A5070972968- Flood Risk Assessment and Management
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Landslides and related hazards
- Cryospheric studies and observations
- Groundwater and Watershed Analysis
- Hydrology and Sediment Transport Processes
- Hydrological Forecasting Using AI
- Remote Sensing in Agriculture
- Climate change and permafrost
- Land Use and Ecosystem Services
- Soil erosion and sediment transport
- Arctic and Antarctic ice dynamics
- Geology and Paleoclimatology Research
- Advanced Data Storage Technologies
- Remote-Sensing Image Classification
- Urban Heat Island Mitigation
- Disaster Management and Resilience
- Climate variability and models
- Species Distribution and Climate Change
- Geochemistry and Geologic Mapping
- Fire effects on ecosystems
- Groundwater and Isotope Geochemistry
- Remote Sensing and Land Use
- Machine Learning and Algorithms
Marwadi University
2024-2025
Chandigarh University
2019-2024
Indian Institute of Technology Kharagpur
2024
Shiv Nadar University
2024
Birla Institute of Technology, Mesra
2024
University Hospital Leipzig
2023
Leipzig University
2023
Tarbiat Modares University
2022
Indian Institute of Technology Roorkee
2017-2022
University of Delhi
2021
Abstract Food security is a global challenge that aligns with several Sustainable Development Goals (SDGs), including SDG 1 ‐ “No Poverty”, 2 “Zero Hunger,” 3 “Good Health and Well‐being,” 13 “Climate Action,” 15 “Life on Land.”. To effectively address this issue, convergence of agriculture technology crucial, incorporating precision agriculture, sustainable bio‐economy advanced technologies such as machineries, Artificial intelligence‐meachine learning geospatial technology. Recent trends...
This work focuses on comparing results of flood susceptibility modelling in the part Middle Ganga Plain, foreland basin. Following inclusivity rule, 12 major explanatory factors including a new one, geomorphology, have been utilized. Out 1000 randomly generated flood-points from 2008 Landsat 5 TM image derived polygon, 70% utilized for training purpose Shannon’s entropy (SE) model and 30% area under receiver operating characteristic (AUROC) method validation both, SE frequency ratio (FR),...
Assessing the performance of land change simulation models is a critical step when predicting future landscape scenario. The study was conducted in district Varanasi, Uttar Pradesh, India because city being "the oldest living world" attracts vast population to reside here for short and long-term, leaving city's ecosystem more exposed fragility less resilient. In this work, an approach based on metrics introduced comparing ensemble designed simulate changes. A set were applied that offered...
There is an evident increase in the importance that remote sensing sensors play monitoring and evaluation of natural hazards susceptibility risk. The present study aims to assess flash-flood potential values, a small catchment from Romania, using information provided Geographic Informational Systems (GIS) databases which were involved as input data into number four ensemble models. In first phase, with help high-resolution satellite images Google Earth application, 481 points affected by...
Fluvial hazards cause severe damage to human lives and properties. The increased intrusion of anthropogenic activities into natural hydrological cycles has hazard severity confounded river channel dynamics. present article studies the epochal erosion, accretion, unaltered sites along 42 km stretch between Polavaram project Dowleshwaram Barrage on Godavari River. Geographic Information System (GIS) Remote Sensing (RS) techniques were used identify changes in morphology. A total five decades...
This study has developed a new ensemble model and tested another for flood susceptibility mapping in the Middle Ganga Plain (MGP). The results of these two models have been quantitatively compared performance analysis zoning susceptible areas low altitudinal range, humid subtropical fluvial floodplain environment part MGP, which is central River Basin (GRB), experiencing worse floods changing climatic scenario causing an increased level loss life property. MGP monsoonal climate, active...
The present study aims to enrich the specialized literature by proposing and calculating a new flash-flood propagation susceptibility index (FFPSI). Thus, firstly Flash-Flood Potential Index (FFPI) using ensembles of next models was calculated: Weights Evidence (WOE), Analytical Hierarchy Process (AHP), Logistic Regression (LR), Classification Trees (CART), Radial Basis Function Neural Network-Weights (RBFN-WOE). A number 255 locations, split into training (70%) validating (30%) samples,...
Flash floods pose a major challenge in various regions of the world, causing serious damage to life and property. Here we investigated Izvorul Dorului river basin from Romania, identify slope surfaces with high potential for flash-flood employing combination fuzzy logic algorithm following four machine learning models: classification regression tree, deep neural network, XGBoost naïve Bayes. Ten predictors were used as independent variables determine index. As dependent variable, areas...
The Mountainous terrain is experiencing rapid development in a bewildering manner, which makes it more susceptible to landslides. Management and mitigation of landslide hazard begin with its mapping by integrating numerous methods Geographic Information System (GIS) tools. However, difficult produce reliable susceptibility maps (LSM) due their complex nature. Therefore, the present study investigates applicability Mamdani's fuzzy inference system (FIS) LSM Himalayan India. It compared...
Prahova river basin located in the central-southern region of Romania. This study aims to assess susceptibility flooding by using state-of-the-art machine learning and optimization procedures. To achieve this goal, we employed ten flood-related variables as independent our models. These include slope angle, convergence index, distance from river, elevation, plan curvature, hydrological soil group, lithology, topographic wetness rainfall, land use. We used 158 flood locations dependent...
ABSTRACT Landslides present a significant danger to both infrastructure and human lives in the challenging terrain of Himalayas. Therefore, it is crucial accurately map areas prone landslides facilitate informed decision‐making proactive planning, allowing for effective management this hazard. Since landslide occurrences are accentuated by floods through toe erosion, wildfires research aims integrate machine learning techniques with analysis multiple hazards, such as forest fires, novel...
Abstract Floods occur frequently in Romania and throughout the world are one of most devastating natural disasters that impact people's lives. Therefore, order to reduce potential damages, an accurate identification surfaces susceptible flood phenomena is mandatory. In this regard, quantitative calculation susceptibility has become a very popular practice scientific research. With development modern computerized methods such as geographic information system machine learning models, result...