Dr Ankit Agarwal

Agarwal

Ankit is a hydro-climatologist interested in interdisciplinary research and teaching to understand multi-scale interactions between different components of Earth, in general, such as Atmosphere and Hydrosphere, and climate patterns and extreme events, in particular. He gained training as a Civil engineer at MBM Engineering College, Jodhpur and hydrologist during his master at IIT-Delhi but diversified his expertise in climatology and nonlinear dynamics during his PhD at the University of Potsdam.

Currently, he is a postdoctoral candidate at the Potsdam Institute for Climate Impact Research and Helmholtz Center for Geosciences, section 5.4 (Hydrology) where he is responsible to develop new methods and apply them in hydrology and climatology for advance understanding. He also enriches master and PhD student of both the institutes with his expertise and knowledge. Lecturing, course design, proposal writing, reviewing journal articles, writing reports, conferences and meetings are other tasks come along way.

Ankit has received International professional training for teaching. He developed and taught courses on “Applications of Matlab in Civil Engineering” and “Hydrometric methods to measure discharge and hydraulic conductivity” at the University of Potsdam.

Department

Curriculum Vitae

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Contact

Potsdam Institute for Climate Impact Research (PIK)
T +49 (0)331 288 20703
agarwal[at]pik-potsdam.de
P.O. Box 60 12 03
14412 Potsdam

ORCID

Ankit Agarwal has his research expertise in the field of Hydrology, Climatology and Nonlinear Dynamics. Particularly, he focused to study the interactions and variability of natural processes, synchronization of extreme events (climatic/hydrology) at different spatial and temporal and even cross-scales. His research shows the flavour of earth system dynamics, climate physics, stochastic hydrology, wavelet analysis, ensemble modelling, climate variability studies and some of its extension parts as regionalization technique, hydrologic classification and related subjects. Few tools which he uses are network theory, event synchronization and wavelet.

Video link:

Paper recognition

Editor's choice and featured article

N.Ekhtiari, A. Agarwal, N. Marwan, R.V. Donner: Disentangling the multi-scale effects of sea-surface temperatures on global precipitation - A coupled networks approach. Chaos. https://aip.scitation.org/doi/10.1063/1.5095565

See short commentary here: https://aip.scitation.org/doi/10.1063/1.5115011.

NPG highlighted article

Kurths, J*., Agarwal, A*., Shukla, R., Marwan, N., Maheswaran, R., Caesar, L., Krishnan, R., and Merz, B.: Unraveling the spatial diversity of Indian precipitation teleconnections via nonlinear multi-scale approach. Nonlinear process in Geophysics discussion. https://www.nonlin-processes-geophys.net/26/251/2019/ 

NPG paper of the month

NPG Paper of the Month: “Unravelling the spatial diversity of Indian precipitation teleconnections via a non-linear multi-scale approach”

https://blogs.egu.eu/divisions/np/2019/09/20/npg-paper-of-the-month-kurths-et-al/


Submitted

  1. Investigating inundation extents of urban flooding by the development of a hybrid model. Journal of Hydrology [Submitted in August 2020]

  2. Evaluation of Satellite-based precipitation products for Streamflow simulation in the Flood-Prone Indian river basin. Journal of Hydrology [Submitted in May 2020].

  3. Downscaling daily precipitation in a semi-arid region: Comparison of methods with emphasis on wavelet-based hybrid models. Journal of Hydrology [Submitted in April 2020].

  4. Multi-objective optimization for stormwater management by green-roofs and infiltration trenches to reduce urban flooding in Central Delhi. Journal of Hydrology [Submitted in April 2020].

    Publications

    1. Durga Prasad Panday, Rakesh Khosa, Rathinasamy Maheswaran, K Ravikumar and Ankit Agarwal (2021). Game-Theoretic Based Modelling of Krishna Waters Dispute - Equilibrium Solutions by Metagame Analysis. European Physics Journal-B. 10.1140/epjb/s10051-021-00107-w

    2. Agrawal, Purushottam; Sinha, Alok; Kumar, Satish; Agarwal, Ankit; Banerjee, Ashes; Villuri, Vasanta G.K.; Annavarapu, Chandra S.R.; Dwivedi, Rajesh; Dera, Vijaya V.R.; Sinha, Jitendra; Pasupuleti, Srinivas (2021). "Exploring Artificial Intelligence Techniques for Groundwater Quality Assessment" Water 13, no. 9: 1172. https://doi.org/10.3390/w13091172

