B1160
Title: Spatial modeling of drought events using max-stable processes
Authors: Marco Oesting - University of Stuttgart (Germany) [presenting]
Alfred Stein - University of Twente (Netherlands)
Abstract: Having severe environmental and socioeconomic impact, drought events belong to the most far-reaching natural disasters in Africa. We analyzed and modeled the spatio-temporal statistical behaviour of the Normalized Difference Vegetation Index (NDVI) as an indicator for drought, reflecting its effects on vegetation. The study used a data set for Rwanda obtained from multitemporal satellite remote sensor measurements during a 14 year period and divided into season-specific spatial random fields. Extreme deviations from average conditions were modeled with max-stable Brown-Resnick processes taking methodological and computational challenges into account. Those are caused by the large spatial extent and the relatively short time span covered by the data. Extensive simulations enabled us to go beyond the observations and, thus, to estimate several important characteristics of extreme drought events, such as their expected return period.
