Contact Dr Basant Yadav
Areas of expertise
- Water Science and Engineering
Basant Yadav completed a two year Master degree at the Indian Institute of Technology Roorkee in Hydrology. The Master's Dissertation was done at the Technical University Stuttgart, Germany. This was followed by a PhD at the Indian Institute of Technology Delhi studying water quantity and quality modeling. Basant was awarded a prestigious National Postdoctoral Fellowship (NPDF) by the Department of Science and Technology (India) in 2017. Basant started as a Research Fellow at Cranfield University in July 2018.
Keen to work with people on emerging contaminates, geogenic contaminants and groundwater modelling/management.
Basant's research emphasizes the integration of experimental, numerical and data-based modeling approaches for the better and efficient management of the groundwater quantity and quality. His work uses a range of numerical, statistical, and stochastic modeling approaches and experimental work to analyze the fate and transport of contaminant in saturated and unsaturated zones.
Basant yadav currently working on a project titled "Impact of rainwater harvesting in India on groundwater quality with specific reference to fluoride and micropollutants".
Articles In Journals
- Gupta PK & Yadav B (2020) Leakage of CO2 from geological storage and its impacts on fresh soil–water systems: a review, Environmental Science and Pollution Research, Available online 3 March 2020 (12).
- Yadav B, Gupta PK, Patidar N & Himanshu SK (2020) Ensemble modelling framework for groundwater level prediction in urban areas of India, Science of the Total Environment, 712 (April) Article No. 135539.
- Gupta PK, Yadav B & Yadav BK (2019) Assessment of LNAPL in subsurface under fluctuating groundwater table using 2D sand tank experiments, Journal of Environmental Engineering, 145 (9).
- Himanshu SK, Pandey A, Yadav B & Gupta A (2019) Evaluation of best management practices for sediment and nutrient loss control using SWAT model, Soil and Tillage Research, 192 (September) 42-58.
- Yadav B & Mathur S (2018) River discharge simulation using variable parameter McCarthy–Muskingum and wavelet-support vector machine methods, Neural Computing and Applications, 32 (7) 2457-2470.
- Khwairakpam E, Khosa R, Gosain A, Nema A, Mathur S & Yadav B (2018) Modeling simulation of river discharge of Loktak Lake catchment in Northeast India, Journal of Hydrologic Engineering, 23 (8).
- Yadav B, Mathur S, Ch S & Yadav B (2018) Simulation-optimization approach for the consideration of well clogging during cost estimation of in situ bioremediation system, Journal of Hydrologic Engineering, 23 (3).
- Yadav B, Mathur S, Ch S & Yadav B (2018) Data-based modelling approach for variable density flow and solute transport simulation in a coastal aquifer, Hydrological Sciences Journal, 63 (2) 210-226.
- Himanshu S, Pandey A & Yadav B (2017) Assessing the applicability of TMPA-3B42V7 precipitation dataset in wavelet-support vector machine approach for suspended sediment load prediction, Journal of Hydrology, 550 (July) 103-117.
- Himanshu S, Pandey A & Yadav B (2017) Ensemble wavelet-support vector machine approach for prediction of suspended sediment load using hydrometeorological data, Journal of Hydrologic Engineering, 22 (7).
- Yadav B & Eliza K (2017) A hybrid wavelet-support vector machine model for prediction of Lake water level fluctuations using hydro-meteorological data, Measurement, 103 (June) 294-301.
- Yadav B, Ch S, Mathur S & Adamowski J (2017) Assessing the suitability of extreme learning machines (ELM) for groundwater level prediction, Journal of Water and Land Development, 32 (1) 103-112.
- Yadav B, Ch S, Mathur S & Adamowski J (2016) Estimation of in-situ bioremediation system cost using a hybrid Extreme Learning Machine (ELM)-particle swarm optimization approach, Journal of Hydrology, 543 (December) 373-385.
- Yadav B, Ch S, Mathur S & Adamowski J (2016) Discharge forecasting using an Online Sequential Extreme Learning Machine (OS-ELM) model: A case study in Neckar River, Germany, Measurement, 92 433-445.
- Yadav B, Perumal M & Bardossy A (2015) Variable parameter McCarthy-Muskingum routing method considering lateral flow, Journal of Hydrology, 523 489-499.