List of Publications (in reverse chronological order)

Summary: Citations - 2658; h-index -30; i10-index - 65 (Google scholar)

Citations - 1890; h-index -25 (Scopus)

(For latest update: Google Scholar, Scopus)

 

Books: 02

Book Chapters: 18

Refereed Journals: 100

Patent/Copyright: 01

Technical Reports: 07

Conferences and Symposia: 86

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Books:

  1. Maity R., (2022), Statistical Methods in Hydrology and Hydroclimatology, 2nd Edition, Springer, Springer Nature Singapore Pte Ltd., pp. 436, e-Book ISBN: 978-981-16-5517-3, Hard Cover ISBN: 978-981-16-5516-6, https://doi.org/10.1007/978-981-16-5517-3. Online link, Coverpage.

First Edition details:

Maity R., (2018), Statistical Methods in Hydrology and Hydroclimatology, Springer, Copyright 2018 Springer Nature Singapore Pte Ltd., pp. 444, e-Book ISBN: 978-981-10-8779-0, Hard Cover ISBN: 978-981-10-8778-3, DOI: 10.1007/978-981-10-8779-0. Online link, Coverpage.

  1. Maity R., and D. Nagesh Kumar, (2014), Hydroclimatic Teleconnection: Indian Perspective, Scholar Press, Copyright 2014 OmniScriptum Gmbh & Co. KG, Heinrich-Bocking-Str. 6-8, 66121, Saarbrucken, Germany, ISBN: 978-3-639-66387-7. Online link, Cover page.

 

Book Chapters:

  1. Maity R., (2024), Hydrological alterations under climate change: Global-scale challenges and opportunities for adaptation and sustainable development, Chapter 5, In Civil Engineering Innovations for Sustainable Communities with Net Zero Targets, CRC Press, Taylor & Francis group, eBook ISBN: 9781032686899, pp. 102-128, https://doi.org/10.1201/9781032686899-7.
  2. Suman M., and R. Maity (2024), Basin-scale agricultural drought across India under changing climate (Chapter 21), In S. C. Pal, S. S. Roy, A. Saha, M. Abioui (Eds.) Water Resources Monitoring, Management, and Sustainability (Application of Geostatistics and Geospatial Modeling), Elsevier, pp. 503-528, ISBN: 978-0-443-23665-5, https://doi.org/10.1016/B978-0-443-23665-5.00021-1.
  3. Srivastava A., R. Maity and V R Desai (2023), Investigating Spatio-Temporal Trends and Anomalies in Long-Term Meteorological Variables to Determine If Maharashtra is an Emerging Warming State in India. In: Sreekeshava, K.S., Kolathayar, S., Vinod Chandra Menon, N. (eds) Civil Engineering for Multi-Hazard Risk Reduction. IACESD 2023. Lecture Notes in Civil Engineering, vol 457. Springer, Singapore, pp. 281-323. https://doi.org/10.1007/978-981-99-9610-0_25.
  4. Palagiri H., M. Pal M., R. Maity (2023). Drought Monitoring Using Satellite Soil Moisture Data Over Godavari Basin, India. In: Timbadiya, P.V., Patel, P.L., Singh, V.P., Mirajkar, A.B. (eds) Geospatial and Soft Computing Techniques. HYDRO 2021. Lecture Notes in Civil Engineering, vol 339. Springer, Singapore, pp. 1-13, https://doi.org/10.1007/978-981-99-1901-7_1.
  5. Khan M.I., and R. Maity (2023). Multi-step Ahead Forecasting of Streamflow Using Deep Learning-Based LSTM Approach. In: Timbadiya, P.V., Patel, P.L., Singh, V.P., Mirajkar, A.B. (eds) Geospatial and Soft Computing Techniques. HYDRO 2021. Lecture Notes in Civil Engineering, vol 339. Springer, Singapore, pp. 399-411, https://doi.org/10.1007/978-981-99-1901-7_32.
  6. Dutta R., and R. Maity, (2023), Temporal Networks: A New Approach to Model Non-stationary Hydroclimatic Processes with a Demonstration for Soil Moisture Prediction. In: Timbadiya, P.V., Singh, V.P., Sharma, P.J. (eds) Climate Change Impact on Water Resources. HYDRO 2021. Lecture Notes in Civil Engineering, vol 313. Springer, Singapore. https://doi.org/10.1007/978-981-19-8524-9_1.
  7. Khan M.I., S. Sarkar, and R. Maity (2022), Artificial Intelligence/Machine Learning Techniques in Hydroclimatology: A Demonstration of Deep Learning for Future Assessment of Streamflow under Climate Change, In Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence, (ISBN: 978-0-323-99714-0) Edited by A.L. Srivastav, Elsevier, Chapter 12, pp. 247-273, https://doi.org/10.1016/B978-0-323-99714-0.00015-7.
  8. Srivastava A., S. Jain, R. Maity, V R Desai (2022), Demystifying Artificial Intelligence amidst Sustainable Agricultural Water Management. In Water Resource Modeling and Computational Technologies. Edited by Zakwan M., Wahid A., Niazkar M., Chatterjee U., Current Directions in Water Scarcity Book Series, Elsevier, Vol 7, pp. 17-35, https://doi.org/10.1016/B978-0-323-91910-4.00002-9.
  9. Srivastava A., R. Maity, V R Desai (2022), Assessing Global-scale Synergy between Adaptation, Mitigation and Sustainable Development for projected Climate Change. In Ecological Footprints of Climate Change: Adaptive Approaches and Sustainability.  (ISBN: ISBN: 978-3-031-15500-0), Edited by Chatterjee U., Akanwa A., Kumar S., Singh S.K., Dutta Roy A., Springer Climate, Springer, Cham, pp. 31-61, https://doi.org/10.1007/978-3-031-15501-7_2.
  10. Pichuka S., and R. Maity, (2021), Time-Varying Downscaling Model (TVDM) and its benefit to capture extreme rainfall, In Climate Change Impacts on Water Resources, Water Science and Technology Library, vol 98, Edited by R. Jha, V.P. Singh, V. Singh, L.B. Roy and R. Thendiyath, Springer Nature, Switzerland, pp. 79-89, https://doi.org/10.1007/978-3-030-64202-0_8.
  11. Dutta R., and R. Maity, (2021), Benefit of time-varying models developed using graphical modeling approach for probabilistic prediction of monthly streamflow, In Climate Change Impacts on Water Resources, Water Science and Technology Library, vol 98, Edited by R. Jha, V.P. Singh, V. Singh, L.B. Roy and R. Thendiyath, Springer Nature, Switzerland, pp. 115-126, https://doi.org/10.1007/978-3-030-64202-0_11.
  12. Maity R., and M. Suman, (2019), Predictability of hydrological systems using the wavelet transformation: Application to drought prediction, In Hydrology in a Changing World: Challenges in Modeling, Edited by S. Singh and C.T. Dhanya, Springer Water, pp. 109-137, https://doi.org/10.1007/978-3-030-02197-9_5. Article link. Article (1.3 MB).
  13. Maity R., and P. P. Bhagwat, (2017), Hydro-Climatic Conceptual Streamflow Modelling, Chapter 10 In Sustainable Holistic Water Resources Management in a Changing Climate, Edited by K. Srinivasa Raju and A. Vasan, M/S Jain Brothers, New Delhi, pp. 179-198. Article (1.3 MB).
  14. Chanda K., and R. Maity, (2018), Global Climate Pattern Behind Hydrological Extremes in Central India, In Climate Change Impact, Edited by V.P. Singh et al., Springer Nature Singapore, pp. 71-89, https://doi.org/10.1007/978-981-10-5714-4_6, Article (0.7 MB).
  15. Maity R., and K. Chanda, (2015), Potential of Genetic Programming in Hydroclimatic Prediction of Droughts: An Indian Perspective, In Handbook of Genetic Programming Applications, Edited by A. H. Gandomi, A. H. Alavi, and C. Ryan, Springer, pp. 381-398, https://doi.org/10.1007/978-3-319-20883-1_15, Article (1.0 MB)
  16. Maity R., (2014), Hydroclimatic teleconnection in the context of climate forcing on hydrologic variables: an Indian perspective, In the Emerging Leaders Report, Vol 2, Australia India Institute, Australia, pp. 46-55.
  17. Nagesh Kumar D., and R. Maity, (2008), Use of Climate Variables for Streamflow Prediction, In Advances in Water Quality & Management (Chapter 15), Edited by Sudhakar M. Rao, Monto Mani and N.H. Ravindranath, Research Publishing Services, Singapore, pp. 292-300.
  18. Nagesh Kumar D., and R. Maity, (2006), An analysis of rainfall in Orissa with sea surface temperature anomaly by similarity search technique, In Prediction in Ungauged Basins for Sustainable Watershed Management, Edited by Dr. K. Srinivasa Raju, M/s Jain Brothers, New Delhi, pp. 27 - 40.

