wcm.02.2026.440.448

KUALA LUMPUR, 28 JULY 2026 —

Headline: wcm.02.2026.440.448 Lead: Details not yet available Body: This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

The aim of the study is to develop and implement an intelligent system for monitoring water quality in the Shavat Canal (Khorezm region, Republic of Uzbekistan) using sensor networks and artificial intelligence (AI) methods. In the course of the work, seasonal monitoring of hydrochemical parameters of water, including temperature, pH, electrical conductivity, dissolved oxygen, turbidity, nitrate (NO3) and phosphate (PO43-) concentrations was carried out. Multilayer neural networks (ANN), LSTM recurrent networks and Random Forest ensemble algorithms, which made it possible to predict the dynamics of water quality, detect anomalies and classify water state based on the WQI integral index. The results showed a pronounced seasonal dynamic of pollution with peak values in summer, the accuracy of WQI forecasting reached 94%. The introduction of the system makes it possible to increase the efficiency of decision-making, minimize environmental risks and contribute to the sustainable management of water resources in the region. The proposed approach has a high potential for scaling to other water bodies in Central Asia and integration into digital water management platforms. Source: Water Conservation and Management Published: 2026-07-22T08:23:15.000Z Region: OSINT Topic: Economy (AI-assisted rewrite, based on the original source)