Geography

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 zon...

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 Original Research Article Raha and Gayen; JGEESI, 22(1): 1-16, 2019; Article no.JGEESI.49074 2 Winexpo model outperforms the other models as it obtains minimized Standard Error (SE), Random Mean Square Error (RMSE), Mean Absolute Error (MAE...

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 identi...

Drought is a 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., Chottanagpur plateau, Deccan plateau, etc., are mostly affected by drought in India. In the past decade, Purulia District of West Bengal, which belongs to northeast part of Chottanagpur plateau, faced severe drought several times. But the assessment of drought in this area was far from a decesive proclamation till date. In this research, an attempt was made to compare the Holt-Winter additive and Holt-Winter multiplicative model in simulation (at 1 month lead time) of meteorological drought (using Standardized Precipitation Index (SPI) of Purulia District, West Bengal, India. The additive model showed better performance than the multiplicative model with minimized Root Mean Squared Error (RMSE) and higher correlation coefficient value (R2). The spatial assessment drought at pre-monsoon, monsoon and post-monsoon pha...

1. Necessity of the Data and Machine Learning Procedures Though there are a lot of work done on folklore and folkloristic but in most of the cases those is qualitative in nature. Thus whenever we compare between the regional variations of cultural belonging it seems to be ambiguous because sometimes it is hard to distinguish qualitatively. Here we feel the necessity of quantitative data and machine learning to integrate the relation between parameters of folklore study. The inherent culture, belief system, traditional belonging of a particular group of people is the effect of environmental determinism. The physical earth makes the harmony with the traditional way of life of human beings. Relationship between the environmental, physical and cultural parameters can be effectively portrayed through the machine learning algorithms. The climatic phenomena in relation to earth surface features can be mapped with GIS and machine learning helps to validate the whole features of it.

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...

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 (Sd) has been established. b) Considering Sd 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 Original Research Article Raha and Gayen; JGEESI, 22(1): 1-16, 2019; Article no.JGEESI.49074 2 Winexpo model outperforms the other models as it obtains minimized Standard Error (SE), Random Mean Square Error (RMSE), Mean Absolute Error (MAE),...

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.

Although the variability and prediction of rainfall is an essential issue of the Santhal Pargana Division of the Jharkhand State but the issue is still far from its' conclusive statement till date. Therefore, this study aimed to simulate the monthly rainfall from 1901 to 2020 using an eight-step procedure. After downloading the monthly rainfall for the Santhal Pargana Division from 1901 to 2020, the TBATS and Naive models were used to simulate the rainfall. The accuracy assessment of each model was done by using the MASE, MAE, RMSE, ME, and R. For the Naïve model, the Godda station was noticed with a comparatively high combined error. The lowest combined error was found for the Pakur station in case of Naïve models. Similar result was also obtained for the TBATS model. The TBATS was found with comparatively higher accuracy, as the combined error was less for the TBATS. The spatial assessment for the standardized rainfall varied from 84.419 mm. to 149.225 mm. For the Naïve predicted model, the rainfall was marked in between 8.133 mm. to 67.059 mm. For the TBATS fitted model, the rainfall fluctuated from the 37.127 mm. to 62.993 mm. Dumka station was noticed with comparatively low rainfall (i.e.,37.127 mm.). Deoghar and Jamtara stations were marked with a moderate rainfall. Remaining stations were marked with higher amount of rainfall for the TBATS fitted model. The Wilcoxon test proved that each model was significant at 95% confidence interval. The result produced in this research is fruitful enough to be utilized for agricultural planning in the Santhal Pargana Division of the Jharkhand state, India.