Category: application

Sikkim Wildfire Spread Forecasting and Monitoring System (SWFMS)

About Project

C-DAC has developed a unique operational Sikkim Wildfire Spread Forecasting and Monitoring System (SWFMS) for the state of Sikkim in collaboration with Department of Science and Technology, Sikkim and Indian Institute of Technology, Kharagapur. The SWFMS has been developed under the project funded by Ministry of Electronics and Information Technology, Govt. of India.

The system facilitates forest fire spread forecasting up-to next 48 hours after the fire ignition location is detected (either through satellites or by the field staff). The open source coupled atmosphere-wildfire model (WRF SFIRE) has been used to simulate forest fire. The system require information about fire ignition location, fuel parameters, landuse landcover map, elevation and forecasted atmospheric data. The system can be deployed on PARAM series of supercomputers.

User need internet connectivity to fire the simulation job on remote High Performance Computing (HPC) system by feeding in easily available inputs i.e. ignition location, date and time of fire and the duration for which simulation needs to be carried out. The job is executed on HPC and results (fire spread area) are sent back to the user. User can visualise the fire spread area in Geographical Information System (GIS) and send the SMS alerts to the registered user in the specified buffer area.

The Sikkim Forest Department has used the forecasted outputs for the forest fires happened on 27 January 2023 and 12 March 2024 and found the system useful in forest fire spread management.

Development and deployment of Forest Fire Spread Forecasting System in the state of Sikkim

  • Forest fire spread forecasting (uo-to next 48 hours)
  • Proximity based SMS alert (useful in sensitising the registered users only in the potentially affected area and thus avoiding the panicky to the unrelated population)
  • GIS depiction of the forecasted forest fire spread area (helpful in instantly visualising the potential forest fire spread in map form and strategies the actions to be taken)
  • Realtime field assistance to control the spreading wildfire. (The .kml version of the potential fire spread help in easy dissemination of information to the field staff and facilitate visualisation of potential fire spread area in google earth).
Visualisation of forecasted forest fire spread in GIS
Visualisation of forecasted forest fire spread in GIS
Sending SMS alerts to the registered user in a defined buffer region
Sending SMS alerts to the registered user in a defined buffer region
SWFMS-application3

Development of Forest Fire Spread Forecasting and Monitoring System (SWFMS) (Achieved)

Forest fire spread forecasts  successfully used for on ground control of spreading wildfire (12 March 2024 and 27 January 2023)

Publications
    • Manish P. Kale, Sri Sai Meher, Manoj Chavan, Vikas Kumar, Md. Asif Sultan, Priyanka Dongre, Karan Narkhede, Jitendra Mhatre, Narpati Sharma, Bayvesh Luitel, Ningwa Limboo, Mahendra Baingne, Satish Pardeshi, Mohan Labade, Aritra Mukherjee, Utkarsh Joshi, Neelesh Kharkar, Sahidul Islam,Sagar Pokale, Gokul Thakare, Shravani Talekar, Mukunda-Dev Behera , D. Sreshtha, Manoj Khare,Akshara Kaginalkar, Naveen Kumar and Parth Sarathi Roy Operational Forest-Fire Spread Forecasting Using the WRF-SFIRE Model, Remote Sens. 2024, 16(13), 2480. https://doi.org/10.3390/rs16132480
    • Satyajit Behera, Basanta Kumar Prusty, Mukunda Dev Behera, Manish Prabhakar Kale Characterizing fuel flammability in a tropical dry community forest in Eastern India using laboratory and remote sensing-based approaches, Trop Ecol 65, 399–411 (2023). https://doi.org/10.1007/s42965-023-00309-6
    • Sujoy Mudi, Somnath Paramanik, Mukunda Dev Behera, A Jaya Prakash, Nikhil Raj Deep, Manish P. Kale, Shubham Kumar, Narpati Sharma, Prerna Pradhan, Manoj Chavan, Partha Sarathi Roy & Dhiren G. Shrestha Moderate resolution LAI prediction using Sentinel-2 satellite data and indirect field measurements in Sikkim Himalaya, Environ Monit Assess 194, 897 (2022). https://doi.org/10.1007/s10661-022-10530-w

Forest department Sikkim has provided feedback in the form of report and letters regarding the utility of the system in controlling the spreading wildfire

  • Department of Science and Technology, Gangtok, Sikkim
  • Centre for Oceans, Rivers, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology, Kharagpur West Medinipur – 721 302, West Bengal, INDIA
  • Forest department, Sikkim

Head of the Department ESEG, C-DAC, Pune.

Phone: 020 – 25503233

Early warning system for flood prediction in the river basins of India

About Project

India is highly vulnerable to floods, which has large scale economic as well as social impacts. To address the issue and lessen the burden of the disaster management agencies, Centre for Development of Advanced Computing (C-DAC), Pune, is executing a project viz., ‘Early Warning System for Flood Prediction for River Basins of India’ under the National Supercomputing Mission of MeitY and DST, Govt. of India.

Under this project, three important aspects of flood management are being handled. Flood Prediction and Early Warning, Integrated Reservoir Operations and Sediment Transport Model.

A free and open source software tool for 2D hydrodynamic modelling is being used for prediction modelling and simulation. The model is designed such that it is both scalable and flexible and without much changes, except input data, and can be implemented in any river basin of India. The simulation runs for predicting floods are being carried out since year 2020. Every year daily flood predictions have been carried out for the monsoon season (June to October) for Mahanadi Basin. The model is massively parallelised and NSM HPC resources are being used for carrying out these daily simulation runs. The results have been shared with State Water Resources Department and Central Water Commission for validations. Since 2022 monsoon season, Tapi River Basin simulations have also been started.

Key Deliverables:

  • Early Warning System for Flood Prediction- 2-days flood forecast (water level, inundation extent, flow, village level % inundation)
  • Integrated framework for flood modelling at River Basin Level adaptable for the entire country

The daily outputs include a 2-day flood forecast in the form of village-level percentage inundation information and predicted inundation spread and water level information. This is the only solution that provides spatial inundation extent and depth of water for visualisation and querying. Every 3 hours, water progression is updated and spatial extents and water level can be visualised using geospatial portal C-FLOOD.

Both Odisha State Water Resources Department and Central Water Commission Bhubaneshwar have been part of this project and as such their continuous support has been fruitful for the project.

  • Design, develop and deploy an Early Warning System for Flood Prediction (EWS-FP) on HPC platform
  • Develop Sediment Transport model
  • Develop Integrated Reservoir Operation tools
  • Design geospatial portal for information dissemination on flood prediction

Weblink for geospatial portal https://inf.cwc.gov.in

Portal for visualization of daily forecast (Inset – Report showing villages that are flooded 40% or more by area)
Portal for visualization of daily forecast (Inset – Report showing villages that are flooded 40% or more by area)
Project showcased in national and international events
Project showcased in national and international events
  • The unified inundation system, C-FLOOD was launched by the Honourable Union Minister of Jal Shakti, Mr. C.R. Patil on the 2nd of July 2025. Shri C. R. Patil appreciated the collaborative efforts of CWC, C-DAC, and NRSC in operationalizing this state-of-the-art flood forecasting dissemination system.(Launch news link: https://www.pib.gov.in/PressReleseDetailm.aspx?PRID=2141608)
C-FLOOD was launched by the Honourable Union Minister of Jal Shakti, Mr. C.R. Patil on the 2nd of July 2025 at New Delhi
C-FLOOD was launched by the Honourable Union Minister of Jal Shakti, Mr. C.R. Patil on the 2nd of July 2025 at New Delhi
C-FLOOD was launched by the Honourable Union Minister of Jal Shakti, Mr. C.R. Patil on the 2nd of July 2025 at New Delhi
C-FLOOD was launched by the Honourable Union Minister of Jal Shakti, Mr. C.R. Patil on the 2nd of July 2025 at New Delhi
  • The system leverages HPC for high-resolution modelling, achieving up to a mere 15-20 cm error in water depth estimation in floodplains.
  • The system offers a 48-hour flood prediction window with a 2-hour simulation turnaround time. This crucial lead time enables authorities to take pre-emptive actions like evacuations.
  • The National Dam Safety Authority has awarded a project worth Rs. 8 CR for the first level Dam Break Rapid Assessment for 6500 dams covering the country using HPC resources.
  • GFCC (Ganga Flood Control commission) has invited C-DAC to submit proposal for Risk-based Comprehensive Plan for Flood Management in Ganga Basin. Technical proposal has been approved, and submitted by GFCC to Ministry for approval.
  • Tamil Nadu Disaster Management Commissioner has expressed their desire to implement this system in all the river basin of Tamil Nadu.
  • Feasibility analysis for proposed embankments, inundation prediction and embankment breach scenario generation for Lakhisarai District.
  • Collaboration between Oak Ridge National Laboratory (ORNL) and Centre for Development of Advanced Computing (C-DAC) on GPU-based flood modelling and simulation.
  • Nominated Member for Working Group on Data, Technology and Innovation under the National Task Force for Integrated Water Resources Development and Management.
  • GANANA: India-EU Initiative for Scientific High Performance Computing.
Publications
Journals
  1. Upasana Dutta, Yogesh Kumar Singh, T. S. Murugesh Prabhu, Girishchandra Yendargaye, Rohini Kale, Manoj Kumar Khare, Binay Kumar, and Rajani Panchang, Embankment Breach Simulation and Inundation Mapping: Leveraging High-Performance Computing for Enhanced Flood Risk Prediction and Assessment, ISPRS Annals Publication. ISPRS Belém 2024 TC3 Symposium. https://doi.org/10.5194/isprs-annals-X-3-2024-117-2024
  2. Upasana Dutta, Yogesh Kumar Singh, T. S. Murugesh Prabhu, Girishchandra Yendargaye, Rohini Gopinath Kale, Binay Kumar, Manoj Khare, Rahul Yadav, Ritesh Khattar and Sushant Kumar Samal, ‘Flood Forecasting in Large River Basins Using FOSS Tool and HPC’, Water 2021, 13(24), 3484; https://doi.org/10.3390/w13243484.
  3. Nisha Agrawal, Abhishek Das, Girishchandra R. Yendargaye, T.S.Murugesh Prabhu, Sandeep K. Joshi, and V. Venkatesh Shenoi. 2021. Performance Analysis of Python-based Finite Volume Solver ANUGA on Modern Architectures. 2021 Thirteenth International Conference on Contemporary Computing (IC3-2021) (IC3 ’21). Association for Computing Machinery, New York, NY, USA, 378–387

  1. Yogesh Kumar Singh, Upasana Dutta, T. S. Murugesh Prabhu, Girishchandra Yendargaye, Leveraging HPC and Advanced Hydrological Modeling for Accurate Flood Forecasting, Energy HPC Conference February 25–27, 2025 BRC Rice University Houston, TX

  2. Rohini Kale Upasana Dutta, Yogesh Kumar Singh, T. S. Murugesh Prabhu, Girishchandra Yendargaye, Multi-Source Elevation Extraction for Improved Hydrodynamic Modeling and Flood Simulation in ISG-ISRS National Symposium 2023

  3. Upasana Dutta, Yogesh Kumar Singh, T. S. Murugesh Prabhu, Girishchandra Yendargaye Remote Sensing Use for Flood and Drought Assessment at Regional and Global Scale, WARMS 2024.

  4. Yogesh Kumar Singh, Upasana Dutta, T. S. Murugesh Prabhu, Girishchandra Yendargaye Harnessing High-Performance Computing for Water Resources Management and Sustainability in Arid Regions

  5. T S Murugesh Prabhu, Yogesh Kumar Singh, Upasana Dutta, Girishchandra Yendargaye, Binay Kumar, Manoj Khare, ‘Altimetry-based gauge-level estimation in the Mahanadi River Basin’, 27th International Conference on Hydraulics, Water Resources, Environmental and Coastal Engineering (HYDRO 2022 INTERNATIONAL).

  6. Dahiwale A. V., Sekhar M., Dutta. U., Yogesh Kumar Singh and Prabhu T. S. M, ‘Modeling Sediment Transport Dynamics of Tel River in the sub-basin’, 27th International Conference on Hydraulics, Water Resources, Environmental and Coastal Engineering (HYDRO 2022 INTERNATIONAL).

  7. Dabra, R., Wadhwa, S., Sood, M.K., Sandhu, H.A.S., Batish, S., Kumar, B., Dutta, U., Yogesh Kumar Singh., Prabhu, T.S.M., Yendergaye, G., Khare, M., ‘Reservoir Operations using Artificial Neural Network – A case study of Hirakud Reservoir’, 27th International Conference on Hydraulics, Water Resources, Environmental and Coastal Engineering (HYDRO 2022 INTERNATIONAL).

  8. Yogesh Kumar Singh, ‘Early Warning System for Flood Prediction in the River Basins Of India’, Jan 2023, First International Conference on Emergency Support and Disaster Management (ISERDM), at National Institute of Technology, Tiruchirappalli (NIT-T), India.

  9. Yogesh Kumar Singh, ‘Early Warning System For Flood Prediction In The River Basins Of India using HPC’, 7th India Water Week – 2022, at India Expo Center, Greater Noida, India.

The Secretary of the Ministry of Jal Shakti has formally requested the Secretary of MeitY to initiate the launch of this system and replicate the deployment of the system to other basins
The Secretary of the Ministry of Jal Shakti has formally requested the Secretary of MeitY to initiate the launch of this system and replicate the deployment of the system to other basins
CWC commended C-DAC for successfully developing the Flood Inundation System, and invited C-DAC to be part of National Level Strategy and Roadmap for Flood Inundation Mapping and expand its implementation across other river basins in India, beginning with the Yamuna, Kosi and Gandak
CWC commended C-DAC for successfully developing the Flood Inundation System, and invited C-DAC to be part of National Level Strategy and Roadmap for Flood Inundation Mapping and expand its implementation across other river basins in India, beginning with the Yamuna, Kosi and Gandak
  • Central Water Commission (CWC), Delhi
  • Indian Institute of Science (IISc), Bengaluru
  • Central Water Commission (CWC)
  • State Water Resources Department (SWRD)
  • National and State Disaster Management Authorities (NDMA, SDMA)
  • National Disaster Response Force (NDRF)
  • District Administration

Ms. Upasana Dutta (PI), upasanad@cdac.in

+91-20-2550233/2550257

A HPC software suite for seismic imaging to aid oil and gas exploration

About Project

Seismic Data is acquired on land and in marine environment to find out the location of oil & gas reservoir in the subsurface. The processing of seismic data involves several steps before it gets converted into a meaningful and interpretable image of earth volume. Seismic Imaging is an advance processing step which converts seismic data to an earth subsurface image. Seismic imaging aims to create high resolution 2D & 3D structural images of subsurface geology. Reverse Time Migration (RTM) is one of the most reliable and preferred solution for seismic imaging of geological subsurface with complex structures. It can handle large velocity variation without any dip limitations for producing the earth subsurface structure with high resolution. It can deliver subsurface images with high accuracy in different mediums. RTM is highly computation, I/O and storage intensive, which requires High Performance Computing (HPC) ecosystem for execution.

