Publications

NPG highlighted article

1. Ekhtiari, N.,  Agarwal, A.,  Marwan, N.,  and Donner, R.V. (2019) Disentangling the multi-scale effects of sea-surface temperatures on global precipitation - A coupled networks approach. Chaos, 29, 250012. https://doi.org/10.1063/1.5095565; 

NPG paper of the month

2. Kurths, J., Agarwal, A., Shukla, R., Marwan, N., Maheswaran, R., Caesar, L., Krishnan, R., and Merz, B. (2019) Unraveling the spatial diversity of Indian precipitation teleconnections via nonlinear multi-scale approach. Nonlinear process in Geophysics discussion. Nonlinear Processes in Geophysics , 26, 251-266, https://doi.org/10.5194/npg-26-251-2019

Editor’s Pick article

3. Buschmann,  S.,  Hoffmann, P., Agarwal, A., Marwan, N., and   Nocke, T. (2023) GPU-based, interactive exploration of large spatio-temporal climate networks, Chaos  33, 043129 https://doi.org/10.1063/5.0131933. 

2024

1. Ganapathy, A., Hannah, D.M., Agarwal, A., 2024. Improved estimation of extreme floods with data pooling and mixed probability distribution. J. Hydrol. 629, 130633. https://doi.org/10.1016/j.jhydrol.2024.130633

2. Agarwal, A., Azais, P., Cifarelli, L., De Boer, J., Eroglu, D., Gebel, G., Hidalgo, C., Jamet, D., Kurths, J., Lefebvre-Joud, F., Linderoth, S., Loarte, A., Marwan, N., Mingo, N., Ozturk, U., Perraud, S., Pitz-Paal, R., Poedts, S., Priem, T., Rech, B., Ripani, M., Sharma, S., Tran, T.Q., Wagner, H.-J., 2024. Physics for the environment and sustainable development, in: Hidalgo, C. (Ed.), EPS Grand Challenges. IOP Publishing, pp. 6-1-6–132. https://doi.org/10.1088/978-0-7503-6342-6ch6 

3. Dhote, P.R., Agarwal, A., Singhal, G., Calmant, S., Thakur, P.K., Oubanas, H., Paris, A., Singh, R.P., 2024. River Water Level and Water Surface Slope Measurement from Spaceborne Radar and Lidar Altimetry: Evaluation and Implications for Hydrological Studies in the Ganga River. IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing 1–20. https://doi.org/10.1109/JSTARS.2024.3379874

4. Raghuvanshi, A. S., & Agarwal, A. (2024). Multiscale dynamics of transient merging between western disturbances and monsoonal lows: Connections to the July 2023 flood in Himachal Pradesh. Atmospheric Research, 304, 107401. https://doi.org/10.1016/j.atmosres.2024.107401

5. Batalini de Macedo, M., Mangukiya, N. K., Fava, M. C., Sharma, A., Fray da Silva, R., Agarwal, A., Razzolini, M. T., Mendiondo, E. M., Goel, N. K., Kurian, M., and Nardocci, A. C.: Performance analysis of physically-based (HEC-RAS, CADDIES) and AI-based (LSTM) flood models for two case studies, Proc. IAHS, 386, 41–46, https://doi.org/10.5194/piahs-386-41-2024, 2024 

6. Guntu, Ravi Kumar, and Ankit Agarwal. "Compound dry and hot extremes: A review and future research pathways for India." Journal of Hydrology (2024): 131199. https://doi.org/10.1016/j.jhydrol.2024.131199

7. Badika, P., Choudhary, M.K., Nayak, T., Jaiswal, R.K., Agarwal, A., 2024. Projected water availability in the Tawa River Basin India in changing climate. Groundwater for Sustainable Development 25, 101176. https://doi.org/10.1016/j.gsd.2024.101176

2023

8. Singh Raghuvanshi, A., & Agarwal, A. (2023). Unraveling atmospheric moisture transport linkages to extreme precipitation events and associated synoptic features over India. Journal of Hydrology, 626, 130290. https://doi.org/10.1016/j.jhydrol.2023.130290

9. Guntu, R.K., Merz, B., and Agarwal, A. (2023) Increased likelihood of compound dry and hot extremes in India. Atmospheric Research, 290, 106789. https://doi.org/10.1016/j.atmosres.2023.106789

10. J. Ashish Manoj, Teresa Pérez Ciria, Gabriele Chiogna, Nadine Salzmann, Ankit Agarwal, Characterising the coincidence of soil moisture - precipitation extremes as a possible precursor to European floods, Journal of Hydrology, 2023, 129445, ISSN 0022-1694, https://doi.org/10.1016/j.jhydrol.2023.129445.

