Testing a new application for TOPSIS: monitoring drought and wet periods in Iran

Abstract

Globally, droughts are a recurring major natural disaster owing to below normal precipitation, and are occasionally associated with high temperatures, which together negatively impact upon human health and social, economic, and cultural activities. Drought early warning and monitoring is thus essential for reducing such potential impacts on society. To this end, several experimental methods have previously been proposed for calculating drought, yet these are based almost entirely on precipitation alone. Here, for the first time, and in contrast to previous studies, we use seven climate parameters to establish drought/wet periods; these include: T min, T max, sunshine hours, relative humidity, average rainfall, number of rain days greater than 1 mm, and the ratio of total precipitation to number of days with precipitation, using the technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. To test the TOPSIS method for different climate zones, six sample stations representing a variety of different climate conditions were used by assigning weight changes to climate parameters, which are then applied to the model, together with multivariate regression analysis. For the six stations tested, model results indicate the lowest errors for Zabol station and maximum errors for Kermanshah. The validation techniques strongly support our proposed new method for calculating and rating drought/wet events using TOPSIS.