 

Patent/Copyright:

  1. HydroClimatic Conceptual Streamflow (HCCS) Model, Copyright Office, Government of India, Registration no. L-61483/2015 dated March 19, 2015. Link to HCCS Model

 

Refereed Journals:

2024

1.      Sarkar S., and R. Maity, (2024), Towards the Development of a Comprehensive Heatwave Proneness Index and Identification of Hotspots across Indian Mainland, Journal of Geophysical Research - Atmospheres, AGU, DOI:10.1029/2024JD041775.

  1. Maity R., A. Srivastava, S. Sarkar, and M. I. Khan (2024), Revolutionizing the Future of Hydrological Science: Impact of Machine Learning and Deep Learning amidst Emerging Explainable AI and Transfer Learning, Applied Computing and Geosciences, Elsevier, 24:100206, https://doi.org/10.1016/j.acags.2024.100206.
  2. Khan M.I., and R. Maity, (2024), Development of a Long-Range Hydrological Drought Prediction Framework (HDPF) using Deep Learning, Water Resources Management, Springer, Springer, 38, 1497-1509, https://doi.org/10.1007/s11269-024-03735-w. Article (2.5 MB)
  3. Sarkar S., and R. Maity, (2024), Unveiling Climate Change-induced Temperature-based Hotspots across India though Multi-model Future Analysis from CMIP6, International Journal of Climatology, Royal Meteorological Society (RMetS), 44(2), 627-646, https://doi.org/10.1002/joc.8348. Article (1.4 MB)
  4. Mahmoudi P., R. Maity, S. M. A. Jahanshahi, K. Chanda, (2024), Changing Changing Pattern of Drought Proneness Across Iran, Iranian Journal of Science and Technology, Transactions of Civil Engineering, Springer, 48, 4709-4729, https://doi.org/10.1007/s40996-024-01579-3.
  5. Naren A., and R. Maity, (2024), Coastal Vulnerability Considering Combined Effect of Tropical Cyclones and Future Sea Level Rise, Journal of Coastal Conservation, Springer, 28:56. https://doi.org/10.1007/s11852-024-01055-0.
  6. Dash, S., T.U. Sreya and R. Maity (2024), Changes in the Spatial Variability of Extreme Precipitation Characteristics across Peninsular India, Discover Geoscience, Springer, 2:17, https://doi.org/10.1007/s44288-024-00019-z.

2023

  1. Srivastava A., and R. Maity (2023), Unveiling an Environmental Drought Index and its Applicability in the Perspective of Drought Recognition amidst Climate Change, Journal of Hydrology, Elsevier, 627:130462, https://doi.org/10.1016/j.jhydrol.2023.130462. Article (5.5 MB).
  2. Srivastava A., and R. Maity (2023), Assessing the Potential of AI-ML in Urban Climate Change Adaptation and Sustainable Development, Feature Article in the Special Issue Artificial Intelligence and Machine Learning (AI/ML) in Climate Change Impacts Analysis, Sustainability, MDPI, 15:16461, https://doi.org/10.3390/su152316461. Article (1.7 MB)
  3. Dash, S., R. Maity, and H. Kunstmann (2023), Population Exposure to Compound Precipitation-Temperature Extremes in the Past and Future Climate across India, Journal of Hydrometeorology, American Meteorological Society, 24(12), 2409-2430, https://doi.org/10.1175/JHM-D-22-0238.1.
  4. Naqash T.B., M. Ahangar and R. Maity, (2023), Impacts of Hydrometeorological Factors on Discharge Simulation in the North West Himalayas: A SUFI-2 Algorithm-driven Investigation using the SWAT Model, Environmental Monitoring and Assessment, Springer, 195:1366, https://doi.org/10.1007/s10661-023-11916-0. Article (7.2 MB).
  5. Maity S.S., R. P. Shaw and R. Maity, (2023), Climate Change may cause Oasification or Desertification both: An analysis based on the Spatio-Temporal change in Aridity across India, Theoretical and Applied Climatology, Springer, 155, 1167-1184, https://doi.org/10.1007/s00704-023-04686-9. Article (7.2 MB).
  6. Paul A. R., and R. Maity, (2023), Future projection of climate extremes across contiguous northeast India and Bangladesh, Scientific Reports, Nature Publishing Group, 13:15616, https://doi.org/10.1038/s41598-023-42360-2. Article (2.7 MB).
  7. Kumar, S., A. Srivastava, and R. Maity (2023), Modeling Climate Change Impacts on Vector-borne Disease Using Machine Learning Models: Case Study of Visceral leishmaniasis (Kala-azar) from Indian State of Bihar, Expert Systems with Applications, Elsevier, 237:121490, https://doi.org/10.1016/j.eswa.2023.121490. Article (6.9 MB).
  8. Sarkar S., S. S Maity, and R. Maity (2023), Precipitation-based Climate Change Hotspots across India through a Multi-model Assessment from CMIP6, Journal of Hydrology, Elsevier, 623:129805, https://doi.org/10.1016/j.jhydrol.2023.129805. Article (6.9 MB).
  9. Dash S. S, and R. Maity (2023), Effect of climate change on soil erosion indicates a dominance of rainfall over LULC changes, Journal of Hydrology: Regional Studies, Elsevier, 47, 101373, https://doi.org/10.1016/j.ejrh.2023.101373. Article link, Article (4.9 MB)
  10. Dash S., and R. Maity (2023), Unfolding unique features of precipitation-temperature scaling across India, Atmospheric Research, Elsevier, 284, 10660, https://doi.org/10.1016/j.atmosres.2022.106601. Article (4.8 MB)
  11. Paul A. R., and R. Maity, (2023), Uniqueness of India’s Northeast with respect to Climate Change Impact: An Assessment of Streamflow Variation in Gomati River Basin, Journal of Water and Climate Change, IWA Publishing, 14(3): 860-877, https://doi.org/10.2166/wcc.2023.442.

2022

  1. Sarkar S., and R. Maity (2022), Future characteristics of extreme precipitation indicate the dominance of frequency over intensity: A multi-model assessment from CMIP6 across India, Journal of Geophysical Research - Atmospheres, American Geophysical Union, 127, e2021JD035539, https://doi.org/10.1029/2021JD035539. Article (4.8 MB)
  2. Maity S.S., and R. Maity (2022), Changing Pattern of Intensity-Duration-Frequency Relationship of Precipitation due to Climate Change, Water Resources Management, Springer, 36, 5371-5399, https://doi.org/10.1007/s11269-022-03313-y. Article (5.8 MB)
  3. Naqash T.B., M. Ahangar, R. Maity (2022), Multi-site Hydrometeorological Simulation of Streamflow for Upper Jhelum Basin in Northwest Himalayas using HEC-HMS Soil Moisture Accounting Algorithm, Modeling Earth Systems and Environment, Springer, 9, 431-455, https://doi.org/10.1007/s40808-022-01510-7.
  4. Khan M.I., and R. Maity (2022), Hybrid Deep Learning Approach for Multi-step-ahead Prediction for Daily Maximum Temperature and Heatwaves, Theoretical and Applied Climatology, Springer, 149, 945-963, https://doi.org/10.1007/s00704-022-04103-7. Article (4.8 MB)
  5. Dutta R., and R. Maity (2022), Value addition in Coupled Model Intercomparison Project phase 6 over phase 5: Global perspectives of Precipitation, Temperature and Soil Moisture fields, Acta Geophysica, Springer, 70, 1401-1415, https://doi.org/10.1007/s11600-022-00793-9. Article (2.0 MB).
  6. Suman M., R. Maity, and H. Kunstmann (2022), Precipitation of Mainland India: Copula-based Bias-corrected Daily CORDEX Climate Data for both Mean and Extreme Values, Geoscience Data Journal, Royal Meteorological Society (RMetS), 9, 58-73, https://doi.org/10.1002/gdj3.118. Article (5.6 MB).
  7. Dutta R., K. Chanda and R. Maity (2022), Future of Solar Energy Potential in a Changing Climate across the World: A CMIP6 Multi-Model Ensemble Analysis, Renewable Energy, Elsevier, 188, 819-829, https://doi.org/10.1016/j.renene.2022.02.023. Article (6.3 MB).
  8. Dutta R., R. Maity, and P. Patel (2022), Short and Medium Range Forecast of Soil Moisture for the Different Climatic Regions of India Using Temporal Networks, Water Resources Management, Springer, 36, 235-251, https://doi.org/10.1007/s11269-021-03025-9. Article (1.9 MB)

