Applied AI Lab
By the student for the student
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Bibhuti Bhusan SahooAssistant ProfessorDepartment of Agricultural EngineeringSchool of Agricultural & Bio EngineeringCenturion University of Technology & Management, Paralakhemundi, OdishaEmail: bibhuti.sahoo@cutm.ac.in bibhuti5000@gmail.comMob: +91 7978173351
Research Interest
Research Interest
Even after decades of research, our fundamental understanding of the hydrologic cycle still has much room for improvement. We work to identify commonalities and learn underlying principles so that we can improve our understanding of the hydrologic cycle.
Our primary research focused on Deep Learning (DL) based prediction of Rainfall, streamflow, and other hydroclimatic variables. The DL has shown great promise for many applications. Please read the argument, review, and opinions on the integration of deep learning in water-related fields by Chaopeng Shen
Publications
Publications
Sahoo, B. B., Najafzadeh, M., Santosh, D. T., Jithendra, T., Panigrahi, B., Mishra, S., Gupta, S. K., & Bhushan, M. (2025). Comparative evaluation of machine-learning models for predicting daily evapotranspiration in a naturally ventilated greenhouse. Journal of Irrigation and Drainage Engineering. https://doi.org/10.1061/JIDEDH.IRENG-10441 (SCIE)
Sahoo, B. B., Raju Giri, Mani Bhushan (2025). Water budget assessment at data sparse Eastern Indian catchment: a seasonal perspective. International Journal of Energy and Water Resources. 10.1007/s42108-025-00349-9. (SCOPUS)
Sovan Sankalp, Sahoo, B. B, Sushindra Kumar Gupta, Mani Bhushan, Rajib Kumar Majhi, Santosh DT (2025). A Deep Learning Approach to Predict Surface Soil Wetness and Its Uncertainty Analysis Over the Tel River Basin, India. CLEAN - Soil, Air, Water. https://doi.org/10.1002/clen.70003. (SCIE)
Gupta SK, Sahoo Sashikanta, Sahoo, B. B, Srivastava PK, Pateriya B, Santosh DT (2024). Prediction of Groundwater Level Changes Based on Machine Learning Techniques in Highly Groundwater Irrigated Alluvial Aquifers of South Central Punjab, India.Physica and Chemistry of Earth, Parts A/B/C. https://doi.org/10.1016/j.pce.2024.103603 .(SCIE)
Sonali S, Paul JC, Sahoo, B.B, Gupta SK, Singh PK (2023). Improving forecasting accuracy of monthly runoff time series of Brahmani River, India using a hybrid deep learning model. Journal of Water and Climate Change. https://doi.org/10.2166/wcc.2023.487 (SCIE)
Sahoo, B.B., Panigrahi, B., Nanda, T. et al. (2023) Multi-step Ahead Urban Water Demand Forecasting Using Deep Learning Models. SN COMPUT. SCI. 4, 752 . https://doi.org/10.1007/s42979-023-02246-6 . (SCOPUS)
Sahoo, B. B., Sankalp, S., & Kisi, O. (2023). A Novel Smoothing-Based Deep Learning Time-Series Approach for Daily Suspended Sediment Load Prediction. Water Resources Management, 37(11), 4271-4292. (SCIE)
Sankalp, S., Sahoo, B. B., & Sahoo, S. N. (2023). Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities. Environmental Monitoring and Assessment, 195(2), 291.https://doi.org/10.1007/s10661-022-10844-9.(SCIE)
Sankalp, S., Sahoo, B. B., & Sahoo, S. N. (2022). Deep learning models comparable assessment and uncertainty analysis for diurnal temperature range (DTR) predictions over Indian urban cities. Results in Engineering, 13, 100326. (SCOPUS)
Sahoo, B. B., & Jha, R. (2020). Assessment of low flow trends and changepoint detection in Mahanadi River basin, India. Sustainable Water Resources Management. DOI: 10.1007/s40899-020-00441-4. (SCOPUS)
Sahoo B.B, Jha R, Singh A, Kumar D (2019). LSTM recurrent neural network for low flow Hydrological Time Series Forecasting. Acta Geophysica. https://doi.org/10.1007/s11600-019-00330-1 (SCIE)
Kumar, D., Singh, A., Jha, R. K., Sahoo, B. B., Sahoo, S. K., & Jha, V. (2019). Source characterization and human health risk assessment of nitrate in groundwater of middle Gangetic Plain, India. Arabian Journal of Geosciences, 12(11), 339. https://doi.org/10.1007/s12517-019-4519-5 (SCIE)
Sahoo B.B, Jha R, Singh A, Kumar D (2018) Application of Support Vector Regression for modeling low flow time series. KSCE Journal of Civil Engineering. https://doi.org/10.1007/s12205-018-0128-1 (SCIE)
Mohanta, A., Patra, K., & Sahoo, B.B. (2018). Anticipate Manning’s Coefficient in Meandering Compound Channels. Hydrology, 5(3), 47. https://doi.org/10.3390/hydrology5030047 (SCOPUS)
Sahoo, B. B., & Jha, R. (2018). Bivariate low flow return period analysis in the Mahanadi River basin, India. International Journal of River Basin Management. https://doi.org/10.1080/15715124.2019.1576698 (SCOPUS)
Conferences
Conferences
- Sagar Kumar Ojha, Neha Rani Samal, Sahoo, B. B and Sujata Chakravarty (2023) Predicting Daily Suspended Sediment Load Using Machine Learning Techniques. Hydro 2023, International Conference (Hydraulics, Water Resources & Coastal Engineering), 21-23 Dec 2023, NIT Warangal, India.
