An Approach for Real-time Levee Health Monitoring Using Signal Processing Methods

Experience of using FEM for real-time flood early warning systems: Monitoring and modeling Boston levee instability

“…In the case of piping erosion in the dike, temperature sensors can provide warning information: decrease of local temperature value from expected soil temperature to the water temperature indicates that piping is occurring in the dike [33]. However piping has never been visually observed or sensor detected at this site.…”

“…• Development of a decision support system for public authorities and citizens that will help making informed decisions in case of emergency and in routine levee quality assessment, thus reducing flood risk and providing advanced tools for flood management. mechanisms [25][26][27], general design and implementation of an EWS [19,29], development of EWS components for simulation of dike breaching and flood spreading [15,21,22], city evacuation [28], and development of an artificial intelligence (AI) system employing data-driven methods [31,32] and its application in conjunction with the finite element analysis module [30,10,11].…”

“…Early warning systems may use the following methods for levee stability assessment: (a) data-driven methods for anomaly detection -machine learning, statistical methods (e.g., [36,33]; (b) reliability analysis based on empirical failure criteria which have been worked out in geotechnical practice during the past two hundred years [41]; (c) limit equilibrium analysis dated to the beginning of 20th century [12,4], et cetera), which is limited to slope slippage prediction only, and therefore is not generic enough to rely on in a general EWS design. A physical-model approach based on the numerical solution of differential equations describing soil deformations is the most generic and comprehensive method for levee stability analysis.…”

Real-time monitoring and forecasting of dike strength

“…Sensor networks to measure pore pressure, inclination and temperature proved to be useful to detect leakage of the Rhine levee [2]. Also, finite element models based on sensors data of tidal fluctuations of river level, pore pressure and temperature inside the levee have been used to assess the real-time stability of the Boston levee [3].…”

“…Sensor networks to measure pore pressure, inclination and temperature proved to be useful to detect leakage of the Rhine levee [2]. Also, finite element models based on sensors data of tidal fluctuations of river level, pore pressure and temperature inside the levee have been used to assess the real-time stability of the Boston levee [3].A model-based forecast of dike stability combines the forecast of water level at the dike with the strength properties of the dike. It consists of a chain of several models with data sequentially given from one model to the next one.…”