2021

  1. Mahmoudi P., R. Maity, S. M. A. Jahanshahi, K. Chanda (2021), Changing spectral patterns of long-term drought propensity in Iran through reliability-resilience- vulnerability (RRV) based drought management index, International Journal of Climatology, Royal Meteorological Society (RMetS), 42(8), 4147-4163, https://doi.org/10.1002/joc.7454. Article (1.0 MB).
  2. Dutta R., and R. Maity, (2021), Time-varying network-based approach for capturing hydrological extremes under climate change with application on drought, Journal of Hydrology, Elsevier, 603:126958, https://doi.org/10.1016/j.jhydrol.2021.126958. Article (4.5 MB)
  3. Dash S. and R. Maity (2021), Revealing alarming changes in spatial coverage of joint hot and wet extremes across India, Scientific Reports, Nature Publishing Group, 11:18031, https://doi.org/10.1038/s41598-021-97601-z, Article (3.3 MB)
  4. Pal M. and R. Maity (2021), Assimilation of Remote Sensing based Surface Soil Moisture to Develop a Spatially Varying Vertical Soil Moisture Profile database for entire Indian Mainland, Journal of Hydrology, Elsevier, 601:126807, https://doi.org/10.1016/j.jhydrol.2021.126807. Article (5.8 MB)
  5. Pichuka S., S. S. Maity and R. Maity, (2021), Benefit of time-varying downscaling model for the assessment of urban temperature rise, Modeling Earth Systems and Environment, Springer, 8, 2431-2447, https://doi.org/10.1007/s40808-021-01239-9. Article link (1.6 MB)
  6. Dutta R., N. Sunanda, A. Patra and R. Maity, (2021), Long-term Simulation of Daily Rainfall across India: Performance of Cumulus Convection Schemes in Regional Climate Model during Southwest and Northeast Monsoon, Atmospheric Research, Elsevier, 259:105675, https://doi.org/10.1016/j.atmosres.2021.105675. Article link (1.8 MB)
  7. Sarkar S., and R. Maity, (2020), Global climate shift in 1970s causes a significant worldwide increase in precipitation extremes, Scientific Reports, Nature Publishing Group, 11:11574, https://doi.org/10.1038/s41598-021-90854-8. Article link (1.8 MB)
  8. Maity R., M.I. Khan, S. Sarkar, R. Dutta, S. S. Maity, M. Pal and K Chanda, (2021), Potential of Deep Learning in Drought Assessment by Extracting Information from Hydrometeorological Precursors, Journal of Water and Climate Change, IWA Publishing, 12(6), 2774-2796, https://doi.org/10.2166/wcc.2021.062. Article link (1.6 MB)
  9. Suman M. and R. Maity (2021), Assessment of basin-wise future agricultural drought status across India under changing climate, Journal of Water and Climate Change, IWA Publishing, 12(6), 2400-2421, https://doi.org/10.2166/wcc.2021.369. Article (1.3 MB)

2020

  1. Dutta R., and R. Maity, (2020), Temporal networks based approach for non-stationary hydroclimatic modelling and its demonstration with streamflow prediction, Water Resources Research, American Geophysical Union (AGU), 56, e2020WR027086, doi: 10.1029/2020WR027086. Article link. Article (3.9 MB)
  2. Dutta R., and R. Maity, (2020), Identification of potential causal variables for statistical downscaling models: effectiveness of graphical modelling approach, Theoretical and Applied Climatology, Springer, Springer, 142, 1255-1269, https://doi.org/10.1007/s00704-020-03372-4. Article link. Article (2.7 MB)

38.  Pichuka S., and R. Maity, (2020), How far the CORDEX high-resolution data represents observed precipitation: An analysis across Indian mainland, Theoretical and Applied Climatology, Springer, 142, 899-910, https://doi.org/10.1007/s00704-020-03355-5. Article link. Article (3.7 MB).

39.  Suman M. and R. Maity (2020), Southward shift of precipitation extremes over south Asia: Evidences from CORDEX data, Scientific Reports, Nature Publishing Group, 10:6452, doi: 10.1038/s41598-020-63571-x. Article link. Article (3.4 MB).

40.  Pichuka S., and R. Maity, (2020), Assessment of Extreme Precipitation in Future through Time-Invariant and Time-Varying Downscaling Approaches, Water Resources Management, Springer, 34(5), 1809-1826, doi: 10.1007/s11269-020-02531-6. Article link. Article (1.3 MB).

41.  Sarkar S., and R. Maity, (2020), High-resolution One-day Probable Maximum Precipitation dataset across India and its Future-projected Changes over India, Data in Brief, Elsevier, 30:105525, doi: 10.1016/j.dib.2020.105525. Article link. Article (0.7 MB).

42.  Sarkar S., and R. Maity, (2020), Estimation of Probable Maximum Precipitation in the context of climate change, MethodsX, Elsevier, 7, doi: 10.1016/j.mex.2020.100904. Article link. Article (0.9 MB)

43.  Dutta R., and R. Maity, (2020), Spatial variation in long-lead predictability of summer monsoon rainfall using a time-varying model and global climatic indices, International Journal of Climatology, Royal Meteorological Society (RMetS), 40(14), 5925-5940, https://doi.org/10.1002/joc.6556. Article link. Article (4.3 MB).

  1. Khan M.I. and R. Maity (2020), Hybrid deep learning approach for multi-step-ahead daily rainfall prediction using GCM simulations, IEEE Access, IEEE, 8(1), 52774-52784, https://doi.org/10.1109/ACCESS.2020.2980977. Article link. Article (1.7 MB).

45.  Sarkar S., and R. Maity, (2020), Increase in Probable Maximum Precipitation in a Changing Climate over India, Journal of Hydrology, Elsevier, 585, 10.1016/j.jhydrol.2020.124806. Article link. Article (1.8 MB).

46.  Maity R., K. Chanda, R. Dutta, J.V. Ratnam, M. Nonaka, and S. Behera (2020), Contrasting features of hydroclimatic teleconnections and the predictability of seasonal rainfall over east and west Japan, Meteorological Applications, Royal Meteorological Society (RMetS), 27:e1881, DOI: DOI: 10.1002/met.1881. Article link. Article (1.3 MB).

47.  Pal M., R. Maity, J.V. Ratnam, M. Nonaka, and S. K. Behera, (2020), Long-lead Prediction of ENSO Modoki Index using Machine Learning algorithms, Scientific Reports, Nature Publishing Group, 10:365, DOI: 10.1038/s41598-019-57183-3. Article link. Article (2.6 MB).

2019

48.  Patra A, Bhaskaran, PK, and R. Maity (2019), Spectral Wave Characteristics over the Head Bay of Bengal: A Modeling Study, Pure and Applied Geophysics, Springer, 176(12), 5463-5486, doi: 10.1007/s00024-019-02292-3. Article link. Article (5.0 MB).

49.  Suman M. and R. Maity (2019), Hybrid wavelet-ARX approach for modeling association between rainfall and meteorological forcings at river basin scale, Journal of Hydrology, Elsevier, 577(123918), DOI: 10.1016/j.jhydrol.2019.123918. Article link. Article (3.1 MB).

50.  Dash S. and R. Maity (2019), Temporal evolution of precipitation based climate change indices across India: Contrast between pre- and post-1975 features, Theoretical and Applied Climatology, Springer, 138(3), 1667-1678, DOI: 10.1007/s00704-019-02923-8. Article link. Article (2.3 MB).

51.  Pal M. and R. Maity (2019), Soil Moisture Retrieval using Quad-Polarized SAR Data from Radar Imaging Satellite 1 (RISAT1) through Artificial Intelligence based Soft Computing Techniques, Journal of the Indian Society of Remote Sensing, Springer, 47(10),1671-1682, DOI: 10.1007/s12524-019-01015-4. Article link. Article (3.4 MB).

52.  Sarkar S., Germer, K., R. Maity, and Durner W. (2019), Measuring Near-Saturated Hydraulic Conductivity of Soils by quasi Unit-Gradient Percolation - 2. Application of the Methodology, Journal of Plant Nutrition and Soil Science, Wiley, 182, 535-540, DOI: 10.1002/jpln.201800383. Article link. Article (1.2 MB).

53.  Sarkar S., Germer, K., R. Maity, and Durner W. (2019), Measuring Near-Saturated Hydraulic Conductivity of Soils by quasi Unit-Gradient Percolation - 1. Theory and Numerical Analysis, Journal of Plant Nutrition and Soil Science, Wiley, 182, 524-534, DOI: 10.1002/jpln.201800382. Article link. Article (1.7 MB).

54.  Maity R., M. Suman, P. Laux, and H. Kunstmann, (2019), Bias correction of zero-inflated RCM precipitation fields: A copula-based scheme for both mean and extreme, Journal of Hydrometeorology, American Meteorological Society (AMetSoc), 20(4), 595-611, DOI: 10.1175/JHM-D-18-0126.1. Article link. Article (2.3 MB).

