Micromega/IR: Design and status of a near-infrared spectral microscope for in situ analysis of Mars samples

MicrOmega is an ultra miniaturized spectral microscope for in situ analysis of samples. It is composed of 2 microscopes; one with a spatial sampling less or equal to 4 μm, working in 4 colors in the visible range: MicrOmega/VIS, and a NIR hyperspectral microscope working in the spectral range 0.9–4 μm with a spatial sampling of 20 μm per pixel: MicrOmega/IR (described in this paper). MicrOmega/IR illuminates and images samples a few mm in size and acquires the NIR spectrum of each resolved pixel in up to 320 contiguous spectral channels. The goal of this instrument is to analyze in situ the composition of collected samples at almost their grain size scale, in a non-destructive way. With the chosen spectral range and resolution, a wide variety of constituents can be identified: minerals, such as pyroxene and olivine, ferric oxides, hydrated phyllosilicates, sulfates and carbonates and ices and organics. The composition of the various phases within a given sample is a critical record of its formation and evolution. Coupled to the mapping information, it provides unique clues to describe the history of the parent body (planet, satellite and small body). In particular, the capability to identify hydrated grains and to characterize their adjacent phases has a huge potential in the search for possible bio-relics.     

Global rockfalls risk management process in ‘La Désirade‘ Island (French West Indies)

The Island of ‘La Désirade‘ is severely affected by rock falls. One house located in the area of ‘Le Souffleur‘ was partly destroyed by blocks in 1997, with two people injured. About 50 people still live under a dangerous cliff along the road from Beauséjour to Baie-Mahault, the two main villages of this eastern end of Guadeloupe archipelago. The first solution proposed by the state based on relocation of few houses was faced to population hostility. Solutions had to be reshaped and designed based on a global assessment of the different hazards affecting the Island (earthquakes, cyclones, flooding), on protection works taking into account the fact that French regulation prohibits new constructions behind protection fences, and on global and local land-use development. Risk management process has included technical analysis, social behaviour, cultural heritage of building and development, responsibility and regulation, short-term and long-term financing, land-use development strategy as well as information and communication. The solutions that are now being implemented seem to give satisfaction to all the partners. This example of landslide risk management carried out in La Désirade is discussed in this paper.     

Artificial intelligence for identifying hydrologically homogeneous regions: A state‐of‐the‐art regional flood frequency analysis

Due to the severity related to extreme flood events, recent efforts have focused on the development of reliable methods for design flood estimation. Historical streamflow series correspond to the most reliable information source for such estimation; however, they have temporal and spatial limitations that may be minimized by means of regional flood frequency analysis (RFFA). Several studies have emphasized that the identification of hydrologically homogeneous regions is the most important and challenging step in an RFFA. This study aims to identify state‐of‐the‐art clustering techniques (e.g., K ‐means, partition around medoids, fuzzy C‐means, K ‐harmonic means, and genetic K ‐means) with potential to form hydrologically homogeneous regions for flood regionalization in Southern Brazil. The applicability of some probability density function, such as generalized extreme value, generalized logistic, generalized normal, and Pearson type 3, was evaluated based on the regions formed. Among all the 15 possible combinations of the aforementioned clustering techniques and the Euclidian, Mahalanobis, and Manhattan distance measures, the five best were selected. Several watersheds' physiographic and climatological attributes were chosen to derive multiple regression equations for all the combinations. The accuracy of the equations was quantified with respect to adjusted coefficient of determination, root mean square error, and Nash–Sutcliffe coefficient, whereas, a cross‐validation procedure was applied to check their reliability. It was concluded that reliable results were obtained when using robust clustering techniques based on fuzzy logic (e.g., K ‐harmonic means), which have not been commonly used in RFFA. Furthermore, the probability density functions were capable of representing the regional annual maximum streamflows. Drainage area, main river length, and mean altitude of the watershed were the most recurrent attributes for modelling of mean annual maximum streamflow. Finally, an integration of all the five best combinations stands out as a robust, reliable, and simple tool for estimation of design floods.