Water scarcity and drought management is the burning issue in India and hence needs serious attention of researchers to develop rigorous plan and management. Areas that belong to various plateaus, e.g., Chotanagpur plateau, Deccan plateau, etc., are mostly affected by drought in India. In the past decade, Bankura District of West Bengal, which belongs to northeast part of Chotanagpur plateau, faced severe drought several times. However, the assessment of drought scenario in this area is far from conclusive statement till date. In this paper, we simulate standardized precipitation index (SPI) using double exponential (DE) and Holt-Winter exponential smoothing model (HW) for several time steps (e.g., 3 months, 6 months, 12 months, 24 months and 48 months) in the time period of 1979-2014. The comparative analysis between two models indicates that DE is more accurate one. DE is observed with relatively low root mean squared error (RMSE) and high R 2 value. Furthermore, drought-prone zones are demarcated using combined scores of principal component analysis (PCA) and those combined scores are estimated using actual, HW and DE simulated SPI in several time steps. At the shorter (3 and 6 months) and longer time step (12, 24 and 48 months), the PCA demonstrates almost same results. The western and northwestern blocks of the district are severely affected by drought, and the southern portions are at mild condition. Spatially distributed RMSE in every time steps is also high in northwestern portions of the study region. Our result may be useful to understand the pattern of drought to take necessary action in management of water resources in Bankura District, West Bengal. Moreover, the study uses an unique methodology to simulate and assess meteorological drought, which is applicable in any region of the world.
This study was designed to demarcate the Ecotourism Potential Zones (ETPZs) of West Bengal using the Analytic Hierarchy Process (AHP) and weighted linear algorithm by considering three sustainable tourism parameters and sixteen indicators. Those three parameters are 1) physical (P), 2) social (S), and 3) availability of scenic beauty and infrastructures (ASI). Overall, 5 parameters are merged under physical (P), 2 parameters are integrated under social (S), and 9 parameters are incorporated under availability of scenic beauty and infrastructures (ASI). A 4-step procedure has been adopted for this study: 1) a simple hierarchical structure has been outlined, 2) pair-wise comparison matrices are formed, 3) weighted linear algorithm technique is utilized to get the ecotourism potentiality zone, and 4) ecotourism potentiality map is classified into high, moderate and low categories based on the principle of Dominant and Distinctive Function (DDF). As a result, about 61.65% area is identified with high ecotourism potential zone, 17.86% area is observed under the moderate ecotourism potential zone, and 20.48% area is recognized as the low ecotourism potential zone. Thus, the study considers an exceptional methodological framework that is applicable in any region of the world.
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