    3. Saurav Raj, Roopam Shukla, Ricardo M. Trigo, Bruno Merz, Maheswaran Rathinasamy, Alexandre M. Ramos, Ankit Agarwal* (2021). Ranking and Characterization of Precipitation Extremes for the past 113 years for Indian western Himalayas. International Journal of Climatology. (Provisionally Accepted)

    4. Yeditha Pavan Kumar, Rathinasamy Maheswaran, Ankit Agarwal, and Bellie Sivakumar (2021). Downscaling daily precipitation using wavelet-based hybrid models. Journal of Hydrology. 10.1016/j.jhydrol.2021.126373

    5. Mayuri Ashokrao Gadhawe, Ravi Kumar Guntu, Ankit Agarwal* (2021). Network-based exploration of basin precipitation based on satellite and observed data. European Physics Journal-Special Topics. https://doi.org/10.1140/epjs/s11734-021-00017-z

    6. Satish Kumar, Ankit Agarwal, Vasant Govind Kumar Villuri, Srinivas Pasupuleti, Dheeraj Kumar, Deo Raj Kaushal, Ashwin Kumar Gosain, Axel Bronstert, Bellie Sivakumar,* (2021). Constructed Wetland Management in Urban Catchments for Mitigating Floods.  Stochastic Environmental Research and Risk Assessment. 10.1007/s00477-021-02004-1

    7. Kalyan, AVS; Ghose, Dillip Kumar; Thalagapu, Rahul; Guntu, Ravi Kumar; Agarwal, Ankit; Kurths, Jürgen; Rathinasamy, Maheswaran. 2021. "Multiscale Spatiotemporal Analysis of Extreme Events in the Gomati River Basin, India" Atmosphere 12, no. 4: 480. https://doi.org/10.3390/atmos12040480

