Category: application

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

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

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





Consortia Partners:

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

Geodata Processing and Interpretation Centre (GEOPIC), ONGC

Indian Institute of Technology Roorkee (IITR)



Collaborators:

  • Centre for Development of Advanced Computing (C-DAC), Pune
  • Geodata Processing and Interpretation Centre (GEOPIC), ONGC
  • Indian Institute of Technology Roorkee (IITR)
End Users:
  • Agencies involved in oil and gas exploration
  • Research organization for deep crustal studies
  • Academia for teaching advance seismic processing
Milestones:
  • CDAC DG Award 2024 (Core Research)
  • National Workshop on HPC in Seismic Imaging “Seeing Below the Earth Surface”, SeisRTM Workshop at Pune held on April 2023)
  • Workshop on Seismic modeling and migration using SeisRTM at IIT Roorkee held on Dec 2024
  • Workshop on Seismic modeling and migration using SeisRTM at IIT(ISM) Dhanbad held on Feb 2025


National Workshop on HPC in Seismic Imaging “Seeing Below the Earth Surface


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 at IIT Roorkee


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 at IIT(ISM) Dhanbad


A three-day workshop on “Seismic Modeling and Migration using SeisRTM” was conducted at IIT (ISM), Dhanbad during February 8th to 10th, 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.




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
Achievements:
  • 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

  • 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

  • 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

  • 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

  • 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  

  • Successfully migrated SeisAcouMod2D CUDA version to SYCL on Intel Datacenter GPU Max 1500 with CDAC’c HPC-Tech and Intel’s team. A case study of 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

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



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

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.

Project Objectives

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.


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




Figure 2: HPC Based Integrated Urban Modelling System



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)




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)
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 (Figure 3)
  • Demonstration of UES2S to Dr. M. Ravichandran, Secretary, MoES, Chairman, PMC and domain experts (Figure 4)
  • 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 3: Typical Daily Rainfall info upto Ward level




Figure 4: Air quality forecast information




Figure 5: Project review by Dr. M. Ravichandran, Secretary, MoES, Chairman, PMC and domain experts



MoUs:
  • MoU signed with Pimpri-Chinchwad Municipal Corporation (PCMC) to share the access and use of Urban Decision Support System

Figure 6: 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) Commissioner, PCMC, PCMC officials



Achievements:
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.

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

Early Warning System for Flood Prediction in the River Basins of India

Objectives:
  • 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
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
End Users:
  • 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
Collaborators:
  • Central Water Commission (CWC), Delhi
  • Indian Institute of Science (IISc), Bengaluru



About the 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.


Figure: Portal for visualization of daily forecast (Inset – Report showing villages that are flooded 40% or more by area)



Status:
  • 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



Project showcased in national and international events:

Urban Environment Science to Society (UES2S)

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



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

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

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





Consortia Partners:

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

Geodata Processing and Interpretation Centre (GEOPIC), ONGC

Indian Institute of Technology Roorkee (IITR)



Collaborators:

  • Centre for Development of Advanced Computing (C-DAC), Pune
  • Geodata Processing and Interpretation Centre (GEOPIC), ONGC
  • Indian Institute of Technology Roorkee (IITR)
End Users:
  • Agencies involved in oil and gas exploration
  • Research organization for deep crustal studies
  • Academia for teaching advance seismic processing
Milestones:
  • CDAC DG Award 2024 (Core Research)
  • National Workshop on HPC in Seismic Imaging “Seeing Below the Earth Surface”, SeisRTM Workshop at Pune held on April 2023)
  • Workshop on Seismic modeling and migration using SeisRTM at IIT Roorkee held on Dec 2024
  • Workshop on Seismic modeling and migration using SeisRTM at IIT(ISM) Dhanbad held on Feb 2025


National Workshop on HPC in Seismic Imaging “Seeing Below the Earth Surface


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 at IIT Roorkee


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 at IIT(ISM) Dhanbad


A three-day workshop on “Seismic Modeling and Migration using SeisRTM” was conducted at IIT (ISM), Dhanbad during February 8th to 10th, 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.




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
Achievements:
  • 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

  • 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

  • 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

  • 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

  • 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  

  • Successfully migrated SeisAcouMod2D CUDA version to SYCL on Intel Datacenter GPU Max 1500 with CDAC’c HPC-Tech and Intel’s team. A case study of 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

Projects

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Urban Environment Science to Society (UES2S)

Science-based decision support framework to address urban environment issues developed under the NSM Urban Modelling Project




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

An Integrated Urban Meteorology, Hydrology and Air Quality modelling and forecasting system


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

"SeisRTM," developed under the National Supercomputing Mission, is a "Make in India" initiative to create customizable and efficient RTM software for high-resolution 2D and 3D seismic imaging. It will be top of the class software in India, providing advanced seismic imaging capabilities for upstream oil and gas exploration companies.
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Materials and Computational Chemistry (MCC)

Development of indigenous scientific (Materials and Computational Chemistry) codes:
  1. Linear Scaling DFT
  2. Multi-Reference Methods with hybrid QM-MM approaches
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Applications

HPC Applications of National Relevance

High-Performance Computing (HPC) applications of national relevance are going to be developed and deployed. The areas chosen for developing these applications include:

  • Computational Biology
  • Climate Modelling and Weather Prediction
  • Engineering including CFD, CEM
  • Seismic Imaging for Oil and Gas Exploration
  • Disaster Simulations and Management
  • Computational Chemistry and Material Science
  • Discoveries Beyond Earth (Astrophysics)
  • Big Data Analytics