Browsing by Author "Lucky Sharma"

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A multi-model approach to analyse multidimensional water poverty index in nepal: implications for sustainable water resource management
(Springer Science and Business Media B.V., 2025) Shiva Kant Dube; Lucky Sharma; Narendra Kumar Rana; Srabani Sanyal
Water poverty remains a pressing challenge in Nepal, where climate change, population growth, and rapid development exacerbate both scarcity and excess of safe water. Addressing this requires a systematic understanding of the socio-economic and environmental dimensions influencing water access. The present study attempted to study spatial variation in multi-dimensional water poverty employing multi-model approach utilizing multi-dimensional water poverty index (MWPI). Principal Component Analysis (PCA), Analytical Hierarchy Process (AHP), Shannon Entropy, and Equal Weight methods were employed to assess spatial variation in water poverty, while the Getis-Ord Gi* statistic was used to identify hotspots and cold spots. The findings reveal that areas under high to very high water poverty range from 39% to 46%, with PCA estimating 39.88%, Entropy 45.67%, Equal Weight 45.88%, and AHP 43.11%. A major hotspot with 99% confidence was identified in the northwestern region, whereas cold spots appeared in the northeastern region (95% confidence) and in central Nepal (99% confidence under entropy). Influential drivers varied across models, with resource and access dominating in PCA, access and capacity in Entropy, and resource and environment in AHP. Strong correlations (r > 0.70) were observed between PCA & AHP and Entropy & Equal Weight approaches, demonstrating methodological consistency. The findings highlight that despite Nepal’s abundant water resources, accessibility and community capacity remain critical barriers. The study recommends targeted interventions in hotspot regions to strengthen access and capacity, offering valuable insights for sustainable water resource management and policymaking. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
Advanced modeling of forest fire susceptibility and sensitivity analysis using hyperparameter-tuned deep learning techniques in the Rajouri district, Jammu and Kashmir
(Elsevier Ltd, 2025) Lucky Sharma; Mohd Rihan; Narendra Kumar Rana; Shiva Kant Dube; Md Sarfaraz Asgher
Forest resources are crucial for sustaining the global population, regulating climate services, and maintaining overall ecological balance. However, forest fires are causing a significant loss of forest cover worldwide. In this context, advanced deep learning techniques, which are novel to date, have been utilized to prepare forest fire susceptibility mapping. The present study aimed to predict forest fire susceptibility using three hyper-tuned techniques: deep neural network (DNN), elman neural network (ENN), and convolutional neural network (CNN). To identify the importance of influencing factors, sensitivity analysis was conducted using the DNN. The forest fire susceptibility map (FFSM) was categorized into five susceptibility zones: very high, high, moderate, low, and very low. Results indicated that the southern and southeastern parts of the study area are most prone to forest fires. The proportion of high susceptibility zone in the study area was found to be 34% for DNN, 37% for ENN, and 30% for CNN. Among all the models, DNN outperformed the others, achieving the highest accuracy of 0.8925, compared to ENN (0.8825) and CNN (0.87). Sensitivity analysis further revealed that evapotranspiration, temperature, land surface temperature (LST), distance to roads, aridity, and elevation were the most influential factors contributing to forest fires in the region. This study demonstrates an advanced and globally relevant approach to forest fire susceptibility analysis. The findings may be crucial for stakeholders and policymakers to make informed decisions regarding effective forest fire management and to protect vulnerable communities from unexpected losses. © 2025 COSPAR
Assessing Multi-hazard risk for disaster risk reduction in Jammu Division in North–West Himalayas, India
(Springer, 2024) Lucky Sharma; Narendra Kumar Rana; Shikha Singh; Shiva Kant Dube
The mountainous region, which holds a diverse ecosystem providing services of global importance, is fragile owing to the varied topography and continuous human pressure. The risk from natural hazards in mountainous regions is substantial posing significant challenges and causing causalities. Northwestern Himalayas being located in the junction of the Eurasian and Indo-Australian plates are delicate and face the brunt of vagaries from multiple hazards as well as anthropogenic pressure. Against this backdrop, the present study investigates multi-hazard risk assessment integrating both multi-hazard susceptibility and social vulnerability to look into possible high-risk-prone areas. The study makes use of frequency ratio in an ensemble with the Shannon entropy method to accomplish multi-hazard susceptibility (earthquake, floods, landslide, drought and forest fire), and for social vulnerability (a total of 13 indicators and 33 variables considered), Shannon information entropy model is utilized. The findings indicate that 58.40% area is highly and very highly susceptible to multi-hazard spanning across central, southeastern, northeastern and northwestern parts of the study area, whereas 40.59% area is highly vulnerable to multi-hazard covering western, northwestern, southwestern and southeastern parts of the study area. The results for multi-hazard risk indicated that southwestern, western and southeastern parts are highly risk prone areas accounting for 36.27% of the total geographical area. The study will be beneficial for the stakeholders in developing and putting into practice efficient strategies for disaster risk reduction. The study also recommends local adaptation strategies like Dhajji Diwari and surface excavation for more awareness and effective risk management. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Assessment of land use change and land degradation in Badagaon block, Jhansi district, India
