Real-Time River Water Level Monitoring and Flood Alert System Using Esp32 and LoRa Technology

Nepal’s complex mountainous topography renders its river basins highly susceptible to devastating flash floods, yet existing monitoring infrastructure is often cost-prohibitive and technically limited in remote hilly regions. This paper presents a terrain-adaptive, real-time Flood Early Warning System (FEWS) utilizing a robust three-tier IoT architecture. The system employs ESP32 microcontrollers interfaced with JSN-SR04T waterproof ultrasonic sensors for non-contact water level detection. A key innovation of this research is the integration of a dedicated hill-top repeater station to overcome the Line-of-Sight (LoS) limitations of LoRa communication in non-linear, mountainous terrains. To ensure signal integrity, a 10-second median filtering algorithm was implemented, effectively eliminating false triggers from surface ripples or debris. Furthermore, a delta-based transmission strategy was utilized, reducing redundant MySQL database load by 98.2%. Experimental validation conducted across a multi-block campus environment confirms that the system achieves a 95% packet success rate in non-line-of-sight conditions and triggers multi-channel emergency alerts (SMS, Email, and localized Siren) with minimal latency. The proposed solution offers a low-cost, scalable, and power-efficient alternative for disaster risk reduction in the flood-prone watersheds of Nepal.