    8. Setti, S.; Maheswaran, R.; Sridhar, V.; Barik, K.K.; Merz, B.; Agarwal, A (2020). Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling. Atmosphere 2020, 11, 1252. https://www.mdpi.com/2073-4433/11/11/1252
    9. Kasi, V., Yeditha, P. K., Rathinasamy, M., Pinninti, R., Landa, S. R., Sangamreddi, C., Agarwal, A. and Dandu Radha, P. R. (2020): A novel method to improve vertical accuracy of CARTOSAT DEM using machine learning models, Earth Sci. Informatics. doi:10.1007/s12145-020-00494-1, 2020
    10. Ravi Kumar Guntu, Rathinasamy Maheswaran, Ankit Agarwal, Vijay P. Singh (2020). “Accounting for temporal variability for improved precipitation regionalization based on self-organizing map coupled with information theory” Journal of Hydrology. 10.1016/j.jhydrol.2020.125236
    11. Yeditha, Pavan Kumar, Venkatesh Kasi, Maheswaran Rathinasamy, and Ankit Agarwal (2020). “Forecasting of Extreme Flood Events Using Different Satellite Precipitation Products and Wavelet-Based Machine Learning Methods.” Chaos: An Interdisciplinary Journal of Nonlinear Science 30(6): 063115. https://doi.org/10.1063/5.0008195
    12. Agarwal, Ankit, Norbert Marwan, Rathinasamy Maheswaran, Ugur Ozturk, Jürgen Kurths, and Bruno Merz (2020). “Optimal Design of Hydrometric Station Networks Based on Complex Network Analysis.” Hydrology and Earth System Sciences 24, no. 5 (May 8, 2020): 2235–51. https://doi.org/10.5194/hess-24-2235-2020. https://www.hydrol-earth-syst-sci.net/24/2235/2020/
    13. Ravi Kumar Guntu, Maheswaran Rathinasamy, Ankit Agarwal, and Bellie Sivakumar (2020).Spatiotemporal Variability of Indian rainfall using multi-scale entropy. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2020.124916
    14. Ravi Kumar Guntu, Pavan Kumar Yeditha, Maheswaran Rathinasamy, Matjaž Perc, Norbert Marwan, Jürgen Kurths, and Ankit Agarwal (2020). Wavelet entropy-based evaluation of intrinsic predictability of time series. Chaos 30, 033117 (2020);  https://aip.scitation.org/doi/10.1063/1.5145005
    15. Jun Meng, Jingfang Fan, Josef Ludescher, Agarwal Ankit, Xiaosong Chen, Armin Bunde, Jurgen Kurths, and Hans Joachim Schellnhuber: Complexity based approach for El Niño magnitude forecasting before the spring predictability barrier (PNAS). https://www.pnas.org/content/early/2019/12/23/1917007117
    16. Roopam Shukla, Ankit Agarwal, Christoph Gronott, Kamna Sachdeva and PK Joshi. Farmer typology to understand differentiated climate change adaptation in the Himalayas. Scientific Reports. https://www.nature.com/articles/s41598-019-56931-9
    17. Rathinasamy, M., Agarwal, A., Sivakumar, B., Marwan, N., and Kurths, J.: "Wavelet analysis of precipitation extremes over India and teleconnections to climate indices. Stochastic Environmental Research and Risk Assessment. https://link.springer.com/article/10.1007/s00477-019-01738-3
    18. Kurths, J*., Agarwal, A*., Shukla, R., Marwan, N., Maheswaran, R., Caesar, L., Krishnan, R., and Merz, B.: Unraveling the spatial diversity of Indian precipitation teleconnections via nonlinear multi-scale approach. Nonlinear process in Geophysics discussion. https://www.nonlin-processes-geophys.net/26/251/2019/ (* equally share the first authorship).
    19. Agarwal, A., Caesar, L., Marwan, N., Maheswaran, R., Merz, B., and Kurths, J.: Network-based identification and characterization of teleconnections on different time scales. https://www.nature.com/articles/s41598-019-45423-5
    20. Agarwal, A., Maheswaran, R., Marwan, N., Caesar, L., and Kurths, J.: Wavelet-based multiscale similarity measure for complex networks, European Physics Journal-B, https://doi.org/10.1140/epjb/e2018-90460-6.
    21. N.Ekhtiari, A. Agarwal, N. Marwan, R.V. Donner: Disentangling the multi-scale effects of sea-surface temperatures on global precipitation - A coupled networks approach. Chaos. https://aip.scitation.org/doi/10.1063/1.5095565.
    22. This article has been selected as an Editor's pick and released as a featured article.https://aip.scitation.org/doi/10.1063/1.5115011.
    23. Agarwal, A., Marwan, N., Rathinasamy, M., Merz, B. and Kurths, J.: Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach, Nonlinear Process. Geophys., 24(4), 599–611, doi:10.5194/npg-24-599-2017, 2017.
    24. Agarwal, A., Marwan, N., Rathinasamy, M., Merz, B. and Kurths, J.: Quantifying the role of single stations within homogeneous regions using complex network. https://doi.org/10.1016/j.jhydrol.2018.06.050.
    25. Agarwal, A., Marwan, N., Rathinasamy, M., Ozturk, U., Merz, B. and Kurths, J.: Optimal Design of Hydrometric Station Networks Based on Complex Network Analysis, Hydrol. Earth Syst. Sci. Discuss., 1–21, doi:10.5194/hess-2018-113, 2018.
    26. Shukla, R., Agarwal, A., Sachdeva, K., Kurths, J., and Joshi, P.K: Climate change perception: Analysis of climate change and risk perception among farmer types of Indian Western Himalayas. Climatic Change.https://link.springer.com/article/10.1007/s10584-018-2314-z
    27. Bronstert, A., Agarwal, A., Boessenkool, B., Crisologo, I., Fischer, M., Heistermann, M., Köhn-Reich, L., López-Tarazón, J. A., Moran, T., Ozturk, U., Reinhardt-Imjela, C. and Wendi, D.: Forensic hydro-meteorological analysis of an extreme flash flood: The 2016-05-29 event in Braunsbach, SW Germany, Sci. Total Environ., 630, 977–991, doi:10.1016/j.scitotenv.2018.02.241, 2018.
    28. Ozturk, U., Wendi, D., Crisologo, I., Riemer, A., Agarwal, A., Vogel, K., López-Tarazón, J. A. and Korup, O.: Rare flash floods and debris flows in southern Germany, Sci. Total Environ., 626, 941–952, doi:10.1016/j.scitotenv.2018.01.172, 2018.
    29. Ozturk, U., Marwan, N., Korup, O., Saito, H., Agarwal, A., Grossman, M. J., Zaiki, M., and Kurths, J.: Complex networks for tracking extreme rainfall during typhoons, Chaos. https://aip.scitation.org/doi/pdf/10.1063/1.5004480
    30. Rathinasamy, M., Agarwal, A., Parmar, V., Khosa, R., & Bairwa, A. (2017). Partial wavelet coherence analysis for understanding the standalone relationship between Indian Precipitation and Teleconnection patternsarXiv preprint arXiv:1702.06568.
    31. Agarwal, A., Maheswaran, R., Kurths, J., & Khosa, R. (2016). Wavelet Spectrum and self-organizing maps-based approach for a hydrologic regionalization-a case study in the western United StatesWater Resources Management30(12), 4399-4413.
    32. Agarwal, A., Maheswaran, R., Sehgal, V., Khosa, R., Sivakumar, B., & Bernhofer, C. (2016). Hydrologic regionalization using a wavelet-based multiscale entropy methodJournal of Hydrology538, 22-32.
    33. Bronstert, A., Agarwal, A., Boessenkool, B., Fischer, M., Heistermann, M., Köhn-Reich, L., Moran T., Wendi, D. (2017): The flood of Braunsbach on May 29, 2016 - the origin, course, and damage of a "centuries event". Part 1: Meteorological and hydrological analysis- hydrology & water management, 61, (3), 150-162; DOI: 10.5675 / HyWa_2017,3_1
    34. Vogel, K., Ozturk, U., Riemer, A., Laudan, J., Sieg, T., Wendi, D., Agarwal, A., Rozer, V., Korup, O., Thieken, A (2017): The flood of Braunsbach on May 29, 2016 - the origin, course and damage of a "centuries event". Part 2: Geomorphological processes and damage analysis - Hydrology & Water Management, 61, (3), 163-175; DOI: 10.5675 / HyWa_2017,3_2.

