Divyesh Manohar Varade

Scopus Publications

Ice-flux divergence and strain rates reveal compressive-flow hotspots on Gangotri glacier
Anikul Islam, Divyesh Varade, Lavkush Kumar Patel, Aliva Nanda, Somil Swarnkar, Rajiv Sinha
Physics and Chemistry of the Earth, 2026
Deciphering flood vulnerability of Himalayan river basin using explainable machine learning and multivariate probabilistic analysis
Soumya Kundu, Somil Swarnkar, Rajiv Sinha, Divyesh Varade, Anubhuti Singh
Environmental and Sustainability Indicators, 2026
Floods pose an escalating hazard in the Upper Ganga Basin (UGB), where rugged Himalayan terrain, intense monsoonal rainfall, and increasing human occupation amplify flood risk. This study presents an integrated assessment of flood susceptibility, vulnerability, and risk across the UGB using explainable machine-learning (ML) models and a multivariate exposure framework. Geomorphological, hydrological, land-surface, and socio-infrastructural conditioning factors were compiled and evaluated. Decision Tree-based ML classifiers, including Random Forest (RF), Extra Trees (ET), XGBoost (XGB), and LightGBM (LGBM), were trained and optimized to generate flood susceptibility maps, while model interpretability was assessed using Shapley Additive exPlanations (SHAP). The ML models demonstrated excellent predictive performance, with RF producing the most spatially coherent susceptibility patterns. Flood susceptibility is highest along valley bottoms and major river corridors and is primarily controlled by elevation, land-use/land-cover, topographic position, proximity to rivers, vegetation condition, and slope. Hydrological connectivity and antecedent moisture further reinforce susceptibility in narrow and deeply incised terrain. A multivariate vulnerability analysis integrating flood-affected areas, population exposure, settlement concentration, and road density reveals strong nonlinear and threshold behaviour in vulnerability escalation. The highest vulnerability occurs in the central and southeastern UGB, where dense settlements and limited connectivity coincide with extensive flood-prone areas. Overall, the results demonstrate that flood risk in the UGB arises from complex interactions between physical susceptibility and human exposure, highlighting the need for integrated flood risk management and sustainable land-use planning in Himalayan regions.
A Maxout-enhanced robust deep convolutional neural network model for flood mapping using Sentinel-1 SAR data
Shubham Awasthi, Gopal Singh Phartiyal, Divyesh Varade, Kamal Jain
Physics and Chemistry of the Earth, 2026
Super-resolution generative adversarial network based dual channel convolutional neural network for hyperspectral image classification
Brajesh Kumar, Mohd. Mustafa Khan, Divyesh Varade
Advances in Space Research, 2026
Investigation of Climate Extremes in Jabalpur District of Madhya Pradesh Trends and Future Implications
Pankaj Kumar Thakur, Dheeraj Mohan Gururani, Abhishek Agrawal, Snehil Dubey, Divyesh Varade, Pushpanjali Kumari
Geospatial Technologies Environmental and Climate Science Applications and Challenges, 2026
Climate change is a long-term change in hydro-meteorological conditions in a particular geographical region. In the present study, spatiotemporal long-term change in rainfall during 1961–2020 was analyzed using IMD 0.25° × 0.25° resolution gridded dataset in the Jabalpur district. The nonparametric Mann–Kendall trend test and Sen’s slope estimator were applied to determine the trend and its magnitude, respectively, in the precipitation time series. Extreme indices were employed to understand the risks and vulnerabilities associated with extreme weather events in the district. Mann–Kendall trend test showed an insignificant trend at 95% confidence interval with Sen’s slope value of −2.98 to 0.73 mm/year. CLIMPACT tool was used to study extreme indices, and it revealed that in the district, consecutive dry days (CDD), R10, R20, and RX5 were nonsignificant and decreasing, whereas consecutive wet days (CWD), RX1, and SDII were found to insignificantly increasing. These results spotlight the need for localized climate adaptation strategies by integrating water resource planning with a sustainable development approach to address the vulnerable rainfall pattern and mitigate risks associated with extreme events in central India, particularly in Jabalpur district.
