Spatiotemporal Drought Analysis at Country Scale Through the Application of the STAND Toolbox

Abstract

Understanding, characterizing, and predicting drought is vital for the reduction of its consequences. In the last few decades, many studies have moved drought analysis from the conventional lumped approach to a more spatiotemporal analysis. Two main developments have motivated this: one is global data availability and the other is the number of models developed to understand and quantify drought. The first one relates to information available from reanalysis products, and the second regards global and regional, distributed and semidistributed model data. Moreover, nowadays, different organizations provide drought monitoring information in near real time. However, a few spatiotemporal analysis studies have been developed slowly and the availability of comprehensive tools is still limited. This chapter proposes a new toolbox that performs the Spatio-Temporal ANalysis of Drought (STAND) in MATLAB, step by step. The toolbox collects some of the applications of previous studies and innovates new concepts on the characterization of drought. The methodologies here allow estimation of drought duration, severity (magnitude), and area, redefining the drought event in space and time. A key component in the analysis is the visualization of outcomes, as well as the spatial interpolation of pointwise data. The proposed STAND toolbox is explained and its use is illustrated with two large-scale examples (India and Mexico). The results have been compared with local reported information. STAND outcomes have been shown to help follow space–time events in terms of patterns, and provide information related to the characterization of extremes for drought analysis.