Abstract
Real-time identification of irrigation water pollution sources and pathways (PSP) is crucial to ensure both environmental and food safety. This study uses an integrated framework based on the Internet of Things (IoT) and the blockchain technology that incorporates a directed acyclic graph (DAG)-configured wireless sensor network (WSN), and GIS tools for real-time water pollution source tracing. Water quality sensors were installed at monitoring stations in irrigation channel systems within the study area. Irrigation water quality data were delivered to databases via the WSN and IoT technologies. Blockchain and GIS tools were used to trace pollution at mapped irrigation units and to spatially identify upstream polluted units at irrigation intakes. A Water Quality Analysis Simulation Program (WASP) model was then used to simulate water quality by using backward propagation and identify potential pollution sources. We applied a “backward pollution source tracing” (BPST) process to successfully and rapidly identify electrical conductivity (EC) and copper (Cu2+) polluted sources and pathways in upstream irrigation water. With the BPST process, the WASP model effectively simulated EC and Cu2+ concentration data to identify likely EC and Cu2+ pollution sources. The study framework is the first application of blockchain technology for effective real-time water quality monitoring and rapid multiple PSPs identification. The pollution event data associated with the PSP are immutable.
Highlights
Illegal wastewater discharge due to rapid industrialization has resulted in heavy metal contamination in farmlands via irrigation channels
We developed a framework for pollution source tracing comprised of an Internet of Things (IoT) real-time monitoring system with sensors which form a WNS (Figures 1–4) arranged as a directed acyclic graph (DAG); a blockchain real-time data tracing platform; a geographic information system (GIS) spatial tracing tool; and a Water Quality Analysis Simulation Program (WASP) model (Figure 1)
While blockchain’s distributed ledger technology allows all users to record transactions in a decentralized data log built on a peer-to-peer internet, a wireless sensor network (WSN) provides real-time remote monitoring data for high-quality production and processing systems with various sensors that are applicable in different fields of study
Summary
Illegal wastewater discharge due to rapid industrialization has resulted in heavy metal contamination in farmlands via irrigation channels. Rapid identification of irrigation water pollution sources and pathways (PSP) is key to managing irrigation water quality for agricultural production, it is an extremely difficult task in agricultural areas that are located within industrialized areas [4,5,6]. A real-time water quality monitoring network can collect water quality information at set (or at network) locations in real-time (or at regular intervals) and can provide monitoring data for both current status analysis and water quality trend forecasts. Potential pollution sources can be identified [7,8], enabling the emergency disposal of pollutants in contaminated areas [9]. A system that allows PSP tracing is essential to providing authorities with real-time documentation
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