Consideration of the multivariate nature of hydro-meteorological processes associated with hydrologic systems is important when assessing the availability of water resources and the risks caused by extreme events and when conducting rainfall-runoff simulation and modeling. Detailed statistical analysis of rainfall, as one of the main factors affecting water availability and extreme conditions, is required for estimating the design parameters. Storm depth, duration, inter-arrival duration, and areal spread are among the main features of rainfall process. One or more of these factors need to be analyzed depending on the type of hydrological application at hand. However, this is further complicated by the fact that a wide range of areal coverage and thereby durations of rainfall are usually of interest Linsley and Franzini 1979, p. 122. Intensity-duration-frequency curves are aimed at the requirements of obtaining extreme rainfall values for different durations and aid design of small to medium-sized drainage systems. Analysis of storm depth and duration, or intensity and duration, along with the inter-arrival duration, on the other hand, is required for applications such as deriving flood frequency distributions from climatic characteristics Eagleson 1972 and simulating rainfall events for the purpose of modeling rainfall-runoff, assessing water availability, and drought studies, among other activities. The application of Gumbel-Hougaard copula for trivariate rainfall frequency analysis in the paper involves the three rainfall variables storm depth, duration, and mean intensity of the annual largest rainfall events. The largest annual rainfall event is identified as the storm having the highest rainfall depth. The mean intensity is obtained as the ratio of the corresponding storm depth and duration. Any pair of two of these three variables constitute a bivariate data set as the joint occurrence of the constituents is random in nature. However, considering all three variables simultaneously makes this a nonsubstantive trivariate case as any one of the variables could be computed from the knowledge of the other two. In other words, as the third variable is algebraically determinable and does not have any randomness in its occurrence when the other two are given, a bivariate frequency analysis may suffice. This one-to-one relationship of mean intensity with depth and duration, as given by Eq. 18b in Zhang and Singh 2006 ,i s illustrated in the perspective plot in Fig. 1a. As in the paper, the annual largest storms at Liberty rainfall station for the period of 1980 to 2006 have been considered in this illustration. A minimum of six hours of dry period between storms is employed as the criteria to define the storms. This helps combine rain spells that are separated by less than six hours into single storms, as such intermittent spells are typically part of the same storm. This is also the criteria employed by the authors to identify the individual storms. It is seen, as expected, that all the observed data points fall exactly on the surface given by