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The research uniquely focuses on advancing the field of fuzzy sets, specifically proposing a novel approach using Hexagonal Type-2 Fuzzy Variable (HT2FV), to handle higher degrees of uncertainty. Flooding, a recurrent and impactful phenomenon, necessitates a robust approach to effective disaster management. The study delves into the humanitarian supply chain dynamics during movement crises and flood catastrophes, introducing a novel methodology to harness the potential of HT2FV. Central to the paper is the innovative defuzzification concept of Critical Value (CV) reduction, strategically employed to eliminate fuzzy components within HT2FV, transforming it into crisp data. The research extends its novelty by proposing a comprehensive approach to distributing relief materials, employing a Multi-objective, Multi-level, Multi-modal (MOMLMM) approach, with a primary focus on boats for inundated areas. Significantly, the study aims to optimize the allocation of resources, minimize time and cost under uncertain environments, and enhance disaster relief operations. The paper is the first to use new hexagonal fuzzy numbers (HFNs) and focuses on how they can be used to sort vulnerable areas using the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of the Multi-Criteria Decision-Making (MCDM) process. A case study of the 2022 Assam flood is looked at and solved using the Weighted Sum (WS), Neutrosophic Compromise (NC), and Goal Programming (GP) systematically on the LINGO solver to see if the suggested method can be used. Further, sensitivity analysis is employed to establish optimal credibility levels to validate the proposed methods. A real-life case study lends practicality, substantiating the approach's efficacy. At the same time, comprehensive comparative analysis compares and contrasts findings from different studies to synthesize existing knowledge and identify future scope, contributing significantly to the field of fuzzy sets. [ABSTRACT FROM AUTHOR]

The research uniquely focuses on advancing the field of fuzzy sets, specifically proposing a novel approach using Hexagonal Type-2 Fuzzy Variable (HT2FV), to handle higher degrees of uncertainty. Flooding, a recurrent and impactful phenomenon, necessitates a robust approach to effective disaster management. The study delves into the humanitarian supply chain dynamics during movement crises and flood catastrophes, introducing a novel methodology to harness the potential of HT2FV. Central to the paper is the innovative defuzzification concept of Critical Value (CV) reduction, strategically employed to eliminate fuzzy components within HT2FV, transforming it into crisp data. The research extends its novelty by proposing a comprehensive approach to distributing relief materials, employing a Multi-objective, Multi-level, Multi-modal (MOMLMM) approach, with a primary focus on boats for inundated areas. Significantly, the study aims to optimize the allocation of resources, minimize time and cost under uncertain environments, and enhance disaster relief operations. The paper is the first to use new hexagonal fuzzy numbers (HFNs) and focuses on how they can be used to sort vulnerable areas using the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of the Multi-Criteria Decision-Making (MCDM) process. A case study of the 2022 Assam flood is looked at and solved using the Weighted Sum (WS), Neutrosophic Compromise (NC), and Goal Programming (GP) systematically on the LINGO solver to see if the suggested method can be used. Further, sensitivity analysis is employed to establish optimal credibility levels to validate the proposed methods. A real-life case study lends practicality, substantiating the approach's efficacy. At the same time, comprehensive comparative analysis compares and contrasts findings from different studies to synthesize existing knowledge and identify future scope, contributing significantly to the field of fuzzy sets. [ABSTRACT FROM AUTHOR]

Agricultural residues are a promising source of biomass energy. However, agricultural residues are seasonally available and loosely distributed over large geographical areas and hence require spatio-temporal assessment. Satellite image is a handy input for such assessment and high resolution image could increase the preciseness of estimation. In the present study, rice cropland is mapped using high resolution WorldView-2 satellite image in a rural area of Assam, India. The rice cropland map in combination with agricultural statistics is then analyzed in GIS in order to assess rice straw availability for potential bioenergy generation. About 54% land of study area belongs to rice cropland, which can contribute 5360 tonnes surplus rice straw per annum (equivalent to 83,296 GJ). Potential electric power capacity from the surplus rice straw in the study area is 523.50 kW. However, at individual village level the potential varies from 4.45 kW to 28.69 kW. Considering the power crisis in India, the findings of this work are expected to assist policy makers and biomass energy developers in decision making process. Particularly, this paper generated information on village level rice straw residue availability and subsequently potential electric power capacity. Such information is limited in the India expect for few states. [ABSTRACT FROM AUTHOR]

Abstract: This study aims at estimating the rate of bed aggradation of the Jia Dhansiri River in Assam, India. It is carried out using two methods: (1) measurement of channel cross section in the field, and (2) measurement of variously dated maps for the period 1995–2006. Following these two methods, data on parameters pertaining to bed aggradation are generated and authenticated by comparison. Data on total bed aggradation during 1995–2006 are extrapolated from cross section graphs and again verified with a model proposed in this paper based on average water level of base year and current year and total bed aggradation. The rates of bed aggradations are 5.27cm/y at Dhansiri Khuti village, 5.09cm/y at Barigain village, 5.27cm/y at Bagishakash village, and 2.64cm/y at Thalthali village. No degradation zones are found in between during the study period except in minor magnitude and localized cases. If these rates of bed aggradation are continued and no significant changes in the channel morphology occur, then the river bed may merge with the low river bank after 11years at Dhansiri Khuti village, 17years at Barigaon village, 6years at Bagishakash village, and 7years at Thalthali village. The average channel aggradation during 11–years of period in the 16–km reach has estimated to be 3.65cm/y. Again, if this rate is continued then the river bed will overtop low banks of the 16–km reach after 16years. At this situation the river may attain a state of geomorphic threshold which may be channel shift following vulnerable slope(s). [Copyright &y& Elsevier]