Under the National Supercomputing Mission (NSM), “A HPC software suite for seismic imaging to aid oil and gas exploration” is a “Make in India” initiative to develop a customizable and efficient RTM software “SeisRTM”. It can provide high-resolution 2D & 3D seismic images of complex geological subsurface using acquired large seismic data. This software provides 2D modelling and RTM capabilities for both isotropic and anisotropic (VTI and TTI) media, as well as 3D isotropic modelling and RTM. SeisRTM is equipped with a suite of data preparation and post-processing tools, optimized to handle high-frequency migration and large datasets efficiently. It is designed for parallel computing environments, making it well-suited for deployment on CPU clusters without core limitations. SeisRTM offers both a Command Line Interface (CLI) and a Graphical User Interface (GUI) for user flexibility and includes an in-house developed data visualization tool to streamline data analysis and visualization. The indigenously developed “SeisRTM,” built on NSM infrastructure, will serve as a seismic imaging facility, delivering 3D RTM capabilities for upstream oil and gas exploration companies in India.

A Seismic Imaging Solution

To develop an indigenous software suite necessary for seismic imaging of complex structure under the earth using state-of the art NSM’s HPC ecosystem.

SeisRTM provides an intuitive and user-friendly interface for setting up and executing seismic modeling and migration workflows. The visualization module of SeisRTM enables users to analyze seismic imaging results through interactive and high-resolution graphical displays.

SeisRTM Work Screen
SeisRTM Work Screen
SeisRTM Visualization Modules
SeisRTM Visualization Modules
  • CDAC DG Award 2024 (Core Research)
  • National Workshop on HPC in Seismic Imaging “Seeing Below the Earth Surface”, SeisRTM Workshop was held at Pune held in April 2023)
A Workshop on HPC in Seismic Imaging “Seeing below the Earth Surface” was organized on 28th April 2023 at Pune. The workshop was inaugurated by Shri E. Magesh, Director General, C-DAC. 120+ Domain and computer science experts attended the workshop. Prominent institutes/organizations such as GEOPIC, ONGC; Directorate General of Hydrocarbon, Delhi; Indian Institute of Technology, Roorkee; CSIR-National Institute of Oceanography, Goa; Oil India Limited (OIL), Dibrugarh, Assam; Reliance Industries Limited etc. participated in the event.

 

  • Workshop on Seismic modeling and migration using SeisRTM was held at IIT Roorkee in December 2024
One day workshop on “Seismic Modeling and Migration using SeisRTM” was conducted at IIT Roorkee on December 6th 2024. 15+ students participated in the workshop. Participants were engaged in hands-on training and gained theoretical and practical insights into seismic imaging techniques. The event included talks by Prof. Anand Joshi, Head of Earth Sciences Dept., IIT Roorkee, and Ms. Richa Rastogi, Scientist F, C-DAC Pune. The workshop aimed to broaden the software’s reach, fostering its development while simultaneously advancing research and development in seismic imaging.

 

  • Workshop on Seismic modeling and migration using SeisRTM was held at IIT(ISM) Dhanbad held in February 2025
A three-day workshop on “Seismic Modeling and Migration using SeisRTM” was conducted at IIT (ISM), Dhanbad during 8th to 10th February, 2025. 140+ students participated in the workshop. Over the three days, participants were engaged in hands-on training and gained theoretical and practical insights into seismic imaging techniques. The sessions covered fundamental and advanced topics equipping attendees with experience in using SeisRTM for seismic data processing. The event included talks by Prof. Anand Joshi, Head of Earth Sciences Dept., IIT Roorkee, and Ms. Richa Rastogi, Scientist F, C-DAC Pune. Further the inaugural and valedictory events were graced by Prof. Sanjit Kumar Pal, Head of Applied Geophysics Dept., IIT (ISM) Dhanbad; Prof. Dheeraj Kumar, Deputy Director, IIT (ISM) Dhanbad and Prof. Mritunjay Kumar Singh, Dean of Academics, IIT (ISM) Dhanbad.

 

  • Workshop on Seismic modeling and migration using SeisRTM was held at BHU, Varanasi in March 2025

 

A three-day workshop on “Seismic Modeling and Migration using SeisRTM” was successfully conducted at BHU, Varanasi, from 26th to 28th March, 2025. More than 100 students enthusiastically participated in the workshop held at the Department of Geophysics, BHU Varanasi. The primary objective of the workshop was to expand the outreach of SeisRTM, encouraging its adoption and further development, while also advancing research and innovation in seismic imaging. The workshop’s valedictory session was graced by Prof. S. K. Upadhyay, Dean, Faculty of Science, BHU Varanasi.

 

  • Workshop on Seismic modeling and migration using SeisRTM was held at IIT Bombay from 29th April to 1st May 2025
A three-day workshop on “Seismic Modeling and Migration using SeisRTM” was successfully conducted at IIT Bombay, from April 29th to May 1st, 2025. Throughout the three-day event, participants were engaged in hands-on training, gaining both theoretical knowledge and practical experience in seismic imaging techniques.

 

MoUs
  • MoU signed on 27th June 2025 with Gujarat Energy Research and Management Institute (GERMI)
  • MoU signed on 04th February 2025 with Reliance Industries Limited
  • NDA signed on 07th December 2024 with Oil India
  • NDA signed on 10th September 2020 with GEOPIC ONGC
2025
  • Sharma, S., Joshi, A., Pandey, M. et al.Modelling of amplification of P-SV waves in an elastic medium using finite difference modelling technique. J Earth Syst Sci 134, 180 (2025). https://doi.org/10.1007/s12040-025-02628-9
  • Richa Rastogi, Abhishek Srivastava and Laxmaiah Bathula, 2025, SeisRTM: 2D/3D Reverse Time Migration (RTM) tool for Seismic Imaging, Beneath the Surface: Innovations in Geoscience SEG Symposium 2025
  • Laxmaiah Bathula, Richa Rastogi, Abhishek Srivastava and Monika Pokharkar, 2025, RTM imaging of reciprocity 2D walkaway VSP data, Beneath the Surface: Innovations in Geoscience SEG Symposium 2025
  • Richa Rastogi, Abhishek Srivastava, Monika Gawade, Bhushan Mahajan, Laxmaiah Bathula and Saheb Ghosh, 2024, Optimal Imaging Aperture for computational efficiency in 2D and 3D Reverse Time Migration using SeisRTM, First Break,2024, https://doi.org/10.3997/1365-2397.fb2024104
  • Rastogi, A. Srivastava, N. Mangalath, B. Mahajan, S. Ghosh and S. Phadke, 2024, Fast Reverse Time Migration with Enhanced Efficiency and Reduced Computational Load Using Partial Snapshot Storage, 85th EAGE Annual Conference & Exhibition, Jun 2024, Volume 2024, p.1 – 5, https://doi.org/10.3997/2214-4609.2024101153
  • Richa Rastogi, Abhishek Srivastava, Monika Pokharkar, Nithu Mangalath, & Saheb Ghosh. (2024). Efficient imaging aperture criterion for reduction of computational cost of TTI RTM. Australian Society of Exploration Geophysicists Extended Abstracts, Volume 2024, 1st ASEG DISCOVER Symposium, Hobart, https://doi.org/10.5281/zenodo.13918172
  • Richa Rastogi, Mr Abhishek Srivastava, Nithu Mangalath Bhushan Mahajan, Mr. Saheb Ghosh and Mr. Suhas Phadke, Fast Reverse Time Migration with enhanced efficiency and reduced computational load using partial snapshot storage. European Association of Geoscientists & Engineers,2024, https://doi.org/10.3997/2214-4609.2024101153
  • Richa Rastogi, Abhishek Srivastava and Laxmaiah Bathula, Reverse Time Migration: A tool for complex seismic Imaging, Conference on Integrated Earth (CITE) – 2024
  • Sharma, S., Joshi, A., Singh, J., Pandey, M., Rastogi, R., and Srivastava, A.: Identification of Point Diffractor body placed in dipping Vertically Transverse Isotropic medium using Reverse Time Migration, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-313, https://doi.org/10.5194/egusphere-egu23-313, 2023.http://dx.doi.org/10.5194/egusphere-egu23-313
  • Sandeep Agrawal, Abhishek Srivastava, Richa Rastogi, Jyotsna Khemka, Vinutha SV, Om Jadhav, Sanjay Wandhekar, Migration of CUDA based Seismic Application to Cross-platform SYCL Implementation, HiPC 2023,  https://doi.ieeecomputersociety.org/10.1109/HiPCW61695.2023.00017
  • Rastogi, R., Srivastava, A., Mangalath, N., Gawade, M., Bathula, L., Phadke, S., Ghosh, S., 2023, Evaluation of RTM implementation approaches using conventional and boundary wavefield savings, SPG-14th International Conference & Exposition, 2023, https://spgindia.org/Kochi2023-expanded-abstracts/evaluation-of-rtmm-implementation-approaches-using-conventional-and-boundary-wavefield-savings.pdf
  • Rastogi, R., Srivastava, A., Phadke, S., Mahajan, B., Bathula, L., Ghosh, S. (2023), Improved RTM imaging of marine streamer data using principle of reciprocity, European Association of Geoscientists & Engineers, Jun 2023, Volume 2023, p.1 – 5, https://doi.org/10.3997/2214-4609.202310353
  • Kumar, A., Rastogi, R., Srivastava, A., Mahajan, B. (2023), RTM image conditioning using deep learning, European Association of Geoscientists & Engineers, Jun 2023, Volume 2023, p.1 – 5, https://doi.org/10.3997/2214-4609.202310451
  • Saurabh Sharma, A. Joshi, Richa Rastogi, Abhishek Srivastava, Bhushan Mahajan, Nithu Mangalath, Reverse Time Migration of 2D isotropic Basin model using staggered-grid finite difference scheme, Earth Sciences in India: Challenges and Emerging Trends (ESICET) – 2023
  • Richa Rastogi, Abhishek Srivastava, Saheb Ghosh, Anand Joshi, Suhas Phadke, Nithu Mangalath, Bhushan Mahajan, Monika Gawade, Laxmaiah Bathula, Hrishikesh Kumbhar, and Saurabh Sharma, SeisRTM: A make in India Initiative for Software Development for Reverse Time Migration (RTM) to aid Oil and Gas Data Processing for Seismic Imaging, Earth Sciences in India: Challenges and Emerging Trends (ESICET) – 2023
  • Successfully migrated SeisAcouMod2D CUDA version to SYCL on Intel Datacenter GPU Max 1500 with CDAC’s HPC-Tech and Intel’s team. A case study regarding the same is published on Intel’s website, https://www.intel.com/content/www/us/en/developer/articles/case-study/c-dac-achieves-1-75x-performance-improvement.html
  • Rastogi, R.,Srivastava, A.,Gawade, M.,Manglath, N., Bathula, L, Mahajan ,B., Phadke, S., 2022, 2D isotropic and vertical transversely isotropic RTM using SEG Hess VTI Model, SEG IMAGE 22-the International Meeting for Applied Geoscience & Energy in Houston, USA. https://doi.org/10.1190/image2022-3745595.1
  • Londhe, A., Rastogi, R.,Srivastava, A.,Khonde, K.,Srisarala, K.,Kharche, K., 2021, Adaptively accelerating FWM2DA seismic modelling program on multicore CPU and GPU architectures. Computers & Geosciences. 146. 104637, https://doi.org/10.1016/j.cageo.2020.104637
5

Consortia Partners

Centre for Development of Advanced Computing (C-DAC), Pune

Geodata Processing and Interpretation Centre (GEOPIC), ONGC

Indian Institute of Technology Roorkee (IITR)

  • Agencies involved in oil and gas exploration
  • Research organization for deep crustal studies
  • Academia for teaching advance seismic processing

Ms. Richa Rastogi (PI), richar@cdac.in

+91-20-25503360

Urban Modelling: Development of multi-sectorial simulation lab and science-based decision support framework to address urban environment issues

Urban Modelling: Development of multi-sectorial simulation lab and science-based decision support framework to address urban environment issues

About Project

India is undergoing a major urban population shift, with a projection to be double by 2050. This rapid urban expansion is reshaping the socio-economic landscape but also intensifying environmental vulnerabilities across cities. As urban areas grow, Indian cities are increasingly experiencing extreme weather events and environmental stressors, such as, intense rainfall and urban flooding, heat and cold waves, and severe air pollution episodes. These are no longer isolated incidents; they are becoming frequent and more severe, posing significant risks to public health, infrastructure, and economy. The cascading effects of these environmental challenges are felt across all levels of governance. Policymakers at the national, state, and local levels are increasingly concerned about the long-term implications of these urban stressors.

To effectively manage and mitigate these challenges, it is vital to understand, simulate, and predict urban extreme events in a timely and accurate manner. This calls for a science-based decision support system that can guide operational responses and policy formulation. Urban environmental systems are essentially cross-sectoral interactions between meteorology, hydrology, and air quality. Addressing these complexities requires a fully integrated modeling platform that includes:

  • High-Performance Computing (HPC)
  • Multi-source input data: satellite, ground observations, and real-time data
  • Validation and verification mechanisms to ensure model accuracy
  • Multi-model interoperability for seamless integration across domains
  • Multi-scale ensemble modeling
  • 2D/3D visualization tools

The comprehensive urban modeling system will encompass, Urban parameterization and canopy modeling, Urban Heat Island (UHI) analysis, Boundary layer and atmospheric dynamics, Chemical and morphological data assimilation, Query frameworks powered by big data analytics and AI/ML technologies. These components will enable to forecast extreme events, assess risks, and help city authorities to plan management strategies.