55.  Pal M. and R. Maity (2019), Development of a spatially-varying statistical soil moisture profile model by coupling memory and forcing using hydrologic soil groups, Journal of Hydrology, Elsevier, 570, 141-155, DOI: 10.1016/j.jhydrol.2018.12.042. Article link. Article (4.2 MB).

56.  Suman M. and R. Maity (2019), Assessment of Streamflow Variability with upgraded HydroClimatic Conceptual Streamflow Model, Water Resources Management, Springer, 33(4),1367-1382, DOI: 10.1007/s11269-019-2185-8. Article link. Article (1.9 MB).

2018

57.  Dutta R., and R. Maity, (2018), Temporal evolution of hydroclimatic teleconnection and long-lead prediction of Indian summer monsoon rainfall using time varying model, Scientific Reports, Nature Publishing Group, 8:10778, DOI: 10.1038/s41598-018-28972-z. Article link. Article (3.6 MB).

58.  Naren A., and R. Maity, (2018), Modelling of Local Sea Level Rise and its Future Projection under Climate Change using Regional Information through EOF Analysis, Theoretical and Applied Climatology, Springer, 134(3-4), 1269-1285, DOI: 10.1007/s00704-017-2338-8. Article link. Article (4.4 MB).

59.  Pichuka S., and R. Maity, (2018), Development of a time-varying downscaling model considering non-stationarity using a Bayesian approach, International Journal of Climatology, Royal Meteorological Society (RMetS), 38(7), 3157-3176, DOI: 10.1002/joc.5491. Article link, Article (1.4 MB).

2017

60.  Chanda K., and R. Maity, (2017), Assessment of Trend in Global Drought Propensity in the 21st century using Drought Management Index, Water Resources Management, Springer, 31(4), 1209-1225, DOI: 10.1007/s11269-017-1571-3. Article link, Article (4.7 MB).

61.  Pichuka S., P.R. Rajendra, R. Maity, and H. Kunstmann, (2017), Development of a method to identify change in the pattern of extreme streamflow events in future climate: Application on the Bhadra reservoir inflow in India, Journal of Hydrology: Regional Studies, Elsevier, 9, 236-246, DOI: 10.1016/j.ejrh.2016.12.084. Article link, Article (1.1 MB).

62.  Pal M., R. Maity, M. Suman, S.K. Das, P. Patel and H.S. Srivastava, (2017), Satellite based Probabilistic Assessment of Soil Moisture using C-band Quad-polarized RISAT 1 data, IEEE Transactions on Geoscience and Remote Sensing, IEEE, 55(3), 1351-1362, DOI: 10.1109/TGRS.2016.2623378. Article link, Article (1.1 MB).

2016

63.  Naren A., and R. Maity, (2016), Hydroclimatic Modelling of Local Sea Level Rise and its Projection in Future, Theoretical and Applied Climatology, Springer, 130(3-4), 761-774, DOI: 10.1007/s00704-016-1897-4. Article link, Article (4.3 MB).

64.  Subbarao P., and R. Maity, (2016), Spatio-temporal downscaling of projected precipitation in 21st century: Indication of a wetter monsoon over the upper Mahanadi basin in India, Hydrological Sciences Journal, Taylor & Francis, 62(3), 467-482, DOI: 10.1080/02626667.2016.1241882. Article link, Article (2.4 MB).

65.  Maity R., M. Suman, and N. K. Verma, (2016), Drought prediction using a wavelet based approach to model the temporal consequences of different types of droughts, Journal of Hydrology, Elsevier, 539, 417-428, DOI: 10.1016/j.jhydrol.2016.05.042. Article link, Article (1.6 MB).

66.  Pal, M., R. Maity, and S. Dey, (2016), Statistical Modelling of Vertical Soil Moisture Profile: Coupling of Memory and Forcing, Water Resources Management, Springer, 30(6), 1973-1986, DOI: 10.1007/s11269-016-1263-4. Article link, Article (0.8 MB).

2015

67.  Chanda K., and R. Maity, (2015), Closure to Discussion of Meteorological Drought Quantification with Standardized Precipitation Anomaly Index for the Regions with Strongly Seasonal and Periodic Precipitation by Kironmala Chanda and Rajib Maity, Journal of Hydrologic Engineering, American Society for Civil Engineering (ASCE), 21(5): 07016004, DOI: 10.1061/(ASCE)HE.1943-5584.0001369. Article link, Article (0.4 MB).

68.  Maity R., A. Aggrawal, and K. Chanda, (2015), Do CMIP5 models hint at a warmer and wetter India in the twenty-first century?, Journal of Water and Climate Change, IWA Publishing, 7(2), 280-295; DOI: 10.2166/wcc.2015.126. Article link, Article (1.3 MB).

69.  Chanda K., and R. Maity, (2015), Meteorological Drought Quantification with Standardized Precipitation Anomaly Index (SPAI) for the Regions with Strongly Seasonal and Periodic Precipitation, Journal of Hydrologic Engineering, American Society for Civil Engineering (ASCE), 20(12), 06015007-1-06015007-8, DOI: 10.1061/(ASCE)HE.1943-5584.0001236. Article link, Article (1.7 MB).

70.  Das S. K, and R. Maity, (2015), A hydrometeorological approach for probabilistic simulation of monthly soil moisture under bare and crop land conditions, Water Resources Research, American Geophysical Union (AGU), 51(4), 2336-2355, DOI:10.1002/2014WR016043. Article link, Article (2.6 MB).

71.  Chanda K., and R. Maity, (2015), Uncovering Global Climate Fields Causing Local Precipitation Extremes, Hydrological Sciences Journal, Taylor & Francis, 61(10), 1227-1237, DOI: 10.1080/02626667.2015.1006232. Article link, Article (1.6 MB).

72.  Maity R., S. Dey, and P. Varun, (2015), Alternative Approach for Estimation of Precipitation using Doppler Weather Radar Data, Journal of Hydrologic Engineering, American Society for Civil Engineering (ASCE), 20(10):04015006, DOI: 10.1061/(ASCE)HE.1943-5584.0001146. Article link, Article (8.9 MB).

2014

73.  Meenu R., R. Maity, R. Ojha, and R. S. Govindaraju, (2014), Predictor selection for streamflows using a graphical modeling approach, Stochastic Environmental Research and Risk Assessment, Springer, 29(6), 1583-1599, DOI: 10.1007/s00477-014-0977-1. Article link, Article (3.5 MB).

74.  Chanda K., R. Maity, A. Sharma, and R. Mehrotra, (2014), Spatiotemporal Variation of Long-term Drought Propensity through Reliability-Resilience-Vulnerability based Drought Management Index, Water Resources Research, American Geophysical Union (AGU), 50(10), 7662-7676, DOI: 10.1002/2014WR015703. Article link, Article (3.5 MB).

75.  Das S. K., and R. Maity, (2014), Potential of Probabilistic Hydrometeorological Approach for Precipitation-Based Soil Moisture Estimation, Journal of Hydrologic Engineering, American Society for Civil Engineering (ASCE), 20(4):04014056, DOI: 10.1061/(ASCE)HE.1943-5584.0001034. Article link, Article (3.6 MB).

76.  Das S. K. and R. Maity, (2014), On the Application of Probabilistic Hydrometeorological Simulation of Soil Moisture across Different Stations in India, Journal of Geoscience and Environment Protection, Scientific Research, 2(3), 159-169. DOI: 10.4236/gep.2014.23021. Article link, Article (0.7 MB).

77.  Bhagwat P.P., and R. Maity, (2014), Development of HydroClimatic Conceptual Streamflow (HCCS) Model for Tropical River Basins, Journal of Water and Climate Change, IWA Publishing, 5(1), 36-60, DOI: 10.2166/wcc.2013/015. Article link, Article (1.2 MB).

  1. Bhagwat P.P., and R. Maity, (2014), Reply to the Discussion by Haddad et al. on Hydroclimatic Streamflow Prediction using Least Square-Support Vector Regression by Bhagwat and Maity (2013), ISH Journal of Hydraulic Engineering, Taylor & Francis, 20(3), 276-277, DOI: 10.1080/09715010.2014.881075. Article link, Article (1.0 MB).

2013

79.  Maity R., R. Meenu, and R.S. Govindaraju, (2013), Identification of Hydrologic Drought Triggers from Hydro-climatic Predictor Variables, Water Resources Research, American Geophysical Union (AGU), 49(7), 4476-4492, DOI: 10.1002/wrcr.20346. Article link, Article (1.3 MB).

80.  Bhagwat P.P., and R. Maity, (2013), Hydroclimatic Streamflow Prediction using Least Square-Support Vector Regression, ISH Journal of Hydraulic Engineering, Taylor & Francis, 19(3), 320-328, DOI: 10.1080/09715010.2013.819705. Article link, Article (1.1 MB).