11. Buschmann,  S., Hoffmann, P., Agarwal,  A., Marwan, N., and   Nocke, T. (2023) GPU-based, interactive exploration of large spatio-temporal climate networks. Chaos 33, 043129 https://doi.org/10.1063/5.0131933

12. Ravindra Kumar Singh, Satish Kumar, Srinivas Pasupuleti, Vasanta Govind Kumar Villuri, Ankit Agarwal; Evaluating evolutionary algorithms for simulating catchment response to river discharge. Journal of Water and Climate Change 2023; jwc2023083. https://doi.org/10.2166/wcc.2023.083 

13. Agarwal A, Kuriqi A and Matthews J (2023) Editorial: Emerging talents in water science. Front. Water 5:1275554. doi: 10.3389/frwa.2023.1275554 

14. Tegegn Kassa Beyene, Ankit Agarwal, Manoj Kumar Jain, Brijesh K. Yadav; Investigation of the propagation of meteorological to hydrological drought and water required to recover from drought over Ethiopian basins. Journal of Water and Climate Change 2023; jwc2023024. doi: https://doi.org/10.2166/wcc.2023.024 

15. Agarwal, A., Sarkar, A., Pandey, A., Kumar, A., & Sharma, A. (2023). Editorial of “Water security for sustainable development”. Water Security, 20, 100157.10.1016/j.wasec.2023.100157 

16. Guntu, R. K., and Agarwal, A.: Improving the predictability of compound dry and hot extremes through complexity science. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/ad0c0c, 2023. 

17. Kulkarni, S., & Agarwal, A. (2023). Quantifying the association between Arctic Sea ice extent and Indian precipitation. International Journal of Climatology, 1–15. https://doi.org/10.1002/joc.8337

2022

18. Sridhara Setti, Karisma Yumnam, Maheswaran Rathinasamy, Ankit Agarwal; Assessment of satellite precipitation products at different time scales over a cyclone-prone coastal river basin in India. Journal of Water and Climate Change 2022; jwc2022166. doi: https://doi.org/10.2166/wcc.2022.166

19. Rawat, S., Ganapathy, A., Agarwal, A., 2022. Drought characterization over Indian sub-continent using GRACE-based indices. Sci. Rep. 12, 15432. https://doi.org/10.1038/s41598-022-18511-2

20. Setti, S., Barik, K. K., Merz, B., Agarwal, A., & Rathinasamy, M. (2022). Investigating the impact of calibration timescales on streamflow simulation, parameter sensitivity and model performance for Indian catchments. Hydrological Sciences Journal, DOI: 10.1080/02626667.2022.2036340

21. Pant, T, Ganapathy, A and Agarwal, A (2022). Investigating streamflow variability and hydroclimatic teleconnections: a comparison of regulated and unregulated streamflow stations. Journal of Water and Climate Change: jwc2022369. https://doi.org/10.2166/wcc.2022.369 

22. Kumar, S., Guntu, K, R., Agarwal, A., Govind Kumar Villuri, V., Pasupuleti, S., RajKaushal, D., Kumar Gosian, A., Bronstert, A., (2022). Multi-objective optimization for stormwater management by green-roofs and infiltration trenches to reduce urban flooding in central Delhi. J. Hydrol. 127455. https://doi.org/10.1016/j.jhydrol.2022.127455

23. Agarwal, A, Guntu, R, K, Banerjee, Abhirup., Mayuri., G Marwan, Norbert., 2022. A complex network approach to study the extreme precipitation patterns in a river basin. Chaos 32, 013113. https://doi.org/10.1063/5.0072520

24. Agarwal, A.; Yuan, N.; Cheung, K.K.W.; Shukla, R. Emerging Hydro-Climatic Patterns, Teleconnections, and Extreme Events in Changing World at Different Timescales. Atmosphere 2022, 13, 56. https://doi.org/10.3390/atmos13010056

25. Dhote, P. R., Bansal, J. K., Garg, V., Thakur, P. K., and Agarwal, A.: Multi-mission altimetry data to evaluate hydrodynamic model-based stage-discharge rating curves in flood-prone Mahanadi River, India, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2022-101, in review, 2022.

26. Ashish Manoj J, Ravi Kumar Guntu., and Ankit Agarwal., 2022. Spatiotemporal Dependence of Soil Moisture and Precipitation over India. Journal of Hydrology https://doi.org/10.1016/j.jhydrol.2022.127898 

27. Beyene, T. K., Jain, M. K., Yadav, B. K., & Agarwal, A. (2022). Multiscale investigation of precipitation extremes over Ethiopia and teleconnections to large-scale climate anomalies. Stochastic Environmental Research and Risk Assessment, 36(5), 1503–1519. https://doi.org/10.1007/s00477-021-02120-y

28. Kashyap, A., Behera, M. D., Pandey, A. K., and Agarwal, A.: Spatial distribution of bedrock landslides over the landscape evolution in NW Himalayan River catchments, EGUsphere, https://doi.org/10.5194/egusphere-2022-533, 2022

29. Steirou, E., Gerlitz, L., Sun, X.,  Apel, H., Agarwal, A., Totz, S & Merz, M.: Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information. Sci Rep 12, 13514 (2022). https://doi.org/10.1038/s41598-022-16633-1

30. Deva Charan Jarajapu, MaheswaranRathinasamy, AnkitAgarwal, Axel Bronstert (2022) Design Flood Estimation using Extreme Gradient Boosting-based on Bayesian Optimization, Journal of Hydrology, 128341. https://doi.org/10.1016/j.jhydrol.2022.128341

31. Steirou, E., Gerlitz, L., Sun, X. et al. “Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information.” Sci Rep 12, 13514 (2022). https://doi.org/10.1038/s41598-022-16633-1

32. Abinesh Ganapathy, Ankit Agarwal (2022) Customized   sea-surface   temperature   indicators   linking   to   streamflow   at   different timescales. International Journal of Climatology. doi:10.1002/joc.7853.