Against this backdrop, the NSM Urban Modelling consortia project (funded by MeitY) is articulated for timely prediction of weather, air quality, and hydrological systems. Urban Modelling project, an integrated urban modelling system and service cyberinfrastructure Urban Environment Science to Society (UES2S) (Figure 1) is developed. This is an online, fully coupled urban ‘meteorology and hydrology, and air quality’ modeling system (Figure 2) which captures the urban representation of micro-scale city environmental conditions.

Figure 1: Homepage of Urban Environment Science to Society (UES2S)
Figure 1: Homepage of Urban Environment Science to Society (UES2S)
Figure 2: HPC Based Integrated Urban Modelling System
Figure 2: HPC Based Integrated Urban Modelling System

The objective of this consortia project is to develop an online fully coupled urban ‘meteorology, hydrology, and air quality’ modeling system to capture the urban representation of micro-scale city environmental conditions. The aim is to improve the skill of urban weather forecasting, atmospheric dispersion and air quality forecasting, and hydrology forecasting useful for exposure assessment, disaster management, daily operations, and policy decisions and create a science-based, HPC-enabled urban data and decision framework with optimized performance and 3D visualization techniques, thereby fulfilling India’s sustainable smart city goals.

The NSM Urban Modelling Project developed the online, fully coupled urban “meteorology, hydrology, and air quality” modelling system called UES2S. The urban illustration of micro-scale city environmental conditions is captured by this approach. Data as a service (Data Hub), modeling platform as a service (Science Gateway), and Decision Support System (DSS) for cross-sector end-user decisions are the three main parts of UES2S. We plan to offer a data-sharing platform and cross-sector data access through Data Hub. On NSM clusters, the Science Gateway (Figures 3 & 4) offers ready-to-use weather, hydrological, and air quality models through automated end-end modeling workflows. The DSS component (Figures 5 and 6) facilitates easy conversion of scientific data into participatory, multi-stakeholder actions. The DSS forecasts reservoir inflows, water levels, and weather, air quality, and hydrology with high resolution. Thus, the DSS is essential to everyday operations, disaster management initiatives, and science-based policymaking.

To solve urban environmental issues, this multi-sector simulation lab and science-based decision framework were created. This interdisciplinary urban testbed and HPC-based automated model execution workflows were created to run meteorological, hydrological, and air quality models in order to predict extreme events. This system’s incredibly user-friendly architecture, researchers and students can execute the models with ease. This would make it easier for research to be smoothly incorporated into operational procedures. The framework enables meteorology, air quality, and hydrology services for a variety of stakeholders by providing an urban modeling system, operational procedures, a data hub, and a DSS.

Science Gateway, a digital platform designed specifically for meteorologists, hydrologists, and air quality modelers that provide easy access to data from specialist tools and collaborative capabilities to improve research and forecasting in these fields. The Weather Research and Forecasting (WRF) workflow (Figure 4) is created in Science Gateway, a cutting-edge mesoscale numerical weather prediction system intended for operational forecasting and atmospheric research applications.

Making decisions during extreme events, such as heat waves, floods, and heavy rains, is aided by a Decision Support System (DSS) (Figure 5). It makes it easier to analyze hydrological indicators like reservoir levels and river flows, air pollution levels like PM2.5, and meteorological events like heat and cold waves, short-duration high-intensity rains, and more.

The reservoir operations module, an essential element of the DSS, presents a series of forecast plots over time as shown in Figure 5. This chart features various parameters like rainfall in the upstream/downstream catchment, the water level of the reservoir, dam discharge, and the inflow to the reservoir for the chosen reservoir by the user. The user, generally a scientist or operational forecaster in weather, environmental science, or disaster management, can utilize this data to make informed decisions and strategize effectively.

In a section of the DSS module (Figure 6), users can choose flood hotspots found in the alerts area and then click on a hotspot marker for a specific location to see water depth relative to human height, enhancing the visualization engaging and intuitive.

