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A recent advancement in petroleum geochemistry is to model fossil oil composition using microthermometric and volumetric data acquired from individual¯uid inclusion analysis. Fourier Transform Infrared (FT-IR) microspectroscopy can record compositional information related to gas (CH 4 and CO 2 ) and alkane contents of petroleum inclusions. In this study, a quantitative procedure for FT-IR microspectrometry has been developed to obtain, from individual¯uid inclusions, mol percentage concentrations of methane, alkanes and carbon dioxide as constraints to thermodynamic modelling. A petroleum inclusion in a sample from the Que  bec City Promontory nappe area was used as a standard to record a reference spectrum of methane. The analytical procedure is based on the measurement of CH 4 /alkane and CH 4 /CO 2 band area ratios. CH 4 /alkane infrared band area ratio is obtained after spectral subtraction of the reference methane spectrum. This area ratio, affected by absolute absorption intensities of methane, methyl and methylene, provides a molar CH 4 /alkane ratio. Methyl/methylene ratio (CH 2 /CH 3 ) ratio is obtained following procedures established in previous work. CO 2 /CH 4 concentration ratio is estimated from relative absolute absorption intensities. Application to natural inclusions from different environments shows good correlation between FT-IR quanti®cation and PIT (petroleum inclusion thermodynamic) modelling.

The violent storms of 22-30 November 2014, resulted in flash floods and wadi floods (rivers) in large parts of Southern Morocco, at the foot of the Atlas Mountains. The Guelmim area was the most affected part with at least 32 fatalities and damages due to inundations. The flooding hazard in the Guelmim region initiated this study in order to investigate the use of remote sensing and geographic information system (GIS) for the detection and identification of areas most likely to be flooded in the future again due to their morphologic properties during similar weather conditions. By combining morphometric analysis and visual interpretation based on Landsat 8 satellite data and derived images such as water index (NDWI) images, areas with relatively higher soil moisture and recently deposited sediments were identified. The resulting maps of weighted overlay procedures, aggregating causal, morphometric factors influencing the susceptibility to flooding (lowest height levels, flattest areas), allowed for the distinguishing of areas with higher, medium and lower susceptibility to flooding. Thus, GIS and remote sensing tools contribut to the recognition and mapping of areas and infrastructure prone to flooding in the Guelmim area.

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