Towards a Digital Twin for a Drinking Water Source in Norway

Abstract

Contamination of drinking water supplies by runoffs, wastewater discharge and other anthropogenic sources has potentially dire consequences for human health and the environment. Surface water bodies are especially vulnerable to such contamination. Water quality digital twins which combine hydrodynamic modeling and fusion of data from networked “internet of things” (IOT) sensors have been proposed as a solution to facilitate more rapid detection and response to contamination. This paper proposes an online dashboard as a primary user interface for a novel water reservoir digital twin architecture using data collected by IOT devices, including unmanned water quality monitoring platform and surface vessels (USVs), The integration of a comprehensive hydrodynamic water quality model with the sensing devices facilitates the validation of a high-resolution model of all water quality parameters. Data is shared between the sensors, model, and an online database allowing for the water reservoir's status and input data to be visualized on an online platform. Emphasis is placed on the system components which communicate the sensing and modeling outputs to users, since development and testing of other components is ongoing.