Figure 3: Components of Science Gateway
Figure 3: Components of Science Gateway
Figure 4: WRF Workflow
Figure 4: WRF Workflow
Figure 5: Decision Support System
Figure 5: Decision Support System
Figure 6: DSS for Flood – Water depth: 0.52 meter (pictorial view) at Pune catchment
Figure 6: DSS for Flood – Water depth: 0.52 meter (pictorial view) at Pune catchment
  • Calibrated and customized model for Indian cities
  • Prepared high resolution LULC map for pilot cities
  • Integrated Met-Hydro-AQ user friendly web-based Model Execution framework (WRF, WRF-Chem, AERMOD, HEC-RAS, HEC-HMS, SWMM), Data hub and Decision Support System
  • End-to-End automated model forecast validation tool
  • Indigenously developed visualization platform
  • Provided access of developed system to IMD
  • Shared ward level Rainfall, Reservoir Water and urban flood, heatwave, air pollution forecast information with IMD, PMC, PCMC and WRD (Figure 3 & 4)
  • Demonstration of UES2S to Dr. M. Ravichandran, Secretary, MoES, Chairman, PMC and domain experts (Figure 5)
  • 36 Publications in peer-reviewed journals & 13 Conference papers
  • MoU signed on 30th October 2024 with Pimpri-Chinchwad Municipal Corporations to share urban Decision Support System weather, flood information, and air quality (jointly with IITM Pune) at ward level
  • Data sharing: Providing weather and flood forecast to IMD, Pune Municipal Corporation, Pimpri Chinchwad Municipal Corporation (PCMC) and water resources departments, govt of Maharashtra
Figure 7: Typical Daily Rainfall info upto Ward level
Figure 7: Typical Daily Rainfall info upto Ward level
Figure 8: Air quality forecast information
Figure 8: Air quality forecast information
Figure 9: Project review by Dr. M. Ravichandran, Secretary, MoES, Chairman, PMC and domain experts
Figure 9: Project review by Dr. M. Ravichandran, Secretary, MoES, Chairman, PMC and domain experts
MoU
  • MoU signed with Pimpri-Chinchwad Municipal Corporation (PCMC) on 30th October 2024 to share the access and use of Urban Decision Support System
(R to L) Dr Sanjay Wandhekar Centre Head, C-DAC Pune, Mr Shekhar Singh (IAS) Commissioner, PCMC, PCMC officials
Journal
2025
  1. Boyaj, A., Sinha, Palash, Karrevula, N.R., Nadimpalli, R., Vinoj, V., Islam, Sahidul., Khare, M. and Mohanty, U.C., 2025. Assessment of the WRF Model for Real-Time Prediction of Heavy Rainfall Events over the Twin Cities of East Coast of India. Pure and Applied Geophysics, pp.1-19. https://doi.org/10.1007/s00024-025-03734-x.
  2. Boyaj, A., Karrevula, N.R., Swain, M., Sinha, Palash., Nadimpalli, R., Islam, Sahidul., Vinoj, V., Khare, M., Niyogi, D. and Mohanty, U.C., 2025. Assessment of the WRF model configuration optimization in predicting the heavy rainfall over urban city Bhubaneswar, India. Computational Urban Science, 5(1), pp.1-21. https://doi.org/10.1007/s43762-025-00180-2.
  3. Ambulkar, R., Govardhan, G., Gavhale, S., Kalita, G., Pande, C., Jat, R., et al. (2025). Crop residue burning in north-western India: Emission estimation and uncertainty quantification. Journal of Geophysical Research: Atmospheres, 130, e2024JD042198. https://doi.org/10.1029/2024JD042198
  4. Govardhan, G., Ghude, S. D., Kumar, R., Sharma, S., Gunwani, P., Jena, C., Yadav, P., Ingle, S., Debnath, S., Pawar, P., Acharja, P., Jat, R., Kalita, G., Ambulkar, R., Kulkarni, S., Kaginalkar, A., Soni, V. K., Nanjundiah, R. S., and Rajeevan, M.: Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India, Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024.
  5. Rajmal Jat, Chinmay Jena, Prafull P. Yadav, Gaurav Govardhan, Gayatry Kalita, Sreyashi Debnath, Preeti Gunwani, Prodip Acharja, PoojaV. Pawar, Pratul Sharma, Santosh H. Kulkarni, Akshay Kulkarni, Akshara Kaginalkar, Dilip M. Chate, Rajesh Kumar, Vijay Kumar Soni, Sachin D. Ghude,Evaluating the sensitivity of fine particulate matter (PM2.5) simulations to chemical mechanism in WRF-Chem over Delhi, Atmospheric Environment,Volume 323,2024,120410,ISSN 1352-2310, https://doi.org/10.1016/j.atmosenv.2024.120410.
  6. Akash S. Vispute, Prodip Acharja, Suresh W. Gosavi, Gaurav Govardhan, Vinayak Ruge, M.N. Patil, T. Dharmaraj, Sachin D. Ghude, Source characteristics of Non-Refractory Particulate Matter (NR-PM1) using High-Resolution Time-of-Flight Aerosol Mass Spectrometric (HR-ToF-AMS) measurements in the urban industrial city in India, Atmospheric Environment,2025,121186,ISSN 1352-2310, https://doi.org/10.1016/j.atmosenv.2025.121186.
  7. Chinmay Jena , et. al.: “ Evaluating the sensitivity of fine particulate matter (PM2.5 ) simulations to chemical mechanism in WRF-Chem over Delhi”., Science of the Total Environment, (2023). https://doi.org/10.1016/j.atmosenv.2024.120410.
  1. Ghude SD, Govardhan G, Kumar R, Yadav PP, Jat R, Debnath S, Rajeevan M (2024) Air Quality warning and Integrated decision support system for emissions(AIRWISE): Enhancing Air Quality management in megacities. Bull Am Meteorol Soc. https://doi.org/10.1175/BAMS-D-23-0181.1
  2. Swain, M., Nadimpalli, R., Das, A.K., Mohanty, U.C. and Niyogi, D., 2023. Urban modification of heavy rainfall: a model case study for Bhubaneswar urban region. Computational Urban Science, 3(1), p.2. https://doi.org/10.1007/s43762-023-00080-3.
  3. Islam, S., Karipot, A., Bhawar, R., Sinha, P., Kedia, S. and Khare, M., 2024. Urban heat island effect in India: a review of current status, impact and mitigation strategies. Discover Cities, 1(1), pp.1-28. https://doi.org/10.1007/s44327-024-00033-3.
  4. Gaikwad S., et al 2024: Harnessing deep learning for forecasting fire-burning locations and unveiling PM2.5 emissions, Modeling Earth Systems and Environment, 10, February 2024, DOI:10.1007/s40808-023-01831-1, 927-941. https://doi.org/10.1007/s40808-023-01831-1.
  5. Govardhan G., et al (2024), Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India, Geoscientific Model Development, 17, April 2024, DOI:10.5194/gmd-17-2617-2024, 2617–2640. https://doi.org/10.5194/gmd-17-2617-2024.
  6. Karrevula, N.R., Nadimpalli, R., Sinha, P., Mohanty, S., Boyaj, A., Swain, M. and Mohanty, U.C., 2024. Performance Evaluation of WRF Model in Simulating Extreme Rainfall Events Over Bhubaneswar Urban Region of East Coast of India. Pure and Applied Geophysics, pp.1-27. https://doi.org/10.1007/s43762-025-00180-2.
  7. Karrevula, N.R., Boyaj, A., Sinha, P., Nadimpalli, R., Mohanty, U.C., Islam, S., Kaginalkar, A. and Vinoj, V., 2024. Role of planetary boundary layer physics in urban-scale WRF model for predicting the heat waves over tropical city Bhubaneswar. Journal of Earth System Science, 133(3), pp.1-26. https://www.researchgate.net/publication/383642297_Role_of_planetary_boundary_layer_physics_in_urban-scale_WRF_model_for_predicting_the_heat_waves_over_tropical_city_Bhubaneswar.
  8. Boyaj, A., Karrevula, N.R., Sinha, P., Patel, P., Mohanty, U.C. and Niyogi, D., 2024. Impact of increasing urbanization on heatwaves in Indian cities. International Journal of Climatology, 44(11), pp.4089-4114. https://doi.org/10.1002/joc.8570.
  9. Boyaj, A., Sinha, P., Mohanty, U.C., Vinoj, V., Ashok, K., Islam, S., Kaginalkar, A. and Khare, M., 2024. Projected frequency of low to high-intensity rainfall events over India using bias-corrected CORDEX models. Atmospheric Research, p.107760. https://www.researchgate.net/publication/385505754_Projected_frequency_of_low_to_high-intensity_rainfall_events_over_India_using_bias-corrected_CORDEX_models.
  1. Mohanty, S., Swain, M., Nadimpalli, R., Osuri, K.K., Mohanty, U.C., Patel, P. and Niyogi, D., 2023. Meteorological conditions of extreme heavy rains over coastal city Mumbai. Journal of Applied Meteorology and Climatology, 62(2), pp.191-208. https://doi.org/10.1175/JAMC-D-21-0223.1
  2. Boyaj, A., Nadimpalli, R., Reddy, D., Sinha, P., Karrevula, N.R., Osuri, K.K., Srivastava, A., Swain, M., Mohanty, U.C., Islam, S. and Kaginalkar, A., 2023. Role of radiation and canopy model in predicting heat waves using WRF over the city of Bhubaneswar, Odisha. Meteorology and Atmospheric Physics, 135(6), p.60. https://doi.org/10.1007/s00703-023-00994-x.
  3. Swain, M., Nadimpalli, R.R., Mohanty, U.C., Guhathakurta, P., Gupta, A., Kaginalkar, A., Chen, F. and Niyogi, D., 2023. Delay in timing and spatial reorganization of rainfall due to urbanization-analysis over India’s smart city Bhubaneswar. Computational Urban Science, 3(1), p.8. https://doi.org/10.1007/s43762-023-00081-2.
  4. Gunwani P., et. al.: “Sensitivity of WRF/Chem to different Meteorological Initial Conditions and PBL parameterization schemes”, Atmospheric Environment (2023). https://doi.org/10.1007/s10661-023-10987-3.
  5.  Madhusmita Swain, et al., 2023: Delay in timing and spatial reorganization of rainfall due to urbanization- analysis over India’s smart city Bhubaneswar. Comput. Urban Sci. 3, 8. https://doi.org/10.1007/s43762-023-00081-2.
  6. Shyama Mohanty,  Madhusmita Swain, Raghu Nadimpalli, K. K. Osuri, U. C. Mohanty, Pratiman Patel, and  Dev Niyogi, 2023: Meteorological Conditions of Extreme Heavy Rains over Coastal City Mumbai. Journal of Applied Meteorology and Climatology, 2023,Vol.62-2, 191–208. https://doi.org/10.1175/JAMC-D-21-0223.1.
  7. V. K. Valappil, Sumita Kedia, A. K Dwivedi, S. S Pokale, Sahidul Islam, Manoj K Khare, Assessing the performance of WRF ARW model in simulating heavy rainfall events over the Pune region: in support of operational applications, Meteorology and Atmospheric Physics, 2023. https://doi.org/10.1007/s00024-025-03734-x.
  8. Madhusmita Swain, R. Nadimpalli, U C Mohanty, P Guhathakurta, A Gupta, A Kaginalkar, F Chen, and D Niyogi. Delay in timing and spatial reorganization of rainfall due to urbanization- Analysis for pre-monsoon conditions in Bhubaneswar, India. Computational Urban Science vol 3, Article number: 8 (2023). https://doi.org/10.1007/s43762-023-00081-2.
  9. Gayatry Kalita, et. al.: “Forecasting of an unusual dust event over Western India by the Air Quality Early Warning System”, Atmospheric Environment (2023). https://doi.org/10.1016/j.atmosenv.2023.120013.
  10. Madhusmita Swain, R. Nadimpalli, U C Mohanty, and D Niyogi. Urban modification of heavy rainfall: a model case study for Bhubaneswar urban region. Computational Urban Science volume 3, Article number: 2 (2023). https://doi.org/10.1007/s43762-023-00080-3
  1. Risma Joseph, P. P. Mujumdar, Rajarshi Das Bhowmik, (2022). Reconstruction of Urban Rainfall Measurements to Estimate the Spatiotemporal Variability of Extreme Rainfall. Water, 14(23), 3900. Doi: https://doi.org/10.3390/w14233900, (2022)
  2. Gaurav Govardhan, et. al.: “Satellite retrieved stubble-burning activities in north-western India in 2021: Contribution to air pollution in Delhi“, Heliyon (2022). https://orcid.org/0000-0003-0213-6289.
  3. Sreyashi Debnath, et. al.: “Implications of implementing promulgated and prospective emission regulations on air quality and health in India during 2030” AAQR (2022). https://doi.org/10.4209/aaqr.220112.
  4. Davis S, Pentakota L, Saptarishy N and Mujumdar PP : A Flood Forecasting Framework Coupling a High-Resolution WRF Ensemble With an Urban Hydrologic Model. Front. Earth Sci. 10:883842. Doi: 10.3389/feart.2022.883842, (2022). https://doi.org/10.3389/feart.2022.883842.
  5. Sengupta A., G. Govardhan, S. Debnath, C. Jena, A.N. Parde, P. Lonkar, P. Gunwani, Santosh H Kulkarni, S. Nivdange, R Kumar, and S.D. Ghude, “Probing into the wintertime meteorology and particulate matter (PM2.5 and PM10) forecast over Delhi”, Atmospheric Pollution Research, (2022). https://doi.org/10.1016/j.apr.2022.101426.
  6. S. Nivdange, C. Jena, P. Pawar-Jadhav, G. Govardhan, Santosh H. Kulkarni, P. Lonkar, A. Vispute, N. Dhangar, A. Parde, P. Acharja, V. Kumar, P. Yadav and N. R Karmalkar: Nationwide CoViD-19 lockdown impact on air quality in India, Mausam, 73, 1, 115-128, (2022). https://doi.org/10.54302/mausam.v73i1.1475.
  1. Nadimpalli, Raghu, Shyama Mohanty, Nishant Pathak, Krishna K. Osuri, U. C. Mohanty, and Somoshree Chatterjee. “Understanding the characteristics of rapid intensity changes of Tropical Cyclones over North Indian Ocean.” SN Applied Sciences 3, no. 1 (2021): 1-12. https://doi.org/10.1007/s42452-020-03995-2.
  2. Mohanty, Shyama, Raghu Nadimpalli, U. C. Mohanty, M. Mohapatra, A. Sharma, Ananda K. Das, and S. Sil. “Quasi-operational forecast guidance of extremely severe cyclonic storm Fani over the Bay of Bengal using high-resolution mesoscale models.” Meteorology and Atmospheric Physics 133, no. 2 (2021): 331-348. https://doi.org/10.1007/s00703-020-00751-4.
  3. Kaginalkar A. et al., Integrated urban environmental system of systems for weather ready cities in India, https://doi.org/10.1175/BAMS-D-20-0279.1, Bulletin of the American Meteorological Society, (2021).
  4. Pawar, P. V., S. D. Ghude, C. Jena, Móring, A., Sutton, M. A., Kulkarni Santosh H., Lal, D. M., Surendran, D., Van Damme, M., Clarisse, L., Coheur, P.-F., Liu, X., Xu, W., Jiang, J., and Adhya, T. K.: Analysis of atmospheric ammonia over South and East Asia based on the MOZART-4 model and its comparison with satellite and surface observations, Atmos. Chem. Phys,. https://doi.org/10.5194/acp-2020-639, (2021)
  5. C. Jena, S. D. Ghude, R. Kumar, S. Debnath, G. Govardhan, V. K. Soni, Santosh H. Kulkarni, G. Beig, R. S. Nanjundiah and M. Rajeevan: Performance of high resolution (400 m) PM2.5 forecast over Delhi. Nature Sci Rep, 11, 4104,  (2021). https://doi.org/10.1038/s41598-021-83467-8.
  6. Sumita Kedia, Sudheer Bhakare, Arun Dwivedi, Sahidul Islam, Akshara Kaginalkar: Estimates of change in surface meteorology and urban heat island over northwest India: Impact of urbanization, Urban Climate, Volume 36, (2021). https://doi.org/10.1016/j.uclim.2021.100782.
  1. S. D. Ghude, R. Kumar, C. Jena, S. Debnath, R. G. Kulkarni, S. Alessandrini, M. Biswas, Santosh H. Kulkrani, P. Pithani, S. Kelkar, V. Sajjan, D.M. Chate, V.K. Soni, S. Singh, R. S. Nanjundiah and M. Rajeevan: Evaluation of PM2.5 forecast using chemical data assimilation in the WRF-chem model: a new initiative under the Ministry of Earth Sciences (MoES) air quality early warning system (AQEWS) for Delhi, Current Science (2020). https://opensky.ucar.edu/system/files/2024-08/articles_23419.pdf.
  2. Kulkarni Santosh H., S. D. Ghude, C. Jena, R. K. Karumuri, B. Sinha, V. Sinha, R. Kumar, V. K. Soni, and M. Khare: How Much Does Large-Scale Crop Residue Burning Affect the Air Quality in Delhi? Environmental Science & Technology, 54 (8), 4790-4799 (2020). https://dx.doi.org/10.1021/acs.est.0c00329?ref=pdf.
  3. Kumar R., Ghude, S. D, M. Biswas, C. Jena, S. Alessandrini, S. Debnath, Santosh Kulkarni, Simone Sperati, Vijay K. Soni, R. S. Nanjundiah, and M. Rajeevan: Enhancing accuracy of air quality and temperature forecasts during paddy crop-residue burning season in Delhi via chemical data assimilation, JGR (Atmosphere), (2020). https://doi.org/10.1029/2020JD033019.
  4. Jena, C., Ghude, S. D., Kulkarni, R., Debnath, S., Kumar, R., Soni, V. K., Acharja, P., Kulkarni  Santosh H., Khare, M., Kaginalkar, A. J., Chate, D. M., Ali, K., Nanjundiah, R. S., and Rajeevan, M. N.: Evaluating the sensitivity of fine particulate matter (PM2.5) simulations to chemical mechanism in Delhi, Atmos. Chem. Phys. Discuss.,  (2020). https://doi.org/10.5194/acp-2020-673.
  5. S. D. Ghude, R. K. Karumuri, C. Jena, R. Kulkarni, G.G. Pfister, V. S. Sajjan, P. Pithani, S. Debnath, R. Kumar, B. Upendra, Santosh H. Kulkarni, D.M. Lal, R.J. Vander A, A. S. Mahajan: What is driving the diurnal variation in tropospheric NO2 columns over a cluster of high emission thermal power plants in India?, Atmospheric Environment: X 5, 100058,  (2020). https://doi.org/10.1016/j.aeaoa.2019.100058.
  1. U C Mohanty, Narayana Reddy Karrevula, Alugula Boyaj, Madhu Smita Swain, Raghu Nadimpalli, Palash Sinha, Sahidul Islam, Manoj Khare (2025). Urban-Scale Weather Modelling System for Prediction of Heavy Rainfall Events during Summer Monsoon Season over India. The Eight International Workshop on Monsoons (IWM8) under the World Weather Research Programme (WWRP) of the World Meteorological Organization (WMO), held at Indian Institute of Tropical Meteorology (IITM) Pune during 17-20 March 2025.
  2. Palash Sinha, Sahidul Islam, Ketaki Belange, Sumita Kedia, T.S. Saikrishna and Manoj Khare: Heatwave Predictions and Decision Support System for Advisory. Presented at TROPMET-2024, 10-12-Dec-2024 at NIT Rourkela, Odisha.
  3. Arun K. Dwivedi, Sumita Kedia, Sagar Pokale, Palash Sinha, Akshara Kaginalkar, Manoj K. Khare, U.C. Mohanty, Sahidul Islam, Assessment of WRF Model in Predicting Heavy Rainfall Events over Complex Topographical Urban City Pune, submitted to International Conference on Urban Climate (ICUC-11), during 28 Aug-1 Sept 2023. https://www.researchgate.net/deref/https%3A%2F%2Fdoi.org%2F10.1007%2Fs00024-025-03734x?_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6InB1YmxpY2F0aW9uIiwicGFnZSI6InB1YmxpY2F0aW9uIn19.
  4. Sumita Kedia, A. K. Dwivedi, S. Pokale, Sahidul Islam, A. Kaginalkar, P. Sinha, S. Ghavale, R. Nadimpalli, U. C. Mohanty, D. Niyogi, M. Khare, Impact of land use information on heavy rainfall event forecast using an urban scale model, accepted and presented during AMS annual meeting 2023.
  5. Dev Niyogi, Pallavi Gavali, Mohamed Niyaz J, Srujan Gavhale, Arun Dwivedi, Sumita K, Sagar Pokale, Gouri Kadam, Sahidul Islam, Akshara Kaginalkar, Pradeep Mujumdar. Abinav Wadhawa, Likhitha P.: Coupled Meteorology and Hydrology Modelling to Forecast Flood Extreme Events: Case Study of Pune, India. AGU Fall meeting 2022 meet, at Chicago 12 -16 Dec 2022, Advances in modeling hydrological extremes and engineering practices.
  6. Gouri Kadam, M. Niyaz, P. G. Gavali, S. Gavhale, L. Pentakota, S. Kedia, S. Islam, A. K. Dwivedi, S. Pokale, A. Kaginalkar, P. Mujumdar, M. Khare, and D. Niyogi:  Multi-Model Hydrology for Urban Flood Early Warning for Pune, India.  103rd American Meteorological Society Annual Meeting, Denver, USA. (37th Conference on Hydrology).
  7. Pallavi Gavali, Srujan Gavhale, Mohamed Niyaz, Sahidul Islam, Sumita Kedia, Sagar Pokale, Arun Dwivedi, Gouri Kadam, Akshara Kaginalkar, Manoj Khare, and Abhinav Wadhwa. Integrated Reservoir Operations using coupled Hydro-Met Multi-Model system for flood forecasting and mitigations for Pune, India, submitted to EGU general Assembly 2023, 23-28 April 2023. https://doi.org/10.5194/egusphere-egu23-15342.
  8. Lead talk: Dr. Sumita Kedia and Dr. Yogesh Kumar Singh on “C-DAC’s Innovative Technological Development for Societal Applications to Adress Weather/Climate Hazards “, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024), S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024.  Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences.
  9. Sahidul Islam, Anandakumar Karipot, Rohini Bhawar, Sumita Kedia, Palash Sinha, Ketaki Belange, T.S. Saikrishna and Manoj Khare, 2024: A high-resolution heat wave forecasting system over urban region in India, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024), S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024.  Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences.
  10. Manoj Khare, Palash Sinha, Manish Kale, Sumita Kedia, 2024: GIS and Remote Sensing for Smart Agriculture, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024), S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024.  Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences
  11. Palash Sinha et al, Assessing WRF model performance in simulating heatwave over India, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024), S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024.  Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences.
  12. Key note lecture by Manoj Khare on Key Note Speakers on Climate change, climate variability and adaptation strategies, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024), S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024.  Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences.
  13. Nagaraju Gaddam, Abhinav Wadhwa, Likhitha P, Pradeep P Mujumdar, “WRF- SWMM Coupled Model Performance Assessment with LCZ Classifications”, AGU Fall Meeting 2022, held in Chicago in 2022.
  14. Likhitha P, Abhinav Wadhwa, Shubha Avinash, Nagaraju Gaddam, “Low Impact Development (LID) as Flood Control Alternatives for Rapidly Changing Urban Landscape”, AGU Fall Meeting 2022, held in Chicago in 2022.
  1. Palash Sinha, Sahidul Islam, Ketaki Belange, Sumita Kedia, T.S. Saikrishna and Manoj Khare: Assessing WRF Model Performance in Simulating Heatwave over India. Submitted (Revised version). https://doi.org/10.1038/s41598-024-52541-2.
  2. Islam, Sahidul, Palash Sinha, Rajiv Kumar Srivastava, and Manoj Khare. “Heat Waves and Heat Stress in the Changing Climate: A Data-Driven Evaluation.” In Mitigation and Adaptation Strategies Against Climate Change in Natural Systems, pp. 267-287. Cham: Springer Nature Switzerland, 2025.
  3. Sinha, Palash, Manish Modani, Sahidul Islam, Manoj Khare, and Rajiv Kumar Srivastava. “Evolution of Weather and Climate Prediction Systems.” In Mitigation and Adaptation Strategies Against Climate Change in Natural Systems, pp. 243-265. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-030-05405-2.
  4. Tiwari, Sarita, Palash Sinha, Manoj Khare, Rajiv Kumar Srivastava, and A. K. Biswal. “Groundwater: A Critical Resource in a Changing Climate.” In Mitigation and Adaptation Strategies Against Climate Change in Natural Systems, pp. 221-239. Cham: Springer Nature Switzerland, 2025.
5

Consortia Partners

Leading Institute: Centre for Development of Advanced Computing (C-DAC), Pune
Indian Institute of Tropical Meteorology (IITM), Pune
Indian Institute of Sciences (IISc), Bengaluru
Indian Institute of Technology Bhubaneshwar (IIT BBS)
5

Associate Partners

  • Automotive Research Association of India (ARAI), Pune
  • National Centre for Medium Range Weather Forecasting (NCMRWF)
  • India Meteorological Department (IMD)
  • Karnataka State Natural Disaster Monitoring Centre (KSNDMC)
  • India Meteorological Department (IMD)
  • Pune Municipal Corporation (PMC), Disaster Management Department
  • Pune Municipal Corporation (PMC) Environment Department
  • Pimpri Chinchwad Municipal Corporation (PCMC)
  • Karnataka State Natural Disaster Monitoring Centre (KSNDMC)
  • Central Pollution Control Board (CPCB)
  • Maharashtra Pollution Control Board (MPCB)
  • Scientists / Researchers
  • Research students at Post Graduate and Ph.D. level

Dr. Manoj Khare (PI), manojk@cdac.in

+91-20-25503233/25503244

Materials and Computational Chemistry (MCC)

Materials and Computational Chemistry (MCC)


Introduction

Scientific research is pursued through the combination of three essential practices: theory, experiment, and computation. Since the emergence of modern computers, computation for modelling and simulation of experiments has led to the emergence of Computational Science. High-performance computing (HPC) has a major role to play to process data and perform complex calculations at high speeds. HPC applications are the drivers of the development of both hardware and software for HPC systems. Computations on HPC for solving many real-life scenarios to solve complex problems in science, business, and engineering have immense potential to influence the economy and the quality of life for human kind. Materials science is a field involving research and discovery of materials. Computational materials science uses modeling, simulation, theory, and informatics to understand materials. The main goals include discovering new materials, determining material behavior and mechanisms, explaining experiments, and exploring materials theories. It is one sub-discipline of both computational science and engineering, containing significant overlap with computational chemistry and computational physics

The outcome of the project “Materials and Computational Chemistry” under National Supercomputing Mission (NSM) is the set of codes (software) developed by the investigators to perform the computations to study properties of atoms, molecules, clusters, alloys, bio-molecules, and composite materials using high-performance computing (HPC).



