Session: 14-02: Applications and Reliability of Sensors

Paper Number: 145950

145950 - Distributed Real-Time Soil Saturation Assessment in Levees Using a Network of Wireless Sensor Packages With Conductivity Probes 

Levees play a critical role in safeguarding communities and assets from flooding, acting as essential defenses against the devastating impacts of inundation. Yet, earthen levees, in particular, are prone to breaches, especially in the face of swift floodwaters. Sensor networks offer the potential to generate spatial maps illustrating soil moisture levels. Long-term monitoring of these spatial maps could identify the identification of vulnerable zones or provide an understanding of how climate change affects levee stability. This study presents an investigation into wireless communication for a network of UAV-deployable smart sensing spike packages aimed at assessing soil conductivity levels in sand-filled embankments crucial for determining soil saturation. The developed smart sensing spikes consist of a spike that penetrates into the ground and measures conductivity between two electrically conductive contacts. The smart sensing spike consists of microprocessors for edge computing, and wireless data communication systems that report data to a way station in real-time. To validate the efficacy of the developed sensors, a flume test is developed as a replica of a levee and monitored under controlled water flow conditions.

The analysis of data from different time stamps revealed the progression of moisture throughout the earthen embankment. Initially, the soil is almost dry. As the controlled water flow proceeds, the area becomes progressively partially saturated, with the final stage showing a dominant presence of saturated soil. The collected data sampled at the measurement points is expanded to a continuous moisture profile using kriging. Gaussian kriging, also known as ordinary kriging, is one of the commonly used variants of the kriging method. In Gaussian kriging, the estimation of values at unsampled locations is based on a linear combination of nearby data points, with weights determined by their spatial relationships. The Gaussian assumption implies that the errors in the estimation process follow a normal distribution. Overall, Gaussian kriging offers a powerful tool for sensor value interpolation over a space, providing accurate estimates while quantifying the inherent uncertainty in the estimation process. There are similarities between the soil conditions seen during the experiment's moisture movement phase and the moisture level estimates obtained using kriging analysis of the moisture profile. Through analysis of data collected at various time intervals, researchers track the propagation of moisture within the levee. This knowledge can lead to insights for predicting vulnerable areas and preempting potential failures. Overall, this study paves the way for further development of a wireless network of sensing spike packages as a UAV-deployable system for levee health assessment and improved infrastructure management.

Presenting Author: Austin r.j. Downey University of South Carolina

Presenting Author Biography: I am an Associate Professor at the University of South Carolina, Department of Mechanical Engineering, Department of Civil and Environmental Engineering.

Authors:

Puja Chowdhury University of South Carolina
James Crews University of South Carolina
Ayman Mokhtar University of South Carolina
Sai Durga Rithvik Oruganti University of South Carolina
Ryan Van Wyk University of South Carolina
Austin r.j. Downey University of South Carolina
Malichi Flemming University of South Carolina
Jason D. Bakos University of South Carolina
Jasim Imran University of South Carolina
Sadik Khan Jackson State University