Arghadyuti Banerjee

PhD Student / PEM Student Researcher

Faculty of Engineering & Design


Research Topic: Tracking dynamic time-dependent groundwater vulnerability using satellite scatterometer observations and land-use stochastic models

Arghadyuti is a doctoral student in the School of Engineering of IT Sligo he holds a Bachelor’s degree in Geography (Hons) and a Master’s degree in Remote Sensing and Geographic Information Systems (GIS). His main research focus concentrates on how to deal with pragmatic socio-environmental issues for the betterment of environmental and social health.

His research interests include biodiversity, natural hazards, natural environment and society, climate change, land-use change, environmental degradation,  natural resources and geospatial technology. Arghdyuti has a strong background in earth observation systems and Geographic Information System (GIS) applications. For his master’s thesis, he wanted to get a better understanding of the impact of a tropical cyclone (‘Aila’) on the deltaic environment as well as on the socio-economy.

Before joining IT Sligo for his doctoral research programme, Arghadyuti worked with many research and development organisations in India (CSIR-IHBT, Forest Survey of India, CSIR-NISCAIR and CSIR-CRRI) and gained knowledge in the field of remote sensing data analysis, geospatial technology, and big data handling. Arghadyuti is pursuing his PhD research on groundwater contamination under the supervision of Dr Salem Gharbia and Dr Leo Creedon at IT Sligo and Dr Noelle Jones from GMIT.

PhD Research Topic:

Tracking dynamic time-dependent groundwater vulnerability using satellite scatterometer observations and land-use stochastic models.

Tracking time-dependent variables is an innovative approach to investigate the evaluation of contamination of groundwater (GW) by non-point sources and to forecast future trends. Therefore, it is important to recognise the cause-effect relationship between temporal changes in GW quality of both natural and anthropogenic factors. This effort will impose a breakthrough advancement in mapping hazardous areas as well as the efficiency in land use planning for groundwater protection.

For this study, Arghadyuti chose nitrate concentration as the response variable. Nitrate, as an abundant contaminant of GW, is an effective indicator of groundwater contamination. The trend of GW contamination will be identified by the analysis of sufficient temporal monitoring of nitrate concentration in GW over a long period. The main aim of this study is to develop a framework/decision support tool that will generate different probabilistic groundwater contamination scenarios considering nitrate as an indicator.

The study will integrate remote sensing, Geographic Information System (GIS) and statistical methods to assess the efficacy of land use planning for groundwater protection. Both natural and anthropogenic factors will be used as evidential themes for the analysis. Nitrogen loading derived from urban areas cannot be easily and directly estimated quantitatively, so other variables like population density will be explored as a proxy for nitrate quantity. Population density will be calculated from census data. Radar satellite images will be used to identify and delineate urban areas. Soil Moisture Active Passive (SMAP) datasets will be analysed to trace the spatiotemporal changes in land cover and soil moisture as an important component for monitoring soil nutrient changes over time.

Temporal multispectral images and very high-resolution optical datasets will be employed to get information on geology, hydrogeology and land use. Other spatial and non-spatial datasets to be studied describe surface conditions (e.g. lithology, soil characteristics), subsurface (e.g. unsaturated zones), underground (e.g. aquifer characteristics), topography, catchments, precipitation and GW recharge etc. After the completion of digital image processing of remotely sensed images and digitization of spatial layers (using ERDAS - Earth Resources Data Analysis System which is a satellite image processing software) all thematic layers will be analysed in the GIS platform (using ArcGIS which is a platform for geographic information system, which can do geospatial analysis, play with geographic information, and produce maps and graphical representations.) for the further validation of the model.

Finally, a geostatistical modelling approach (using R - which is a programming language for geostatistical computing and graphics) will be developed to analyse the groundwater volume and quality fluctuations under different scenarios of climate change and land use. The outcome of this study will provide policymakers with a tool to link groundwater pollution risk and time-dependent drivers.


Projects handled:

  1. Bioresource Inventorization with a focus on bioprospecting of Pteridophytes of Western Himalaya.

  2. Vulnerability Assessment and Development of Adaptation Strategies for Climate Change Impact with Special Reference to Coasts and Island Ecosystems of India.

  3. Multi-criteria Based Landslide Hazard Evaluation Study Using Spatio-temporal Data- A case study of Munnar Watershed, India

Research Outputs:

  1. Pankaj Gupta, Arghadyuti Banerjee, Neelam J. Gupta (2020). Spatio-temporal Study on Changing Trend of Land Use and Land Cover Pattern in Munnar area, Idukki District, Western Ghats, India, Indian Journal of Geo Marine Sciences. Vol. 49 (06): 1055-1067. (SCI Journal)

  2. Arghadyuti Banerjee, Mamta Devi, Akshay Nag, Ram Kumar Sharma, Amit Kumar (2017). Modelling Probable Distribution of Podophyllum hexandrum In North-Western Himalaya, Indian Forester. 143 (12):1255-1259. (Peer Reviewed Journal)

  3. Alka Kumari, Arghadyuti Banerjee, Amit Kumar (2018). Distribution and species richness of ferns along an elevational gradient in Himachal Pradesh, Western Himalaya. Pteridology Today: Challenges and Opportunities, Proceedings of the Symposium held at BSI, WRC, Pune, pp-361-377. (Conference paper)

  4. J Sundaresan, Arghadyuti Banerjee, Mutum Ibomcha Singh, Upasana Datta, Abhijit Mitra (January 2017). Can the estuarine salinity of Indian Sundarbans be a potential proxy to climate change? Environmental Coastguards: Understanding Mangrove Ecosystem and Carbon Sequestration. Pages 234-248, ISBN 978-81-7236-352-9. (Book Chapter)

  5. Arghadyuti Banerjee, Alka Kumari, Brij Lal, Amit Kumar (December 2014). Using geospatial techniques for mapping of the potential distribution of Diplazium esculentum (Retz.) Sw. In Kangra region of Himachal Pradesh. Proceeding on National Conference on Modern Approaches to Pteridophytes: Biology, Biodiversity and Bioresources, CSIR-IHBT, Palampur, Himachal Pradesh, India, December 20th-21st, Page-41. (Abstract).

  6. An assessment on Physico-cultural status of selected blocks of Sundarban at post Aila phase using geo-informatics techniques (M.Sc. Dissertation)


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