations in small earthquakes are suppressed relative to the long term average. We estimate a probability of less than 1% that this coincidence is due to random clustering.