On 1 August 1674, very severe thunderstorms occurred along a squall line from northern France to the northern parts of Holland, where damages were particularly severe. Using reported and pictured observations of damages, a reconstruction of this storm is made and an interpretation using modern meteorological concepts is given. Special attention is given to the city of Utrecht, which was hit hardest and where the impact of this storm is still recognisable in the cityscape.
Alessandro D'Anca, Laura Conte, Paola Nassisi, Cosimo Palazzo, Rita Lecci, Sergio Cretì, Marco Mancini, Alessandra Nuzzo, Maria Mirto, Gianandrea Mannarini, Giovanni Coppini, Sandro Fiore, and Giovanni Aloisio
Updated situational sea awareness requires an advanced technological system to make data available for decision makers, improving the capacity of intervention and supporting users in managing emergency situations due to natural hazards. The TESSA data platform meets the request of near-real-time access to heterogeneous data with different accuracy, resolution or degrees of aggregation providing efficient and secure data access and strong support to operational oceanographic high-level services.
EMODnet initiative aims to provide access to European marine data in an interoperable and free of restrictions way. EMODnet Chemistry lot focuses on the fulfillment of EU MSFD and INSPIRE directives requirements to assess eutrophication and contaminants. It could play two main roles: provide standardized and quality-checked buffers of data for specific regions and act as an umbrella for standards, best practices, and infrastructure to aggregate at regional level the single member states.
A state-of-the-art nested flood model (MSN_Flood) is applied to simulate complex coastal-fluvial urban flooding in order to critically examine the model’s capability to forecast evolution of urban inundation. The model demonstrates high accuracy of results without incurring the computational expense of high spatial resolution over the entire model domain. MSN_Flood provides full characteristics of water levels and flow regimes necessary for flood hazard identification and flood risk assessment.
Landslides threaten communities globally, yet predicting their occurrence is challenged by uncertainty about slope properties and climate change. We present an approach to identify the dominant drivers of slope instability and the critical thresholds at which slope failure may occur. This information helps decision makers to target data acquisition to improve landslide predictability, and supports policy development to reduce landslide occurrence and impacts in highly uncertain environments.
Freezing rain is a high-impact wintertime weather phenomenon. The direct damage it causes to critical infrastructure (transportation, communication and energy) and forestry can be substantial. In this work a method for estimating the occurrence of freezing rain was evaluated and used to derive the climatology. The method was able to accurately reproduce the observed, spatially aggregated annual variability. The highest frequencies of freezing rain were found in eastern and central Europe.
The article aims at presenting the first-hand dataset and results from the field investigation, laboratory test, and numerical analysis for the flowslide
that occurred on 20 December 2015 in Shenzhen, China: a devastating event causing significant human and property losses. The article concluded that the
landfill stagnated groundwater flow and resulted in high water pressure due to the absence of a drainage system, with both disposal rate and amount
exceeding the maximum design capacity.
The goal of this study was to quantify the effect of forests on the occurrence frequency and intensity of rockfalls. This was done based on 3-D rockfall simulations for different forest and non-forest scenarios on a virtual slope. The rockfall frequency and intensity below forested slopes is significantly reduced. Statistical models provide information on how specific forest and terrain parameters influence this reduction and they allow prediction and quantification of the forest effect.