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National Institute of Technology Calicut (2021)

Spatial Decision Support System for Drought Assessment and Management

Drisya J,

Titre : Spatial Decision Support System for Drought Assessment and Management

Auteur : Drisya J,

Université de soutenance : National Institute of Technology Calicut

Grade : Doctor of Philosophy (PhD) 2021

A spatial decision support system (SDSS) is an interactive computer system newlinedesigned to support the user or planners by providing a computing environment in a newlinegeographical information system (GIS) to solve complex problems that necessitate newlinespatial inputs. Drought, a natural phenomenon, has a widespread and significant impact newlineon the world s economy, environment, society and industries. Drought assessment, newlineforecasting and management measures evaluation have spatial and temporal newlinedimensions. Currently, there are no custom made tools readily available in the GIS newlineplatform for integrated drought studies. The overall objective is to develop a prototype newlineSpatial Decision Support System (SDSS) that can be used for drought assessment and newlinemanagement. Hence, an attempt has been made to design and develop a new spatial newlineDSS (Dme-SDSS). The Kalpathypuzha watershed in the Palakkad district of Kerala is newlinefacing severe drought in recent years, is considered as the case study catchment. newlineThe reliability of the output from SDSS largely depends on the input data quality, newlinealgorithms used for data processing and methodologies adopted. Therefore, it is newlineessential to assess the accuracy of the individual datasets in any project that employs newlinespatial data. The spatial data quality assessment is carried out for digital elevation newlinemodels (DEMs), soil map and land use map. Three freely available satellite-based newlineDEMs are compared for their accuracy using vector and raster-based techniques. It is newlinefound that the stream network generated using CartoDEM data has a minimum root newlinemean square error (31.72m) and mean absolute error (27.07m). The highest newlinecombination of correctness index (0.603) and figure of merit (0.491) is obtained for newlineCartoDEM derived stream network. Field investigations and laboratory tests were newlineconducted to analyse and categorise soil samples collected from various locations in the newlinewatershed. These results were used as reference data to compare and assess the quality newlineof the soil dataset.

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