Glacier dynamics, proglacial lake expansion, and GLOF risk assessment in the lato basin, Trans-Himalayan Ladakh
Rayees Ahmed, Janhavi Jadhav, Rasiq A. Mir, Hemant Singh, Lander Van Tricht, Syed Towseef Ahmad, Riyaz Ahmad Mir, Devendra Nagale, Divyesh Varade, Pervez Ahmed
Frontiers in Earth Science, 2026
The accelerating retreat of glaciers and expansion of glacial lakes in the Trans-Himalayan region of Ladakh are intensifying the risk of Glacial Lake Outburst Floods (GLOFs), posing significant threats to vulnerable downstream communities. However, high-altitude basins like Lato remain poorly assessed in terms of integrated glacier–lake dynamics and hazard potential. In this study, we present a detailed, multi-parameter assessment of the Lato glacier–lake system over a 40-year period (1980–2020), combining remote sensing, empirical modeling, and hydrodynamic simulations. Our results show an ∼11.5% reduction in glacier area, a mean terminus retreat of ∼171 m at the rate of 4.2 m yr -1 , and a decline in total ice volume from 0.48 km 3 to 0.41 km 3 (1980–2020). Glacier surface velocities, derived using Glacier Image Velocimetry (GIV), ranged from 0.97 to 15.73 m yr -1 , with mean values between 7.63 and 8.03 m yr -1 . Ice thickness was estimated using GlabTop2 and ensemble modeling approaches, yielding average thicknesses of 76 m and 58 m, respectively. Geodetic mass balance calculations indicate a persistent negative trend, with an average loss of −0.33 m w.e. yr -1 since the early 2000s. The proglacial Lato lake expanded by ∼66%, reaching 0.088 km 2 in 2020. Lake depth and volume were estimated using multiple empirical models, with the most robust estimate placing the lake volume at 1.47 × 10 6 m 3 . GLOF susceptibility analysis using the Analytical Hierarchy Process (AHP) assigned a high-risk index of 0.82 to the lake. Two-dimensional hydrodynamic simulations using HEC-RAS under full and partial breach scenarios forecast peak discharges of 3726 m 3 s -1 and 2309 m 3 s -1 , respectively, with a potential impact zone extending ∼23 km downstream. This study not only identifies Lato lake as a high-risk GLOF site but also offers region-specific recommendations including glacier and lake monitoring, early warning systems, and the integration of GLOF risk into regional planning and disaster preparedness frameworks.
Intensified occurrences of snow droughts are related to the snow cover dynamics in the Hindu Kush Himalayas
Hemant Singh, Divyesh Varade, Vivek Gupta
Scientific Reports, 2025
Identification of potential snow drought (SD) hotspots is critical, especially considering seasonal snow imbalances in the recent years, with snow being one of the significant water resource in the Hindu Kush Himalayas (HKH). The critical linkage between the spatio-temporal anomalies of snow cover days (SCD) and SD remains under-observed in the HKH region. To investigate this linkage, we identified the SD at basin (11 basins) using the snow water equivalent index (SWEI) based on the High Mountain Asia Snow Reanalysis (HMASR) data from 1999 to 2016 water cycle. The declined snow cover days (DSCD) and snow cover persistence anomalies (SCPA) at sub-km spatial resolution from 2002 to 2018 were estimated from the improved MOYDGL06 snow cover data, respectively. Our basin scale findings indicate moderate to severe snow droughts were observed in 2008, 2011, 2015 and 2016 in the North-West (NW), Amu-Darya (AD), Indus (IN), and Salween (SA) and Mekong (MK) basins with strong linkages to DSCD and SCPA. The observed frequencies of snow-droughts were 25, 16, 14, 5, and 3 in the NW, AD, IN, MK, SA basins, respectively. These basins also exhibit significant DSCD, approximately 12, 11, 12 in NW, AD, IN, respectively, and 14 days in MK and SA basins each. Further, it is noted that significantly higher negative SCPA coincides with the SD episodes in drought years. Both SD and DSCD were more prominent between 3000 and 6000 m elevations in the HKH, which are often considered under elevation dependent warming (EDW) scenarios in various studies. Overall, we observed that a higher frequency of drought events corresponds to a greater DSCD and higher negative magnitudes of SCPA. These insights indicate the urgent need for snow-conservation strategies and development and enforcement of strong policies.