81.  Das S. K., and R. Maity, (2013), Probabilistic Simulation of Surface Soil Moisture using Hydrometeorological Inputs, ISH Journal of Hydraulic Engineering, Taylor & Francis, 19(3), 227-234, DOI: 10.1080/09715010.2013.798907. Article link, Article (0.7 MB).

82.  Maity R., A. Sharma, D. Nagesh Kumar, and K. Chanda, (2013), Characterizing drought using the reliability-resilience-vulnerability concept, special issue on Data Driven Approaches to Droughts, Journal of Hydrologic Engineering, American Society for Civil Engineering (ASCE), 18(7), 859-869, DOI: 10.1061/(ASCE)HE.1943-5584.0000639. Article link, Article (1.6 MB).

2012

83.  Maity R., (2012), Probabilistic Assessment of one-step-ahead Rainfall Variation by Split Markov Process, Hydrological Processes, Wiley, 26(7), 3182-3194, DOI: 10.1002/hyp.8245. Article link, Article (0.6 MB).

84.  Kashid S.S., and R. Maity (2012), Prediction of Monthly Rainfall on Homogeneous Monsoon Regions of India Based on Large Scale Circulation Patterns using Genetic Programming, Journal of Hydrology, Elsevier, 454-455, 26-41, DOI: 10.1016/j.jhydrol.2012.05.033. Article link, Article (1.3 MB).

85.  Bhagwat P.P., and R. Maity, (2012), Multistep-ahead River Flow Prediction using LS-SVR at Daily Scale, Journal of Water Resource and Protection (JWARP), 4(7), 528-539, DOI: 10.4236/jwarp.2012.47062. Article link, Article (1.8 MB).

2011

86.  Maity R., and S. S. Kashid, (2011), Importance Analysis of Local and Global Climate Inputs for Basin-Scale Streamflow Prediction, Water Resources Research, American Geophysical Union (AGU), 47(11), W11504, DOI:10.1029/2010WR009742. Article link, Article (1.4 MB).

2010

87.  Kashid S. S., S. Ghosh, and R. Maity, (2010), Streamflow Prediction using Multi-Site Rainfall Obtained from Hydroclimatic Teleconnection, Journal of Hydrology, Elsevier, 395(1-2), 23-38, DOI: 10.1016/j.jhydrol.2010.10.004. Article link, Article (1.3 MB).

88.  Maity R., and S. S. Kashid, (2010), Short-term basin-scale streamflow forecasting using large-scale coupled atmospheric oceanic circulation and local outgoing longwave radiation, Journal of Hydrometeorology, American Meteorological Society (AMetSoc), 11(2), 370-387, DOI: 10.1175/2009JHM1171.1. Article link, Article (1.2 MB).

89.  Maity R., P. P. Bhagwat and A. Bhatnagar, (2010), Potential of Support Vector Regression for Prediction of Monthly Streamflow using Endogenous Property, Hydrological Processes, Wiley, 24(7), 917-923, DOI: 10.1002/hyp.7535. Article link, Article (0.3 MB).

2009

90.  Maity R., and S. S. Kashid, (2009), Hydroclimatological approach for monthly streamflow prediction using genetic programming, ISH Journal of Hydraulic Engineering, Taylor & Francis, 15(2), 89-107, DOI: 10.1080/09715010.2009.10514943. Article link, Article (1.3 MB).

91.  Maity R., and D. Nagesh Kumar, (2009), Hydroclimatic influence of large-scale circulation on the variability of reservoir inflow, Hydrological Processes, Wiley, 23(6), 934-942, DOI: 10.1002/hyp.7227. Article link, Article (0.2 MB).

92.  Maity R., S. S. Kashid and A. Bhatnagar, (2009), Hydrometeorological modeling approaches using Support Vector Regression (SVR) and Genetic Programming (GP), Special Issue of the ISH Journal of Hydraulic Engineering, Taylor & Francis, 15(SP1), 244-257, DOI: 10.1080/09715010.2009.10514978. Article link, Article (0.9 MB).

2008

93.  Maity R., and D. Nagesh Kumar, (2008), Probabilistic prediction of hydroclimatic variables with nonparametric quantification of uncertainty, Journal of Geophysical Research - Atmospheres, American Geophysical Union (AGU), 113(D14), D14105, DOI: 10.1029/2008JD009856. Article link, Article (0.9 MB).

94.  Nagesh Kumar D., and R. Maity, (2008), Bayesian dynamic modeling for nonstationary hydroclimatic time series forecasting along with uncertainty quantification, Hydrological Processes, Wiley, 22(17), 3488-3499, DOI: 10.1002/hyp.6951. Article link, Article (0.3 MB).

95.  Maity R., and D. Nagesh Kumar, (2008), Basin-scale streamflow forecasting using the information of large-scale atmospheric circulation phenomena, Hydrological Processes, Wiley, 22(5), 643-650, DOI: 10.1002/hyp.6630. Article link, Article (0.3 MB).

2007

96.  Maity R., D. Nagesh Kumar and Ravi S. Nanjundiah, (2007), Review of hydroclimatic teleconnection between hydrologic variables and large-scale atmospheric circulation indices with Indian perspective, ISH Journal of Hydraulic Engineering, Taylor & Francis, 13(1), 77-92, DOI: 10.1080/09715010.2007.10514859. Article link, Article (1.1 MB).

97.  Nagesh Kumar D., M. J. Reddy and R. Maity, (2007), Regional Rainfall Forecasting using Large Scale Climate Teleconnections and Artificial Intelligence Techniques, Journal of Intelligent Systems, De Gruyter, 16(4), 307-322, DOI: 10.1515/JISYS.2007.16.4.307. Article link, Article (0.3 MB).

98.  Maity R., and D. Nagesh Kumar, (2007), Hydroclimatic teleconnection between global sea surface temperature and rainfall over India at subdivisional monthly scale, Hydrological Processes, Wiley, 21(14), 1802-1813, DOI: 10.1002/hyp.6300. Article link, Article (1.2 MB).

2006

99.  Maity R., and D. Nagesh Kumar, (2006), Hydroclimatic association of monthly summer monsoon rainfall over India with large-scale atmospheric circulation from tropical Pacific Ocean and Indian Ocean region, Atmospheric Science Letters, Royal Meteorological Society (RMetS), 7(4), 101-107, DOI: 10.1002/asl.141. Article link, Article (0.8 MB).

100.   Maity R., and D. Nagesh Kumar, (2006), Bayesian dynamic modeling for monthly Indian summer monsoon rainfall using El Niño-Southern Oscillation (ENSO) and Equatorial Indian Ocean Oscillation (EQUINOO), Journal of Geophysical Research - Atmospheres, American Geophysical Union (AGU), 111(D7), D07104, DOI:10.1029/2005JD006539. Article link, Article (PDF 1.5 MB).

 

Project/Technical Report:

  1. Maity R., (2020), Exploration of Vertical Soil Moisture Profile by Assimilating the Surface Soil Moisture Data Retrieved from Remotely Sensed SAR Data, Submitted to Space Application Centre (SAC), Indian Space Research Organization (ISRO), Govt. of India, Ahmedabad, pp. 67.
  2. Maity R., (2019), Modelling of Soil Moisture in a Changing Climate using the Potential of Probabilistic Hydrometeorological Approach, Ministry of Earth Sciences, Govt. of India, New Delhi, India, pp. 56.
  3. Maity R., (2017), Probabilistic Estimation of Soil Moisture from RISAT1 Data along with Uncertainty Quantification, Submitted to Space Application Centre (SAC), Indian Space Research Organization (ISRO), Govt. of India, Ahmedabad, pp. 64.
  4. Maity R., and A. Dhar, (2014), Performance evaluation study in respect of work Keliaghai-Kapaleswari-Baghai drainage basin scheme (Phase-II, 2012-2013) under flood management programme, GOI, Submitted to Superintending Engineer, Western Circle-II, I&W Directorate, Dist. Paschim Mednipur, Govt. of West Bengal, pp. 24.
  5. Maity R., and A. Dhar, (2013), Performance evaluation study in respect of work Keliaghai-Kapaleswari-Baghai drainage basin scheme (Phase-I, 2010-2011) under flood management programme, GOI, Submitted to Superintending Engineer, Western Circle-II, I&W Directorate, Dist. Paschim Mednipur, Govt. of West Bengal, pp. 10.
  6. Maity R., and P. K. Gupta, (2011), River basin stream flow simulation using remote sensing data and climate model output, Under PRogrAmme on Climate change Research In Terrestrial envIronment (PRACRITI), Submitted to Space Application Centre, Indian Space Research Organisation (ISRO), Government of India, Ahmedabad, Gujarat, India, pp. 83.
  7. Maity R., (2009), Assessment of hydroclimatic Teleconnection for basin-scale, real-time streamflow and its use in real-time streamflow forecasting, Submitted to Science and Engineering Research Council (SERC), Department of Science and Technology (DST), Govt. of India, pp. 91, New Delhi, pp. 91.

