Ines Oueslati

This research aims at quantifying some hydrological processes such as runoff, through the identification of physical and chemical soil properties (texture, structure, bulk density, organic matter…) that are in direct relationship with the hydraulic parameters (mainly soil moisture and hydraulic conductivity). The main issue is to find tools and methodologies that can predict and generate an accurate spatial distribution of the soil properties. Those tools include the use of pedotransfer functions that aim to predict hard to measure soil properties from primary soil data (texture, porosity,..) and the digital soil mapping that can be defined as the creation, and population of spatial soil information systems by the use of field and laboratory observational methods coupled with environmental factors called ancillary data (following the corpan model: climate variables (c), vegetation and land use (o), relief (r), parent material (p), age (a) and spatial coordinate (n)) using statistical and geostatistitical techniques. Current activity deals with the prediction of the top soil organic matter in forestThis research aims at quantifying some hydrological processes such as runoff, through the identification of physical and chemical soil properties (texture, structure, bulk density, organic matter…) that are in direct relationship with the hydraulic parameters (mainly soil moisture and hydraulic conductivity). The main issue is to find tools and methodologies that can predict and generate an accurate spatial distribution of the soil properties.