- Shradhanjalee Pradhan, Abhishek Bibhar, Mani Bhushan, Shashi Shankar Ojha, Sahoo, B. B and Sovan Sankalp (2023) Soil erosion Potential Zone Mapping using Analytical Hierarchy Process and GIS. Hydro 2023, International Conference (Hydraulics, Water Resources & Coastal Engineering), 21-23 Dec 2023, NIT Warangal, India.
- S. Rabi Kumar Rao, Shashi Shankar Ojha, Mani Bhushan and Sahoo, B. B (2023) Human health risk assessment of nitrate in groundwater of Faridabad and Gurgaon districts of National Capital Region, India. Hydro 2023, International Conference (Hydraulics, Water Resources & Coastal Engineering), 21-23 Dec 2023, NIT Warangal , India.
Debarghya Dey Priya Khanda Sahoo, B. B (2023) Hydro-Geomorphological characterization of the Tel River basin for Integrated Water Resource Management. RHAR2023. 3rd International Conference on RIVER HEALTH: ASSESSMENT TO RESTORATION (RHAR2023) at IIT BHU, 12-14 Oct 2023, Indian Institute of Technology, BHU, India.
Priya Khanda Debarghya Dey Sahoo, B. B (2023) Remote sensing based water quality monitoring in Chilika Lake. RHAR2023. 3rd International Conference on RIVER HEALTH: ASSESSMENT TO RESTORATION (RHAR2023) at IIT BHU, 12-14 Oct 2023, Indian Institute of Technology, BHU, India
Debanand Mahapatro Lipsita Choudhury Sahoo, B. B (2023) Environmental Flow Assessment of Mahanadi River. RHAR2023. 3rd International Conference on RIVER HEALTH: ASSESSMENT TO RESTORATION (RHAR2023) at IIT BHU, 12-14 Oct 2023, Indian Institute of Technology, BHU, India.
Lipsita Choudhury, Debanand Mahapatro, Sahoo, B. B (2023) Analysis of Hydrological alteration in Main river,Germany. RHAR2023. 3rd International Conference on RIVER HEALTH: ASSESSMENT TO RESTORATION(RHAR2023) at IIT BHU, 12-14 Oct 2023, Indian Institute of Technology, BHU, India.
- Pradhan S, Dash P K, Sahoo, B. B (2019) Uncertainty assessment of monthly inflow prediction using Monte Carlo simulation. Hydro 2019, International Conference (Hydraulics, Water Resources & Coastal Engineering), 18-20 Dec 2019, Osmania University, Hyderabad, India.
- Srikanth B, Selvarani G Sahoo, B. B (2019). Forecasting Monthly Discharge Using Machine Learning Techniques. International Conference on Smart Applications for Environmental Quality Assessment and Promoting Health Care Systems Using Internet of Things (ICSAIOT- 2019), 28 - 29 August 2019
- Sahoo, B. B., & Jha, R. (2018). Analysis of Trend in Low Flow Using Non Parametric Statistical Methods CLIMATE CHANGE AND WATER RESEARCH (C3WR) 9-11 Feb, 2018, Suresh Gyan Vihar University,
- Sahoo, B. B., & Jha, R. (2013). “Critical Analysis of drought indices in the KBK (Kalahandi, Bolangir and Koraput) Districts of Odisha”.National Seminar on “RECENT APPROACHES TO WATER RESOURCE
- Sahoo B.C, Swain J.B and Sahoo, B. B. (2012). Selection of Centrifugal Pumps for Various Categories of Farmers in Odisha” Livelihood and Environmental Security through Resource Conservation in. Eastern
Applied Hydrology Research
Applied Hydrology Research
Environmental Flow Modelling, River Engineering, Water Quality Modelling.
Watershed modeling, Crop water modeling, Irrigation water management.
Statistical Modelling: Copula, Drought & Flood modeling,
Multivariate Statistics
Non Stationary flood frequency analysis
Impacts of climate change on water resource
Application of Artificial Intelligence, Machine-learning techniques in Hydrology & Water Resources, AI on Climate change,AI in Agriculture
Application of Remote Sensing and GIS for Water resources.
Statistical Downscaling of Global Climate Models
Flood and drought Forecasting
Expert Talks
Expert Talks
A Novel Smoothing-Based Deep Learning Time-Series Approach for Daily Suspended Sediment Load Prediction. Deliver a lecture in the training course on "Machine Learning Techniques for Sustainable Water Resources Management", 18–22 August 2025, organized by the National Institute of Hydrology (NIH), Roorkee, Uttarakhand, India.
Rainfall-runoff Modelling using AI, Faculty Development Program on Interventions in Agricultural Engineering for Sustainable Agricultural Production and Processing (IAESAPP) 12th-16th March, 2024 at Department of Agricultural Engineering, School of Agricultural and BioEngineering, CUTM, Odisha.
Rainfall and runoff modelling of a watershed using AI techniques. Skill development training on GIS/RS, Modeling, and data analysis for the REWARD project stakeholders, during 5th-7th March, 2024, at ICAR-IISWC, RC, Sunabeda, Koraput, Odisha, India
Students Intern
Our Students at IIT BHU
Our Students @ NIT Warangal
HYDRO 2023
Our Students @ NIT Warangal
HYDRO 2023
Skill development training on GIS/RS, Modeling and data analysis for the REWARD project stakeholders” during 5th-7th March, 2024 at ICAR-IISWC, RC, Sunabeda, Koraput, Odisha
Expert Talk on Rainfall and runoff modelling using AI techniques
5th-7th March, 2024 at ICAR-IISWC, RC
GIS DAY 2023 CUTM
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