2021

33. Karisma Yumnam., Ravi Kumar Guntu., Maheswaran Rathinasamy., Ankit Agarwal., 2021. Quantile-based Bayesian Model Averaging approach towards merging of precipitation products. Journal of Hydrology 127206. https://doi.org/10.1016/j.jhydrol.2021.127206

34. Pavan Kumar Yeditha, Tarun Pant, Maheswaran Rathinasamy, Ankit Agarwal; Multi-scale investigation on streamflow temporal variability and its connection to global climate indices for unregulated rivers in India. Journal of Water and Climate Change 2021; jwc2021189. doi: https://doi.org/10.2166/wcc.2021.189

35. Pavan Kumar Yeditha, Maheswaran Rathinasamy, Sai Sumanth Neelamsetty, Biswa Bhattacharya, Ankit Agarwal; Investigation of satellite rainfall-driven rainfall–runoff model using deep learning approaches in two different catchments in India. Journal of Hydroinformatics 2021; jh2021067. doi: https://doi.org/10.2166/hydro.2021.067

36. Kumar, S., Agarwal, A., Ganapathy, A. et al. Impact of climate change on stormwater drainage in urban areas. Stoch Environ Res Risk Assess (2021). https://doi.org/10.1007/s00477-021-02105-x

37. Yeditha, P. K., Pant, T., Rathinasamy, M., & Agarwal, A. (2021). Multi-scale investigation on streamflow temporal variability and its connection to global climate indices for unregulated rivers in India. Journal of Water and Climate Change. https://doi.org/10.2166/wcc.2021.189

38. Ravi Kumar Guntu and Ankit Agarwal*. “Disentangling increasing compound extremes at regional scale during Indian summer monsoon”, Scientific Reports, 11, 16447 (2021). https://doi.org/10.1038/s41598-021-95775-0  

39. Ravikumar K, Khosa R, Agarwal A* (2021) Metagame analysis of Cauvery River dispute incorporating interannual variability in virgin runoff potential of the basin. Eur Phys J B 94:172. https://doi.org/10.1140/epjb/s10051-021-00174-z

40. Durga Prasad Panday, Rakesh Khosa, Rathinasamy Maheswaran, K Ravikumar and Ankit Agarwal (2021). Game theoretic-based modelling of Krishna waters disputes Equilibrium solutions by hypergame analysis (2021). European Physics Journal-B. 10.1140/epjb/s10051-021-00135-6

41. 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. /10.1002/joc.7215

42. 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  https://doi.org/10.1140/epjb/s10051-021-00107-w

43. 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

44. 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

45. Agrawal P, Sinha A, Kumar S, Agarwal A, Banerjee A, Villuri VGK, Annavarapu CSR, Dwivedi R, Dera VVR, Sinha J, Pasupuleti S. Exploring Artificial Intelligence Techniques for Groundwater Quality Assessment. Water. 2021; 13(9):1172. https://doi.org/10.3390/w13091172

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

47. 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

2020

48. Setti, S.; Maheswaran, R.; Sridhar, V.; Barik, K.K.; Merz, B.; Agarwal, Ankit. Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling. Atmosphere 2020, 11, 1252. https://doi.org/10.3390/atmos11111252

49. 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

50. Guntu, Ravi Kumar, Rathinasamy Maheswaran, Ankit Agarwal, and Vijay P. Singh. "Accounting for temporal variability for improved precipitation regionalization based on self-organizing map coupled with information theory." Journal of Hydrology (2020): 125236. https://doi.org/10.1016/j.jhydrol.2020.125236

51. 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

52. 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

53. 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

54. Setti, S.; Maheswaran, R.; Sridhar, V.; Barik, K.K.; Merz, B.; Agarwal, A. Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling. Atmosphere 2020, 11, 1252.https://doi.org/10.3390/atmos11111252

55. Jun Meng, Jingfang Fan, Josef Ludescher, Agarwal Ankit, Xiaosong Chen, Armin Bunde, Jurgen Kurths, and Hans Joachim Schellnhuber (2020): Complexity based approach for El Niño magnitude forecasting before the spring predictability barrier (PNAS). https://www.pnas.org/content/early/2019/12/23/1917007117

56. 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://www.hydrol-earth-syst-sci.net/24/2235/2020/

2019

57. Roopam Shukla, Ankit Agarwal, Christoph Gronott, Kamna Sachdeva and PK Joshi (2019). Farmer typology to understand differentiated climate change adaptation in the Himalayas. Scientific Reports. https://www.nature.com/articles/s41598-019-56931-9

58. Rathinasamy, M., Agarwal, A., Sivakumar, B., Marwan, N., and Kurths, J. (2019): "Wavelet analysis of precipitation extremes over India and teleconnections to climate indices. Stochastic Environmental Research and Risk Assessment. https://doi.org/10.1007/s00477-019-01738-3

59. Kurths, J.*, Agarwal, A*., Shukla, R., Marwan, N., Maheswaran, R., Caesar, L., Krishnan, R., and Merz, B. (2019): Unraveling the spatial diversity of Indian precipitation teleconnections via nonlinear multi-scale approach. Nonlinear process in Geophysics. (* equally share the first authorship). https://www.nonlin-processes-geophys.net/26/251/2019/  (This article has been selected as the NPG paper of the month and released as a featured article in EGU blogpost.)