(Springer Science and Business Media Deutschland GmbH, 2025) Neetesh Kumar; Narendra Kumar Rana; Lucky Sharma; Shiva Kant Dube
Land is a crucial resource under extreme pressure getting degraded due to overexploitation by increased urbanisation and high population growth. Thus, the risk from land degradation is significantly posing a serious threat to human lives by rendering land unproductive challenging food security and sustainability. In this backdrop, this paper attempted to assess the land degradation in semi-arid environment in Badagaon block of Jhansi district. The study is accomplished by finding the change in land use cover, loss of vegetation and soil erosion. Field survey is also conducted to identify the types of land degradation. The findings revealed that cropland increased by 90 per cent from 1996 to 2024 followed by built up area at the expense of natural vegetation and barren rocky lands got reduced by 24 per cent claimed by mining activities. Normalised difference Vegetation Index (NDVI) analysis showed that there is a drastic change in health of vegetation as evident from 0.96 (highest) indice value in 1996 to 0.45 in 2024. The soil erosion computed using RUSLE equation revealed higher erosion in agricultural area with moderate slopes as well as near-by river banks. Mainly sheet erosion, mining induced degradation, surface ponding and industrial waste identified using field survey have caused irreparable ecological damage. This intensified land degradation needs intervention such as soil conservation, effective water management strategies and continuous geo-monitoring of land degradation. This study would be beneficial for policy makers and stakeholders for implementing effective land use management strategies to tackle this environmental issue. Graphic abstract: (Figure presented.) © The Author(s), under exclusive licence to Accademia Nazionale dei Lincei 2025.
Examining social vulnerability to multi-hazards in North-Western Himalayas, India
(John Wiley and Sons Inc, 2024) Lucky Sharma; Narendra Kumar Rana; Shiva Kant Dube
The enhancing risk from human action and multi-hazard interaction has substantially complicated the hazard–society relationship. The underlying vulnerabilities are crucial in predicting the probable impact to be caused by multi-hazards. Thus, the evaluation of social vulnerability is decisive in inferring the driving factor and preparing for mitigation strategies. The Himalayan landscape is prone to multiple hazards as well as possesses a multitude of vulnerabilities owing to changing human landscape. Thus, an attempt has been made to inquire into the underlying socioeconomic factors enhancing the susceptibility of the region to multi-hazards. The social vulnerability index (SVIent) has been introduced, consisting of 13 indicators and 33 variables. The variables have been standardized using the maximum and minimum normalization method and the relative importance for each indicator has been determined using Shannon entropy methods to compute SVIent. The findings revealed that female population, population above 60 years old, net irrigated area, migrant population, dilapidated house, nonworkers, bank, and nonworkers seeking jobs were found to be relatively significant contributors to the vulnerability. The western part of the study area was classified as the highly vulnerable category (SVI > 0.40628), attributed to high dependence, and higher share of unemployed workers and high poverty. The SVIent was shown to have positive correlation between unemployment, socioeconomic status, migration, dependency, and household structure significant at two-tailed test. The study's impact can be found in influencing the decision of policymakers and stakeholders in framing the mitigation strategies and policy documents. © 2024 Society for Risk Analysis.
Exploring Local Scale Climatic Variability in West Rapti River Basin, Nepal
(Springer, 2025) Shiva Kant Dube; Narendra Kumar Rana; Lucky Sharma
Climate changes are inevitable, underscored by a growing populace and the concurrent expansion of infrastructure. The consequences extend from the local scale to the global necessitating a thorough investigation of local scale variation to devise appropriate measures. Therefore, this study is undertaken to scrutinize climatic variability within the West Rapti River Basin (WRRB) in Nepal for a forty-two-year period of 1981–2022. The spatio-temporal variation in mean monthly temperature and annual precipitation (as crucial parameters of climate) is studied annually, seasonally and monthly using the homogeneity test and trend analysis. The results are produced station wise and then reproduced in the map form for the WRRB. The findings indicate a notable rise of 2.7 mm per year in precipitation alongside a slight descend of 0.09 °C per year in temperature. The annual variation remarkably shows a significantly positive trend for precipitation, while temperature portrays a negative trend. The pre-monsoon and monsoon seasons show negative trends with acceptable significance in case of temperature whereas considering precipitation all seasons except winter show a substantially positive trend. Despite a decreasing trend in temperature, January and December display a positive change in trend contrasted by a negative trend in precipitation for the same months. The sub-basins lying in the eastern side exhibit high variability in case of precipitation, whereas the variability is high in sub-basins on the western side in case of temperature. This study revealed that the mean monthly temperature and annual precipitation trend is quite opposite to that of the global. This local scale variation has a significant impact on the livelihood of indigenous people, water resource management, and their adaptation strategies. Consequently, this study’s insights are pivotal for informing climate policy formulation in a Nepal’s context emphasizing the need for a tailored regulatory framework to address the region’s distinct climate change. © Indian Society of Remote Sensing 2025.
