This study presents the criteria and conditions that supported the development of a proposed vulnerability index and its application in the Crrego do Ribeiro do Feijo Basin, which is located in the central portion of the state of So Paulo, southeastern Brazil. This basin was selected, because it is representative of very large areas in the south, west, and southeast regions of Brazil, is the main source of freshwater for the municipality of So Carlos, and has been undergoing accelerated changes due to diversified anthropogenic activities, thus increasing the number of contaminant sources. The proposed index is based on a hierarchy of information that includes a total of 46 attributes categorized into groups (4 rainfall attributes, 6 point contaminant sources, 5 non-point contaminant sources, 5 unconsolidated material 1, 4 unconsolidated material 2, 4 rock substrate 1, 4 rock substrate 2, 1 relief, 6 unconsolidated material 3, 4 rock substrate 3, and 3 groundwater), which were obtained from principles and procedures of engineering geological mapping and laboratory tests. The final vulnerability index for each land unit was obtained as a percentage using the total vulnerability index, which is the sum of the partial indices (these indices are normalized eigenvectors of the unit) and the maximum value that a unit can reach, considering the classes of maximum influence in vulnerability. The basin was divided into 29 categories controlled by engineering geological units and types of land uses, resulting in 94 land units, of which 17 were classified as Class 1, with the highest vulnerability; 41, 23, and 13 were classified as Classes 2, 3, and 4, respectively, with decreasing degrees of vulnerability. The results verify that the proposed index enables an adequate subdivision of the region and classification of the units, respecting the natural variability and the anthropogenic aspects. The attributes associated with land units and the datasheet used for data treatment permit a dynamic vulnerability analysis, because it is easier to identify and characterize the anthropogenic changes (mainly related to contaminant sources) per land unit in situ and to obtain new results that will require new control or planning measures. (AU) |