A5079098948- Numerical methods in engineering
- Groundwater flow and contamination studies
- Hydrology and Watershed Management Studies
- Hydrological Forecasting Using AI
- Advanced Numerical Methods in Computational Mathematics
- Soil and Unsaturated Flow
- Groundwater and Isotope Geochemistry
- Water Systems and Optimization
- Electromagnetic Simulation and Numerical Methods
- Lattice Boltzmann Simulation Studies
- Dam Engineering and Safety
- Geotechnical Engineering and Underground Structures
- Infrastructure Maintenance and Monitoring
- Flood Risk Assessment and Management
- Geotechnical Engineering and Analysis
- Water resources management and optimization
- Computational Fluid Dynamics and Aerodynamics
- Hydraulic Fracturing and Reservoir Analysis
- Seismic Imaging and Inversion Techniques
- Reservoir Engineering and Simulation Methods
- Climate variability and models
- Landslides and related hazards
- Image Processing and 3D Reconstruction
- Fluid Dynamics Simulations and Interactions
Indian Institute of Technology Bombay
2018-2023
Abstract. Accurate estimate of groundwater recharge is crucial for prediction table dynamics and dependent eco-hydrological processes. Despite its importance, benchmark data at fine (~ daily) temporal resolution lacking. We present a first-of-a-kind daily per unit specific yield (RpSy) over periods 2–38 years 485 monitoring wells in the US. The RpSy these locations are calculated from time series using water fluctuations (WTF) method. Although direct validation not possible, since it first...
Among the different hydrological models used for water resources assessment, conceptual are gaining popularity due to their simple structure and satisfactory performance. In this study, performance of two rainfall-runoff models, GR4J (Génie Rural) AWBM (Australian Water Balance Model), working in Source modelling platform is evaluated at catchments upper Godavari basin, Maharashtra, India. an integrated resource management tool, developed by eWater Ltd, Australia. a four parameter store...
Abstract Contaminants in groundwater may enter through various sources which are required to be identified for informed decision-making regarding remediation. In early stages of contamination an aquifer, the generally unknown. To estimate unknown release histories at potential sources, governing equations contaminant transport solved backwards time renders inverse problem as ill-posed. Furthermore, due measurement or operational errors, observed breakthrough curves can noisy induce...
Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Deep neural network-based surrogate model linked with particle swarm optimization for identification of subsurface contamination sourcesAuthorsAatishAnshumaniDT.I.EldhoSee all authors Aatish AnshumaniDCorresponding Author• Submitting AuthorIndian Institute Technology BombayiDhttps://orcid.org/0000-0002-3849-9420view email addressThe was not providedcopy addressT.I. EldhoIndian Bombayview address
<p>Groundwater is the largest source for freshwater which plays an important role in hydrological cycle. The pollution of groundwater on rise due to various natural and anthropogenic sources such as landfills, agricultural lands, underground waste storage facilities etc. These pollutants can be subjected reactions depending contaminant type subsurface environment along with advection dispersion processes.  As used human activities drinking, agriculture industrial...