An Open, Multi-Sensor, Dataset of Water Pollution of Ganga Basin and its Application to Understand Impact of Large Religious Gathering

TL;DR

This paper introduces a comprehensive multi-sensor water pollution dataset for the Ganga Basin, enabling analysis of pollution impacts during large religious gatherings and supporting water management efforts in India.

Contribution

It provides an open, multi-modal water pollution dataset from diverse sources, including real-time sensors, lab results, and community inputs, accessible via an API platform.

Findings

Analyzed pollution impact during the 2016 religious gathering.

Demonstrated the dataset's utility for real-time water quality monitoring.

Enabled community contributions to water pollution data.

Abstract

Water is a crucial pre-requisite for all human activities. Due to growing demand from population and shrinking supply of potable water, there is an urgent need to use computational methods to manage available water intelligently, and especially in developing countries like India where even basic data to track water availability or physical infrastructure to process water are inadequate. In this context, we present a dataset of water pollution containing quantitative and qualitative data from a combination for modalities - real-time sensors, lab results, and estimates from people using mobile apps. The data on our API-accessible cloud platform covers more than 60 locations and consists of both what we have ourselves collected from multiple location following a novel process, and from others (lab-results) which were open but hither-to difficult to access. Further, we discuss an application of released data to understand spatio-temporal pollution impact of a large event with hundreds of millions of people converging on a river during a religious gathering (Ardh Khumbh 2016) spread over months. Such unprecedented details can help authorities manage an ongoing event or plan for future ones. The community can use the data for any application and also contribute new data to the platform.