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Automated environmental compliance monitoring of rivers with IoT and open government data

  • Environmental monitoring of rivers is a cornerstone of the European Union's Water Framework Directive. It requires the estimation and reporting of environmental flows in rivers whose characteristics vary widely across the EU member states. This variability has resulted in a fragmentation of estimation and reporting methods for environmental flows and is exhibited by the myriad of regulatory guidelines and estimation procedures. To standardise and systematically evaluate environmental flows at the pan-European scale, we propose to formalise the estimation procedures through automation by reusing existing river monitoring resources. In this work, we explore how sensor-generated hydrological open government data can be repurposed to automate the estimation and monitoring of river environmental flows. In contrast to existing environmental flows estimation methods, we propose a scalable IoT-based architecture and implement its cloud-layer web service. The major contribution of this work is the demonstration of an automated environmental flows system based on open river monitoring data routinely collected by national authorities. Moreover, the proposed system adds value to existing environmental monitoring data, reduces development and operational costs, facilitates streamlining of environmental compliance and allows for any authority with similar data to reuse or scale it with new data and methods. We critically discuss the opportunities and challenges associated with open government data, including its quality. Finally, we demonstrate the proposed system using the Estonian national river monitoring network and define further research directions.

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Metadaten
Document Type:Article
Language:English
Author(s):Lizaveta Miasayedava, Keegan McBride, Jeffrey Andrew Tuhtan
Parent Title (English):Journal of Environmental Management
Publication year:2022
Publishing Institution:Hertie School
DOI:https://doi.org/10.1016/j.jenvman.2021.114283
Release Date:2023/02/07
Volume:303
Issue:114283
Hertie School Research:Centre for Digital Governance
Licence of document (German):Metadaten / metadata
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