Browsing by Author "Narendra Kumar Rana"

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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
Analysis of morphological change of lentic water bodies by using spatial vulnerability index (SVI) in Tarai region of Rapti river plains, India
(Taylor and Francis Ltd., 2024) Alka Singh; Vishwambhar Nath Sharma; Narendra Kumar Rana
Spatio-temporal analysis of waterbodies in terms of detection of morphological change could serve as a guiding tool to restore the lentic ecosystem. This research analysed the loss of lake extent within 50 years (1969–2019) through natural, anthropogenic reasons, as well as a lack of attention to protecting lakes in the Tarai region. In 1969, 75 lakes were found, but now only 46 lakes are alive. Among the 75 lakes, seventeen transformed into large ponds after reduction in extent, and twelve lakes either appeared as waterlogging zones during the rainy season or were permanently extinct and used as agricultural fields’ built-up activities. The spatial vulnerability index (SVI) measured the level of deterioration and urgency of lake restoration. 8 lakes were determined to be highly vulnerable (below 29.26%) and lost about 311.20 hectares of potential area of lake beds due to gradual increasing shallowness. Regression analysis measured a very weak correlation between the reducing percent of lake extent (during 50 years) and current lake extent (R2 = 0.1336), average depth (R2 = 0.0035), circumference (R2 = 0.0543), and volume (R2 = 0.0728) of 46 lakes. This study elucidated the restoration practices of the lakes to prevent their gradual extinction. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON).
Analysis of morphological change of lentic water bodies by using spatial vulnerability index (SVI) in Tarai region of Rapti river plains, India
(Taylor and Francis Ltd., 2025) Alka Singh; Vishwambhar Nath Sharma; Narendra Kumar Rana
Spatio-temporal analysis of waterbodies in terms of detection of morphological change could serve as a guiding tool to restore the lentic ecosystem. This research analysed the loss of lake extent within 50 years (1969–2019) through natural, anthropogenic reasons, as well as a lack of attention to protecting lakes in the Tarai region. In 1969, 75 lakes were found, but now only 46 lakes are alive. Among the 75 lakes, seventeen transformed into large ponds after reduction in extent, and twelve lakes either appeared as waterlogging zones during the rainy season or were permanently extinct and used as agricultural fields’ built-up activities. The spatial vulnerability index (SVI) measured the level of deterioration and urgency of lake restoration. 8 lakes were determined to be highly vulnerable (below 29.26%) and lost about 311.20 hectares of potential area of lake beds due to gradual increasing shallowness. Regression analysis measured a very weak correlation between the reducing percent of lake extent (during 50 years) and current lake extent (R2 = 0.1336), average depth (R2 = 0.0035), circumference (R2 = 0.0543), and volume (R2 = 0.0728) of 46 lakes. This study elucidated the restoration practices of the lakes to prevent their gradual extinction. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON).
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.
Assessment of Soil and Sediment Loss in the Ken River Basin, Central India, Using RUSLE and InVEST SDR Models
(John Wiley and Sons Inc, 2025) Suresh Chandra Bhatt; Moirangthem Mourdhaja Singh; Sudhir Kumar Kumar Singh; Narendra Kumar Rana; Rakesh Kumar Kori; Adesh Patel; Hrithik Sachan
Assessing soil and sediment loss are the main aims of the paper using the Revised Universal Soil Loss Equation (RUSLE) and the InVEST SDR models in the Ken River Basin (KRB). The annual soil loss varied from few-ton/hectare/year to 1630.5. The high erosion susceptibility was prevalent in the elevated area and low soil erosion severity was seen in the low-lying plains of the middle and lower reaches. The maximum sediment export (430.16-ton/hectare/year) was noticed in the hills of the Vindhyans, Bundelkhand, and Deccan traps. Contrary to this the low sediment transport was observed in the flat alluvium plains. The conservation practices are slightly more effective in the KRB. Its crop cover reduces the impact of rain's kinetic energy, increase recharge, and mitigates soil erosion. These research output may be helpful to planners in minimizing soil and sediment loss and in enhancing the soil conservation and agricultural productivity. © 2025 Wiley Periodicals LLC.