 

Conferences and Symposia:

  1. Paul A. R, and R. Maity (2024), Interconnected Climate-Induced Impacts on Water Resources in Geographically Diverse Regions: A Spotlight on Northeast India and Bangladesh, In the Proceedings of International Conference on Water Resources, Ocean and Environmental Engineering (ICWROEE 2024), during February 17-18, 2024, held at National Institute of Technology Silchar, Assam, India.
  2. Maity R., S. Sarkar, and A.R. Paul (2024), Changing Characteristics of Extreme Precipitation and Temperature across Northeast India and Bangladesh, In the Proceedings of 21st Annual Meeting of Asia Oceania Geosciences Society (AOGS2024), during June 23-28, 2024, held at Pyeongchang, Gangwon-do, South Korea.
  3. Mahapatra S., S. Pandey, N.M. Velpuri, A. Sikka, R. Maity, P.K. Mishra, A. Parey (2023) Discharge Estimation of a Data-Scarce Integrated River Basin System in Eastern India, In the proceedings of Roorkee Water Conclave 2024, during March 03-06, 2024, held at Indian Institute of Technology Roorkee, Uttarakhand, India.
  4. Srivastava A., and R. Maity (2023), Beyond traditional drought perspectives: quantifying environmental droughts using heuristic method amidst climate change, In AGU Fall Meeting, Abstract ID #1310348, December 11-15, 2023, San Francisco, CA, USA.
  5. Paul A. R, R. Maity (2023), Future Projections of Extreme Climate Change Indices over Northeast India and Bangladesh, In the proceedings of 9th International Conference on Water and Flood Management-ICWFM 2023, during October 14-16, 2023, held at Dhaka, Bangladesh.
  6. Maity S. S., and R. Maity (2023), Analysis of Flash Droughts across Indian Mainland: A comparison between CMIP6 simulations and ERA5 reanalysis data, In the proceedings of HYDRO 2023 International, 28th International Conference on Hydraulics, Water Resources and River Engineering, during December 21-23, 2023, held at National Institute of Technology Warangal, Telangana, India.
  7. Dutta R., R. Maity, Y. Markonis (2023), Direct and Indirect Coupling of Evapotranspiration with Energy Fluxes over the Indian Subcontinent, In the proceedings of HYDRO 2023 International, 28th International Conference on Hydraulics, Water Resources and River Engineering, during December 21-23, 2023, held at National Institute of Technology Warangal, Telangana, India.
  8. Paul A. R, R. Maity (2023), Assessing Future Climate Extremes in Northeast India and Bangladesh: A Multi-Model Ensemble Approach using CMIP6, In the proceedings of HYDRO 2023 International, 28th International Conference on Hydraulics, Water Resources and River Engineering, during December 21-23, 2023, held at National Institute of Technology Warangal, Telangana, India.
  9. Srivastava A., R. Maity and V R Desai (2023), Investigating spatio-temporal trends and anomalies in long-term meteorological variables to determine if Maharashtra is an emerging warming state in India, In Proceedings of the International Conference on Interdisciplinary Approaches in Civil Engineering for Sustainable Development (IACESD-2023) - A G20 C20 event on Civil Engineering Innovations for Sustainable Communities with Net Zero Targets, held at Jyothy Institute of Technology, Bengaluru, during July 7-8, 2023.
  10. Maity R., R. Dutta, K. Chanda (2023), Future of Renewable Energy Potential in a Changing Climate using CMIP6 Simulations for the Indian Subcontinent, In the proceedings of International Perspectives on Water Resources and the Environment (IPWE 2023), during January 04-06, 2023, held at Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh.
  11. Dutta R., and R. Maity (2023), Streamflow Modelling and Prediction using Temporal Networks, In the proceedings of International Perspectives on Water Resources and the Environment (IPWE 2023), during January 04-06, 2023, held at Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh.
  12. Dash S., Dutta R., and R. Maity, (2022), Change in the Intensity of Consecutive Precipitation Events across India, AGU Fall Meeting, Abstract ID# 1167926, Final Paper# H51E-05, December 12-16, 2022, Chicago, IL, USA.
  13. Dash S., R. Dutta and R. Maity (2022), An Evaluation of Future Changes in Hydroclimate Extremes across India, In the proceedings of HYDRO 2022, International Conference (Hydraulics, Water Resources and Coastal Engineering), December 22-24, 2022 at Punjab Engineering College, Chandigarh. India.
  14. Sarkar S., and R. Maity, (2022), Homogeneous Precipitation Zones: Newly proposed Zones for India and their Future-projected Changes in Precipitation Characteristics, n the proceedings of HYDRO 2022, International Conference (Hydraulics, Water Resources and Coastal Engineering), December 22-24, 2022 at Punjab Engineering College, Chandigarh. India.
  15. Maity S.S., S. Sarkar, R. Maity, A. Rahman (2022), Changes in Precipitation Intensity-Duration-Curve: A comparison based on CMIP5 and CMIP6, In the Proceedings of the 3rd International Conference on Water and Environmental Engineering (iCWEE2022), Nov 27-30, 2022, Sydney, Australia.
  16. Sarkar S., S. S. Maity and R. Maity, (2022), Are the cities becoming potentially vulnerable due to change in precipitation characteristics? A pan-India analysis with CMIP6 simulations, In the Proceedings of the 19th Annual Meeting of Asia Oceania Geosciences Society (Virtual) during August 01-05, 2022.
  17. Khan, M. I. and R. Maity, (2022), Prediction of daily air temperature: Comparison of a hybrid ML approach with four other ML approaches, In the Proceedings of the 19th Annual Meeting of Asia Oceania Geosciences Society (Virtual) during August 01-05, 2022.
  18. Maity R., and R. Dutta, (2022), Time-varying characteristics of droughts: A modelling scheme with temporal networks for future assessment, In the proceedings of the 39th IAHR World Congress, June 19 - 24, 2022, Granada, Spain.
  19. Dutta R., S. Dash and R. Maity (2022), Spatio-temporal characteristics of extreme rainfall events in India and possible connection to the large-scale atmospheric circulations, In the proceedings of the 39th IAHR World Congress, June 19 - 24, 2022, Granada, Spain.
  20. Dutta R., and R. Maity, (2021), Long-lead prediction of monthly streamflow: Potential of temporal networks in capturing the time-varying characteristics, AGU Fall Meeting, Abstract ID# 884252, December 13-17, 2021, New Orleans LA, USA.
  21. Pal, M., R. Maity, J.V. Ratnam, M. Nonaka, and S. K. Behera, (2021), Evaluation of Machine Learning algorithms for long-lead forecasting of ENSO Modoki Index, AGU Fall Meeting, Abstract ID# 885820, December 13-17, 2021, New Orleans LA, USA.
  22. Khan, M.I. and R. Maity (2021), Streamflow Forecasting with LSTM based Deep Learning Approach, In the proceedings of HYDRO 2021, International Conference (Hydraulics, Water Resources and Coastal Engineering), December 23-25, 2021 at Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat, India.
  23. Dutta R., and R. Maity (2021), Temporal Networks: A new approach in hydroclimatic studies to capture time-varying characteristics, In the proceedings of HYDRO 2021, International Conference (Hydraulics, Water Resources and Coastal Engineering), December 23-25, 2021 at Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat, India.

24.  Palagiri H., M. Pal and R. Maity (2021), Drought Monitoring using Satellite Soil Moisture Data over Godavari Basin, India, In the proceedings of HYDRO 2021, International Conference (Hydraulics, Water Resources and Coastal Engineering), December 23-25, 2021 at Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat, India.

  1. Khan, M.I. and R. Maity (2021), Potential of Deep Learning Approach to Predict Multi-step ahead Daily Rainfall, Japan Geoscience Union Meeting, JpGU 2021, On-site May30-June01, Online June 03-06, 2021, Yokohama, Tokyo, Japan.

26.  Suman M., and R. Maity, (2021), Future Changes in extreme precipitation over South Asia and its causes, In session HS2.4.2, Hydrological change: Regional hydrological behaviour under transient climate and land use conditions, EGU21-1736, virtual European Geosciences Union General Assembly 2021 (vEGU 2021), April 19-30, 2021.

  1. Dash S., and R. Maity, (2020), Change in Combined Precipitation and Temperature Modes Across India, 17th Annual Meeting of Asia Oceania Geosciences Society (AOGS 2020) at Sono Belle Vivaldi Park, Hongcheon during Jun 28 to July 04, 2020.