Project Summary

Development of indigenous scientific codes:(l)Linear Scaling DFT,(2)Multi-Reference Methods with hybrid QM-MM approaches,(3)Excited state dynamics toolkit, (4) Multiscale Microstructure Simulation and Modelling, (5) GUI for home-grown quantum chemistry code



Objective

Development of indigenous scientific codes

  1. AMDKIIT: Linear scaling hybrid-DFT code for ab initio molecular dynamics
  2. ANN-CI: Computational chemistry, code augmented by machine learning for studying complex biological systems
  3. LITESOPH: Layer Integrated Toolkit and Engine for Simulations of Photo-induced phenomena is a toolkit for simulations of photo-induced phenomena
  4. μ2mech: It is a multiscale modeling approach combining atomistic and phase-field simulations for microstructure modeling during solid-state phase transformations.
  5. MTASpec: Ouantum chemistry code based on the fragmentation-based molecular tailoring approach.
  6. Materials and Computational Chemistry (MSCC) application support* activity: Porting and deployment of the five** indigenous software on NSM systems and application support [C-DAC, Pune]

*Since March 2023, Materials and Computational Chemistry application support activity was added  [on the reccomendations of the PMC and TAC] for the proliferation of the five indigenous software developed.



Deliverables

Five indigenously developed software in the domain of Materials and Computational Chemistry, Publications in reputed international journals, One training workshop for all five software.



Partners
  1. C-DAC
  2. IIT Kanpur
  3. IISER Bhopal
  4. S P Pune University


Achievements

Five indigenously developed and open-source software:

  1. AMDKIIT [Linear scaling DFT],
  2. ANN-CI [Multi-reference methods based on MLwith QM/MM methods],
  3. LITESOPH [Excited state dynamics toolkit],
  4. μ2mech [Multiscale Microstructure Simulation and Modelling], and
  5. MTA Spec [GUI for home-grown Quantum Chemistry code].


PhD Thesis(Six):
  1. Ab Initio Molecular Dynamics with Hybrid Density Functionals: Implementation and Application by Sagarmoy Mandal [IIT Kanpur] (July, 2020).
  2. Theoretical investigation of excited state phenomena in photoprotection and self-repair of DNA by  Satyajit Mandal [IISER Bhopal] (November 2021).
  3. Renormalization and machine learning approaches for strongly correlated systems - development and applications, by Madhumita Rano [IACS Kolkata] (2023).
  4. Development of Machine Learning Approaches for Strongly Correlated Systems, by Sumanta K. Ghosh [IACS Kolkata] (2023).
  5. Accelerating Excited State Calculations, by Koushik Seth[IACS Kolkata] (2024).
  6. Speeding-up Hybrid Density Functional based Ab Initio Molecular Dynamics Simulation by Ritama Kar [IIT Kanpur] (Expected submission: April, 2025).


Publications

31 Publications in International Journals from five sub-projects

  1. Achieving an Order of Magnitude Speedup in Hybrid-Functional- and Plane-Wave-Based Ab Initio Molecular Dynamics: Applications to Proton-Transfer Reactions in Enzymes and in Solution, S. Mandal, V. Thakkur, B. Meyer, N. N. Nair, J. Chem. Theory Comput. (2021), 17, 4, 2244.
  2. Improving the scaling and performance of multiple time stepping-based molecular dynamics with hybrid density functionals, S. Mandal, R. Kar, T. Klöffel, B. Meyer, N. N. Nair, J. Comput. Chem. (2022), 43 (9), 588.
  3. Hybrid Functional and Plane Waves based Ab Initio Molecular Dynamics Study of the Aqueous Fe2+/Fe3+ Redox Reaction, S. Mandal, R. Kar, B. Meyer, N. N. Nair, ChemPhysChem (2023), 24, e202200617.
  4. Speeding-up Hybrid Functional-Based Ab Initio Molecular Dynamics Using Multiple Time-stepping and Resonance-Free Thermostat, R. Kar, S. Mandal, V. Thakkur, B. Meyer, and N. N. Nair, J. Chem. Theory Comput. (2023), 19 (22), 8351.
  5. Dynamics of Anthracene Excimer Formation within a Water-soluble Nanocavity at Room Temperature, Aritra Das, Ashwini Danao, Shubhojit Banerjee, A. Mohan Raj, Gaurav Sharma; Rajeev Prabhakar, Varadharajan Srinivasan, Vaidhyanathan Ramamurthy, and Pratik Sen, Am. Chem. Soc. (2021), 143, 2025.
  6. Size and Composition Dependence of Plasmonic Excitations in Transition Metal Dichalcogenide Nanoflakes, Paresh C. Rout, Vignesh K. Balaji, Nesta B. Joseph, Shalini Tomar, and Varadharajan Srinivasan, Phys. Chem. C  (2023), 127, 33, 16464.
  7. Universal Measure for the Impact of Adiabaticity on Quantum Transitions, Ritesh Pant, Pramod K. Verma, Chakradhar Rangi, Elious Mondal, Mansi Bhati, Varadharajan Srinivasan, and Sebastian Wüster, Rev. Lett.  (2024), 132, 126903.
  8. Ultrafast Processes in Upper Excited Singlet States of Free and Caged 7-Diethylaminothiocoumarin, Abhijit Dutta, Sujit Kumar Ghosh, Satyajit Mandal, Varadharajan Srinivasan, Vaidhyanathan Ramamurthy, and Pratik Sen, Phys. Chem. A (2024), 128, 33, 6853.
  9. A supramolecular approach towards the photorelease of encapsulated caged acids in water: 7‑diethylaminothio‑4‑coumarinyl molecules as triggers, Sujit Kumar Ghosh, Shreya Chatterjee, Paras Pratim Boruah, Satyajit Mandal, José P. Da Silva, Varadharajan Srinivasan, and Vaidhyanathan Ramamurthy, Photochem Photobiol Sci (2024), 23, 2057.
  10. Plasmon Induced Charge Transfer Dynamics in Metallic Nanoparticle-MoSe2 Nanoflake Heterostructures, Pramod K. Verma, Vignesh B. Kumar, and Varadharajan Srinivasan, Adv. Optical Mater. (Under Review).
  11. Support Vector Regression-Based Monte Carlo Simultion of Flexible Water Clusters, S. Bose, S. Chakrabarty, D. Ghosh, ACS Omega, (2020), 5, 7065.
  12. Configuration interaction trained by neural networks: Application to model polyaromatic hydrocarbons, S.K. Ghosh, M. Rano, D. Ghosh, J. Chem. Phys., (2021), 154, 094117.
  13. Active learning assisted MCCI to target spin states, K. Seth, D. Ghosh, J. Chem. Theory Comput., (2023), 19, 524.
  14. Machine learning matrix product state ansatz for strongly correlated systems, S.K. Ghosh, D. Ghosh, J. Chem. Phys., (2023), 158,
  15. Efficient machine learning configuration interaction for the bond breaking problem, M. Rano, D. Ghosh, J. Phys. Chem.A, (2023), 127, 3705.
  16. Machine learning the quantum mechanical wavefunction, M. Dey, D. Ghosh, J. Phys. Chem. A, (2023), 127, 9159.
  17. Computational Techniques for Strong Electron Correlation: Matrix Product State Ansatz and its Optimization, Rano, S. K. Ghosh, and D. Ghosh, “Comprehensive computational chemistry,” in Y. Manual and R. J. Boyd, Eds. Elsevier, Inc., 2024, vol. 1, ch. , p. 121.
  18. μ2Mech: A software package combining microstructure modeling and mechanical property prediction, A. Linda, A. S. Negi, V. Panwar, R. Chafle, S. Bhowmick, K. Das, and R. Mukherjee, Physica Scripta (2024) 99 (5), art. no. 055256.
  19. Accelerating microstructure modeling via machine learning: A method combining Autoencoder and ConvLSTM, Ahmad, N. Kumar, R. Mukherjee, and Bhowmick, Phys. Rev. Materials (2023) 7 (8), art. no. 083802, .
  20. Anomalous coarsening behaviour in Ni-Al alloys: Insights from phase-field simulations, R. Chafle, and  Mukherjee, Materials Letters (2020) 279, art. no. 128444.
  21. Constructing Potential Energy Surface with Correlated Theory for Dipeptides Using Molecular Tailoring Approach, S. S. Khire, N. Gattadahalli, N. D. Gurav, A. Kumar, and S. R. Gadre, ChemPhysChem., (2023), 24, e202200784.
  22. Enabling Rapid and Accurate Construction of CCSD(T)-Level Potential Energy Surface of Large Molecules Using Molecular Tailoring Approach, S. S. Khire, N. D. Gurav, A. Nandi, and S. R. Gadre, J. Phys. Chem. A  (2022), 126, 1458.
  23. Ring-Polymer Instanton Tunneling Splittings of Tropolone and Isotopomers using a Δ-Machine Learned CCSD(T) Potential: Theory and Experiment Shake Hands, A. Nandi, G. Laude, S. S. Khire, N. D. Gurav, C. Qu, R. Conte, Q. Yu, S. Li, P. L. Houston, S. R. Gadre, J. O. Richardson, F. Evangelista, and J. M. Bowman, J. Am. Chem. Soc. (2023), 145 , 9655.
  24. Theoretical and experimental study of IR spectra of large phenol-acetylene clusters, Ph(Ac)n for 8 ≤ n ≤ 12E. M. Kabadi, S.S.Khire, S. S. Pingale, S. R. Gadre, T. Chiba, and A.Fujji, J. of the Indian Chem. Society, (2021), 98, 100100.
  25. MTASpec software for calculating the vibrational IR and Raman spectra of large molecules at ab initio level, (2022), S. S. Khire, N. Sahu, and S. R. Gadre, Phys.  Comm., (2022), 270, 108175.
  26. Development and testing of an algorithm for efficient MP2/CCSD(T) energy estimation of molecular clusters with the 2–body approach, S. S. Khire, and S. R. Gadre, J. Comput. Chem. , (2023), 44, 261.
  27. Direct and Reliable Method for Estimating the Hydrogen Bond Energies and Cooperativity in Water Clusters, Wn, n = 3 to 8, B.  Ahirwar, S. R. Gadre, and M. M. Deshmukh, J. Phys. Chem. A (2020) , 124, 6699.
  28. Molecular Tailoring Approach for Estimating Individual Intermolecular Interaction Energies in Benzene Clusters, B. Ahirwar, N. D. Gurav, S. R. Gadre, and M. M. Deshmukh, J. Phys. Chem. A (2021), 125, 6131.
  29. Hydration shell model for expeditious and reliable individual hydrogen bond energies in large water clusters, B. Ahirwar, N. D. Gurav, S. R. Gadre, and M. M. Deshmukh, Phys. Chem. Chem. Phys., (2022), 24, 15462.
  30. On the Short-Range Nature of Cooperativity in Hydrogen-Bonded Large Molecular Clusters, B. Ahirwar, S. R. Gadre, and M. M. Deshmukh, J. Phys. Chem. A (2023), 127, 4394.
  31. Combining fragmentation method and high-performance computing: Geometry optimization and vibrational spectra of proteins [submitted to J. Chem. Phys. Special Issue on HPC].


Training and Workshops

Efforts for the proliferation of the software among the user community

  1. Three-day user workshop conducted on 9-11 October 2023 at C-DAC Pune [25 participants (C-DAC, Pune + 30 (online)]
  2. Conducted Online workshop for handholding users of the software,
    • AMDKIIT (25 April 2024) [32 participants],
    • LITESOPH (22 May 2024) [42 participants ],
    • MTASpec (25 July  2024) [45 participants],
    • ANN-CI (13 Sept. 2024) [60 participants ], and 
    • μ2mech (24 Jan. 2025) [50 participants]
  4. Deployment of these software on NSM systems and facilitating user manuals
  5. Engagement with the development teams for scaling and performance tuning exercises, identifying scope for further parallelism and code optimization


Workshop Photographs

Figure: Three-day user workshop conducted on 9-11 October 2023 at C-DAC Pune


A HPC software suite for seismic imaging to aid oil and gas exploration-sample

About Project

Seismic Data is acquired on land and in marine environment to find out the location of oil & gas reservoir in the subsurface. The processing of seismic data involves several steps before it gets converted into a meaningful and interpretable image of earth volume. Seismic Imaging is an advance processing step which converts seismic data to an earth subsurface image. Seismic imaging aims to create high resolution 2D & 3D structural images of subsurface geology. Reverse Time Migration (RTM) is one of the most reliable and preferred solution for seismic imaging of geological subsurface with complex structures. It can handle large velocity variation without any dip limitations for producing the earth subsurface structure with high resolution. It can deliver subsurface images with high accuracy in different mediums. RTM is highly computation, I/O and storage intensive, which requires High Performance Computing (HPC) ecosystem for execution.