60. N.Ekhtiari, A. Agarwal, N. Marwan, R.V. Donner (2019): 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 (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.)

61. Agarwal, A., Caesar, L., Marwan, N., Maheswaran, R., Merz, B., and Kurths, J. (2019): Network-based identification and characterization of teleconnections on different time scales, Scientific Reports. https://www.nature.com/articles/s41598-019-45423-5

2018

62. Agarwal, A., Marwan, N., Maheswaran, R., Merz, B. and Kurths, J. (2018): Quantifying the roles of single stations within homogeneous regions using complex network analysis, Journal of Hydrology, doi:10.1016/j.jhydrol.2018.06.050, 2018 

63. Agarwal, A., Maheswaran, R., Marwan, N., Caesar, L., and Kurths, J. (2018): Wavelet-based multiscale similarity measure for complex networks, European Physics Journal-B, https://doi.org/10.1140/epjb/e2018-90460-6.

64. 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

65. 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

2017

66. Agarwal, A., Marwan, N., Rathinasamy, M., Merz, B. and Kurths, J. (2017): 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.

67. Ozturk, U., Marwan, N., Korup, O., Saito, H., Agarwal, A., Grossman, M. J., Zaiki, M., and Kurths, J. (2017): Complex networks for tracking extreme rainfall during typhoons, Chaos. https://aip.scitation.org/doi/pdf/10.1063/1.5004480

68. Shukla, R., Agarwal, A., Sachdeva, K., Kurths, J., and Joshi, P.K (2017)s: 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 

69. 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 patterns. arXiv preprint arXiv:1702.06568. 

70. 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

71. 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

2016

72. Agarwal, A., Maheswaran, R., Kurths, J., & Khosa, R. (2016). Wavelet Spectrum and self-organizing maps-based approach for hydrologic regionalization-a case study in the western United States. Water Resources Management, 30(12), 4399-4413. https://doi.org/10.1007/s11269-016-1428-1

73. Agarwal, A., Maheswaran, R., Sehgal, V., Khosa, R., Sivakumar, B., & Bernhofer, C. (2016). Hydrologic regionalization using wavelet-based multiscale entropy method. Journal of Hydrology, 538, 22-32. https://doi.org/10.1016/j.jhydrol.2016.03.023

2023

1. Gupta, H., Raghuvanshi, A.S., Agarwal, A. (2023). Multiday Extreme Precipitation Ranking and Association with Atmospheric Moisture Transport During Indian Summer Monsoon. In: Pandey, M., Gupta, A.K., Oliveto, G. (eds) River, Sediment and Hydrological Extremes: Causes, Impacts and Management. Disaster Resilience and Green Growth. Springer, Singapore. https://doi.org/10.1007/978-981-99-4811-6_16

2. Kumari, A., Raghuvanshi, A.S., Agarwal, A. (2023). Quantifying the Reliability of Reanalysis Precipitation Products Across India. In: Pandey, M., Gupta, A.K., Oliveto, G. (eds) River, Sediment and Hydrological Extremes: Causes, Impacts and Management. Disaster Resilience and Green Growth. Springer, Singapore. https://doi.org/10.1007/978-981-99-4811-6_6

2022

3. Agarwal, A,  Yuan, N., Kevin K.W. Cheung andShukla, R.,(Eds.). Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales. ISBN 978-3-0365-2952-3 (PDF). https://doi.org/10.3390/books978-3-0365-2952-3

2020

4. Guntu, Ravi Kumar, and Ankit Agarwal. "Investigation of Precipitation Variability and Extremes Using Information Theory." (2020). https://doi.org/10.3390/ecas2020-08115

2019

5. 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

6. 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

2024

1. Raghuvanshi, A. S. and Agarwal, A.: Deciphering the connections between extreme precipitation events, atmospheric moisture transport, and associated synoptic features over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1625, https://doi.org/10.5194/egusphere-egu24-1625, 2024.

2. Gaspar, T., M. Trigo, R., M. Ramos, A., Singh Raghuvanshi, A., Russo, A., M.M. Soares, P., Ferreira, T., and Agarwal, A.: Multi-day precipitation extremes ranking and their association with atmospheric moisture fluxes over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3951, https://doi.org/10.5194/egusphere-egu24-3951, 2024.

3. Raghuvanshi A. S.*, Agarwal A., (2024). Dynamic Features of 2023 Himachal Pradesh Floods: Multiscale Insights.  Blocking and Extreme Weather in a Changing Climate Workshop, March 18-20, 2024, Boulder, Colorado, USA. https://usclivar.org/abstract-blocking-2024/dynamic-features-2023-himachal-pradesh-floods.

