Introduction

Drought is one of the extreme climatic events with important consequences for society. Unlike other weather events such as floods, hurricanes, tornadoes, with distributions rather restricted in the spatial and temporal scales, droughts present regimes more difficult to determine with regard to its duration; and its area of influence can be substantially larger than that for events mentioned above.

 Another difficulty in the case of drought, compared with the rest of extreme weather events, is to achieve a consensus on its definition. This adds to the difficulty of defining methods to determine, quantify, estimate or predict this kind of events.

Moreover, drought is not a static entity that can be expressed in terms of average values based on historical records. The trends with respect to global climate change and the sustained increase in the water demands by society results in  complex scenarios with dynamic relationships.
One factor aggravating the problem of the vulnerability of society in case of drought, apart from the possible definitions of drought that is adopted, is the uncertainty in estimating their spatial and temporal scale. There are several  approaches aimed at the phenomenon of drought, such as indicators for different spatial and temporal scales as well as complex simulation models designed to support early warning systems for drought. Independent of the approach, a common goal is the gradual reduction of uncertainty.

In this context, rather than the static situation related to knowing that a specific site is located in an area vulnerable to extreme events of drought, is the possibility of establishing how often or defining what is the probability of a drought with certain magnitude to occur. One possibility like this, however, is subject to one of the most common restrictions in the field of hydrologic analysis, which is the lack of an adequate source of records for estimating extreme events.

For these reasons, it is essential in arid and semi-arid areas, to use methodologies that allow more efficient use of available information for the purposes of estimating more accurately the probability associated with an event of drought and can be used in generating a map to an appropriate scale that facilitates decision-making. The Regional Frequency Analysis methodology is the best way of responding to these requirements and the purpose of the project, which is described here, is to promote professional skills in various institutions to tackle the task of developing a Drought Atlas for arid  and semiarid zones of Latin America and the Caribbean.

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