 

Under the National Supercomputing Mission (NSM), “A HPC software suite for seismic imaging to aid oil and gas exploration” is a “Make in India” initiative to develop a customizable and efficient RTM software “SeisRTM”. It can provide high-resolution 2D & 3D seismic images of complex geological subsurface using acquired large seismic data. This software provides 2D modelling and RTM capabilities for both isotropic and anisotropic (VTI and TTI) media, as well as 3D isotropic modelling and RTM. SeisRTM is equipped with a suite of data preparation and post-processing tools, optimized to handle high-frequency migration and large datasets efficiently. It is designed for parallel computing environments, making it well-suited for deployment on CPU clusters without core limitations. SeisRTM offers both a Command Line Interface (CLI) and a Graphical User Interface (GUI) for user flexibility and includes an in-house developed data visualization tool to streamline data analysis and visualization. The indigenously developed “SeisRTM,” built on NSM infrastructure, will serve as a seismic imaging facility, delivering 3D RTM capabilities for upstream oil and gas exploration companies in India.

 

  • CDAC DG Award 2024 (Core Research)
  • National Workshop on HPC in Seismic Imaging “Seeing Below the Earth Surface”, SeisRTM Workshop was held at Pune held in April 2023)
A Workshop on HPC in Seismic Imaging “Seeing below the Earth Surface” was organized on 28th April 2023 at Pune. The workshop was inaugurated by Shri E. Magesh, Director General, C-DAC. 120+ Domain and computer science experts attended the workshop. Prominent institutes/organizations such as GEOPIC, ONGC; Directorate General of Hydrocarbon, Delhi; Indian Institute of Technology, Roorkee; CSIR-National Institute of Oceanography, Goa; Oil India Limited (OIL), Dibrugarh, Assam; Reliance Industries Limited etc. participated in the event.
 
  • Workshop on Seismic modeling and migration using SeisRTM was held at IIT Roorkee in December 2024
One day workshop on “Seismic Modeling and Migration using SeisRTM” was conducted at IIT Roorkee on December 6th 2024. 15+ students participated in the workshop. Participants were engaged in hands-on training and gained theoretical and practical insights into seismic imaging techniques. The event included talks by Prof. Anand Joshi, Head of Earth Sciences Dept., IIT Roorkee, and Ms. Richa Rastogi, Scientist F, C-DAC Pune. The workshop aimed to broaden the software’s reach, fostering its development while simultaneously advancing research and development in seismic imaging.
 
  • Workshop on Seismic modeling and migration using SeisRTM was held at IIT(ISM) Dhanbad held in February 2025
A three-day workshop on “Seismic Modeling and Migration using SeisRTM” was conducted at IIT (ISM), Dhanbad during 8th to 10th February, 2025. 140+ students participated in the workshop. Over the three days, participants were engaged in hands-on training and gained theoretical and practical insights into seismic imaging techniques. The sessions covered fundamental and advanced topics equipping attendees with experience in using SeisRTM for seismic data processing. The event included talks by Prof. Anand Joshi, Head of Earth Sciences Dept., IIT Roorkee, and Ms. Richa Rastogi, Scientist F, C-DAC Pune. Further the inaugural and valedictory events were graced by Prof. Sanjit Kumar Pal, Head of Applied Geophysics Dept., IIT (ISM) Dhanbad; Prof. Dheeraj Kumar, Deputy Director, IIT (ISM) Dhanbad and Prof. Mritunjay Kumar Singh, Dean of Academics, IIT (ISM) Dhanbad.
 
    • Workshop on Seismic modeling and migration using SeisRTM was held at BHU, Varanasi in March 2025
 
A three-day workshop on “Seismic Modeling and Migration using SeisRTM” was successfully conducted at BHU, Varanasi, from 26th to 28th March, 2025. More than 100 students enthusiastically participated in the workshop held at the Department of Geophysics, BHU Varanasi. The primary objective of the workshop was to expand the outreach of SeisRTM, encouraging its adoption and further development, while also advancing research and innovation in seismic imaging. The workshop’s valedictory session was graced by Prof. S. K. Upadhyay, Dean, Faculty of Science, BHU Varanasi.
 
    • Workshop on Seismic modeling and migration using SeisRTM was held at IIT Bombay from 29th April to 1st May 2025
A three-day workshop on “Seismic Modeling and Migration using SeisRTM” was successfully conducted at IIT Bombay, from April 29th to May 1st, 2025. Throughout the three-day event, participants were engaged in hands-on training, gaining both theoretical knowledge and practical experience in seismic imaging techniques.
 
    • MoUs
      • MoU signed on 04th February 2025 with Reliance Industries Limited
      • NDA signed on 07th December 2024 with Oil India
      • NDA signed on 10th September 2020 with GEOPIC ONGC
    • Publications
      • Richa Rastogi, Abhishek Srivastava and Laxmaiah Bathula, 2025, SeisRTM: 2D/3D Reverse Time Migration (RTM) tool for Seismic Imaging, Beneath the Surface: Innovations in Geoscience SEG Symposium 2025
      • Laxmaiah Bathula, Richa Rastogi, Abhishek Srivastava and Monika Pokharkar, 2025, RTM imaging of reciprocity 2D walkaway VSP data, Beneath the Surface: Innovations in Geoscience SEG Symposium 2025
      • Richa Rastogi, Abhishek Srivastava, Monika Gawade, Bhushan Mahajan, Laxmaiah Bathula and Saheb Ghosh, 2024, Optimal Imaging Aperture for computational efficiency in 2D and 3D Reverse Time Migration using SeisRTM, First Break,2024, https://doi.org/10.3997/1365-2397.fb2024104
      • R. Rastogi, A. Srivastava, N. Mangalath, B. Mahajan, S. Ghosh and S. Phadke, 2024, Fast Reverse Time Migration with Enhanced Efficiency and Reduced Computational Load Using Partial Snapshot Storage, 85th EAGE Annual Conference & Exhibition, Jun 2024, Volume 2024, p.1 – 5. https://doi.org/10.3997/2214-4609.2024101153
      • Richa Rastogi, Abhishek Srivastava, Monika Pokharkar, Nithu Mangalath, & Saheb Ghosh. (2024). Efficient imaging aperture criterion for reduction of computational cost of TTI RTM. Australian Society of Exploration Geophysicists Extended Abstracts, Volume 2024, 1st ASEG DISCOVER Symposium, Hobart, https://doi.org/10.5281/zenodo.13918172
      • Joshi, A., Pandey, M., Singh, J., Richa, R., Srivastava, A., Mangalath, N., 2023,” Effect of topography and shallow velocity model on amplification of P wave: A case study of the Tohoku earthquake of 11 March, 2011 (Under Review), Journal of Soil Dynamics and Earthquake Engineering 
      • Londhe, A., Rastogi, R.,Srivastava, A.,Khonde, K.,Srisarala, K.,Kharche, K., 2021, Adaptively accelerating FWM2DA seismic modelling program on multicore CPU and GPU architectures. Computers & Geosciences. 146,104637 https://doi.org/10.1016/j.cageo.2020.104637
      • Richa Rastogi, Mr Abhishek Srivastava, Nithu Mangalath Bhushan Mahajan, Mr. Saheb Ghosh and Mr. Suhas Phadke, Fast Reverse Time Migration with enhanced efficiency and reduced computational load using partial snapshot storage. European Association of Geoscientists & Engineers,2024, https://doi.org/10.3997/2214-4609.2024101153
      • Rastogi, R., Srivastava, A., Phadke, S., Mahajan, B., Bathula, L., Ghosh, S. (2023), Improved RTM imaging of marine streamer data using principle of reciprocity, European Association of Geoscientists & Engineers, Jun 2023, Volume 2023, p.1 – 5, https://doi.org/10.3997/2214-4609.202310353
      • Kumar, A., Rastogi, R., Srivastava, A., Mahajan, B. (2023), RTM image conditioning using deep learning, European Association of Geoscientists & Engineers, Jun 2023, Volume 2023, p.1 – 5, https://doi.org/10.3997/2214-4609.202310451
      • Rastogi, R.,Srivastava, A.,Gawade, M.,Manglath, N., Bathula, L, Mahajan ,B., Phadke, S., 2022, 2D isotropic and vertical transversely isotropic RTM using SEG Hess VTI Model, SEG IMAGE 22-the International Meeting for Applied Geoscience & Energy in Houston, USA. https://doi.org/10.1190/image2022-3745595.1
      • Saurabh Sharma, A. Joshi, Richa Rastogi, Abhishek Srivastava, Bhushan Mahajan, Nithu Mangalath, Reverse Time Migration of 2D isotropic Basin model using staggered-grid finite difference scheme, Earth Sciences in India: Challenges and Emerging Trends (ESICET) – 2023  
      • Richa Rastogi, Abhishek Srivastava, Saheb Ghosh, Anand Joshi, Suhas Phadke, Nithu Mangalath, Bhushan Mahajan, Monika Gawade, Laxmaiah Bathula, Hrishikesh Kumbhar, and Saurabh Sharma, SeisRTM: A make in India Initiative for Software Development for Reverse Time Migration (RTM) to aid Oil and Gas Data Processing for Seismic Imaging, Earth Sciences in India: Challenges and Emerging Trends (ESICET) – 2023  
      • Richa Rastogi, Abhishek Srivastava and Laxmaiah Bathula, Reverse Time Migration: A tool for complex seismic Imaging, Conference on Integrated Earth (CITE) – 2024  
5

Consortia Partners

Centre for Development of Advanced Computing (C-DAC), Pune

Geodata Processing and Interpretation Centre (GEOPIC), ONGC

Indian Institute of Technology Roorkee (IITR)

5

Collaborators

  • Centre for Development of Advanced Computing (C-DAC), Pune
  • Geodata Processing and Interpretation Centre (GEOPIC), ONGC
  • Indian Institute of Technology Roorkee (IITR)
5

End Users

  • Agencies involved in oil and gas exploration
  • Research organization for deep crustal studies
  • Academia for teaching advance seismic processing

Urban Modelling: Development of multi-sectorial simulation lab and science-based decision support framework to address urban environment issues-sample

Urban Modelling: Development of multi-sectorial simulation lab and science-based decision support framework to address urban environment issues

About Project

India reported to have more urban population in the coming years and it is projected to double its size by 2050. Due to this rapid urban expansion in Indian cities is giving rise to environmental issues such as extreme rainfall, heat waves, pollution, and urban floods. In recent years Indian cities are experiencing more frequent occurrences of extreme events of floods, heat/cold waves, and severe pollution events. Due to these events, the health and socio-economic issues of the urban population are growing concerns to policymakers and citizens at national, state and local level. Thus, it is imperative to understand, simulate and timely predict urban extreme episodes to take more informative operational and policy decision to overcome the urban problems. It is worthy to note that all these events consist of cross-sectoral physical system which requires an integrated modeling system to predict these issues. To develop the integrated platform, the modeling system should include high-performance computing (HPC) resources, input data, observations, satellite data, validation and verification mechanisms, multi-model interoperability, multi-scale ensemble modeling, and 2D/3D visualization. Implementing this system will require high-resolution models with robust data handling and computational capabilities. The comprehensive modeling ecosystem will encompass ensemble modeling, urban parameterization, urban canopy, urban heat island, boundary layer, atmospheric, chemical, and morphological data assimilation, and a query framework utilizing high-performance computing (HPC) and big data analytic technology. Against this backdrop, the NSM Urban Modelling consortia project (funded by MeitY) is formulated for timely prediction of weather, air quality, and hydrological systems.

Under NSM Urban Modelling project, an integrated urban modelling system and service cyberinfrastructure Urban Environment Science to Society (UES2S) (Figure 1) is developed. This is an online fully coupled urban ‘meteorology and hydrology, and air quality’ modeling system (Figure 2) which captures the urban representation of micro scale city environmental conditions.

Figure 1: Homepage of Urban Environment Science to Society (UES2S)
Figure 1: Homepage of Urban Environment Science to Society (UES2S)
Figure 2: HPC Based Integrated Urban Modelling System
Figure 2: HPC Based Integrated Urban Modelling System

The objective of this consortia project is to develop an online fully coupled urban ‘meteorology, hydrology, and air quality’ modeling system to capture the urban representation of micro-scale city environmental conditions. The aim is to improve the skill of urban weather forecasting, atmospheric dispersion and air quality forecasting, and hydrology forecasting useful for exposure assessment, disaster management, daily operations, and policy decisions and create a science-based, HPC-enabled urban data and decision framework with optimized performance and 3D visualization techniques, thereby fulfilling India’s sustainable smart city goals.

UES2S is an online fully coupled urban ‘meteorology, hydrology, and air quality’ modeling system developed under the NSM Urban Modelling Project. This system captures the urban representation of micro-scale city environmental conditions. UES2S has three major components: Data as a service (DataHub), modeling platform as a service (Science Gateway), and Decision Support System (DSS) for cross-sector end-user decisions. Through DataHub, we intend to provide cross-sector data access and a data-sharing facility. The Science Gateway (Figures 3 & 4) has automatic end-end modeling workflows enabling ready-to-use weather, hydrology, and air quality models on NSM clusters. The DSS component (Figures 5 & 6) facilitates the translation of scientific data into multi-stakeholder interactive actions. The DSS provides high-resolution weather, air quality, and hydrology forecasts along with the forecast of reservoir inflows, water levels, and discharge for flood management and mitigation. Thus, the DSS is integral to disaster management activities, daily operations, and science-based policy decisions.

This multi-sectorial simulation lab and science-based decision framework is developed to address urban environment issues. This HPC-based automated model execution workflows with an interdisciplinary urban testbed has been developed to execute weather, air quality, and hydrology models for the prediction of extreme events. The system is designed to be exceptionally user-friendly, enabling researchers and students to execute the models easily. This would facilitate the seamless transition of research into operational practices. The framework offers an urban modeling system, operational processes, a data hub, and a DSS, enabling meteorology, air quality, and hydrology services for diversified user categories.