    Conference proceeding and workshop  presentations

    1. (Ravi Kumar Guntu, and Ankit Agarwal. Investigation of Precipitation Variability and Extremes Using Information Theory. https://sciforum.net/manuscripts/8115/manuscript.pdf

    2. Ankit Agarwal, Levke Caesar, Norbert Marwan, Rathinasamy Maheswaran, Bruno Merz, Juergen Kurths: Detection of short- and long-range teleconnections in SST patterns on different time scales. European Geophysical Union 2019; 04/2019.
    3. Shukla, R., Agrawal, A., Sachdeva, K., Kruths, J., Joshi, P. K. 2019. Perception of climate change and its impact among Himalayan farmers. European Geophysical Union 2019, Vienna.  https://meetingorganizer.copernicus.org/EGU2019/EGU2019-6072.pdf
    4. Ankit Agarwal, Norbert Marwan, Rathinasamy Maheswaran, Bruno Merz, Ravi Krishnan Juergen Kurths: Unravelling Regionwise Teleconnections of Indian Rainfall Using Event Synchronization-Based Multiscale Nonlinear Method. Asian Oceanic Geosciences meeting-2018; 06/2018.
    5.  Ankit Agarwal, Norbert Marwan, Rathinasamy Maheswaran, Bruno Merz, Juergen Kurths, R: Complex network-based approach for identification of influential and expandable station across rainfall network. European Geophysical Union 2018; 04/2018
    6. Ankit Agarwal, Norbert Marwan, Rathinasamy Maheswaran, Bruno Merz, Juergen Kurths, R: Multiscale complex network analysis: An approach to study spatiotemporal rainfall pattern in south Germany. European Geophysical Union 2017; 04/2017
    7. Ankit Agarwal, Norbert Marwan, Rathinasamy Maheswaran, Ugur Ozturk, Bruno Merz, Juergen Kurths: Multiscale event synchronization analysis for unravelling climate processes: A wavelet-based approach. American Geophysical Union 2016, San Francisco; 12/2016
    8. Jonas Laudan, Ugur Öztürk, Tobias Sieg, Dadiyorto Wendi, Adrian Riemer, Ankit Agarwal, Viktor Rözer, Oliver Korup, Annegret Thieken, and Kristin Vogel. A retrospective analysis of the flash flood in Braunsbach on May 29th, 2016. EGU2017-13464, European Geophysical Union 2016, Vienna; 04/2017.
    9. Axel Bronstert, Agarwal Ankit, Boessenkool Berry, Fischer Madlen, Heistermann Maik, Köhn-Reich Lisei, Moran Thomas, and Wendi Dadiyorto. The Braunsbach Flashflood of May 29, 2016: A forensic analysis of the meteorological origin and the hydrological development an extreme hydro-meteorological event. EGU2017-2942, European Geophysical Union 2016, Vienna; 04/20167.
    10. Ankit Agarwal, Norbert Marwan, Rathinasamy Maheswaran, Ugur Ozturk, Bruno Merz, Juergen Kurths: Multiscale event synchronization measure: A wavelet-based approach. Perspectives in Nonlinear Dynamics 2016, Humboldt-University Berlin, Germany; 07/2016, DOI:10.13140/RG.2.2.16589.64485
    11. Ugur Ozturk, Ankit Agarwal, Norbert Marwan, Jürgen Kurths, Oliver Korup: Spatiotemporal Pattern of Seasonal Extreme Rainfall over Japan Using Complex Networks. International school and conference of network science, Seoul 2016, South Korea; 05/2016
    12. Ankit Agarwal, Rathinasamy Maheswaran, Juergen Kurths, Rakesh Khosa: Wavelet Spectrum and Self-Organizing Maps-Based Approach for Hydrologic Regionalization -a Case Study in the Western United States. Water Resources Management, European Geophysical Union-2016; 04/2016
    13. Ankit Agarwal, Maheswaran Rathinasamy, Rakesh Khosa: Hydrologic Regionalization Using Wavelet-based Multi-Scale Entropy Method. American Geophysical Union-2015, San Fransisco, USA; 12/2015, DOI:10.13140/RG.2.1.2155.5289

