Methodology

Abstract

The proposed indicator was developed with the help of multi-criteria decision-making method analytical hierarchy process to make the index objective and artificial neural network variant group method of data handling to include cognitivity into the indicator. The parameter of the indicator was collected with respect to its citation frequency in the published literature. In the MCDM step, the input parameters were selected and rated based on different criteria. The weights of importance or priority value as derived from the MCDM method was used in the weight function to constitute the indicator. The ANN model was developed to provide cognitivity as well as to make it platform independent and also to hide the weights of importance of the parameters so that a non-preferential decision-making can be conducted. The output from climate models was used to estimate the climatic vulnerability of the selected river basins by the developed indicator.