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 R² 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.

Since the drought is a significant issue in India, therefore, the scientists should pay close attention in order to manage it. Purulia District experienced the drought on numerous occasions in the past ten years, but the accurate and definite conclusions have not arrived yet. Hence, the Standardized Precipitation Index (SPI) for the 34 years (1979–2014) was utilised in this research together with the change point to evaluate the annual and seasonal drought in the Purulia District. Theil Sen's slope and the Mann-Kendal (MK) test were both employed to determine the trend and its’ magnitude. A trend-free pre-whitening technique was used to remove the influence of lag-1 correlation data from the series. The 1988-89 was marked as the best probable single change (shift) point in the time series of SPI. By calculating the percentage deviation from the SPI's mean trend, the magnitude of the change was calculated. The percentage change of Sen's slope and MK test was high (+ve) at the eastern parts of Purulia, whereas it was observed as the smallest at the southern parts of the region. Thus, it could be concluded that the drought had begun to spread to the study region's eastern sections after the change point. As Purulia is dependent on agricultural crop production, this research would significantly contribute to agricultural planning following the local level management of crop water and rain-water harvesting. Therefore, this research is extremely important for the drought risk management on a regional scale.

Simulation of drought is needed for proper planning and management of water resources. This study has been developed using the following five key points: a) primarily from rainfall Standard Precipitation Index (SPI), Percentage to Normal (PN), Decile based drought index (DI), Rainfall Anomaly Index (RAI), China Z Index (CZI), and Z-score are estimated on yearly basis (1901-2017), those indices are added and a new index standardized total drought (S_d) has been established. b) Considering S_d as the input parameter a comparative assessment has been made between 4 individual models (3 models from exponential smoothing, 1 model from machine learning) in simulation and prediction of drought status of next 18 time steps (years) in Bankura District and Winexpo model outperforms the other models as it obtains minimized Standard Error (SE), Random Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) and highest Correlation coefficient (R²) value. c) The cumulative drought proneness of the region is also assessed and it is found that the whole district will be drought-prone within the year 2100. This region is historically a drought prone region and agricultural shock is the common issue. In such a circumstance simulation of drought is a good attempt. Though a lot of models already developed in case of simulation of drought but still a perfect, continuous long term prediction is a big issue to solve. This study provides a comparative study between exponential smoothing and machine-learning procedures and also introduces a new combined index standardized total drought.

Tourism is a multidimensional sector having significant contributions to sustainable development, economic upliftment, and social benefits. Although the Bankura is full of tourism potential, but its’ tourism potentiality has not been properly used. This study is designed to identify the tourism potential zones of the Bankura district using a 5-steps integrated methodology, which includes the preparation of the thematic layers (Eight parameters and thirty-four indicators) (Step-1); creation of matrices for pair-wise comparisons (Step-2); classification of the raster maps (Step-3); use of the weighted sum method to get the composite variables (Step-4) and classification of tourism potential map using the natural breaks (Step-5). This study has selected eight parameters, which are the Tourist Intensity Measure (TIM), Climate (C), Physical (P), Social (S), Economy (E), Environmental Quality (EQ), Amenities (AN), and Diversity in Local Art and Crafts (LAC′). Approximately, 23.33% area is identified with a high tourism potentiality, 58.74% area is observed under the moderate tourism potentiality, and 17.92% area is recognized as a low tourism potentiality. Efficiency testing of the tourism potentiality map indicates high precision utilizing the considerably high R-square value (0.94). The study uses an exceptional methodological framework applicable in any region.