Inversion of snow geophysical parameters using the VHR PAZ X-band dual polarimetric SAR data: first known experiments in the Himalayan region
Hemant Singh, Divyesh Varade
International Journal of Applied Earth Observation and Geoinformation, 2025
• First known experiment of VHR PAZ –X band SAR data for snow geophysical parameter retrieval. • Utilized the dynamic range of snow density instead of constant value to retrieve the CPD thereby improving estimates. • Improved algorithm using average CPD shows high accuracy with R 2 = 0.85 for snow depth and R 2 = 0.77 for SWE. Results indicate the applicability of the approach in old/settled alpine snowpack with predominantly dry conditions. Snow plays a vital role in mountain hydrology, water resources, and Earth’s planetary budgets. Therefore, monitoring snow geophysical parameters (SGPs), such as snow density, Snow depth (SD), and snow water equivalent (SWE), is imperative hydrological dynamics and forecasting water availability. Moreover, radar remote sensing offers significant capabilities for estimating these parameters. In this study, we utilized PAZ X-band dual-polarimetric data to estimate SGPs. To the best of our knowledge, this is the first known experiment using PAZ data for SGP estimation. In the present work, we utilized the copolar phase difference (CPD) for SD and Integral Equation model (IEM) for snow density. In this study, we proposed an improved algorithm for SD inversion, instead of relying on a single in-situ snow density value, we incorporated a range of snow densities (0.15 to 0.27 g/cm3), optimizing the axial ratio between 1.13 and 1.17. This density range and optimized axial ratio were used to minimise the error between C P D O b s and the average C P D M o d . The algorithm yielded high-resolution modelled SD and density at a 2.5 m spatial resolution, which were later used to estimate SWE. Algorithm validation was performed using in-situ data of Gulmarg region of Kashmir, India, with statistical metrics such as mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2), and percentage error (PE). SD estimates showed high correlation, with R2 = 0.85, RMSE = 3.18 cm, PE = 1 %, and MAE = 2.85 cm. Similarly, SWE estimates had an R2 of 0.77, RMSE = 1.032 cm, PE = 5 %, and MAE = 0.814 cm, demonstrating the model’s accuracy and reliability.
Unlocking hydrological insights: Spatial data analysis for modeling and management
Advances in Hydrology Spatial Intelligence Climate Change and Sustainable Water Resource Management, 2025
Ensemble modelling of ice volume dynamics of Chhota Shigri Glacier in Himachal Pradesh from 2017 to 2022
Diksha Sinha, Hemant Singh, Divyesh Varade
Journal of Water and Climate Change, 2024
Glaciers are the source of freshwater for many perennial rivers around the world. Out of 215,000 glaciers apart from the polar ice sheets, the Himalayas constitute about 54,000 glaciers and are often referred to as the third pole on the Earth. In recent decades, the Himalayan glaciers have been experiencing increased recession as a consequence of climate change. Subsequently, understanding the dynamics of glacier ice parameters and volume becomes significant. In this study, an ensemble model of laminar-flow-based and basal-shear-stress-based models on the Chhota Shigri Glacier was investigated to understand the dynamics of glacier ice thickness over six years, from 2017 to 2022. The glacier volume was determined from the ensembled ice thickness. Our results indicate that the ensemble model yields the minimum ice thickness measurement of 102 ± 17.38 m and the maximum of 112 ± 19.04 m for the years 2017 and 2019, respectively. The estimated results show a correlation of 81% with a global ice thickness dataset. The ensemble approach provides better estimates for ice thickness accounting for more parameters affecting the glacier dynamics. From 2017 to 2022, the Chhota Shigri Glacier volume has been observed to show a slightly negative trend.