4. Raghuvanshi A. S.*, Agarwal A., (2024). A Climatology of Cloudburst-Like Events in India. Roorkee Water Conclave (RWC) March 3-6, 2024, IIT Roorkee, India.

5. Badika, P.*, Raghuvanshi, A.S., & Agarwal, A.,  “Climate Change Impact Assessment on Hydrological response for Sustainable Water Management''. International Conference on Future of Water Resources (ICFWR 2024), 01/2024, IIT Roorkee, India.

6. Badika, P., Raghuvanshi, A. S., and Agarwal, A.: Climate Change Impact Assessment on Hydrological response of Tawa Basin for Sustainable Water Management , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-618, https://doi.org/10.5194/egusphere-egu24-618, 2024.

7. Badika, P.*, Choudhary, M. K., Nayak, T., Jaiswal, R., & Agarwal, A., 2023. Projected water availability in the Tawa River Basin in changing climate. Roorkee Water Conclave (RWC) March 3-6, 2024, IIT Roorkee, India

8. Dhote, P.R.*, Agarwal A. and Thakur, P.K., (2024). Remote sensing-based river bathymetry estimation and its hydrodynamic modeling implications. Roorkee Water Conclave (RWC) March 3-6, 2024, IIT Roorkee, India

9. Kulkarni, S.* and Agarwal, A.:(2024) The association between Arctic Sea Ice Extent and Indian Precipitation: A Quantitative Analysis. Roorkee Water Conclave (RWC) March 3-6, 2024, IIT Roorkee, India

10. Kulkarni, S*. and Agarwal, A.: (2024) The association between Arctic Sea Ice and Indian Precipitation: A Quantitative Analysis. Asia Oceania Geosciences Society (AOGS) from 23-28 June Pyeongchang-gun, Gangwon-do, South Korea.

11. Kulkarni, S*. and Agarwal, A.: Deciphering the Multiscale Association between Indian Precipitation-Arctic Teleconnections Using Wavelet Analysis.   European Geophysical Union General Assembly 2024, Vienna, Austria, 14-19 Apr 2024

2023

12. Ganapathy, Abinesh., Hannah, David M. and Agarwal, Ankit:  Hydrograph-based flood classification approach for flood frequency analysis, IUGG General Assembly 2023, Berlin, Germany, 11-20 July 2023, H09p-037, https://doi.org/10.57757/IUGG23-4674

13. Raghuvanshi, A. S., Agarwal, A. (2023): Linking Anomalous High Moisture Transport to Extreme Precipitation, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023). https://doi.org/10.57757/IUGG23-3955

14. Guntu, R.K, Merz, B., Agarwal, A: Modulators of compound extremes unravelled by Event coincidence analysis-based Complex networks, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG), 07/2023, Berlin, Germany. https://doi.org/10.57757/IUGG23-0020

15. Abinesh Ganapathy*, Ankit Agarwal. (2023). Multi-scale SST-Streamflow connectivity: A complex network approach. Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives. PIK Potsdam, Germany. (March 15-17 2023). https://nda23.pik-potsdam.de/?a=poster

16. Akash Singh Raghuvanshi*, Ankit Agarwal. (2023). Linking Anomalous High Moisture Transport to Extreme Precipitation. Nonlinear Data Analysis and Modeling: Advances, Applications, Perspectives. PIK Potsdam, Germany. (March 15-17 2023). https://nda23.pik-potsdam.de/?

17. Abinesh Ganapathy*, David M Hannah, Ankit Agarwal. (2023). Flood frequency analysis integrated with unprecedented flood samples and mixed probability distribution. EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4046. https://doi.org/10.5194/egusphere-egu23-4046 

18. Kulkarni, S. and Agarwal, A.: Unraveling the association between artic region and Indian summer monsoon – an empirical study , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2111, https://doi.org/10.5194/egusphere-egu23-2111

19. Ravi Kumar Guntu, Bruno Merz and Ankit Agarwal.  Challenges for assessing the risk of compound extremes.EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023. https://doi.org/10.5194/egusphere-egu23-154 

20. Ankit Agarwal*. Disentangling the characteristics and Drivers of Compound Drought and Hot Extremes. EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8830.

21. Singh Raghuvanshi, A. and Agarwal, A.: Linking Atmospheric Moisture Transport to Extreme Precipitation Events Associated with Floods over India, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-336, https://doi.org/10.5194/egusphere-egu23-336, 2023.

22. Kumari, A., Singh Raghuvanshi, A., and Agarwal, A.: Evaluation of different Precipitation Products with IMD dataset emphasizing on Hydrological Modelling., EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16849, https://doi.org/10.5194/egusphere-egu23-16849

23. Gupta, H., Singh Raghuvanshi, A., and Agarwal, A.: Moisture transport associated with multi-day precipitation events in India, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-781, https://doi.org/10.5194/egusphere-egu23-781

24. Guntu, R., Merz, B., Agarwal, A. (2023): Modulators of compound extremes unravelled by Event coincidence analysis-based Complex networks, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023). https://doi.org/10.57757/IUGG23-0020

25. Ganapathy, Abinesh., Hannah, David M. and Agarwal, Ankit:  Hydrograph-based flood classification approach for flood frequency analysis, IUGG General Assembly 2023, Berlin, Germany, 11-20 July 2023, H09p-037, https://doi.org/10.57757/IUGG23-4674

26. Dhote, P. R., Agarwal, A., Thakur, P. K. (2023): Performance evaluation of spaceborne altimetry and its implications for river water level dynamics assessment, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023). https://doi.org/10.57757/IUGG23-0652 

2022

27. Kulkarni, Sujata, Ugur Öztürk, Norbert Marwan, Juergen Kurths, Bruno Merz, and Ankit Agarwal. "COMPLEX NETWORKS IN HYDROLOGIC SCIENCES." In the Fall Meeting 2022. AGU, 2022.