28.  Dutta R., and R. Maity, (2020), Time-varying Model for Seasonal Rainfall Prediction in Japan Based on the Temporal Evolution of Hydroclimatic Teleconnection, 17th Annual Meeting of Asia Oceania Geosciences Society (AOGS 2020) at Sono Belle Vivaldi Park, Hongcheon during Jun 28 to July 04, 2020.

29.  Das P., K. Chanda and R. Maity, (2020), How useful are CORDEX products for the assessment of future agricultural drought propensity across the Indian subcontinent?, In session HS2.4.7, Hydrological change: Regional hydrological behaviour under transient climate and land use conditions, EGU2020-6856, European Geosciences Union General Assembly 2020, May 03-08, 2020, Vienna, Austria.

30.  Suman M., and R. Maity, (2020), Modeling of Basin Scale Hydro-meteorological association by Hybrid Wavelet-ARX approach, In session HS2.4.7 Hydrological change: Regional hydrological behaviour under transient climate and land use conditions, EGU2020-6856, European Geosciences Union General Assembly 2020, May 03-08, 2020, Vienna, Austria.

31.  Maity R., K. Chanda, R. Dutta, J. V. Ratnam, M. Nonaka and S. Behera (2020), How dissimilar are the large-scale hydroclimatic precursors and predictability of anomalous monthly rainfall in east and west Japan?, In session HS2.4.7 Hydrological change: Regional hydrological behaviour under transient climate and land use conditions, EGU2020-6856, European Geosciences Union General Assembly 2020, May 03-08, 2020, Vienna, Austria

32.  Pal M., and R. Maity, (2020), Spatially-Varying Statistical Soil Moisture Profile Model by Coupling Memory and Forcing using Hydrologic Soil Groups to Estimate Vertical Soil Moisture Profile, In session HS2.4.7 Hydrological change: Regional hydrological behaviour under transient climate and land use conditions, EGU2020-6856, European Geosciences Union General Assembly 2020, May 03-08, 2020, Vienna, Austria.

33.  Maity R., M. Suman, P. Laux, and H. Kunstmann (2019), Copula-based Bias correction scheme for zero-inflated RCM precipitation fields, In the proceeding of Water Future Conference 2019, at Indian Institute of Science (IISc), Bangaluru, India during September 24-27, 2019.

34.  Naren A, and R. Maity (2019), Hydroclimatic Projection of Coastal Inundation for the 21st Century during Tropical Cyclone Thane in the Bay of Bengal, In the proceedings of 6th Biennial Conference of Oceanic Society of India (OSICON-19) at Centre for Marine Living Resources & Ecology, Ministry of Earth Science, Kochi, Kerala, India during December 12-14, 2019.

35.  Chanda K., and R. Maity, (2019), Hydroclimatic Prediction using Machine Learning Approach incorporating Time-varying Concept, In the Proceedings of the 16th Annual Meeting of Asia Oceania Geosciences Society (AOGS 2019) at Singapore during 28th July 28 to August 02, 2019.

36.  Dash S., and R. Maity, (2019), Temporal Evolution of Precipitation and Temperature Based Climate Change Indices Across India, In the Proceedings of the 16th Annual Meeting of Asia Oceania Geosciences Society (AOGS 2019) at Singapore during 28th July 28 to August 02, 2019.

37.  Dutta R., and R. Maity, (2019), Potential of Graphical Modelling in Long-lead Seasonal Prediction of Regional Summer Monsoon Rainfall in Context of Climate Change, In the Proceedings of the 16th Annual Meeting of Asia Oceania Geosciences Society (AOGS 2019) at Singapore during 28th July 28 to August 02, 2019.

38.  Sarkar S., and R. Maity, (2019), Observed Change in Spatio-temporal Distribution of Global Probable Maximum Precipitation in a Changing Climate, In the Proceedings of the 16th Annual Meeting of Asia Oceania Geosciences Society (AOGS 2019) at Singapore during 28th July 28 to August 02, 2019.

39.  Naren A., and R. Maity, (2019), Hydroclimatic Projection of Coastal Inundation for the 21st Century during Tropical Cyclone AILA in the Bay of Bengal, In session NH5.7/AS4.63/CL3.10/GM11.10/OS2.12 - Natural hazards and climate change impacts in coastal areas, EGU2019-4383, European Geosciences Union General Assembly 2019, April 07-12, 2018, Vienna, Austria

40.  Pichuka S., and R. Maity, (2019), Assessment of urban temperature rise with time-varying downscaling model, In the proceedings of National Environmental Conference 2019, January 31- February 02, 2019, IIT Bombay, India.

41.  Pichuka S., and R. Maity, (2018), Downscaling of Soil Moisture using Time-Varying Downscaling Model, AGU Fall Meeting, Abstract ID# 135846, December 10-14, 2018, Washington DC, USA.

42.  Dutta R., and R. Maity, (2018), Probabilistic Prediction of Monthly Streamflow using Graphical Modeling Approach, In the proceedings of HYDRO 2018 International conference, HYD-18-120, December 19-21, 2018 at National Institute of Technology Patna, India.

43.  Pichuka S., and R. Maity, (2018), Assessment of Extremes using Time-Varying Downscaling Model, In the proceedings of HYDRO 2018 International conference, HYD-18-109, December 19-21, 2018 at National Institute of Technology Patna, India.

44.  Chanda K., and R. Maity, (2018), Trivariate Probabilistic Assessment of Meteorological Drought to Develop Drought Severity Maps, In the session HS2.4.1 Hydrologic Extremes in a Changing Climate, AOGS 15th Annual Meeting, June 03-08, 2018, Honolulu, Hawaii.

45.  Pichuka S., and R. Maity, (2018), Time-Invariant and Time-Varying Downscaling Approaches for the Assessment of Extreme Temperatures Rise during 21st Century, In session HS2.4.1 Hydrological change: Regional hydrological behaviour under transient climate and land use conditions, Vol. 20, EGU2018-11645, European Geosciences Union General Assembly 2018, April 08-13, 2018, Vienna, Austria.

46.  Chanda K., and R. Maity, (2018), Spatio-temporal Variation of Soil Moisture Drought Propensity at the Continental Scale over the 21st century, In session HS2.4.1 Hydrological change: Regional hydrological behaviour under transient climate and land use conditions, Vol. 20, EGU2018-742, European Geosciences Union General Assembly 2018, April 08-13, 2018, Vienna, Austria.

47.  Pichuka S., and R. Maity, (2018), How far the CORDEX high-resolution data represents observed precipitation for the Indian region? 6th Vietnam International Water Week, VACI 2018, 4-8 March, 2018, Hanoi.

48.  Naren A., and R. Maity, (2017), Modelling of Local Sea Level Rise and its Projection in Future under Climate Change, In the Proceedings of the 14th Annual Meeting of Asia Oceania Geosciences Society (AOGS 2017) at Singapore during 6-11 August 2017, Singapore.

49.  Maity R., (2017), Streamflow Modelling Considering Changing Climate and Watershed Characteristics, Invites speaker in a session on Impact & Consequences of Changing Climate and Landuse on Hydrology at 14th Annual Meeting of Asia Oceania Geosciences Society (AOGS 2017) at Singapore during 6-11 August 2017, Singapore.

50.  Pal M., M. Suman, S. K. Das, and R. Maity, (2017), Probabilistic Assessment of Soil Moisture using C-band Quad-polarized Remote Sensing Data from RISAT1, In Session HS6.4 Remote sensing of soil moisture, EGU2017-14907, European Geosciences Union General Assembly 2017, 23-28 April, 2017 in Vienna, Austria.

51.  Maity R., (2016), Development of a time-varying downscaling approach in a changing climate considering nonstationarity issue, Network Meeting of the Alexander von Humboldt Foundation, Freiburg, October 05-07, 2016.

52.  Suman M., and R. Maity, (2016), Foreseeing the Agricultural and Hydrological Drought Knowing the Ongoing Meteorological Scenarios through Wavelet Analysis, International Conference on Hydraulics, Water Resources, Coastal & Environmental Engineering (HYDRO 2016 International), December 8-10, 2016 at CWPRS, Pune, abstract accepted (Abstract ID# HYD-16-418).

53.  Das S. K., and R. Maity, (2016), Copula-based Probabilistic Estimation of Soil Moisture and its Potential Application in Air Pollution Meteorology, AGU Fall Meeting, Abstract ID# 135846, December 12-16, 2016, San Francisco, California, USA.

54.  Chanda K., and R. Maity, (2016), Identification of Distinct Global Climate Patterns behind Hydrological Extremes in North-Eastern and Western India, Special session on Extreme Events in a Changing Climate, 7th International Conference on Sustainable Built Environment 2016, December 16-18, 2016, Kandy, Sri Lanka.

