  Changing climate signals and the continuous world population growth requires
proper hydrologic risk analysis to build and operate water resource
infrastructures in a sustainable way. Although modernized computational
facilities are becoming popular to understand complex systems, there is not a
proper approach for the space - time analysis of extreme rainfall events. Many
statistical approaches have been suggested to describe the space-time structure
of rainfall; nevertheless, none of them is good enough to represent, for all
observational scales, the geometrical structure observed in either rainfall
time series or rainfall-derived spatial fields. This research presents a
geometric approach to understand the intensity - area - duration - frequency
(IADF) relationship without losing information or statistical assumptions.
Moreover, this study introduces a promising conceptualization about how
understand the space-time structure of rainfall via codimension functions and
dynamic scaling theory.