Utilizing statistical and MCDM techniques in indexing morphometric parameters towards improved watershed management in the Nandhour-Kalish drainage system
Dheeraj Mohan Gururani, Divyesh Varade, Himanshu Joshi, Hemant Singh, Yogendra Kumar, Vinod Kumar
Journal of Water and Climate Change, 2024
High-resolution mapping of seasonal snow cover extent in the Pamir Hindu Kush using machine learning-based integration of multi-sensor data
Abdul Basir Mahmoodzada, Pragyan Das, Divyesh Varade, Mohd Arslaan Akhtar, Sawahiko Shimada
Acta Geophysica, 2024
ESTIMATION OF SNOW DENSITY AND PERMITTIVITY USING ALOS PALSAR-2 FULLY POLARIMETRY
Hemant Singh, Divyesh Varade
2024 IEEE India Geoscience and Remote Sensing Symposium Ingarss 2024, 2024
Surface Soil Moisture Retrieval based on Model-Based Decomposition of Dual-Polarimetric Sentinel-1 Data
C Aparna, Divyesh Varade
2024 IEEE India Geoscience and Remote Sensing Symposium Ingarss 2024, 2024
Assessment of Adjusted and Normalized Mutual Information Variants For Band Selection in Hyperspectral Imagery
Bhagyashree Chopade, Vikas Gupta, Divyesh Varade
Supervised and Unsupervised Data Engineering for Multimedia Data, 2024
Stress Field Prediction in Particulate Polymer Composite Materials Using Paired Image-To-Image Translation Approach
Sristi Gupta, Vinod Kushvaha, Divyesh Varade
Lecture Notes in Mechanical Engineering, 2024
Prediction of Stress Fields in Particulate Polymer Composites Using Micromechanics-Based Artificial Intelligence Model
Sristi Gupta, Tanmoy Mukhopadhyay, Divyesh Varade, Vinod Kushvaha
Lecture Notes in Civil Engineering, 2024
Investigating Deep Learning-Based Stress Prediction in Particulate Polymer Composites Using Multiple Quality Measures
Sristi Gupta, Tanmoy Mukhopadhyay, Divyesh Varade, Vinod Kushvaha
Springer Proceedings in Physics, 2024
Glacial lake outburst flood risk assessment of a rapidly expanding glacial lake in the Ladakh region of Western Himalaya, using hydrodynamic modeling
Abid Farooq Rather, Rayees Ahmed, Joshal Kumar Bansal, Rasiq Ahmad Mir, Pervez Ahmed, Ishfaq Hussain Malik, Divyesh Varade
Geomatics Natural Hazards and Risk, 2024
Early Warning Potential of Regional Seismic Network: Seismic Assessment of One of the Precursors of Chamoli 2021 Disaster
Deepak Rawat, M. L. Sharma, Divyesh Varade, Roshan Kumar, Debi Prasanna Kanungo, Rayees Ahmed, S. C. Gupta, Hemant Singh, Nishant Saxena
Earth Systems and Environment, 2024
Assessment of urban sprawls, amenities, and indifferences of LST and AOD in sub-urban area: a case study of Jammu
Divyesh Varade, Hemant Singh, Abhinav Pratap Singh, Shubham Awasthi
Environmental Science and Pollution Research, 2023
Quantification of Amu River Riverbank Erosion in Balkh Province of Afghanistan during 2004–2020
Abdul Basir Mahmoodzada, Divyesh Varade, Sawahiko Shimada, Hiromu Okazawa, Shafiqullah Aryan, Gulbuddin Gulab, Abd El-Zaher M. A. Mustafa, Humaira Rizwana, Yogesh K. Ahlawat, Hosam O. Elansary
Land, 2023
Assessment of potential present and future glacial lake outburst flood hazard in the Hunza valley: A case study of Shisper and Mochowar glacier
Hemant Singh, Divyesh Varade, Maximillian Van Wyk de Vries, Kirtan Adhikari, Manish Rawat, Shubham Awasthi, Deepak Rawat
Science of the Total Environment, 2023
Cloudburst Events in the Indian Himalayas: A Historical Geospatial Perspective
Hemant Singh, Divyesh Varade, Prabhash K. Mishra
International Handbook of Disaster Research, 2023
Assessment of Land Deformation and the Associated Causes along a Rapidly Developing Himalayan Foothill Region Using Multi-Temporal Sentinel-1 SAR Datasets
