Work

Next-Generation River Health Monitoring: Integrating AI, GIS, and eDNA for Real-Time and Biodiversity-Driven Assessment

Year: 2025

Type: article

Abstract: Freshwater ecosystems face escalating degradation, demanding real-time, scalable, and biodiversity-aware monitoring solutions. This review proposes an integrated framework combining artificial intelligence (AI), geographic information systems (GISs), and environmental DNA (eDNA) to overcome these limitations and support next-generation river health assessment. The AI-GIS-eDNA system was applied to four representative river basins—the Mississippi, Amazon, Yangtze, and Danube—demonstrating enhanced predictive accuracy (up to 94%), spatial pollution mapping precision (85–95%), and species detection sensitivity (+18–30%) compared to conventional methods. Furthermore, the framework reduces operational costs by up to 40%, highlighting its potential for cost-effective deployment in low-resource regions. Despite its strengths, challenges persist in the areas of regulatory acceptance, data standardization, and digital infrastructure. We recommend legal recognition of AI and eDNA indicators, investment in explainable AI (XAI), and global data harmonization initiatives. The integrated AI-GIS-eDNA framework offers a scalable and policy-relevant tool for adaptive freshwater governance in the Anthropocene.

Source: Hydrobiology

DOI: 10.3390/hydrobiology4030019

Authors: Su-Ok Hwang, Byeong-Hun Han, Hyo-Gyeom Kim, Baik-Ho Kim

Institutions: Hanyang University, Korea Environment Institute

Language: English

Topic: Environmental DNA in Biodiversity Studies

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Clean water and sanitation, Life on land

Open Access status: gold

Estimated APC paid: $1,207