Avaliação de incerteza dos fatores de caracterização regionalizados para escassez hídrica no semiárido brasileiro - Alves, Kilvia de Freitas (2019)
Despite the recommendations, sensitivity and uncertainties are still little incorporated in LCA studies, especially in obtaining characterization factors (CF). Andrade (2018) performed the regionalization of water scarcity CF by the AWARE model for the Brazilian semi-arid region. The mais goal of this study is to evaluate uncertainties and sensitivity in the regionalization of water scarcity CF for the Brazilian semi-arid region.The methodology used for the qualitative evaluation of uncertainties was the score of quality indicators according to an adapted Pedigree matrix (Weidema and Wesnaes, 1996). For the quantitative evaluation of uncertainties, classical statistical analysis and Monte Carlo simulations with 10,000 iterations were used to evaluate and propagate uncertainties, respectively. When estimating uncertainty parameters, coefficients of variation were estimated according to Meier (1997) and Sonnemann et al. (2003). For sensitivity analysis, scenario analysis was used by proposing 8 scenarios with variation of plus and minus 10% of each of the four input variables of the AWARE model and the unidirectional sensitivity analysis to understand its variation. The availability data obtained best score in the qualitative evaluation, while the ecosystem demand of Pastor et al. (2014) had the worse score. The results showed that the availability data of the Fluviometric Stations were mainly responsible for the uncertainties in the input data and, consequently, the output data. This is due to the great temporal variability typical of the Brazilian semi-arid region, which was considered in these data and disregarded in the other variables. It was also noted that the adoption of smaller data series led to the reduction of mean and standard deviation. It was also observed that moderate CF are more uncertain, while more extreme CFs show lower variation, corroborating with previous analyzes. The most sensitive variable was the availability. Aggregations led to more uncertain and sensitive CF, but there was no significant difference between agricultural, non-agricultural and generic aggregates. It was concluded that availability is a key issue in the regionalization of water scarcity by the AWARE model for the Brazilian semi-arid region. It was also concluded that, depending on the scope of each work, larger series can be adopted to cover the region's behavior over the years, or smaller series, in order to approach the current scarcity situation. Another option would be to adopt always the worst case, in order to avoid scarcity in all possible scenarios.