Shubham Awasthi, Divyesh Varade, Sutapa Bhattacharjee, Hemant Singh, Sana Shahab, Kamal Jain
Land, 2022
Analyzing urbanization induced groundwater stress and land deformation using time-series Sentinel-1 datasets applying PSInSAR approach
Shubham Awasthi, Kamal Jain, Sutapa Bhattacharjee, Vivek Gupta, Divyesh Varade, Hemant Singh, Avadh Bihari Narayan, Alessandra Budillon
Science of the Total Environment, 2022
Development of a novel approach for snow wetness estimation using hybrid polarimetric RISAT-1 SAR datasets in North-Western Himalayan region
Shubham Awasthi, Divyesh Varade, Praveen Kumar Thakur, Ajeet Kumar, Hemant Singh, Kamal Jain, Snehmani
Journal of Hydrology, 2022
Capability assessment of Sentinel-1 data for estimation of snow hydrological potential in the Khanabad watershed in the Hindu Kush Himalayas of Afghanistan
Abdul Basir Mahmoodzada, Divyesh Varade, Sawahiko Shimada, Farid Ahmad Rezazada, Abdul Saboor Mahmoodzada, Abdul Nasir Jawher, Mohammadi Toghyan
Remote Sensing Applications Society and Environment, 2022
Remote sensing for snowpack monitoring and its implications
Divyesh Varade, Surendar Manickam, Gulab Singh
Geographic Information Science for Land Resource Management, 2021
Recent advances in the remote sensing of alpine snow: a review
Shubham Awasthi, Divyesh Varade
Giscience and Remote Sensing, 2021
Unsupervised band selection of hyperspectral data based on mutual information derived from weighted cluster entropy for snow classification
Divyesh Varade, Ajay K. Maurya, Onkar Dikshit
Geocarto International, 2021
Effect of Pansharpening in Fusion Based Change Detection of Snow Cover Using Convolutional Neural Networks
Ajay K. Maurya, Divyesh M. Varade, Onkar Dikshit
IETE Technical Review Institution of Electronics and Telecommunication Engineers India, 2020
Estimation of snow depth in the hindu kush himalayas of Afghanistan during peakwinter and early melt season
Abdul Basir Mahmoodzada, Divyesh Varade, Sawahiko Shimada
Remote Sensing, 2020
Assessment of winter season land surface temperature in the Himalayan regions around the Kullu area in India using landsat-8 data
Divyesh Varade, Onkar Dikshit
Geocarto International, 2020
Snow depth in Dhundi: an estimate based on weighted bias corrected differential phase observations of dual polarimetric bi-temporal Sentinel-1 data
Divyesh Varade, Ajay K. Maurya, Onkar Dikshit, Gulab Singh, Surendar Manickam
International Journal of Remote Sensing, 2020
Modelling of early winter snow density using fully polarimetric C-band SAR data in the Indian Himalayas
Divyesh Varade, Surendar Manickam, Onkar Dikshit, Gulab Singh, Snehmani
Remote Sensing of Environment, 2020
Identification of Snow Using Fully Polarimetric SAR Data Based On Entropy and Anisotropy
Divyesh Varade, Gulab Singh, Onkar Dikshit, Surendar Manickam
Water Resources Research, 2020
Potential of multispectral reflectance for assessment of snow geophysical parameters in Solang valley in the lower Indian Himalayas
Divyesh Varade, Onkar Dikshit
Giscience and Remote Sensing, 2020
Potential of Landsat-8 and Sentinel-2A composite for land use land cover analysis
Divyesh Varade, Anudeep Sure, Onkar Dikshit
Geocarto International, 2019
Capability assessment of sentinel-1 bi-temporal dual polarimetric SAR data for inferences on snow density
Divyesh Varade, Onkar Dikshit, Surendar Manickam, Gulab Singh, Snehmani
2019 IEEE MTT S International Microwave and RF Conference Imarc 2019, 2019
