Global groundwater droughts are more severe than they appear in hydrological models:an investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model

Realistic representation of hydrological drought events is increasingly important in world facing decreased freshwater availability. Index-based drought monitoring systems are often adopted to represent the evolution and distribution of hydrological droughts, which mainly rely on hydrological model simulations to compute these indices. Recent studies, however, indicate that model derived water storage estimates might have difficulties in adequately representing reality. Here, a novel Markov Chain Monte Carlo - Data Assimilation (MCMC-DA) approach is implemented to merge global Terrestrial Water Storage (TWS) changes from the Gravity Recovery And Climate Experiment (GRACE) and its Follow On mission (GRACE-FO) with the water storage estimations derived from the W3RA water balance model. The modified MCMC-DA derived summation of deep-rooted soil and groundwater storage estimates is then used to compute standardized groundwater drought indices globally to show the impact of GRACE/GRACE-FO DA on a global index-based hydrological drought monitoring system. Our numerical assessment covers the period of 2003–2021, and shows that integrating GRACE/GRACE-FO data modifies the seasonality and inter-annual trends of water storage estimations. Considerable increases in the length and severity of extreme droughts are found in basins that exhibited multi-year water storage fluctuations and those affected by climate teleconnections

Deslizamientos submarinos en el margen continental de Palomares (Mediterráneo Occidental). Morfometría y distribución

Trabajo final presentado por Leire Anne Retegui Schiettekatte para un máster de la Universidad de Jaen (UJA), realizado bajo la dirección del Dr. David Casas Layora del Institut de Ciències del Mar (ICM-CSIC) y de la Dra. Mª Clara de Lacy Perez de la Universidad de Jaen (UJA).-- 60 pages, figures, tables[EN] In this work a regional inventory of landslides is constructed by the observation of the morphology of the continental margin of Palomares (Western Mediterranean), with the aim of studying the role of these processes in the regional geology. The analysis of the bathymetry of the margin has led to the identification of 937 events, mobilizing a total sediment volume of 10.34 km3. For each event, morphometric parameters which are considered relevant for the study of landslides have been measured. [EN] The magnitude-frecuency statistical analysis carried out shows that the data set can be fitted by both an inverse power law (partial fit for the two largest orders of magnitude) and a log-normal function (fit of the whole inventory). The latter allows to define a characteristic event size for each zone which is determined by the geomorphologic conditions and a variance related to the features of the regional triggers (mainly landslides)[ES] En este trabajo se elabora un inventario de inestabilidades sedimentarias a partir del análisis de la morfología del margen continental de Palomares (Mediterráneo Occidental) con el objetivo de estudiar el papel de estos procesos en la geología regional. El análisis de datos batimétricos del margen ha permitido identificar 937 eventos que movilizan un volumen total de sedimento de aproximadamente 10.34 km3. Para cada evento se han medido distintos parámetros morfométricos relevantes para el estudio de inestabilidades. El análisis estadístico de magnitud-frecuencia llevado a cabo indica que el conjunto de datos se puede ajustar tanto a una potencia inversa (ajuste parcial para los dos órdenes de magnitud mayores) como a una función log-normal (ajuste de la totalidad del inventario). Éste último permite definir un tamaño de evento característico para cada zona determinado por las condiciones geomorfológicas y una varianza ligada a las características de los detonantes que afectan la región (terremotos)Este trabajo se ha realizado gracias a los datos aportados por el proyecto del plan nacional de I+D+i Fauces (CTM2015-65461-C2-1-R