Multisensor Data Fusion and GIS-DRASTIC Integration for Groundwater Vulnerability Assessment With Rainfall Consideration

Abstract

In many areas of the world, particularly in arid and semi-arid regions, groundwater is the primary source of fresh water, and it supplies around one-third of the world's fresh water. Agriculture is the primary economic sector on the coast in the southern district (Nowshera). More food productivity is required due to the expanding population and diminishing agricultural lands, which increases the use of chemical pesticides and fertilizers in farming. The current study was conducted in northwestern parts of Pakistan to evaluate the impacts of the frequent use of pesticides and fertilizers in agricultural fields. Nine hydrogeological parameters were considered, and the GIS-based DRASTIC index was used to generate the final groundwater vulnerability map. The index map (ranging from 220 to 1980) was further classified into five classes based on index vulnerability: very low (220–345), low (346–670), moderate (671–730), high (731–1239), and very high (1240–1980). Nitrate and TDS, the two reliable and recognized scientific water quality measurements, have been used to validate the model. By regulating and controlling anthropogenic and agricultural pollution, the danger of contamination can be decreased. This research will aid in understanding the possible dangers and risks related to the usage of pesticides in agriculture and other industries. Furthermore, it will help identify the specific pesticides causing the contamination, assess the extent and severity of the contamination, and develop strategies to protect public health and the environment.

Keywords

• Agricultural management
• groundwater contamination
• multispectral data
• rainfall
• vulnerability