Advanced Continuous Monitoring System—Tools for Water Resource Management and Decision Support System in Salt Affected Delta

Author:

Reljić Marko1,Romić Marija1ORCID,Romić Davor1ORCID,Gilja Gordon2ORCID,Mornar Vedran3,Ondrasek Gabrijel1ORCID,Bubalo Kovačić Marina1ORCID,Zovko Monika1ORCID

Affiliation:

1. Department of Soil Amelioration, Faculty of Agriculture, University of Zagreb, Svetosimunska 25, 10000 Zagreb, Croatia

2. Department of Hydroscience and Engineering, Faculty of Civil Engineering, University of Zagreb, Fra Andrije Kacica Miosica 26, 10000 Zagreb, Croatia

3. Department of Applied Computing, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia

Abstract

The greatest environmental problem facing the world today is climate change, with a rise in sea level being one of the most important consequences, especially in low-lying coastal areas, such as river deltas where changes are exacerbated by human impacts, leading to increased seawater intrusion into coastal aquifers and the degradation of water quality. Water quality monitoring systems are being developed and deployed to monitor changes in the aquatic environment. With technological progress, traditional sampling-based water monitoring has been supplemented with sensors and automated data acquisition and transmission devices, resulting in the automation of water quality monitoring systems. This paper reviews the recent development and application of automated continuous water quality monitoring systems. It also draws on the results of our own experience in implementing such a system in the Neretva River Delta on the Croatian Adriatic coast. The installed system provides (near) real-time data on parameters such as temperature, pH, EC, TDS, and DO in the water, as well as a number of soil and weather variables, with data available at a high frequency through a developed database and web portal for various stakeholders. Continuous monitoring enables the collection of big data that can be used to develop models for predictions of water quality parameters and to develop guidelines for future management.

Funder

European Regional Development Fund

Environmental Protection and Energy Efficiency Fund of the Republic of Croatia

Publisher

MDPI AG

Subject

Plant Science,Agronomy and Crop Science,Food Science

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