Assessing Rainfall-EVI Relationships in the Okavango Catchment Employing MODIS Time Series Data and Distributed Lag Models

Aboveground net primary productivity (ANPP) is limited by water availability especially in dry and desert regions, and many studies have linked ANPP to current and previous “effective” rainfall events. In this study a distributed lag model (DLM) was used to assess the impact of current and previous 16 day rainfall anomalies on the Enhanced Vegetation Index (EVI) as a proxy for ANPP in the Okavango catchment (South Africa). The two important aspects in using DLMs are the explained total ANPP variability by the rainfall regime and the duration of that dependency. The results indicate that more than 50 % of the Okavango Basin are sensitive towards current and previous rainfall anomalies. These regions are mainly restricted to the southern semi-arid parts of the catchment, whereas in the humid and sub-humid northern areas significant correlations were observed only locally. Here, the dominant land cover classes are shrub- and grassland, thornbush savannahs and mixed woodlands. The duration of significant rainfall-EVI dependencies ranges from concurrent anomalies to a time-shift of 3.5 months. A logistic regression model was applied to discriminate among the sensitive and non-sensitive areas in the basin in terms of possible physiogeographic covariates. The model was able to correctly classify ~80 % of the available pixels. Most relevant explanatory covariates were evaporation, elevation and land cover.