Hydro-climatology
Prabal Das
Research Scholar
Dhanbad
Summary
Currently pursuing Ph.D. in Water Resources Engineering from Department of Civil Engineering, IIT (ISM) Dhanbad. Working on the applications of Machine Learning in predictions of various hydro-climatic phenomenon. Proficient in predictive analysis and data processing required for various ML based hydrological modeling. Capable of developing ML models in various platforms like R and Python.
Overview
5
5
years of professional experience
10
10
years of post-secondary education
Work History
Research Scholar
Department of Civil Engineering, IIT (ISM)
Dhanbad
2018.08 - Current
- Working on the applications of Machine Learning (ML) in predictions of various hydroclimatic phenomenon as well as hydroclimatic extremes.
- Studied the potential of Bayesian Networks (BN), a class of Graphical Modeling, for identifying the important precursors responsible for modeling various primary hydrologic variables like rainfall and streamflow.
- The identified precursors are then used for prediction of primary hydrologic variables like rainfall and streamflow.
- Some of the ML models used in this regard are Artificial Neural Networks (ANN), Support Vector Regression (SVR), Gaussian Process Regression (GPR), Random Forest (RF) etc.
Assistant Professor
IMPS College of Engineering and Technology
Malda
2018.01 - 2018.06
- Used variety of learning modalities and support materials to facilitate learning process and accentuate presentations.
- Proctored exams and provided remediation for learning improvement goals.
Assistant Professor
Vignan Institue of Technology and Science
Hyderabad
2017.06 - 2017.12
- Used variety of learning modalities and support materials to facilitate learning process and accentuate presentations.
- Created materials and exercises to illustrate application of course concepts.
- Proctored exams and provided remediation for learning improvement goals.
Education
Ph.D. - Water Resources Engineering
Indian Institute of Technology (ISM)
Dhanbad 2018.08 - Current
M.Tech - Water Resources Engineering And Management
National Institute of Technology Karnataka
Surathkal 2015.07 - 2017.05
B.Tech - Civil Engineering
IMPS College of Engineering & Technology
Malda 2010.08 - 2014.06
Skills
Programming Languages: R Studio, Python, MATLAB
undefinedInterests
Hydrological Extremes
Applications of Machine learning in Hydrology
Publications
Peer Reviewed Journals:
- Das, P., & Chanda, K. (2022). A Bayesian Network Approach for understanding the role of Large-Scale and Local Hydro-Meteorological Variables as Drivers of Basin-Scale Rainfall and Streamflow. Stochastic Environmental Research and Risk Assessment. (Under Review, First Revision completed)
- Das, P., & Chanda, K. (2020). Bayesian Network based modeling of regional rainfall from multiple local meteorological drivers. Journal of Hydrology, 591, 125563. https://doi.org/https://doi.org/10.1016/j.jhydrol.2020.125563.
- Das, P., Naganna, S. R., Deka, P. C., & Pushparaj, J. (2020). Hybrid wavelet packet machine learning approaches for drought modeling. Environmental Earth Sciences, 79(10), 1–18. https://doi.org/10.1007/s12665-020-08971-y
- Das, P. & Deka, P.C, (2017). Application of Hybrid Wavelet Packet-ANN in drought forecasting, International Journal of Water Resources Engineering. 3(2), 70-80.
Book Chapters:
- Das, P., Chanda, K. (2022). Feature Selection for Rainfall Prediction and Drought Assessment Using Bayesian Network Technique. In: Kolathayar, S., Mondal, A., Chian, S.C. (eds) Climate Change and Water Security. Lecture Notes in Civil Engineering, vol 178. Springer, Singapore. https://doi.org/10.1007/978-981-16-5501-2_10
Conferences:
- Das, P., Chanda, K., and Maity, R (2020). How useful are CORDEX products for the assessment of future agricultural drought propensity across the Indian subcontinent?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15885, https://doi.org/10.5194/egusphere-egu2020-15885.
- Das, P., Palchaudhuri, M., Biswas, S., and Deka, P.C. (2017). Analysis Of Agricultural Drought Severity Using MODIS Satellite Images, in Proceedings of the International Conference on "Global Civil Engineering Challenges in Sustainable Development and Climate Change" (ICGCSC 2017), pp. 277-282, Mangalore Institute of Technology and Engineering.
References
- Dr. Kironmala Chanda, Assistant Professor, Department of Civil Engineering, IIT (ISM) Dhanbad, Phone - 9430351290
- Dr. Srinivas Pasupuleti, Associate Professor, Department of Civil Engineering, IIT (ISM) Dhanbad, Phone - 7377725777
Timeline
Research Scholar
Department of Civil Engineering, IIT (ISM)
2018.08 - Current
Ph.D. - Water Resources Engineering
Indian Institute of Technology (ISM)
2018.08 - Current
Assistant Professor
IMPS College of Engineering and Technology
2018.01 - 2018.06
Assistant Professor
Vignan Institue of Technology and Science
2017.06 - 2017.12
M.Tech - Water Resources Engineering And Management
National Institute of Technology Karnataka
2015.07 - 2017.05
B.Tech - Civil Engineering
IMPS College of Engineering & Technology
2010.08 - 2014.06
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