55.  Pichuka S., and R. Maity, (2016), Impact of Climate Change on Monthly Precipitation during 21st Century in Upper Mahanadi Basin, India, In the Proceedings of 3rd National Conference on Sustainable Water Resources Development and Management (SWARDAM-2016), July 4-5, 2016, Organised by Department of Civil Engineering, Government College of Engineering, Aurangabad-431005, Maharashtra, India.

56.  Chanda K., and R. Maity, (2016), Global Climate Pattern behind Hydrological Extremes in Central India, International Conference on Water, Environment, Energy and Society (ICWEES-2016), organized jointly by the Texas A & M University, Texas, USA and AISECT University, March 15-18, 2016, Bhopal, India.

57.  Subbarao P., and R. Maity, (2015), Development of a Time Varying Downscaling Model Using Bayesian Approach and its Comparison with Statistical Downscaling Model, In the Proceedings of the 20th International Conference on Hydraulics, Water Resources and River Engineering (HYDRO-2015), December 17-19, 2015, IIT Roorkee.

58.  Chanda K., and R. Maity, (2015), Assessment of trend in drought propensity across the globe using CanESM2 projections, AGU Joint Assembly, 3-7 May 2015, Abstract ID: 34864, Final paper No. AS13B-02, Montreal, Canada.

59.  Maity R., (2015), Water Resources and Climate Change: HydroClimatic Conceptual Streamflow (HCCS) Model as a potential approach for watershed hydrologic modeling, In the proceedings of 47th IWWA Annual Convention, 30 Jan to 01 Feb, 2015, Kolkata, pp. 140-152.

60.  Maity R., K. Chanda, D. Nagesh Kumar, A. Sharma and R. Mehrotra, (2014), Potential of the Reliability-Resilience-Vulnerability (RRV) Based Drought Management Index (DMI), AGU Fall Meeting, Final paper # H23N-1085, December 15-19, 2014, San Francisco, California, USA.

61.  Das S. K., and R. Maity, (2014), On the Application of Probabilistic Hydrometeorological Simulation of Soil Moisture Across Different Stations in India, In the Proceedings of 2nd Hydrology, Ocean and Atmosphere Conference (HOAC 2014) during June 13-15, 2014 at Beijing, China.

62.  Maity R., S. Dey and A. Koppa, (2014), HydroClimatic Conceptual Streamflow (HCCS) Model: A New Approach for Watershed Hydrologic Modeling, In the proceedings of 19th IAHR - APD Congress, September 21 - 24, 2014, WRU, Hanoi, Vietnam.

63.  Chanda K., and R. Maity, (2013), Variation of Reliability-Resilience-Vulnerability based Drought Managemnet Index (DMI) for Mahanadi basin, In the Proceedings of National conference on Sustainable Water Resources Planning, Management and Impact of Climate Change, during April 5-6, 2013 at BITS, Pilani Hyderabad Campus, India. 

64.  Das S. K., and R. Maity, (2012), Probabilistic Simulation of Surface Soil Moisture using Hydrometeorological Inputs, In the Proceedings of Conference on Hydraulics, Water Resources, Coastal and Environmental Engineering (HYDRO-2012), December 7-8, 2012, IIT Bombay, Mumbai, India.

65.  Bhagwat P. P., and R. Maity, (2012), Multistep-Ahead Stream Flow Prediction using Least Square-Support Vector Regression, In the Proceedings of Conference on Hydraulics, Water Resources, Coastal and Environmental Engineering (HYDRO-2012), December 7-8, 2012, IIT Bombay, Mumbai, India.

66.  Maity R., and K. Chanda, (2012), Spatio-temporal analysis of drought predictability across India, In the Proceedings of 5th International Congress of Environmental Research (ICER), November, 22-24, 2012, Universiti Malaysia Terengganu (UMT), Terengganu, Malaysia.

67.  Chanda K., and R. Maity, (2012), Influence of local hydrometeorological variables on basin scale drought status, In the Proceedings of 5th International Congress of Environmental Research (ICER), November, 22-24, 2012, Universiti Malaysia Terengganu (UMT), Terengganu, Malaysia.

68.  Maity R., R. Ojha, and R. S. Govindaraju, (2012), Assessment of multi-dimensional coupled association among hydroclimatic variables using graphical modelling approach, Presented in World Environment and Water Resources Congress, EWRI, ASCE, May 20-24, 2012.

69.  Maity R., M. Ramadas and R. S. Govindaraju, (2012), Dimensionality reduction in hydroclimatic variables for probabilistic streamflow prediction using a hybrid approach, Presented in World Environment and Water Resources Congress, EWRI, ASCE, May 20-24, 2012.

70.  Maity R., and K. Chanda, (2011), Probabilistic prediction of streamflow using the information of Outgoing Longwave Radiation through Placket copula, In the proceedings of International conference on Sustainable Water Resources Management and Climate Change Adaptation, National Institute of Technology, Durgapur, February 17-19, 2011, pp. 119-130.

71.  Maity R., and M. Sawant, (2010), Uncertainty quantification for predicted stream flow through a semi parametric approach, In the conference on Sustainable Water Resources Management and Impact of Climate Change, March 5-6, 2010, BITS-Pilani, Hyderabad Campus, India, pp. 280-290.

72.  Maity R., (2010), Large-scale climatic forcing along with local meteorological influence on hydrologic variables, 5th IWA Young Water Professional Conference, July 5-7, 2010, Sydney, Australia.

73.  Kashid S.S., and R. Maity, (2010), Prediction of monthly rainfall over homogeneous monsoon regions of India based on large scale circulation patterns using genetic programming, In EWRI's 3rd developing nations conference: India 2010 - An International Perspective on Current & Future State of Water Resources & the Environment, January 5-7, 2010, Chennai, India.

74.  Kashid S.S., and R. Maity, (2009), Hydroclimatological Approach for Monthly Basin Scale Streamflow Prediction using Genetic Programming, AIAWRM-02, 4th Indian International Conference on Artificial Intelligence (IICAI-09), December 16-18, 2009, Tumkur, India.

75.  Kashid S.S., and R. Maity, (2009), Analysis of basin-scale streamflow variation using local and global climatic inputs, In the Proceedings of the workshop entitled Development and Application of Advanced Soft Computing Techniques in Multidimensional Geospatial Data Analysis, 15-16 October, 2009, IIT Kanpur, Invited paper.

76.  Maity R., and D. Nagesh Kumar, (2009), Rainfall-runoff modeling using system concept of watershed characteristics, In the Proceedings of An International Perspective on Environmental and Water Resources, EWRI, ASCE, 5-7 January 2009, Bangkok, Thailand.

77.  Maity R., and D. Nagesh Kumar, (2009), Uncertainty Quantification for Hydrologic Models using Copula, In the Proceedings of International Conference on Water, Environment, Energy and Society (WEES-2007), New Delhi, India.

78.  Maity R., S. S. Kashid, and A. Bhatnagar, (2008), Hydrometeorological modeling approachesusing support vector regression and genetic programming, In the Proceeding of the Brainstorming Workshop on Application of Advanced Soft Computing Techniques in Geo-Spatial Data Analysis, September 22-23, 2008, IIT Bombay, Mumbai, pp. 185-195, Invited paper.

79.  Maity R., (2007), An Introduction to climate forcing on hydrologic variables, In the Proceedings of the national conference on Hydraulics and Water Resources, HYDRO - 2007, Organized by SVNIT, Surat, and Indian Society for Hydraulics, December 21 - 22, 2007, pp. 40 - 46.

80.  Maity R., and D. Nagesh Kumar, (2007), Bayesian dynamic linear modeling for streamflow forecasting using large-scale atmospheric circulations, In the Proceedings of International Conference on Civil Engineering in the New Millennium: Opportunities and Challenges (CENeM-2007), January 11-14, 2007, 150- year anniversary conference at Bengal Engineering and Science University, Shibpur, Howrah, West Bengal, India, Vol. IV, pp. 2736-2744, Invited Paper.

81.  Maity R., and D. Nagesh Kumar, (2006), Artificial Neural Network approach for hydroclimatic streamflow forecasting in India using ENSO and EQUINOO, In the Proceedings of World Environmental and Water Resources Congress, EWRI, ASCE, Omaha, Nebraska, USA.

82.  Nagesh Kumar D., M. Janga Reddy and R. Maity, (2005), Regional Rainfall Forecasting using Large Scale Climate Teleconnections and Evolutionary Algorithms, In the Proceedings of 2nd Indian International Conference on Artificial Intelligence, WR 105, Pune, India, pp. 1169 - 1182.

83.  Nagesh Kumar D., and R. Maity, (2004), Analysis of Orissa rainfall with sea surface temperature anomaly by similarity search technique, In the Proceedings of Prediction in Ungauged Basin for Sustainable Water Resources Planning and Management (PUBSWRPM-2004), BITS, Pilani, India, pp.7-15, Invited Paper.

 

Last Updated: November, 2024