Applications of Remote Sensing, Geographic Information System and Geostatistics in the Study of Arsenic Contamination in Groundwater

Abstract

The arsenic-related groundwater problem is threatening huge areas in different countries like India, Bangladesh, China, Chile, Mexico etc. Arsenic contamination in ground water affects human health through its direct and indirect consumption. In order to combat this problem, an in-depth understanding of the background process of arsenic contamination is needed. Remote Sensing and Geographic Information System (GIS) offer a suitable solution for understanding and mapping the extent of the arsenic-infected areas. Various thematic maps on geomorphology, landuse/landcover, hydrology etc. can be prepared by interpreting remote sensing data, i.e. satellite imagery of the concerned area. These thematic maps can be further utilized to explore and discover relationships between that particular theme and the distribution of arsenic. Digital elevation models prepared using photogrammetric techniques utilizing Remote Sensing data may help in understanding the nature of distribution of arsenic-contaminated areas. GIS helps capturing, retrieving and analysing geospatial data. It recreates a real-world scenario and helps in analysing and creating new relevant information. In arsenic affected areas, people are exposed to arsenic contamination through its direct consumption with drinking water as well as through consumption of crops contaminated due to irrigation with arsenic rich groundwater. Risk and vulnerability assessment of such population can be done using GIS. Web-based GIS offers a unique opportunity of crowdsourcing and development of participatory public GIS. It can help in generation and analysis of distribution and assessment of impact of arsenic contamination and evolving mitigation strategy. Geostatistical methods help in interpolating the degree of arsenic contamination in unsampled locations as well as modelling uncertainty about unknown values. Initially experimental semivariograms are constructed and are fitted with suitable models like spherical, Gaussian etc. Various techniques of kriging are employed to interpolate level of arsenic contamination in unsampled 198 A. R. Ghosh and K. Parial locations using parameters obtained from variography. Zonation of arsenic contamination levels helps in the assessment of risk and vulnerability of residents of arsenic-contaminated areas and the development of efficient mitigation strategies.