Investigating landslide susceptibility in the mountainous area of Union Territory Jammu and Kashmir, India: a comparative perspective
(Inderscience Publishers, 2024) Lucky Sharma; Narendra Kumar Rana; Gaggan Kumar
The escalation of geo-hazards, particularly landslides, has become a pressing concern, exacerbated by both natural factors and human activities. The frequency of rainfall-triggered landslides in mountainous regions is surging, posing imminent threats to lives and infrastructure. Jammu and Kashmir witness this peril throughout the year, affecting millions. This study focuses on creating a landslide susceptibility map for District Doda, employing a multi-method approach. A comparative analysis of multi-criteria decision method-analytical hierarchy process (AHP) and Shannon information entropy (SIE) determines their efficacy. The inventory, comprising 250 landslides, incorporates nine conditioning factors. AHP designates 91% of the area as very high or highly susceptible, while SIE identifies 46.49% as vulnerable. Area under curve (AUC) values of 0.898 and 0.976 for AHP and SIE, respectively, underscore the latter's superior predictive capability. This study is instrumental in aiding stakeholders with decision-making, land-use planning, and formulating effective mitigation strategies. Copyright © 2024 Inderscience Enterprises Ltd.
Micro-level assessment of agricultural vulnerability to climate variability in Mirzapur District, Uttar Pradesh
(Springer, 2025) Lucky Sharma; Shikha K. Singh; Priyanka Das; Priyanka Gupta; Nikhil Kumar Tiwary; Subham Oraon
The variation in climatic parameters like temperature, precipitation and humidity significantly influences agricultural ecosystem and human societies by affecting crop yield, cropping pattern and overall agricultural practices. Understanding agricultural vulnerability to these variations is crucial for preventing long-term consequences such as food security, changing human settlement patterns and economic instability. Thus, this study attempted to study micro level vulnerability in agriculture in Mirzapur district of Uttar Pradesh. The study aimed to introduce Agriculture Vulnerability Index (AVI) and evaluate the farmer perception about climate change and significant impact on agriculture utilising both primary and secondary data. The primary data was collected from 240 respondent using multistage random stratified sampling. The AVI was computed utilising Shannon Information Entropy method based on four indicators such as exposure to climatic variability, exposure, sensitivity, and adaptive capacity divided into 23 indicators. Ground Water Extraction (17.03%), Agricultural Wasteland (9.92%), Rural population (7.30%), and Barren land (6.21%) disproportionately influenced the agricultural vulnerability. The findings of the study revealed significant variation in agricultural vulnerability in which Hallia, Kon, Nagar, and Pahari block were found to be severely vulnerable to climatic variation. The farmers opinion revealed that the study area is experiencing erratic climatic variation like unseasonal rains and droughts causing serious distress to them. The agricultural landscape has undergone a notable transformation, characterized by a transition to a rice–wheat-gram cropping system, primarily facilitated by enhanced irrigation infrastructure as observed from primary survey. The farmers are compelled to revert to their old system of millet-gram-wheat cropping system due to increased ground water exploitation and present climatic variability. The research underscores the critical imperative of implementing agricultural diversification strategies, drought-resistant crop varieties, micro-irrigation, or policy incentives to mitigate climate vulnerability and improve food sustainability. The study reinforces the farmers opinion-based research to integrate indigenous knowledge system with conventional science-based knowledge to enhance resilience and ensure agricultural development at the micro level. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025.
Prioritization of Susceptibility Zones for Multi-Hazard Risk in Jammu Division of the North-West Himalayas, India for Disaster Risk Reduction
(IDRiM Society, 2024) Lucky Sharma; Narendra Kumar Rana
Environmental hazards have always been a source of serious concern as they are becoming more severe and wider in scope, enhancing the risk of additional losses to the environment and public health. The comprehensive risk assessment has emerged as a core component of disaster mitigation strategy. After the international convention on sustainable development in 1992, the multi-hazard approach is widely used as part of Disaster Risk Reduction (DRR) strategy. Lying in the vicinity of the North-West Himalayan region, Jammu Division is prone to multiple hazards which have led to numerous causalities. In this study, landslides, floods, earthquakes, droughts, forest fires and soil erosion are considered for prioritizing risk from multi-hazard. Analytical Hierarchy Process have been adopted for data processing for the standardisation and normalisation of the weights. The area prone to multiple hazards is delineated after overlaying all the individual assessment of hazard events using weights computed by an objective approach. The multi-hazard susceptibility map is categorised into five zones: very low, low, moderate, high and very high. The findings revealed that 43.43 % of area lying in south eastern, central and eastern part is suffering from multiple hazards are prioritized for preventing communities to suffer from the multiple hazards. This area lies in central part of the study area in proximity to faults and weak lithology. The identified area under multi-hazard should be well studied for potential cascading of hazards. The targeted interventions and proactive measures should be adopted for enhancing the resilience and disaster risk reduction. The prioritized zones will be extremely valuable for risk profiling, vulnerability assessment and formulation or revision of DRR strategy action plans. © 2024 IDRiM Society. All rights reserved.