Enhancing drought resilience: machine learning–based vulnerability assessment in Uttar Pradesh, India
(Springer, 2024) Barnali Kundu; Narendra Kumar Rana; Sonali Kundu
Drought is a natural and complex climatic hazard. It has both natural and social connotations. The purpose of this study is to use machine learning methods (MLAs) for drought vulnerability (DVM) in Uttar Pradesh, India. There were 18 factors used to determine drought vulnerability, separated into two groups: physical drought and meteorological drought. The study found that the eastern part of Uttar Pradesh is high to very highly prone to drought, which is approximately 31.38% of the area of Uttar Pradesh. The receiver operating characteristic curve (ROC) was then used to evaluate the machine learning models (artificial neural networks). According to the findings, the ANN functioned with AUC values of 0.843. For policy actions to lessen drought sensitivity, DVMs may be valuable. Future exploration may involve refining machine learning algorithms, integrating real-time data sources, and assessing the socio-economic impacts to continually enhance the efficacy of drought resilience strategies in Uttar Pradesh. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Estimation of Morphometric and Morphotectonic Indices of the Kanhan River Basin, Central India, Implication for Susceptibility of Soil Erosion and Groundwater Potential
(Springer Science and Business Media Deutschland GmbH, 2025) Suresh Chandra Bhatt; Moirangthem Mourdhaja Singh; Pallvi Rana; Adesh Patel; Narendra Kumar Rana; Sudhir Kumar Kumar Singh; Kaushal Kishor
The Kanhan River, the Wainganga’s longest tributary, runs through the central Indian districts of Chhindwara and Nagpur. The SRTM, remote sensing, and GIS data, were used to investigate morphometric and morphotectonic indices of the Kanhan River Basin and these parameters (linear, areal, and relief) were further employed to assess the vulnerability of the basin to soil erosion, flood hazards, groundwater potential, and tectonic activity. Several morphotectonic parameters including lineament, lineament density, sinuosity, hypsometric integral, and drainage basin asymmetry were estimated for the Kanhan River Basin (KRB). The lineament density was validated across five classes ranging from 0 to 0.91 km/km2. We observed that a high lineament density indicates a high ground water potentiality. The hypsometric integral value (HI = 0.315) suggests that the Kanhan River is in its old or monadnock stage. The Standard Sinuosity Index (SSI) infers that the river follows a sinuous course. The Hydraulic Sinuosity Index (HSI = 61%) suggests that the river has developed flood plains during excessive flooding. The transverse topographic symmetry (TTS) ranges from 0.07 to 0.57, which shows that the basin has an asymmetric nature. Based on these findings, we can interpret that the elongated basin dominated by the old stage is represented by low stream frequency, high permeability, mild slope, and low surface runoff. © The Author(s), under exclusive license to Springer Nature Switzerland AG 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.
Governance Issues for Sustainable Water Management in Rapti River Basin, Uttar Pradesh
(Springer, 2021) Narendra Kumar Rana; Neha Singh
During the last two decades, various key concepts emerged in the field of water management both in developed as well as developing countries. In the developing world compulsion for the integration of ecological, social, and economic aspects of sustainable development in water management led to several debates on the notions of integration, good water governance, and participatory water management. The present empirical study on a small river basin shows that even if integration, good governance, and participation have many potential benefits, these are difficult to achieve in practice. In this context, a critical analysis of water resource management is pertinent. The Rapti is a hill-fed river basin shared by two riparian nations, i.e., India and Nepal. Due to inadequate management, the resource potential of the river basin is not fully utilized, rather the river became a symbol of underdevelopment in the region. With the increasing concentration of anthropogenic activities both at upstream as well as downstream part, river ecology has been continuously degrading and numbers of environmental and social conflicts are emerging. With the help of primary and secondary data, the study highlights how integration is difficult in the case of a river shared by two riparian nations and identified the complexity caused by multiple stakeholders at the basin level. The study also identifies a number of governance issues like, management of floodplains and their resources, compliance to flood forecasting and warning, public utility management within the active channel zones, annual maintenance of river banks, illegal sand mining, integration of development schemes within the context of floodplain environment, livelihood issues and incorporation of community expectations that need to be prioritized for sustainable water management at basin scale at microlevel. Besides, the study highlighted several potential issues for future research. © Springer Nature Switzerland AG 2021.
Integration of SPEI and machine learning for assessing the characteristics of drought in the middle ganga plain, an agro-climatic region of India
(Springer, 2024) Barnali Kundu; Narendra Kumar Rana; Sonali Kundu; Devendra Soren
Drought, as a natural and intricate climatic phenomenon, poses challenges with implications for both natural ecosystems and socioeconomic conditions. Evaluating the characteristics of drought is a significant endeavor aimed at mitigating its impact on society and individuals. This research paper explores the integration of the Standardized Precipitation Evapotranspiration Index (SPEI) and machine learning techniques for an assessment of drought characteristics in the Middle Ganga Plain, a crucial agro-climatic region in India. The study focuses on evaluating the frequency, intensity, magnitude, and recurrence interval of drought events. Various drought models, including Random Forest (RF), Artificial Neural Networks (ANN), and an ensemble model combining ANN and RF, were employed to analyze and predict drought patterns at different temporal scales (3-month, 6-month, and 12-month). The performance of these models was rigorously validated using key metrics such as precision, accuracy, proportion incorrectly classified, over-all area under the curve (AUC), mean absolute error (MAE), and root mean square error (RMSE). Furthermore, the research extends its application to delineating drought vulnerability zones by establishing demarcations for high and very high drought vulnerability areas for each model and temporal scale. Results indicate that the south-western part of the middle Ganga plain falls under the highly drought-vulnerable zone, which averagely covers 40% of the study region. The core and buffer regions of drought vulnerability have also been identified. The south-western part of the study area is identified as the core region of drought. Ground verification of the drought-vulnerable area has been done by using soil moisture meter. Validation metrics show that the ensemble model of ANN and RF exhibits the highest accuracy across all temporal scales. This research's findings can be applied to improve drought preparedness and water resource management in the Middle Ganga Plain. By identifying high-risk drought zones and utilizing accurate prediction models, policymakers and farmers can implement targeted mitigation strategies. This approach could enhance agricultural resilience, protect livelihoods, and optimize water allocation in this vital agro-climatic region. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
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.
