Flood Detection

Published on November 02, 2025

By B.E. Alejandro

Introduction and Justification

The state of Hidalgo (Mexico) faces a critical, recurring water-risk problem, showing up as flooding from overflowing rivers and dams. This is made worse by the lack of constant monitoring systems and the absence of a robust, accessible Early Warning System (EWS) for the population in at-risk areas.

Every intense rainy season, thousands of Mexican families — particularly in Hidalgo — are affected by these overflows, resulting in loss of life and property. A tragic, emblematic example was the Tula river flood in September 2021, where the overflow reached up to two meters in height, affecting more than 2,500 homes and taking the lives of 17 people at the IMSS General Hospital (HGZ) No. 5 in Tula de Allende 1, 2.

The municipalities identified as most vulnerable to this type of event include Tula de Allende, Huehuetla, Tianguistengo, and other areas of the Huasteca and the Sierra Hidalguense 3, 4. In addition, the management of reservoirs such as the La Esperanza Dam (which has reached 100% of its capacity) and the Tejocotal Dam (at risk of overflowing during high-precipitation seasons) underscores the urgent need for real-time monitoring 5.

Proposed Solution: A Flood Detection System Based on Meshtastic/LoRa

This project proposes a Flood Detection and Early Warning System (SAT-I) using Meshtastic mesh-networking technology over long-range, low-power radio infrastructure (LoRa). The system is designed to operate autonomously and resiliently, even if conventional communication networks (mobile telephony or Wi-Fi) go down 6.

Components and Operation

Water Level Detection:

Industrial-grade ultrasonic sensors with accuracy of up to ±1 cm will be used for continuous water-level measurement in rivers or dams.
These sensors will be housed in a hermetic enclosure, ensuring resistance to corrosion and extreme environmental conditions.

Autonomous Communication (Meshtastic/LoRa):

Sensor data will be transmitted through LoRa modules running the Meshtastic firmware. This technology uses long-range, low-power radio waves, enabling off-grid communication (outside the electrical or telecom grid) over distances of several kilometers.
Meshtastic’s mesh network nature lets every node act as a repeater, extending the system’s range and redundancy. If one node fails, information can be relayed by other nodes on the network.

Early Warning and Additional Applications:

The system will not only detect imminent overflows, but can also be adapted to detect droughts by monitoring minimum levels, aiding water management in dams or rural areas.
Alerts can be sent to portable devices (such as smartphones running the Meshtastic app) or to local alarm systems, ensuring an early evacuation of the population.

Minimum Requirements for the Prototype

An initial monitoring node and its repeater require:

Component	Quantity	Function
LoRa/Meshtastic Modules	2	Autonomous communication nodes (one for the sensor, one as receiver/gateway).
Ultrasonic Sensors	2	Precise (±1 cm) water-level measurement.
Autonomous Repeater	1	Additional node with solar power to extend the mesh network’s range.

Deployment Considerations

Deployment of the system must be preceded by a detailed topographic study. This study is crucial to:

Determine the optimal location of nodes and repeaters to maximize the LoRa network’s range.
Establish alert thresholds based on the area’s topography and historical overflow levels.

All repeaters should be autonomous and solar-powered, taking advantage of LoRa’s energy efficiency and low power consumption.

Scalability and Additional Applications: Benefits for Agriculture

The modular, resilient architecture of the Meshtastic/LoRa-based SAT-I system allows for immediate scalability to integrate other sensors and data sources, extending its usefulness beyond flood prevention. Since Hidalgo is a state with a significant agricultural sector, this scalability offers direct benefits to the primary sector.

Integrating Weather Systems for Rainfall Prediction

This project proposes integrating autonomous weather stations (solar-powered and equipped with precipitation, temperature, and humidity sensors) that also use the Meshtastic/LoRa network for data transmission.

Additional Data	Benefit for Flood Prevention	Benefit for Agriculture
Accumulated Rainfall	Allows modeling of soil saturation and predicting river flow with greater precision, improving early-warning lead time.	Helps farmers optimize irrigation and plan planting and harvesting based on water availability.
Temperature and Humidity	Provides context for predicting intense storms and hydro-meteorological phenomena.	Facilitates pest and disease management, and optimizes growing conditions for specific crops.

By sending this data over the mesh network, a decentralized, robust environmental information system is created. Combining weather forecasting (rainfall data) with real-time hydrological monitoring (water level) provides a much more complete analytical tool for disaster prevention.

Conclusion

Integrating precision sensors with the resilient Meshtastic/LoRa communication network offers an autonomous, self-sufficient solution for early detection of water-related risks in Hidalgo. This approach not only addresses the vulnerability of conventional networks, but also provides a vital tool for safeguarding the population and protecting their property against an imminent overflow.