Abstract
Earthen levees are crucial flood defense systems but are susceptible to failure due to internal erosion and saturation-induced instability, potentially causing breaches and endangering lives, infrastructure, and ecosystems in protected areas. Understanding soil saturation dynamics is vital for improved monitoring and resilience. This study presents a novel method of levee health monitoring by deploying a wireless sensor network consisting of nine small sensing spike packages with long-term UAV-deployability potential. In-package pressure, temperature, humidity, and—most importantly—soil conductivity are all measured by the suite of environmental sensors integrated into each spike package. This integrated sensing capability gives spatiotemporal information about the embankment’s subsurface moisture conditions. A 2 m long, 1 m wide, and 0.45 m tall sand-filled embankment replica was built for a controlled flume experiment to verify the system, enabling close examination of moisture permeability and propagation. The deployment of cutting-edge analytical methods for data interpretation is one of this study’s main contributions. Discrete conductivity measurements were converted into continuous, two-dimensional maps of moisture propagation using interpolation techniques, namely radial basis function (RBF). This makes it possible to see the changing moisture front inside the embankment structure in detail. Important information about early warning signs of possible instability (piping failures) is provided by this combined analytical framework. Using a network of nine wireless sensing spike packages, the proposed framework monitored moisture propagation within a 2 m long earthen embankment over a 105 min lab experiment and identified resistance changes associated with piping-like seepage behavior at approximately 19 min and 34 min, which exited approximately 10 min after detection. However, only seven of the nine packages produced viable readings. Improving flood risk forecasting models, improving infrastructure health monitoring applications, and guiding the development of more resilient levee systems are all directly impacted by this. This study demonstrates the potential in autonomous levee monitoring and management given that it combines robust spatial analytics and an interpolation method with inexpensive, quickly deployable sensing technology.