28. Guntu, R.K, Merz, B and Agarwal, A; “Complex networks for quantifying modulators of compound extremes”. Water Security and Climate Change Conference," 12/2022, Bangkok. 

29. Guntu, R.K*, Merz, B and Agarwal, A; Effect of reference period on the likelihood of the compound dry and hot event. AGU Fall Meeting, 12/2022, Chicago.

30. Ganapathy, A*., Hannah, D.M., and Agarwal, A.; Flood Classification Based on Hydrograph Characteristics. AGU Fall Meeting, 12/2022, Chicago.

31. Dhote, P.R*., Agarwal, A., Thakur, P.K. Satellite radar and lidar altimeters observed seasonal variation in water level of Ganga River. AGU Fall Meeting, 12/2022, Chicago.

32. Kassa, T, Jain, M.K.*, Agarwal, A, and Yadav, B.K. Spatial Characteristics of Drought Propagation from Meteorological to Hydrological Drought over Ethiopia. Abstract ID: 1104086, Paper No. A46E-12. Presented at AGU Fall Meeting, Chicago IL, USA, December 12 – 16, 2022.

33. Ashish Manoj J*, Ravi Kumar Guntu, Ankit Agarwal: Disentangling soil moisture and precipitation coupling over India from a compound flood risk assessment perspective. Risk KAN workshop on Understanding and Modeling Complex Risks in Coupled Human-Environment Systems. 02/2022

34. Singhal, P*., Goel, N. K., Agarwal, A., Bronstert, A., and Vormoor, K.: Projection of flood seasonality Changes in the Himalayan Region River due to global warming, taking the Garhwal Himalayas river basin as an example, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5512, https://doi.org/10.5194/egusphere-egu22-5512, 2022.

35. Dhote, P. R.*, Moothedan, A. J., Thakur, P. K., and Agarwal, A.: Flood risk assessment framework for Himalayan river basin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-595, https://doi.org/10.5194/egusphere-egu22-595, 2022.

36. Moothedan, A. J.*, Dhote, P. R., Thakur, P. K., and Agarwal, A.: Projection of future pluvial flood events over Himalayan river basin under CMIP6 climate data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-438, https://doi.org/10.5194/egusphere-egu22-438, 2022.

37. Guntu, R.K* and Agarwal, A.; Disentanglement of compound dry and hot extremes over the homogenous regions of India using a complex network-based multivariate standardized index Approach. Roorkee Water Conclave (RWC) 2022, IIT Roorkee, India

38. Guntu, R.K*, Merz, B., and Agarwal, A: Understanding and quantifying potential drivers of compound extremes: A complex network based on multiscale entropy approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-215, https://doi.org/10.5194/egusphere-egu22-215, 2022

39. Manoj J, Ashish*, Pérez Ciria, T., Chiogna, G., Salzmann, N., and Agarwal, Ankit: Investigating Spatial Patterns And Characteristics Of Preconditioned Compound Flooding Over Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10435, https://doi.org/10.5194/egusphere-egu22-10435, 2022.

40. Ganapathy, Abinesh* and Agarwal, Ankit: Event clustering approach for flood frequency analysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-93, https://doi.org/10.5194/egusphere-egu22-93, 2022.

41. Singh, K. N*., Nocke, T., Shukla, R., Joshi, P. K., Agarwal, Ankit., and Kurths, J.: Quantifying emerging patterns of greening and browning in the Himalayan region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8654, https://doi.org/10.5194/egusphere-egu22-8654, 2022.

42. Ashish Manoj J*, Ravi Kumar Guntu, Ankit Agarwal: Investigating Spatiotemporal Patterns of Soil Moisture - Precipitation Dependence over India. in Hydrocomplexity: Addressing Challenges in Hydrology from a Holistic Perspective -  Online Discussion Session. AGU Frontiers in Hydrology Meeting 2022. 22 June 2022. https://doi.org/10.1002/essoar.10511686.1 

43. Ankit Agarwal*. Multiscale approaches in forecasting extreme floods and their global connections.  IAHS-AISH Scientific Assembly 2022. Montpellier, France on 03rd June 2022.

44. Singh, K. N., Nocke, T., Shukla, R., Joshi, P. K., Agarwal, A., and Kurths, J.: Quantifying emerging patterns of greening and browning in the Himalayan region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8654, https://doi.org/10.5194/egusphere-egu22-8654, 2022.

