Sensitivity and uncertainty analysis of water footprint application and its scenarios on watersheds

Abstract

The Water Footprint indicator has been gained ever wider space in several areas of study and market niches, however, it has also been an object of several questions about the reliability of the results released for the products and sectors all over the world. Our primary goal here is to propose the analysis of sensitivity and uncertainty of the WF´s components (WFblue, WFgreen and WFgrey) and the total WF, as well as checking the uncertainty propagation in the next stages of assessment, mitigation and scenarios of WF in watersheds. In this study, we will use the following methodologies for uncertainty analysis: Séries de Taylor; Bayesian Recursive parameter Estimation (BaRE); Markov Chain Monte Carlo (MCMC); e Generalised Likelihood Uncertainty Estimation (GLUE). While the sensitivity analysis will be assessed by Monte Carlo simulation. The uncertainty scenarios will be evaluated in the steps of defining and implementing the scenarios proposed. Thus, taking into account international collaboration, we hope that project results can help the consolidate an adequate methodology for sensitivity and uncertainty analysis of the WF results. Moreover, we expect to help develop this study theme, which is still little explored in Brazil, but is very important in the water resources management context. We intend to disclose of the results in the form of 2 papers to be published in journals with high impact factor at water resources area, as well as the presentation and discussion in national and international scientific events. (AU)