Science Gateway (Figure 3) is a digital platform customized for meteorologists, hydrologists, and air quality modelers, offering convenient access to data from specialized tools and collaboration features to enhance research and forecasting in these areas. Workflow of the Weather Research and Forecasting (WRF) (Figure 4) is developed in Science Gateway, a state-of-the-art mesoscale numerical weather prediction system designed for atmospheric research and operational forecasting applications.

A Decision Support System (DSS) (Figure 5) helps in decision-making during extreme events like heavy rainfall, floods, and heatwaves. It facilitates analyses of meteorological patterns like short-duration high-intensity rainfall, heat and cold waves, hydrological parameters such as reservoir levels and river flows, and air quality parameters like PM 2.5. For instance, during an extreme event, the DSS provided accurate forecasts and risk assessments through charts, shaded and non-shaded plots, and vector plots, assisting users in rainfall information, flood control, air quality monitoring, and climate resilient planning.

The reservoir operations module, which is a key component of the DSS, displays a time series forecast plots as shown in Figure 5. This plot includes various parameters such as upstream/downstream catchment rainfall, reservoir water level, dam discharge, and reservoir inflow for the user-selected reservoir. The user, typically a scientists or operational forecasters in weather, environmental science, or disaster management, can use this information to make informed decisions and plan accordingly.

In one of the DSS module (Figure 6), users can select flood hotspots in the alerts section and then click on a hotspot pin for a particular location to visualize water depth relative to human height, making the representation more intuitive and engaging.

Figure 3: Components of Science Gateway
Figure 3: Components of Science Gateway
Figure 4: WRF Workflow
Figure 4: WRF Workflow
Figure 5: Decision Support System
Figure 5: Decision Support System
Figure 6: DSS for Flood – Water depth: 0.52 meter (pictorial view) at Pune catchment
Figure 6: DSS for Flood – Water depth: 0.52 meter (pictorial view) at Pune catchment
  • Calibrated and customized model for Indian cities
  • Prepared high resolution LULC map for pilot cities
  • Integrated Met-Hydro-AQ user friendly web-based Model Execution framework (WRF, WRF-Chem, AERMOD, HEC-RAS, HEC-HMS, SWMM), Data hub and Decision Support System
  • End-to-End automated model forecast validation tool
  • Indigenously developed visualization platform
  • Provided access of developed system to IMD
  • Shared ward level Rainfall, Reservoir Water and urban flood, heatwave, air pollution forecast information with IMD, PMC, PCMC and WRD (Figure 3 & 4)
  • Demonstration of UES2S to Dr. M. Ravichandran, Secretary, MoES, Chairman, PMC and domain experts (Figure 5)
  • 36 Publications in peer-reviewed journals & 13 Conference papers
  • MoU signed on 30th October 2024 with Pimpri-Chinchwad Municipal Corporations to share urban Decision Support System weather, flood information, and air quality (jointly with IITM Pune) at ward level
  • Data sharing: Providing weather and flood forecast to IMD, Pune Municipal Corporation, Pimpri Chinchwad Municipal Corporation (PCMC) and water resources departments, govt of Maharashtra
Figure 7: Typical Daily Rainfall info upto Ward level
Figure 7: Typical Daily Rainfall info upto Ward level
Figure 8: Air quality forecast information
Figure 8: Air quality forecast information
Figure 9: Project review by Dr. M. Ravichandran, Secretary, MoES, Chairman, PMC and domain experts
Figure 9: Project review by Dr. M. Ravichandran, Secretary, MoES, Chairman, PMC and domain experts
MoUs:
  • MoU signed with Pimpri-Chinchwad Municipal Corporation (PCMC) on 30th October 2024 to share the access and use of Urban Decision Support System
(R to L) Dr Sanjay Wandhekar Centre Head, C-DAC Pune, Mr Shekhar Singh (IAS) Commissioner, PCMC, PCMC officials
Publications
Peer reviewed journal papers:
  1. Kaginalkar A. et al., Integrated urban environmental system of systems for weather ready cities in India, Bulletin of the American Meteorological Society, (2021),https://doi.org/10.1175/BAMS-D-20-0279.1
  2. Islam, S., Karipot, A., Bhawar, R., Sinha, P., Kedia, S. and Khare, M., 2024. Urban heat island effect in India: a review of current status, impact and mitigation strategies. Discover Cities, 1(1), pp.1-28.
  3. Kulkarni Santosh H., S. D. Ghude, C. Jena, R. K. Karumuri, B. Sinha, V. Sinha, R. Kumar, V. K. Soni, and M. Khare: How Much Does Large-Scale Crop Residue Burning Affect the Air Quality in Delhi?, Environmental Science & Technology, 54 (8), 4790-4799 (2020)
  4. Sumita Kedia, Sudheer Bhakare, Arun Dwivedi, Sahidul Islam, Akshara Kaginalkar: Estimates of change in surface meteorology and urban heat island over northwest India: Impact of urbanization, Urban Climate, Volume 36, (2021)
  5. Gaikwad S., et al 2024: Harnessing deep learning for forecasting fire-burning locations and unveiling PM2.5 emissions, Modeling Earth Systems and Environment, 10, February 2024, https://doi.org/10.1007/s40808-023-01831-1, 927-941
  6. Govardhan G., et al (2024), Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India, Geoscientific Model Development, 17, April 2024,https://doi.org/10.5194/gmd-17-2617-2024, 2617–2640
  7. Karrevula, N.R., Nadimpalli, R., Sinha, P., Mohanty, S., Boyaj, A., Swain, M. and Mohanty, U.C., 2024. Performance Evaluation of WRF Model in Simulating Extreme Rainfall Events Over Bhubaneswar Urban Region of East Coast of India. Pure and Applied Geophysics, pp.1-27.
  8. Karrevula, N.R., Boyaj, A., Sinha, P., Nadimpalli, R., Mohanty, U.C., Islam, S., Kaginalkar, A. and Vinoj, V., 2024. Role of planetary boundary layer physics in urban-scale WRF model for predicting the heat waves over tropical city Bhubaneswar. Journal of Earth System Science, 133(3), pp.1-26.
  9. Boyaj, A., Karrevula, N.R., Sinha, P., Patel, P., Mohanty, U.C. and Niyogi, D., 2024. Impact of increasing urbanization on heatwaves in Indian cities. International Journal of Climatology, 44(11), pp.4089-4114.
  10. Boyaj, A., Sinha, P., Mohanty, U.C., Vinoj, V., Ashok, K., Islam, S., Kaginalkar, A. and Khare, M., 2024. Projected frequency of low to high-intensity rainfall events over India using bias-corrected CORDEX models. Atmospheric Research, p.107760.
  11. Boyaj, A., Nadimpalli, R., Reddy, D., Sinha, P., Karrevula, N.R., Osuri, K.K., Srivastava, A., Swain, M., Mohanty, U.C., Islam, S. and Kaginalkar, A., 2023. Role of radiation and canopy model in predicting heat waves using WRF over the city of Bhubaneswar, Odisha. Meteorology and Atmospheric Physics, 135(6), p.60.
  12. Mohanty, S., Swain, M., Nadimpalli, R., Osuri, K.K., Mohanty, U.C., Patel, P. and Niyogi, D., 2023. Meteorological conditions of extreme heavy rains over coastal city Mumbai. Journal of Applied Meteorology and Climatology, 62(2), pp.191-208.
  13. Swain, M., Nadimpalli, R.R., Mohanty, U.C., Guhathakurta, P., Gupta, A., Kaginalkar, A., Chen, F. and Niyogi, D., 2023. Delay in timing and spatial reorganization of rainfall due to urbanization-analysis over India’s smart city Bhubaneswar. Computational Urban Science, 3(1), p.8.
  14. Gunwani P., et. al.: “Sensitivity of WRF/Chem to different Meteorological Initial Conditions and PBL parameterization schemes”, Atmospheric Environment (2023).
  15. Madhusmita Swain, et al., 2023: Delay in timing and spatial reorganization of rainfall due to urbanization- analysis over India’s smart city Bhubaneswar. Comput. Urban Sci. 3, 8.
  16. Shyama Mohanty, Madhusmita Swain, Raghu Nadimpalli, K. K. Osuri, U. C. Mohanty, Pratiman Patel, and Dev Niyogi, 2023: Meteorological Conditions of Extreme Heavy Rains over Coastal City Mumbai. Journal of Applied Meteorology and Climatology, 2023,Vol.62-2, 191–208
  17. V. K. Valappil, Sumita Kedia, A. K Dwivedi, S. S Pokale, Sahidul Islam, Manoj K Khare, Assessing the performance of WRF ARW model in simulating heavy rainfall events over the Pune region: in support of operational applications, Meteorology and Atmospheric Physics, 2023.
  18. Madhusmita Swain, R. Nadimpalli, U C Mohanty, P Guhathakurta, A Gupta, A Kaginalkar, F Chen, and D Niyogi. Delay in timing and spatial reorganization of rainfall due to urbanization- Analysis for pre-monsoon conditions in Bhubaneswar, India. Computational Urban Science vol 3, Article number: 8 (2023)
  19. Gayatry Kalita, et. al.: “ Forecasting of an unusual dust event over Western India by the Air Quality Early Warning System”, Atmospheric Environment (2023)
  20. Madhusmita Swain, R. Nadimpalli, U C Mohanty, and D Niyogi. Urban modification of heavy rainfall: a model case study for Bhubaneswar urban region. Computational Urban Science volume 3, Article number: 2 (2023)
  21. Swain, M., Nadimpalli, R., Das, A.K., Mohanty, U.C. and Niyogi, D., 2023. Urban modification of heavy rainfall: a model case study for Bhubaneswar urban region. Computational Urban Science, 3(1), p.2.
  22. Chinmay Jena , et. al.: “ Evaluating the sensitivity of fine particulate matter (PM2.5 ) simulations to chemical mechanism in WRF-Chem over Delhi”., Science of the Total Environment, (2023).
  23. Risma Joseph, P. P. Mujumdar, Rajarshi Das Bhowmik, (2022). Reconstruction of Urban Rainfall Measurements to Estimate the Spatiotemporal Variability of Extreme Rainfall. Water, 14(23), 3900. Doi: https://doi.org/10.3390/w14233900 (2022)
  24. Gaurav Govardhan, et. al.: “Satellite retrieved stubble-burning activities in north-western India in 2021: Contribution to air pollution in Delhi“, Heliyon (2022).
  25. Sreyashi Debnath, et. al.: “Implications of implementing promulgated and prospective emission regulations on air quality and health in India during 2030” AAQR (2022).
  26. Davis S, Pentakota L, Saptarishy N and Mujumdar PP : A Flood Forecasting Framework Coupling a High-Resolution WRF Ensemble With an Urban Hydrologic Model. Front. Earth Sci. 10:883842. doi: 10.3389/feart.2022.883842 (2022)
  27. Sengupta A., G. Govardhan, S. Debnath, C. Jena, A.N. Parde, P. Lonkar, P. Gunwani, Santosh H Kulkarni, S. Nivdange, R Kumar, and S.D. Ghude, “Probing into the wintertime meteorology and particulate matter (PM2.5 and PM10) forecast over Delhi”, Atmospheric Pollution Research, (2022).
  28. S. Nivdange, C. Jena, P. Pawar-Jadhav, G. Govardhan, Santosh H. Kulkarni, P. Lonkar, A. Vispute, N. Dhangar, A. Parde, P. Acharja, V. Kumar, P. Yadav and N. R Karmalkar: Nationwide CoViD-19 lockdown impact on air quality in India, Mausam, 73, 1, 115-128, (2022)
  29. Nadimpalli, Raghu, Shyama Mohanty, Nishant Pathak, Krishna K. Osuri, U. C. Mohanty, and Somoshree Chatterjee. “Understanding the characteristics of rapid intensity changes of Tropical Cyclones over North Indian Ocean.” SN Applied Sciences 3, no. 1 (2021): 1-12.
  30. Mohanty, Shyama, Raghu Nadimpalli, U. C. Mohanty, M. Mohapatra, A. Sharma, Ananda K. Das, and S. Sil. “Quasi-operational forecast guidance of extremely severe cyclonic storm Fani over the Bay of Bengal using high-resolution mesoscale models.” Meteorology and Atmospheric Physics 133, no. 2 (2021): 331-348.
  31. Pawar, P. V., S. D. Ghude, C. Jena, Móring, A., Sutton, M. A., Kulkarni Santosh H., Lal, D. M., Surendran, D., Van Damme, M., Clarisse, L., Coheur, P.-F., Liu, X., Xu, W., Jiang, J., and Adhya, T. K.: Analysis of atmospheric ammonia over South and East Asia based on the MOZART-4 model and its comparison with satellite and surface observations, Atmos. Chem. Phys,. https://doi.org/10.5194/acp-2020-63, (2021)
  32. C. Jena, S. D. Ghude, R. Kumar, S. Debnath, G. Govardhan, V. K. Soni, Santosh H. Kulkarni, G. Beig, R. S. Nanjundiah and M. Rajeevan: Performance of high resolution (400 m) PM2.5 forecast over Delhi. Nature Sci Rep, 11, 4104, (2021)
  33. S. D. Ghude, R. K. Karumuri, C. Jena, R. Kulkarni, G.G. Pfister, V. S. Sajjan, P. Pithani, S. Debnath, R. Kumar, B. Upendra, Santosh H. Kulkarni, D.M. Lal, R.J. Vander A, A. S. Mahajan: What is driving the diurnal variation in tropospheric NO2 columns over a cluster of high emission thermal power plants in India?, Atmospheric Environment: X 5, 100058, (2020)
  34. S. D. Ghude, R. Kumar, C. Jena, S. Debnath, R. G. Kulkarni, S. Alessandrini, M. Biswas, Santosh H. Kulkrani, P. Pithani, S. Kelkar, V. Sajjan, D.M. Chate, V.K. Soni, S. Singh, R. S. Nanjundiah and M. Rajeevan: Evaluation of PM2.5 forecast using chemical data assimilation in the WRF-chem model: a new initiative under the Ministry of Earth Sciences (MoES) air quality early warning system (AQEWS) for Delhi, Current Science (2020)
  35. Kumar R., Ghude, S. D, M. Biswas, C. Jena, S. Alessandrini, S. Debnath, Santosh Kulkarni, Simone Sperati, Vijay K. Soni, R. S. Nanjundiah, and M. Rajeevan: Enhancing accuracy of air quality and temperature forecasts during paddy crop-residue burning season in Delhi via chemical data assimilation, JGR (Atmosphere), (2020)
  36. Jena, C., Ghude, S. D., Kulkarni, R., Debnath, S., Kumar, R., Soni, V. K., Acharja, P., Kulkarni Santosh H., Khare, M., Kaginalkar, A. J., Chate, D. M., Ali, K., Nanjundiah, R. S., and Rajeevan, M. N.: Evaluating the sensitivity of fine particulate matter (PM2.5) simulations to chemical mechanism in Delhi, Atmos. Chem. Phys. Discuss., (2020)
Conference Publications:
  1. Arun K. Dwivedi, Sumita Kedia, Sagar Pokale, Palash Sinha, Akshara Kaginalkar, Manoj K. Khare, U.C. Mohanty, Sahidul Islam, Assessment of WRF Model in Predicting Heavy Rainfall Events over Complex Topographical Urban City Pune, submitted to International Conference on Urban Climate (ICUC-11), during 28 Aug-1 Sept 2023.
  2. Sumita Kedia, A. K. Dwivedi, S. Pokale, S. Islam, A. Kaginalkar, P. Sinha, S. Ghvhale, R. Nadimpalli, U. C. Mohanty, D. Niyogi, M. Khare, Impact of land use information on heavy rainfall event forecast using an urban scale model, accepted and presented during AMS annual meeting 2023.
  3. Dev Niyogi, Pallavi Gavali, Mohamed Niyaz J, Srujan Gavhale, Arun Dwivedi, Sumita K, Sagar Pokale, Gouri Kadam, Sahidul Islam, Akshara Kaginalkar, Praddep Mumdar. Abinav Wadhawa, Likhitha P.: Coupled Meteorology and Hydrology Modelling to Forecast Flood Extreme Events: Case Study of Pune, India. AGU Fall meeting 2022 meet, at Chicago 12 -16 Dec 2022, Advances in modeling hydrological extremes and engineering practices.
  4. Gouri Kadam, M. Niyaz, P. G. Gavali, S. Gavhale, L. Pentakota, S. Kedia, S. Islam, A. K. Dwivedi, S. Pokale, A. Kaginalkar, P. Mujumdar, M. Khare, and D. Niyogi: Multi-Model Hydrology for Urban Flood Early Warning for Pune, India . 103rd American Meteorological Society Annual Meeting, Denver, USA. (37th Conference on Hydrology).
  5. Pallavi Gavali, Srujan Gavhale, Mohamed Niyaz, Sahidul Islam, Sumita kedia, Sagar Pokale, Arun Dwivedi, Gouri Kadam, Akshara Kaginalkar, Manoj Khare, and Abhinav WadhwaIntegrated Reservoir Operations using coupled Hydro-Met Multi-Model system for flood forecasting and mitigations for Pune, India, submitted to EGU general Assembly 2023, 23-28 April 2023
  6. Lead talk by Dr. Sumita Kedia and Dr. Yogesh Kumar Singh on “C-DAC’s Innovative Technological Development for Societal Applications to Adress Weather/Climate Hazards “.
  7. International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024) , S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024. Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences
  8. Sahidul Islam et al., A high-resolution heat wave forecasting system over urban region in India, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024) , S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024. Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences
  9. Manoj Khare et al, GIS and Remote Sensing for Smart Agriculture, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024) , S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024. Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences
  10. Palash Sinha et al, Assessing WRF model performance in simulating heatwave over India, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024) , S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024. Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences
  11. Key note lecture by Manoj Khare on Key Note Speakers on Climate change, climate variability and adaptation strategies, International Conference on “Sustainable Agricultural Development with Climate Smart Systems” (SADCSS-2024) , S’O’A (Deemed to be University) Bhubaneswar, India during July 18-20, 2024. Organized by Centre for Climate Smart Agriculture and Faculty of Agricultural Sciences
  12. Nagaraju Gaddam, Abhinav Wadhwa, Likhitha P, Pradeep P Mujumdar, “WRF- SWMM Coupled Model Performance Assessment with LCZ Classifications”, AGU Fall Meeting 2022, held in Chicago in 2022.
  13. Likhitha P, Abhinav Wadhwa, Shubha Avinash, Nagaraju Gaddam, “Low Impact Development (LID) as Flood Control Alternatives for Rapidly Changing Urban Landscape”, AGU Fall Meeting 2022, held in Chicago in 2022.
5