2021

45. Guntu, R.K* and Agarwal, A.; Disentangling increasing compound extremes at regional scale during Indian Summer Monsoon. AGU 2021 Fall Meeting. https://doi.org/10.1002/essoar.10508931.2

46. Guntu, R.K* and Agarwal, A.; Assessment of compound dry and hot extremes over India using a copula-based multivariate standardized index. AGU 2021 Fall Meeting. https://doi.org/10.1002/essoar.10508932.2

47. Yumnam, K*., Guntu, R.K., Agarwal, A., and Maheswaran, R.; Quantile-based Bayesian Model Averaging approach towards merging of rainfall products. AGU 2021 Fall Meeting. https://doi.org/10.1002/essoar.10509240.1

48. Gadhawe, M*., Guntu, R.K, Banerjee, A., Marwan, N., and Agarwal, A.; A complex network approach to study the extreme precipitation patterns in a river basin. AGU 2021 Fall Meeting. https://doi.org/10.1002/essoar.10509273.2

49. Abinesh Ganapathy*., Ravikumar Guntu., Ugur Ozturk., Bruno Merz., Ankit Agarwal. 2021. Unraveling multiscale relationship between German streamflow and global SST using climate networks. NG52A: Scales, Scaling, Symmetries, and Complexity: From Theory to Big Data, from Urban Systems to Climate and Pandemics I Oral. AGU 2021 (17.12.2021). https://doi.org/10.1002/essoar.10508881.1

50. Shivam Rawat*, Abinesh Ganapathy, Ravi Kumar Guntu, Ankit Agarwal (2021).Drought Characterization using GRACE-based drought index over Indian sub-continent| poster.AGU 2021 (13.12.2021) https://doi.org/10.1002/essoar.10509305.1

51. Ashish Manoj J*, Ravi Kumar Guntu, Ankit Agarwal: Understanding Soil Moisture – Precipitation (SM-P) Coupling over India from a Compound Flood Risk Assessment Perspective https://doi.org/10.1002/essoar.10508965.1

52. Ashish Manoj J*, Ravi Kumar Guntu, Ankit Agarwal: Can Soil Moisture Anomalies Trigger Extreme Precipitation Events over India? https://doi.org/10.1002/essoar.10509317.1

53. Ashish Manoj J*, Ravi Kumar Guntu, Ankit Agarwal Characterisation of Compound Soil Moisture - Precipitation Events Over India, WCRP Workshop on Extremes in Climate Prediction Ensembles (ExCPEns), Hosted by  APEC Climate Center (APCC), Institute for Basic Science (IBS) Center for Climate Physics (ICCP), Pusan National University.

54. Ravi Kumar, Guntu* and Ankit Agarwal: Disentangling increasing compound extremes at regional scale during Indian Summer Monsoon. 2nd International Conference on Natural Hazards and Risks in a Changing World; 10/2021

55. Ravi Kumar, Guntu* and Ankit Agarwal: Accounting for temporal variability for improved precipitation regionalization based on self-Organizing map coupled with information theory. 2nd International Conference on Natural Hazards and Risks in a Changing World; 10/2021

56. Abinesh Ganapathy*, Ravi Kumar Guntu, Ugur Ozturk, Bruno Merz, Ankit Agarwal."Multi-timescale SST-Streamflow connectivity: A complex network approach" poster presentation at "WCRP workshop on the attribution of multi-annual to decadal changes in the climate system" held online from September 22-24, 2021. https://wcrp-epesc.sciencesconf.org/data/363896.pdf

57. Abinesh, Ganapathy*, Ravi Kumar, G., Ugur, O., Bruno, M., Ankit, A., (2021). Multiscale SST streamflow connectivity via wavelet complex network techniques. NatRiskChange 2021. (05- 06 Oct, 2021). 

58. Ashish Manoj J*, Ravi Kumar Guntu, Ankit Agarwal. “Investigating Compound Soil Moisture – Precipitation Coupling Over India”, oral presentation at World Climate Research Program Workshop on Attribution of Multi-annual to Decadal Changes in the Climate System, 22-24 September 2021 https://wcrp-epesc.sciencesconf.org/data/363768.pdf

59. Ravi Kumar, Guntu* and Ankit Agarwal: Wavelet Entropy Energy Measure (WEEM): A multiscale measure to grade a geophysical system's predictability. European Geophysical Union; 04/2021 https://doi.org/10.5194/egusphere-egu21-703

60. Abinesh, G.*, Ravi Kumar, Guntu, Ugur Ozturk, Bruno Merz, and Ankit Agarwal: Merging of satellite precipitation products: Network-based approach to unravel sea-surface temperature and streamflow connectivity at different timescales. European Geophysical Union; 04/2021. https://doi.org/10.5194/egusphere-egu21-4670

61. Karisma, Y.*, Ravi Kumar, Guntu, Ankit Agarwal and Maheswaran Rathinasamy: Merging of satellite precipitation products: A quantile based Bayesian model averaging approach. European Geophysical Union; 04/2021. https://doi.org/10.5194/egusphere-egu21-3024  

62. Mayuri, AR.G*, Ravi Kumar, Guntu and Ankit Agarwal: Network-based approach to explore basin network comparing observed and satellite dataset. European Geophysical Union; 04/2021. https://doi.org/10.5194/egusphere-egu21-4840