    Book chapters

    1. Agarwal, A., Marwan, N., Ozturk, U., and  Rathinasamy, M.: Unfolding Community Structure in Rainfall Network of Germany Using Complex Network-Based Approach.  Water Resources and Environmental Engineering II; 10.1007/978-981-13-2038-5_17
    2. Chaudhary, S., Agarwal, A., and Nakamura, T.: Rainfall Projection in Yamuna River Basin, India, Using Statistical Downscaling. Water Resources and Environmental Engineering II; 10.1007/978-981-13-2038-5_2

    Technical reports

    1. Agarwal, A., B. Boessenkool, M. Fischer, I. Hahn, L. Köhn, J. LAUDAN, T. Moran, U. Oztürk, A. Riemer, V. Rözer, T. Sieg, K. Vogel, D. Wendi, A Bronstert, A. THIEKEN (2016): Die Sturzflut in Braunsbach, Mai 2016 - Eine Bestandsaufnahme und Ereignisbeschreibung. Taskforce im Rahmen des DFG-Graduiertenkollegs Natural Hazards and Risks in a Changing World, Universität Potsdam. 20 S. (in German, PDF-File).  http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-394881

    Scientific blog

    1. Ankit Agarwal. Quantifying the Roles of Single Rain Gauges within Homogeneous Regions of a Rainfall Network. Scientific Trends 2018.
    2. Roopam Shukla and Ankit Agarwal. Do Perceptions of Climate Change and its Impacts Differ Among Farmers in Indian Western Himalayas? Scientific Trends 2019.
    3. Forecasting El Niño with entropy—a year in advance, https://arstechnica.com/science/2019/12/forecasting-el-nino-with-entropy-a-year-in-advance/

    Thesis

    1. Ankit Agarwal. "Unravelling spatio-temporal climatic patterns using the multi-scale complex network." Ph.D. diss., University of Potsdam, Potsdam, Germany, 2018. DOI: 10.25932/publishup-42395
    2.  Ankit Agarwal. "Hydrologic Regionalization Using Wavelet-based Multiscale Entropy Technique." M.Tech, Indian Institute of Technology, DELHI, 2015. DOI: 10.13140/RG.2.1.2175.5287

    Toolbox and codes

    Climate Downscaling Toolbox

    Forecasting of extreme flood events using different satellite precipitation products and wavelet-based machine learning methods.

    PDF document paper1.pdf — PDF document, 2.69 MB

     

    • COPREPARE:Collaborative Indo-German PRoject on Estimating and Predicting NAtural Hazards in the Himalayan REgion

    • Multivariate cross-scale dynamics

    • Climate change perception- A case study in Indian Western Himalayans

    • Complex Network analysis based on event synchronization of Natural hazard

    • Task force Braunsbach flash flood-2016

    • Hydrologic regionalization using wavelet-based multiscale entropy technique 

    • Wavelet spectrum and self-organizing maps-based approach for hydrologic regionalization -A case study in the western United States

    Hydrological measurement (discharge and soil conductivity) technique.

    MATLAB applications in Civil Engineering.

    Hydrometeorology and Climate Change

    Awarded “start-up funding for 9 months by DFG German Research Foundation to pursue a postdoc at Potsdam Institute for Climate Impact Research, Germany.

    DAAD Scholarship Award for being department topper in IIT-Delhi to complete research work in Technical University-Dresden (Germany).

    Singapore University of Technical design (SUTD) Graduate Award Fellowship.

    Natural Hazards and Risk in a Changing world (NatRiskChange) Graduate school fellowship funded by DFG.

    Ministry of Human Resources and Development Fellowship (A Fellowship by Indian Govt. for higher education) to pursue Master of Technology at IIT-Delhi, India.