Mud volcanism and turbidites occurrence as joint tools to identify paleoearthquakes in the Gulf of Cadiz and adjacent abyssal plains

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Paleoseismology is a relatively recent branch of earthquake-related studies but, since its birth, it is rapidly expanding back in time the earthquakes (EQs) catalogues worldwide. Its contribution to historical and geological EQs detection has shed light on one of the most crucial challenges of modern geology: high magnitude EQs recurrence and our ability to “predict” them. Only this way, improving the characterization of seismic hazard by estimating magnitude and recurrence interval between large events, one would be able to mitigate the seismic risk and implement proper prevention policies for the nearby population. The TURBOMUD proposal is aiming to expand and refine this knowledge for the Gulf of Cadiz (GoC) accretionary wedge, using a large dataset collected during the most recent and previous expeditions carried out in the region. An innovative research plan has been designed, which will conjugate mud volcanism and turbidites occurrence, to better estimate the seismic hazard for this convergent area. With the help of unique material and data, including two long sediment cores obtained with the seafloor drill rig MeBo, several gravity cores, as well as bathymetric and seismic surveys, an extensive study on the GoC paleoseismology will be implemented. Specifically, several statistical techniques will be used to post-process the data, which will allow to test synchronicity of EQ-related events. Following a pioneering approach, the proponent is planning to apply and integrate the classical methods for the study of turbidite deposits to the suites of techniques used to describe mud volcanoes’ episodicity, in order to pinpoint past EQ events. The novel idea of joining these two ways of studying subduction zones EQs will provide an enhanced understanding as well as a more exhaustive mean of EQ risk assessment for this region. Given the uncertainties in the available paleoseismological methods, the TURBOMUD project will contribute to a major advance in this field.