Unsupervised hyperspectral band selection using ranking based on a denoising error matching approach
Divyesh Varade, Ajay K. Maurya, Onkar Dikshit
International Journal of Remote Sensing, 2019
Development of Spectral Indexes in Hyperspectral Imagery for Land Cover Assessment
Divyesh M. Varade, Ajay K. Maurya, Onkar Dikshit
IETE Technical Review Institution of Electronics and Telecommunication Engineers India, 2019
Dry/wet snow mapping based on the synergistic use of dual polarimetric SAR and multispectral data
Divyesh Varade, Onkar Dikshit, Surendar Manickam
Journal of Mountain Science, 2019
Improved Assessment of Atmospheric Water Vapor Content in the Himalayan Regions Around the Kullu Valley in India Using Landsat-8 Data
D. Varade, O. Dikshit
Water Resources Research, 2019
HICF: A matlab package for hyperspectral image classification and fusion for educational learning and research
A. K. Maurya, D. Varade, O. Dikshit
International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences ISPRS Archives, 2018
Estimation of surface snow wetness using sentinel-2 multispectral data
D. Varade, O. Dikshit
ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences, 2018
Potential of Information Fusion of Optical and SAR Data for Snow Cover Characterization
Divyesh Varade, Ajay K Maurya, Onkar Dikshit
2018 International Conference on Computational and Characterization Techniques in Engineering and Sciences Cctes 2018, 2018
Ppmasks: A Simple and Effective Tool for Basic Land Cover Characterization
Divyesh Varade, Ajay K Maurya, Sonam Sharma, Onkar Dikshit
2018 International Conference on Computational and Characterization Techniques in Engineering and Sciences Cctes 2018, 2018
Estimating root zone soil moisture from AMSR2 remotely sensed surface soil moisture data
Anudeep Sure, Divyesh Varade, Onkar Dikshit
2018 3rd International Conference on Microwave and Photonics Icmap 2018, 2018
Evaluation of multi-spectral cube from multi-sensor imagery corresponding to hyperspectral imagery
Divyesh Varade, Anudeep Sure, Onkar Dikshit
International Geoscience and Remote Sensing Symposium IGARSS, 2017
Factors determining spatio-temporal variations of soil moisture using microwave data
Anudeep Sure, Divyesh Varade, Onkar Dikshit
2017 International Conference on Emerging Trends in Computing and Communication Technologies Icetcct 2017, 2017
Supervised classification of snow cover using hyperspectral imagery
Divyesh Varade, Ajay K Maurya, Anudeep Sure, Onkar Dikshit
2017 International Conference on Emerging Trends in Computing and Communication Technologies Icetcct 2017, 2017
Enhancement of snow cover change detection with sparse representation and dictionary learning
D. Varade, O. Dikshit
International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences ISPRS Archives, 2014

RECENT SCHOLAR PUBLICATIONS

Ice-flux divergence and strain rates reveal compressive-flow hotspots on Gangotri glacier
A Islam, D Varade, LK Patel, A Nanda, S Swarnkar, R Sinha
Physics and Chemistry of the Earth, Parts A/B/C, 104482 , 2026
2026
Glacier dynamics, proglacial lake expansion, and GLOF risk assessment in the lato basin, Trans-Himalayan Ladakh
R Ahmed, J Jadhav, RA Mir, H Singh, L Van Tricht, ST Ahmad, RA Mir, ...
Frontiers in Earth Science 14, 1740374 , 2026
2026
Hydro-meteorological and Infrastructural Damage Analysis of the Recent Ramban Cloudburst Event in the North-Western Himalayan Region of Jammu and Kashmir, India
S Awasthi, A Jose, S Barbhuiya, AK Taloor, D Varade, AK Rai, V Gupta, ...
