Studies worldwide suggest that the risk of water shortage in regions affected by climate change is
growing. Decision support tools can help governments to identify future water supply problems in order
to plan mitigation measures. Treated wastewater is considered a suitable alternative water resource and
it is used for non-potable applications in many dry regions around the world. This work describes a
decision support system (DSS) that was developed to identify current water reuse potential and the
variables that determine the reclamation level. The DSS uses fuzzy inference system (FIS) as a tool and
multi-criteria decision making is the conceptual approach behind the DSS. It was observed that water
reuse level seems to be related to environmental factors such as drought, water exploitation index, water
use, population density and the wastewater treatment rate, among others. A dataset was built to analyze
these features through water reuse potential with a FIS that considered 155 regions and 183 cities.
Despite some inexact fit between the classification and simulation data for agricultural and urban water
reuse potential it was found that the FIS was suitable to identify the water reuse trend. Information on
the water reuse potential is important because it issues a warning about future water supply needs based
on climate change scenarios, which helps to support decision making with a view to tackling water
shortage.