Tarun Kumar Lohani | Environmental and Sustainable Materials | Best Academic Researcher Award

Prof. Tarun Kumar Lohani | Environmental and Sustainable Materials | Best Academic Researcher Award

Professor | Arba Minch University | India

Prof.  Tarun Kumar Lohani is a distinguished Professor at the Arba Minch Water Technology Institute (AWTI), Arba Minch University, Ethiopia, specializing in Water Technology, hydrological modelling, groundwater systems, climate-change–induced water challenges, GIS–based environmental analysis, and machine-learning applications in hydrology. With an extensive research portfolio comprising 119 scholarly documents, 1063 citations, an h-index of 16, and 31 i10-index publications, he has established himself as a leading contributor to contemporary water resource science and sustainability research.Prof. Lohani’s early work on construction materials, particularly the highly cited study on the optimum utilization of quarry dust as a partial replacement of sand in concrete 143 citations demonstrated his ability to bridge engineering materials research with green and cost-efficient construction practices. Over the years, his scholarship has evolved toward advanced hydrological systems climate resilience and watershed modelling. His research contributions span critical themes such as flood susceptibility mapping using multi-criteria decision-making and machine learning 70 citations groundwater quality assessment in Ethiopia’s major basins sediment transport modelling using HEC-RAS and the application of the WetSpass and SWAT models for surface–subsurface water balance and sediment yield simulations.A hallmark of his career is his strong interdisciplinary and international collaboration reflected in joint publications with researchers across India Ethiopia China and multiple global institutions. His work intersects water resource engineering environmental science remote sensing and emerging computational techniques. Notable contributions include hydrodynamic modelling of climate-change scenarios reservoir operation optimization MIKE11-NAM streamflow simulations for data-scarce regions LULC change detection using SVM and ANN models and the integration of metaheuristic and machine-learning approaches in agricultural and environmental systems.Through his research Prof. Lohani has significantly advanced understanding of sustainable water management climate-induced hydrological risks and water security in vulnerable regions. His work supports government agencies local communities and international stakeholders in improving disaster preparedness groundwater sustainability and environmental planning. Recognized for scientific rigor collaborative leadership and societal impact Prof. Lohani continues to contribute meaningfully to global water research and capacity building in the Horn of Africa.

Profiles : ORCID | Scopus | Google Scholar | ResearchGate

Featured Publications

1.Lohani, T. K., Padhi, M., Dash, K. P., & Jena, S. (2012). Optimum utilization of quarry dust as partial replacement of sand in concrete. International Journal of Applied Science and Engineering Research, 1(2), 391–404. Cited by : 143

2.Rakhra, M., Singh, R., Lohani, T. K., & Shabaz, M. (2021). Metaheuristic and machine learning-based smart engine for renting and sharing of agriculture equipment. Cited by : 82

3.Sharma, C., Amandeep, B., Sobti, R., Lohani, T. K., & Shabaz, M. (2021). A secured frame selection based video watermarking technique to address quality loss of data: Combining graph-based transform, singular value decomposition, and hyperchaotic. Cited By : 57

4.Yao, Q., Shabaz, M., Lohani, T. K., Bhatt, M. W., Panesar, G. S., & Singh, R. K. (2021). 3D modelling and visualization for vision-based vibration signal processing and measurement. Cited By : 57

5.Ukumo, T. Y., Abebe, A., Lohani, T. K., & Edamo, M. L. (2023). Flood hazard mapping and analysis under climate change using hydro-dynamic model and RCPs emission scenario in Woybo River catchment of Ethiopia.
Cited By : 32

Prof. Lohani’s work advances hydrological modelling and climate-resilient water management, providing scientifically robust tools that strengthen water security, disaster preparedness, and sustainable resource planning for vulnerable regions.