Consortia Partners

Centre for Development of Advanced Computing (C-DAC), Pune
Indian Institute of Tropical Meteorology (IITM), Pune
Indian Institute of Sciences (IISc), Bengaluru
Indian Institute of Technology Bhubaneshwar (IIT BBS)
5

Collaborators

  • Automotive Research Association of India (ARAI), Pune
  • National Centre for Medium Range Weather Forecasting (NCMRWF)
  • India Meteorological Department (IMD)
  • Karnataka State Natural Disaster Monitoring Centre (KSNDMC)
5

End Users

  • India Meteorological Department (IMD)
  • Pune Municipal Corporation (PMC), Disaster Management Department
  • Pune Municipal Corporation (PMC) Environment Department
  • Pimpri Chinchwad Municipal Corporation (PCMC)
  • Karnataka State Natural Disaster Monitoring Centre (KSNDMC)
  • Central Pollution Control Board (CPCB)
  • Maharashtra Pollution Control Board (MPCB)
  • Scientists / Researchers
  • Research students at Post Graduate and Ph.D. level

Urban Environment Science to Society (UES2S)-sample

About Urban Environment Science to Society (UES2S)

UES2S is an online fully coupled urban ‘meteorology, hydrology, and air quality’ modeling system developed under the NSM Urban Modelling Project (Figure 1). This system captures the urban representation of micro-scale city environmental conditions. UES2S has three major components: Data as a service (DataHub), modeling platform as a service (Science Gateway), and Decision Support System (DSS) for cross-sector end-user decisions. Through DataHub, we intend to provide cross-sector data access and a data-sharing facility. The Science Gateway (Figures 2 & 3) has automatic end-end modeling workflows enabling ready-to-use weather, hydrology, and air quality models on NSM clusters. The DSS component (Figures 4 & 5) facilitates the translation of scientific data into multi-stakeholder interactive actions. The DSS provides high-resolution weather, air quality, and hydrology forecasts along with the forecast of reservoir inflows, water levels, and discharge for flood management and mitigation. Thus, the DSS is integral to disaster management activities, daily operations, and science-based policy decisions.


Figure 1: Homepage of Urban Environment Science to Society (UES2S)



This multi-sectorial simulation lab and science-based decision framework is developed to address urban environment issues. This HPC-based automated model execution workflows with an interdisciplinary urban testbed has been developed to execute weather, air quality, and hydrology models for the prediction of extreme events. The system is designed to be exceptionally user-friendly, enabling researchers and students to execute the models easily. This would facilitate the seamless transition of research into operational practices. The framework offers an urban modeling system, operational processes, a data hub, and a DSS, enabling meteorology, air quality, and hydrology services for diversified user categories.

Science Gateway (Figure 2) is a digital platform customized for meteorologists, hydrologists, and air quality modelers, offering convenient access to data from specialized tools and collaboration features to enhance research and forecasting in these areas.


Figure 2: Components of Science Gateway



Workflow of the Weather Research and Forecasting (WRF) (Figure 3) is developed in Science Gateway, a state-of-the-art mesoscale numerical weather prediction system designed for atmospheric research and operational forecasting applications.


Figure 3: WRF Workflow



A Decision Support System (DSS) (Figure 4) helps in decision-making during extreme events like heavy rainfall, floods, and heatwaves. It facilitates analyses of meteorological patterns like short-duration high-intensity rainfall, heat and cold waves, hydrological parameters such as reservoir levels and river flows, and air quality parameters like PM 2.5. For instance, during an extreme event, the DSS provided accurate forecasts and risk assessments through charts, shaded and non-shaded plots, and vector plots, assisting users in rainfall information, flood control, air quality monitoring, and climate resilient planning.

The reservoir operations module, which is a key component of the DSS, displays a time series forecast plots as shown in Figure 4. This plot includes various parameters such as upstream/downstream catchment rainfall, reservoir water level, dam discharge, and reservoir inflow for the user-selected reservoir. The user, typically a scientists or operational forecasters in weather, environmental science, or disaster management, can use this information to make informed decisions and plan accordingly.


Figure 4: Decision Support System



In one of the DSS module (Figure 5), users can select flood hotspots in the alerts section and then click on a hotspot pin for a particular location to visualize water depth relative to human height, making the representation more intuitive and engaging.


Figure 5: DSS for Flood – Water depth: 0.52 meter (pictorial view) at Pune catchment



End Users:
  • India Meteorological Department (IMD)
  • Pune Municipal Corporation (PMC), Disaster Management Department
  • Pune Municipal Corporation (PMC) Environment Department
  • Pimpri Chinchwad Municipal Corporation (PCMC)
  • Karnataka State Natural Disaster Monitoring Centre (KSNDMC)
  • Central Pollution Control Board (CPCB)
  • Maharashtra Pollution Control Board (MPCB)
  • Scientists / Researchers
  • Research students at Post Graduate and Ph.D. level
Milestones:
  • Calibrated and customized model for Indian cities
  • Prepared high resolution LULC map for pilot cities
  • Integrated Met-Hydro-AQ user friendly web-based Model Execution framework (WRF, WRF-Chem, AERMOD, HEC-RAS, HEC-HMS, SWMM), Data hub and Decision Support System
  • End-to-End automated model forecast validation tool
  • Indigenously developed visualization platform
  • Provided access of developed system to IMD
  • Shared ward level Rainfall, Reservoir Water and urban flood, heatwave, air pollution forecast information with IMD, PMC, PCMC and WRD (Image 6 & 7)




Figure 6: Typical Daily Rainfall info upto Ward level




Figure 7: Air quality forecast information




Figure 8: Demonstration of UES2S to Project review committee lead by
Dr. M. Ravichandran, Secretary, MoES, Chairman, and domain experts



MoUs:
  • MoU signed with Pimpri-Chinchwad Municipal Corporations to share the access and use of urban Decision Support System

Figure 9: MOU Signed between C-DAC and PCMC on 30 October 2024
(R to L) Dr Sanjay Wandhekar Centre Head, C-DAC Pune, Mr Shekhar Singh (IAS) Municipal Commissioner of Pimpri Chinchwad Municipal Corporation (PCMC), PCMC Officials



Early warning system for flood prediction in the river basins of India_sample

About Project

India is highly vulnerable to floods, which has large scale economic as well as social impacts. To address the issue and lessen the burden of the disaster management agencies, Centre for Development of Advanced Computing (C-DAC), Pune, is executing a project viz., ‘Early Warning System for Flood Prediction for River Basins of India’ under the National Supercomputing Mission of MeitY and DST, Govt. of India.

Under this project, three important aspects of flood management are being handled. Flood Prediction and Early Warning, Integrated Reservoir Operations and Sediment Transport Model.

A free and open source software tool for 2D hydrodynamic modelling is being used for prediction modelling and simulation. The model is designed such that it is both scalable and flexible and without much changes, except input data, and can be implemented in any river basin of India. The simulation runs for predicting floods are being carried out since year 2020. Every year daily flood predictions have been carried out for the monsoon season (June to October) for Mahanadi Basin. The model is massively parallelised and NSM HPC resources are being used for carrying out these daily simulation runs. The results have been shared with State Water Resources Department and Central Water Commission for validations. Since 2022 monsoon season, Tapi River Basin simulations have also been started.

The daily outputs include a 2-day flood forecast in the form of village-level percentage inundation information and predicted inundation spread and water level information. After proper validation and calibration exercises the model may be implemented in other flood affected river basins of the country. Both Odisha State Water Resources Department and Central Water Commission Bhubaneshwar have been part of this project and as such their continuous support has been fruitful for the project.

  • Design, develop and deploy an Early Warning System for Flood Prediction (EWS-FP) on HPC platform
  • Develop Sediment Transport model
  • Develop Integrated Reservoir Operation tools
  • Design geospatial portal for information dissemination on flood prediction
  • Early Warning System for Flood Prediction- 2-days flood forecast (water level, inundation extent, flow, village level % inundation)
  • Integrated framework for flood modelling at River Basin Level adaptable for the entire country
  • Central Water Commission (CWC)
  • Odisha State Water Resources Department (OSWRD)
  • National and State Disaster Management Authorities (NDMA, SDMA)
  • National Disaster Response Force (NDRF)
  • District Administration
  • Central Water Commission (CWC), Delhi
  • Indian Institute of Science (IISc), Bengaluru
  • Currently the water level, inundation spread and flow forecast for the next 24 hours is being shared with the Odisha State Water Resources Department (OSWRD) on a daily-basis. The accuracy and lead time of the forecast is appreciated by the department
  • Geospatial Portal (SimInu) being developed on open source technology presents an opportunity to develop indigenous early warning dissemination systems for the country
Portal for visualization of daily forecast (Inset – Report showing villages that are flooded 40% or more by area)
Portal for visualization of daily forecast (Inset – Report showing villages that are flooded 40% or more by area)
Project showcased in national and international events
Project showcased in national and international events

Projects

NSM Projects

The National Supercomputing Mission (NSM) initiated by the Government of India aims towards achieving the goals of attaining self-reliance in supercomputing and problem solving in various domains of scientific and technological endeavors. Under this mission C-DAC is working on various projects for societal benefits using inhouse HPC resources.
Early Warning System for Flood Prediction in the River Basins of India
5
Under this project, three important aspects of flood management are being handled. Flood Prediction and Early Warning, Integrated Reservoir Operations and Sediment Transport Model.
View More
5
Under this project, three important aspects of flood management are being handled. Flood Prediction and Early Warning, Integrated Reservoir Operations and Sediment Transport Model.
View More
Urban Modelling: Development of multi-sectorial simulation lab and science-based decision support framework to address urban environment issues
5
Under NSM Urban Modelling project, an integrated urban modelling system and service cyberinfrastructure Urban Environment Science to Society (UES2S) is developed.
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A HPC software suite for seismic imaging to aid oil and gas exploration
5
Under the National Supercomputing Mission (NSM), “A HPC software suite for seismic imaging to aid oil and gas exploration” is a “Make in India” initiative to develop a customizable and efficient RTM software “SeisRTM”.
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Development of indigenous scientific (Materials and Computational Chemistry) codes:
5
  1. Linear Scaling DFT
  2. Multi-Reference Methods with hybrid QM-MM approaches
  3. Excited state dynamics toolkit
  4. Multiscale Microstructure Simulation and Modelling
  5. GUI for home-grown quantum chemistry code
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