International Journal of Disaster Risk Reduction, 106126 , 2026
2026
Flash Snow Drought: Escalating Risks to Mountain Water Resources at local scale
H Singh, M Mehraj, D Varade
EGU26 , 2026
2026
Understanding the Role of Snowmelt Processes on Soil Moisture Storage and Vegetation Dynamics acrossTopographic Gradients of Himalayan Catchments
A Nanda, A Bharti, D Varade
EGU26 , 2026
2026
Super-Resolution Generative Adversarial Network Based Dual Channel Convolutional Neural Network for Hyperspectral Image Classification
B Kumar, M Khan, Mustafa, D Varade
Advances in Space Research , 2026
2026
A Maxout-Enhanced Robust Deep Convolutional Neural Network Model for Flood Mapping using Sentinel-1 SAR Data
S Awasthi, G Parthiyal, D Varade, K Jain
Physics and Chemistry of the Earth , 2026
2026
Unlocking hydrological insights: Spatial data analysis for modeling and management
A Raia, A Bhardwajb, A Ahmedc, RA Mird, D Varaded, P Kumara
Advances in Hydrology: Spatial Intelligence, Climate Change, and Sustainable … , 2025
2025
Intensified occurrences of snow droughts are related to the snow cover dynamics in the Hindu Kush Himalayas
H Singh, D Varade, V Gupta
Scientific Reports 15 (1), 36101 , 2025
2025
Citations: 2
Inversion of snow geophysical parameters using the VHR PAZ X-band dual polarimetric SAR data: first known experiments in the Himalayan region
H Singh, D Varade
International Journal of Applied Earth Observation and Geoinformation 141 … , 2025
2025
Citations: 1
Understanding the Gangotri glacier dynamics: Implications from a fully distributed inversion of equivalent water-volume change
A Islam, D Varade, A Nanda, S Swarnkar, R Sinha
EGUsphere 2025, 1-40 , 2025
2025
Citations: 1
Glacial lake outburst flood risk assessment of a rapidly expanding glacial lake in the Ladakh region of Western Himalaya, using hydrodynamic modeling
AF Rather, R Ahmed, JK Bansal, RA Mir, P Ahmed, IH Malik, D Varade
Geomatics, Natural Hazards and Risk 15 (1), 2413893 , 2024
2024
Citations: 15
Surface Soil Moisture Retrieval based on Model-Based Decomposition of Dual-Polarimetric Sentinel-1 Data
C Aparna, D Varade
2024 IEEE India Geoscience and Remote Sensing Symposium (InGARSS), 1-4 , 2024
2024
Estimation of Snow Density and Permittivity Using ALOS PALSAR-2 Fully Polarimetry
H Singh, D Varade
2024 IEEE India Geoscience and Remote Sensing Symposium (InGARSS), 1-4 , 2024
2024
Investigation of Climate Extremes in Jabalpur District of Madhya Pradesh: Trends and Future Implications
PK Thakur, DM Gururani, A Agrawal, S Dubey, D Varade, P Kumari
Geospatial Technologies, 356-380 , 2024
2024
Ensemble modelling of ice volume dynamics of Chhota Shigri Glacier in Himachal Pradesh from 2017 to 2022
D Sinha, H Singh, D Varade
Journal of Water and Climate Change 15 (7), 3190-3209 , 2024
2024
Citations: 7
Prediction of Stress Fields in Particulate Polymer Composites Using Micromechanics-Based Artificial Intelligence Model.
S Gupta, T Mukhopadhyay, D Varade, V Kushvaha
Recent Developments in Structural Engineering, Volume 1. SEC 2023. Lecture … , 2024
2024
Citations: 2
Utilizing statistical and MCDM techniques in indexing morphometric parameters towards improved watershed management in the Nandhour-Kalish drainage system
DM Gururani, D Varade, H Joshi, H Singh, Y Kumar, V Kumar
Journal of Water and Climate Change 15 (5), 2501-2517 , 2024
2024
Citations: 11
Stress Field Prediction in Particulate Polymer Composite Materials Using Paired Image-To-Image Translation Approach
S Gupta, V Kushvaha, D Varade
Advances in Theoretical and Applied Mechanics. ISTAM 2022. Lecture Notes in … , 2024
2024
Citations: 1
Polymer Composite Materials Using Paired Image-To-Image Translation
S Gupta, V Kushvaha, D Varade
Advances in Theoretical and Applied Mechanics: Proceedings of ISTAM 2022, 285 , 2024
2024

Divyesh Manohar Varade

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