63. Ravi Kumar, Guntu*, Ankit Agarwal and Bramha Dutt Vishwakarma: Unravelling teleconnections of terrestrial water storage via complex networks. IAG-ICCC 2021 workshop. 03/2021. https://cloud.hcu-hamburg.de/nextcloud/index.php/s/wNYqwxc3ooWBPLS#pdfviewer

64. Guntu, R.K.*, Agarwal, A. 2021. Space-time framework for precipitation regionalization based on neural networks coupled with information entropy, 6th IAHR Europe Congress, Poland, February 15-18, 2021. In: Kalinowska, M; Rowinski, P; Okruszko, T; Nones, M (Eds.), 6th IAHR Europe Congress Abstract Book, 542-543; ISBN: 978-83-66847-01-9      link to Abstract: https://iahr2020.pl/wp-content/uploads/2021/02/Book-of-Abstracts-15-02-2021.pdf

65. Guntu, R.K.*, Agarwal, A. 2021. Concurrent dry and hot events during the Indian summer monsoon and its linkages to ENSO, Workshop on Compound Weather and Climate Events, University of Bern, Switzerland, 12 - 15 January 2021 link to paper: https://www.oeschger.unibe.ch/unibe/portal/fak_naturwis/g_dept_kzen/d_c_oeschger/content/e54522/e54528/e118437/e920856/e920874/e920877/CompoundEvents2021_Abstracts_eng.pdf

66. Dhote, P. R., Bansal, J., Garg, V., Thakur, P.K., Agarwal, A., 2021. Potential of Multi-mission Satellite Altimetry Observations and Hydrodynamic Model to Establish Virtual Gauging Network in Sparsely Gauged Basin. AGU 2021 Fall meeting. Earth and Space Science Open Archive, pages13, https://doi.org/10.1002/essoar.10509744.1

67. Tarun Pant*, Pavan kumar Yedith, Ankit Agarwal and Maheswaran Rathinasamy 2021. Disentangling spatiotemporal characteristics of six different unregulated streamflow stations in India. EGUGeneral Assembly. https://doi.org/10.5194/egusphere-egu21-7362,2021  

68. Yeditha Pavan Kumar*, Rathinasamy Maheswaran, Biswa Bhattacharya and Ankit Agarwal. Rainfall-runoff modelling for two Indian catchments with satellite rainfall products using Machine learning approaches. A merican Geophysical Union; 12/2021

69. Yeditha Pavan Kumar*, Rathinasamy Maheswaran, Bellie Shivakumar and Ankit Agarwal. Wavelet based hybrid models for climatic downscaling of daily precipitation. A merican Geophysical Union; 12/2021

2020

70. Guntu, R.K.*, Agarwal, A. 2020. Spatial extent of concurrent extremes over India and its teleconnection to climate indices. AGU 2020 Fall Meeting. https://doi.org/10.1002/essoar.10505419.1

71. Yumnam, K.*, Guntu, R.K., Kumar, A., Agarwal, A. 2020. Emerging Spatiotemporal Patterns of Trends of Extremes in Indian Summer Monsoon. AGU 2020 Fall Meeting. https://doi.org/10.1002/essoar.10505423.1

72. Saurav Raj*, Ankit Agarwal. Accounting magnitude, spatial extent and duration for ranking of extreme precipitation events in Indian Western Himalayan. American Geophysical Union; 12/2020. agu2020fallmeeting-agu.ipostersessions.com/Default.aspx?s=9D-99-83-35-99-B6-4D-36-E0-E1-60-BD-01-FF-37-25

73. Ankit Agarwal*, Norbert Marwan, Rathinasamy Maheswaran, Ugur Ozturk, Jürgen Kurths, and Bruno Merz . Optimal Design of Hydrometric Station Networks Based on Complex Network Analysis. American Geophysical Union; 12/2020. 

74. Ravi Kumar, Guntu* and  Ankit Agarwal (2020). Standardized Variability Index (SVI): A multiscale index to assess the variability of precipitation. JpGU-AGU Joint Meeting 2020, Chiba, Japan. https://doi.org/10.1002/essoar.10503941.1 

1. Ankit Agarwal. Quantifying the Roles of Single Rain Gauges within Homogeneous Regions of a Rainfall Network. Scientific Trends 2018. https://sciencetrends.com/quantifying-the-roles-of-single-rain-gauges-within-homogeneous-regions-of-a-rainfall-network/

2. Roopam Shukla and Ankit Agarwal. Do Perceptions of Climate Change and its Impacts Differ Among Farmers in Indian Western Himalayas? Scientific Trends 2019.https://sciencetrends.com/do-perceptions-of-climate-change-and-its-impacts-differ-among-farmers-in-indian-western-himalayas/

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/

1. Agarwal, A., B. Boessenkool, M. Fischer, I. Hahn, L. Köhn, J. Lauden, 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. https://gfzpublic.gfz-potsdam.de/pubman/faces/ViewItemFullPage.jsp?itemId=item_1659896_3

2. Ankit Agarwal. "Unravelling spatio-temporal climatic patterns using multi-scale complex network." Ph.D. diss., University of Potsdam, Potsdam, Germany, 2018. DOI: 10.25932/publishup-42395

3. 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