The threat and occurrence of high-magnitude, uncontrolled induced seismicity has been a persisting issue in several kinds of subsurface systems for decades now. Research on limiting induced seismicity to improve the safety of these systems began ever since the first observed cases in wastewater injection. The number of groups working to solve this problem only increased with every major event, focusing on various aspects of induced seismicity. Our understanding of the underlying processes has improved consistently, but the recent events at Pohang, Castor, Groningen, etc., have showcased that there is more to learn in terms of the physics, and demand better characterization, monitoring and forecasting systems in place.

This Workshop aims at fostering debate on the latest advances in process understanding, subsurface characterization and forecasting of induced seismicity. We welcome contributions from the academia and industry alike in topics ranging from, but not limited to numerical modeling, laboratory experiments, field studies, application of AI in induced seismicity, etc. We welcome contributions in the form of both posters and oral presentations that broadly fit into the following sessions:

Session 1: Understanding of the causes of induced seismicity

Session 2: Post-injection seismicity: can we forecast it?

Session 3: Subsurface characterization

Session 4: Forecasting induced seismicity

Session 5: Case Studies of induced seismicity

Confirmed invited speakers

• Gillian Foulger (Durham University)


• Peter Meier (GeoEnergie Suisse)


• Serge Shapiro (Freie Universität Berlin)


• Leo Eisner (Seismik)


• Jesús Carrera (CSIC)


• Ioannis Stefanou (Nantes University)


• Marie Violay (EPFL)


• Keita Yoshioka (Montanuniversität Leoben)


• Grzegorz Kwiatek (GFZ)


• Yusuke Mukuhira (Tohoku University)


• Luis Cueto-Felgueroso (Technical University of Madrid)


• Qinghua Lei (Uppsala University)


• Silvia De Simone (CSIC)


• Mateo Acosta (CalTech)


• Alexis Sáez (EPFL)


• Jean Schmittbuhl (Strasbourg University)


• Sarah Weihmann (RWTH Aachen University)


• James Verdon (University of Bristol)

Closing of the registration: 29th of February 2024

Registration here

Abstract

Marine macrophyte ecosystems are considered as a fundamental habitat throughout the world. However, these communities are seriously threatened by the continuous increase in anthropogenic activities and are highly vulnerable to the pressures derived from global change.

This has led to an increased interest in restoration, and in assessing different factors that may promote their recovery and resilience. In seagrasses, firsts life stages (seeds and seedlings) can be critical when determining the natural recovery of the ecosystem. In this sense, identifying the factors that positively influence the development and establishment of these early stages, particularly considering future stressors, is essential for ecosystem conservation and restoration. The study of microbiome can be a determining factor to understand the functionality and resilience of marine ecosystems. Although the study of seagrass microbiomes is still in its early stages, the beneficial effect of microorganisms has already been described in terrestrial plants, so this study aims to evaluate the influence of microbiome on germination and development of C. nodosa seeds.

To test the hypothesis that the presence of certain microorganisms influences the development of seagrass, a manipulative factorial experiment was carried out in the laboratory using C. nodosa seeds. Six treatments from the interaction between two factors were examined: (1) sterilization (or not) of the seeds and (2) sediment type (sediment from vegetated environments, sediment from non-vegetated environments or artificial sediment). Germination success was strongly influenced by the presence of the seed microbiome, and sediment type (and thus soil microbiome) also influenced germination and seed development. These results are important to understand natural drivers of seagrass germination success and to consider for restoration techniques.

Abstract

The generation and propagation of waves towards the coastal regions during storm events can substantially increase coastal hazards associated with extreme sea levels. While the Mediterranean Sea is characterized by a fetch-limited environment, the progression of extra-tropical cyclones over its surface often engenders powerful waves. As climate numerical models consistently converge towards a global warming climate over the past few decades, the present wave climate is expected to undergo alterations. However, the reliability of the model projections differ among climate variables, exhibiting for instance higher confidence in the temperature than in precipitation variables. This study investigates future changes in the wave climate across the Mediterranean region using an extensive ensemble of wave numerical simulations.

These simulations were forced with wind fields from thirty-one GCM-RCMs (general circulation - regional climate models) of the European Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX), integrating WaveWatch III and SCHISM numerical models. Future changes in the mean and intense (quantile 0.95) wave climate of significant wave height (Hs), peak wave period (Tp), peak wave direction (Dp) are assessed. Furthermore, we evaluate changes in 100-year return levels of Hs toward the end of the century. Extreme events from each GCM-RCM are aggregated into a single coherent distribution, following a bias correction procedure assuming the Cumulative Distribution Function (CDF) of extreme events to adhere to either a parametric Gumbel or Generalized Extreme Value (GEV) CDF, individually for each model. Return levels are then computed by fitting a GEV distribution to the unified distribution for both historical and future periods.

Our findings reveal an intensification of extreme waves towards the end of the century in several areas of the Mediterranean basin. Despite limitations inherent to bias-correction methods and return level computation, our study underscores the contrasting outcomes between analyzing the entire statistical distribution versus focusing solely on the tail, emphasizing the importance of considering both aspects in wave climate projections.