A Web GIS application to assess the groundwater vulnerability to pollution using the DRASTIC index

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Calheiros, R (Author) Other; Marques, JM (Author) FCUP; Ana Teodoro (Author) FCUP; Lia Duarte (Author) FCUP

Conference proceedings International

Title: ICGDA 2021: 4th International Conference on Geoinformatics and Data Analysis, Marseille, France, April 14-16, 2021

Pages: 41-45

4th International Conference on Geoinformatics and Data Analysis, ICGDA 2021

14 April 2021 through 16 April 2021

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-00V-S5Y

DOI: 10.1145/3465222.3465226

Abstract (EN): Groundwater is one of the most important natural resources in daily life. Geographical Information Systems (GIS)-based methods are commonly used to estimate groundwater vulnerability. There are several methods commonly used to estimate the groundwater vulnerability to pollution. DRASTIC is one of the methods most widely used. Several studies used GIS software to assess the groundwater vulnerability due to its easiness and simplicity to manipulate the spatial information. However, nowadays, with the evolution of web GIS applications, some methods start to be implemented in web mapping services in several research areas. Given the main interest in the assessment and study of the aquifer vulnerability, the main objective of this work was to present a new, simple, and intuitive web GIS application, DRASTIC Web GIS, based on the client-server model, that incorporates the DRASTIC index methodology to assess the groundwater vulnerability to pollution. The web GIS incorporates the input and parameters fields to obtain all the maps involved in the DRASTIC index methodology. DRASTIC Web GIS allows the user to view and interact at each step of creating the DRASTIC index map, also allowing to view and interact with the resulting map for each variable. It is free and open-source and it will be accessible to any user in the world. © 2021 Association for Computing Machinery.

Language: English

Type (Professor's evaluation): Scientific