Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
5 results
Search Results
Item Analyzing landslide susceptibility, health vulnerability and risk using multi-criteria decision-making analysis in Arunachal Pradesh, India(Springer Science and Business Media Deutschland GmbH, 2023) Rehman, S.; Azhoni, A.Landslides being a widespread disaster are associated with susceptibility, vulnerability and risk. The physical factors inducing landslides are relatively well-known. However, how landslide susceptibility will be exacerbated by climate change, impede the attainment of the sustainable development goals and increase health vulnerability is relatively less explored. We present an integrated assessment of landslide susceptibility, health vulnerability and overall risk to understand these interconnected dimensions using Arunachal Pradesh, India, as a case study, which is susceptible to landslides due to its topography and climate conditions. Landslide susceptibility was examined using twenty landslide conditioning parameters through the fuzzy analytical hierarchy process (FAHP). The susceptibility map was validated using the area under the ROC curve (AUC). National Family Health Survey (NFHS 4) data were used to analyze the health vulnerability, while the overall risk was computed through the integration of susceptibility and vulnerability. Landslide susceptibility analysis indicated that nearly 22% area of the state is characterized by moderate susceptibility followed by high (17%) and very high susceptibility (13%). High elevation, slope, rainfall, SPI, drainage density and complex geology were identified as the causative factors of landslides. In the case of health vulnerability, East Kameng and Lohit districts were found to be very highly vulnerable, while Papum Pare, Changlang and Tirap districts experience high health vulnerability due to high degree of exposure and sensitivity. Overall risk analysis revealed over 16.8% area of the state is under moderate risk followed by high (9.8%) and very high (4.2%) risk. Linking this analysis with the climate change projections and SDG goals attainment revealed that Papum Pare, Upper Subansiri, Tirap and West Kameng require priority for lessening susceptibility, vulnerability and risk for achieving sustainable development. A strong correlation (99%) between HVI and risk further demonstrates the need for lessening health vulnerability and risk in the study area. Furthermore, our study contributes additional insights into landslide susceptibility by considering heal vulnerability and risk which may help in planning sustainable development strategies in a changing climate. © 2022, The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences.Item Livelihood vulnerability assessment and climate change perception analysis in Arunachal Pradesh, India(Springer Science and Business Media Deutschland GmbH, 2023) Rehman, S.; Azhoni, A.; Chabbi, P.H.Climate change induced frequent disasters pose severe threats to agro-based rural livelihoods. Perceptions of risks play a critical role in planning and averting disasters. Lack of analytical documentation concerning how vulnerable communities perceive climate risks is a barrier to addressing and averting disasters and maladaptation. Applying a mixed approach, this study examines the perception of households concerning climate change and analyses the impacts of climate change on livelihood in Arunachal Pradesh, the largest northeastern state of India, with severe climate related challenges. Conceptual livelihood vulnerability index (LVI) framework of Intergovernmental Panel on Climate Change is adopted to analyse the climate change induced vulnerability on livelihood. A total 450 households from 18 villages located in the districts of Arunachal Pradesh were surveyed during October, 2021 for retrieving the ground complexities in the region. Decrease in yields, frequent landslides and floods, livestock losses and unpredictable weather condition were perceived by the sampled households. The LVI analysis indicated that households are vulnerable in Arzoo, Perum, Pekong and Amliang villages requiring priority for lessening livelihood vulnerability and increasing coping capacity of the communities. Correlation analysis indicated that climate variability, natural disaster, health, food and social components attributed to livelihood vulnerability in the study area. Alternate livelihood, enhancing preparedness to disasters, inclusion of women in workforce, sustainable livelihood practices and government assistance are some of the suggestions made to enhance the adaptation of local communities in a sustainable way. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.Item Multihazard Assessment of the Sutlej-Beas River Basin Using Bivariate Statistical Frequency Ratio (FR) Model and Management Barriers of Land-River Interface(Springer Science and Business Media Deutschland GmbH, 2023) Rehman, S.; Azhoni, A.Climate change coupled with increased anthropogenic activities intensifies the potency and frequency of extreme weather events. While multihazard assessments of these extreme weather events enhance the estimation of hazard susceptibility, it must be coupled with identifying institutional barriers of managing the land-river interface. Thus, this study has carried out a multihazard susceptibility assessment based on landslide and flood susceptibility in the Sutlej-Beas River basin and prepared flood and landslide susceptibility maps using eleven causative parameters through a bivariate statistical frequency ratio (FR) model. This statistical evaluation of hazard susceptibility from multiple factors is supplemented by identifying the key barriers of managing the land-river interface, producing a more comprehensive understanding of the challenges of mitigating extreme weather-related hazards in a river basin. Nearly 51% of the study area was identified as susceptible to landslide while 43% was under flood and 48% area was observed under multihazard susceptibility. Landslides, floods, and multihazard followed a similar pattern of spatial distribution where elevation, population, drainage density, stream power index (SPI), and rainfall were identified as the contributing parameters. Changing attitudes of people toward rivers, lack of coordination among different stakeholders, and deficit funds were identified as prominent barriers in the case of land-river management. Susceptibility maps generated in this study will help in identifying the areas under hazard susceptibility while the identified institutional barriers may guide towards contextual sustainable planning of the basin and attainment of sustainable development goals. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Item Impact of recent floods on river morphology of Upper Krishna River: a decadal analysis using remote sensing approach(Springer Science and Business Media Deutschland GmbH, 2024) Choudhary, P.; Azhoni, A.; Devatha, C.P.Alluvial rivers are dynamic landscapes on the earth’s surface that evolve with time. While many studies have examined the immediate effects of floods on river channels, there is a lack of research that investigates the longer-term evolution of river morphology following such events. The present study was carried out on the Upper Krishna River which flows between the southern part of Maharashtra and the northern part of Karnataka states in India for 375 Km. The morphological parameters were analyzed for three decades (1991–2021) and the year 2019 with the highest flood level was also considered for change analysis. The assessment was done for change in active channel area, mean width, bank line migration, sinuosity index, and erosion-accretion. The land use classification was also analyzed for the study period to understand the exposure to future floods. The spatial data was retrieved from different satellite missions and analyzed with the help of Remote Sensing (RS) and Geographical Information System (GIS). The river was divided into seven segments (R1, R2, R3, R4, R5, R6, and R7) and bank lines were digitised manually to minimise possible errors. The results show that during the study period, the river channel has been modified in terms of active channel area expansion in the R1, R5, R6, and R7, and erosion was found the dominating process while the left bank was more erosive than the right bank of the river. The built-up area was seen going through a major expansion than any other land use class. The discharge and sediment data confirm the flood years (1994, 2005, 2006, and 2019) which accelerated the morphological activity in the river segment. The results of the study provide new insights related to short-term morphological changes in the Upper Krishna River and can be used by policymakers and managers to carry out future development plans and river training work at affected sites. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.Item Integration of multi-layer perceptron neural network and cellular Automata-Markov chain approach for the prediction of land use land cover in land change modeler(Elsevier B.V., 2025) Choudhary, P.; Devatha, C.P.; Azhoni, A.Land use and land cover (LULC) significantly influence the hydrological cycle and various earth processes. Understanding these dynamics is essential for effectively managing environmental issues within river basins. The study focuses on a highly dynamic and flood-prone sub-basin of the Upper Krishna River, where major urban settlements and intensive agricultural activities are concentrated along the riverbanks. The uniqueness of this research comes from the selection of this hydrologically sensitive landscape, shaped by both natural processes and anthropogenic pressures, which presents a critical case for land use and land cover modeling. Utilizing high-resolution satellite data (10 m), combined with the advanced Multi-Layer Perceptron Neural Networks (MLPNN) and Cellular Automata-Markov Chain (CA-Markov) modeling techniques within TerrSet's Land Change Modeler (LCM), which is not only capable of generating spatial transitions and dynamic maps but also identifies the key contributors in gain and loss of various land use classes. We projected LULC scenarios for the mid-century (2049) and end-century (2099) using data from 2015 to 2020. Our model was validated against the actual LULC map from 2024 and showed a strong correlation (Kappa = 0.85). The results indicate significant urban growth along the riverbank and predict an increase in built-up area from 6.53 % in 2024 to 9.59 % in 2049 and further to 15 % by 2099 of the total geographical area. We observed consistent declines in forest cover, cropland, and barren land. These findings are valuable for future hydrological studies and provide important insights for policymakers to support sustainable urban planning and flood risk management. © 2025