Monitoring vegetation loss and shoreline change due to tropical cyclone Fani using Landsat imageries in Balukhand-Konark Wildlife Sanctuary, India
(Springer Science and Business Media B.V., 2021) Manoranjan Mishra; Celso Augusto Guimarães Santos; Richarde Marques da Silva; Narendra Kumar Rana; Dipika Kar; Nihar Ranjan Parida
The study analyzes the coastline oscillations and land use and land cover (LULC) change due to the impact of the cyclone Fani in Balukhand-Konark Wildlife Sanctuary (BKWS), located in East India. In this study, two Landsat 8 images in the pre- and post-cyclone periods in 2019 were used. The transition zone discriminating land and water was calculated using normalized difference water index (NDWI) and desktop digitization. The digital shoreline analysis system (DSAS), an extension of ArcGIS, was used to model changes in the shorelines, and the net shoreline movement (NSM) was used to extract the change statistics. The vegetation damage was analyzed using the soil-adjusted vegetation index (SAVI) and the LULC changes were assessed using geospatial techniques. Then, LULC degradation maps were produced. The results highlight the dynamic character of the studied coastline with erosion in the flat sandy forests, and show that some areas had accretion in the northern portion. The results show that SAVI has decreased along with patches close to critical erosion points, regardless of climate trends. It was observed that the severe cyclonic storm Fani had created both ecological and physical disturbances in the sandy flat BKWS area. In the future, this study can provide important information on ecological and physical changes induced by cyclonic storms and be beneficial for restoring the biodiversity niche of this unique fragile coastal forest on the east coast of India. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.
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.
Unravelling blue landscape fragmentation effects on ecosystem services in urban agglomerations
(Elsevier Ltd, 2024) Sonali Kundu; Narendra Kumar Rana; Susanta Mahato
The blue landscape (BL), which refers to the wetlands, rivers, lakes, and other bodies of water, is of immense importance for a sustainable environment. It provides a variety of ecosystem services, including carbon sequestration, water purification, soil fertility, and habitat for diverse flora and fauna. These services are crucial for sustaining the livelihoods of local communities and maintaining the health of the environment. In megacities like Kolkata, India, the BL is often subjected to fragmentation and degradation due to rapid urbanisation, industrialization, and other human activities. This has serious implications for ecosystem services and the overall health of the environment. This study is intended to value ecosystem service losses over the last 25 years and assess the influence of blue landscape fragmentation on ecosystem services in Kolkata, India. To accomplish this goal, satellite data was collected from 1994 to 2019 for both pre-monsoon and post-monsoon seasons. The results of the study showed that significant losses in ecosystem services were observed over this time period, primarily due to the decline of the East Kolkata Wetland and its conversion for settlement and agricultural purposes. Despite the existence of some policies aimed at protecting the wetland, more robust restrictions and remedial strategies are required to conserve and restore the blue landscape in Kolkata. This work adds to the corpus of research on the value of blue landscapes (BLs) and the environmental services they provide. The findings of this study highlight the need for increased attention to the conservation and management of BLs in India and provide a valuable foundation for future research and policy development. Furthermore, this research introduces the innovative concept of urban BLs as a nature-based framework for understanding urban landscape fragmentation, a novel contribution that fills a gap in the existing literature on this topic. © 2024 Elsevier Ltd
Wetland degradation and its impacts on livelihoods and sustainable development goals: An overview
(Elsevier B.V., 2024) Sonali Kundu; Barnali Kundu; Narendra Kumar Rana; Susanta Mahato
Wetlands, vital ecosystems that support 40 % of the world's species and serve as nature's water filters, are disappearing three times faster than forests. While global research extensively examines the increasing degradation of wetland health, there exists a significant research gap concerning its impact on livelihoods and the achievement of Sustainable Development Goals (SDGs). To address this gap, a systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, utilising data from 1270 database records and 350 research studies spanning 1990 to 2023. The study reveals alarming annual wetland health loss rates ranging from 0.02 % to 3.14 %, driven globally by built-up areas, agricultural expansion, climate change, and pollution. Notably, developing countries and those with lower development indices exhibit the highest rates of wetland health degradation, primarily attributed to agricultural and urban expansion, as well as pollution. The analysis establishes a negative correlation between wetland health degradation rates, driving factors, and key indicators such as the Sustainable Development Goal Index (SDGI) (r = −0.38), Environmental Performance Index (EPI) (r = −0.34), Income Classification (r = −0.42), and Human Development Index (HDI) (r = −0.38). The study emphasizes the imperative of improving economic and socio-ecological conditions to enhance conservation and restoration efforts in wetland areas, thereby contributing to the achievement of SDGs. The interconnectedness of wetland health with broader SDGs underscores the need for targeted interventions. Recommendations include prioritizing comprehensive strategies for environmental and societal well-being, urging policymakers and practitioners to consider the holistic implications of wetland health degradation in their decision-making processes. © 2024 Institution of Chemical Engineers