Edge-enabled GNSS-IR for efficient water level monitoring in harsh environments

Accurate water level monitoring in remote and harsh environments is critical for managing water resources, assessing climate impacts, and anticipating flood risks. Traditional in situ sensors often fail in these contexts due to corrosion, biofouling, or limited access for maintenance. Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) offers a passive, low-cost alternative by extracting water level information from multipath reflections of GNSS signals. However, using multi-constellation GNSS-IR for near real-time monitoring is challenging due to its high computational and communication demands, especially in low-power, low-connectivity areas.

This paper presents a novel edge computing-based GNSS-IR system designed for deployment in harsh environments. The system, validated in the highly saline La Mata–Torrevieja Natural Park (Spain), integrates a low-cost GNSS receiver and a modular gateway that executes the GNSS-IR processing locally. To efficiently transmit results over long distances, it uses the AlLoRa protocol, an advanced LPWAN solution optimized for high-throughput, low-power communication. By eliminating the need for raw data transmission and enabling local analytics, the system reduces bandwidth, enhances responsiveness, and supports continuous operation in constrained conditions. Experimental validation demonstrates the system’s effectiveness in achieving near real-time water level estimation with minimal infrastructure.