In its three-dimensional (3-D) characterization, drought is approached as an event whose spatial extent changes over time. Each drought event has an onset and end time, a location, a magnitude, and a spatial trajectory. These characteristics help to analyze and describe how drought develops in space and time, i.e., drought dynamics. Methodologies for 3-D characterization of drought include a 3-D clustering technique to extract the drought events from the hydrometeorological data. The application of the clustering method yields small ‘artifact’ droughts. These small clusters are removed from the analysis with the use of a cluster size filter. However, according to the literature, the filter parameters are usually set arbitrarily, so this study concentrated on a method to calculate the optimal cluster size filter for the 3-D characterization of drought. The effect of different drought indicator thresholds to calculate drought is also analyzed. The approach was tested in South America with data from the Latin American Flood and Drought Monitor (LAFDM) for 1950–2017. Analysis of the spatial trajectories and characteristics of the most extreme droughts is also included. Calculated droughts are compared with information reported at a country scale and a reasonably good match is found.

Drought is a major threat to global agriculture and can trigger or intensify food price increase and migration. Assessment and monitoring are essential for proper drought management. Drought indices play a fundamental task in this respect. This research introduces the Wet-environment Evapotranspiration and Precipitation Standardized Index (WEPSI) for drought assessment and monitoring. WEPSI is inspired by the Standardized Precipitation Evapotranspiration Index (SPEI), in which water supply and demand are incorporated into the drought index calculation. WEPSI considers precipitation (P) for water supply and wet-environment evapotranspiration (ETw) for water demand. We use an asymmetric complementary relationship to calculate ETw using actual (ETa) and potential evapotranspiration (ETp). WEPSI is tested in the transboundary Lempa River basin located in the Central American dry corridor. ETw is estimated based on evapotranspiration data calculated using the Water Evaluation And Planning (WEAP) system hydrological model. To investigate the performance of our introduced drought index, we compare it with two well-known meteorological indices (Standardized Precipitation Index and SPEI), together with a hydrological index (Standardized Runoff Index), in terms of correlation and mutual information (MI). We also compare drought calculated with WEPSI and historical information, including crop cereal production and Oceanic Niño Index (ONI) data. The results show that WEPSI has the highest correlation and MI compared with the three other indices used. It is also consistent with the records of crop cereal production and ONI. These findings show that WEPSI can be applied for agricultural drought assessments.