Accurate real-time forecasts of inundation depth and extent during typhoon flooding are crucial to disaster emergency response. To manage disaster risk, the development of a flood inundation forecasting model has been recognized as essential. In this paper, a forecasting model by integrating a hydrodynamic model, k-means clustering algorithm and support vector machines (SVM) is proposed. The task of this study is divided into four parts. First, the SOBEK model is used in simulating inundation hydrodynamics. Second, the k-means clustering algorithm classifies flood inundation data and identifies the dominant clusters of flood gauging stations. Third, SVM yields water level forecasts with 1–3 h lead time. Finally, a spatial expansion module produces flood inundation maps, based on forecasted information from flood gauging stations and consideration of flood causative factors. To demonstrate the effectiveness of the proposed forecasting model, we present an application to the Yilan River basin, Taiwan. The forecasting results indicate that the simulated water level forecasts from the point forecasting module are in good agreement with the observed data, and the proposed model yields the accurate flood inundation maps for 1–3 h lead time. These results indicate that the proposed model accurately forecasts not only flood inundation depth but also inundation extent. This flood inundation forecasting model is expected to be useful in providing early flood warning information for disaster emergency response.

Piers with back-to-back stems or columns and piers for which part of the foundation becomes exposed as a result of the development of scour over large periods of time or because of severe flood events are fairly common at bridge waterways. The present paper uses eddy-resolving numerical simulations to study flow and turbulence structure at piers of complex shape and/or with multiple components. In particular, the study considers cases with one and two back-to-back pier columns for which the section of the main column is neither circular nor rectangular. In addition to a design case for which the foundation of each pier column is submerged, the study analyzes a case when scour exposes part of the foundation of the main column. The results show that the shape and size of the pier column have a significant effect on the spatial and temporal distributions of the bed friction velocity induced by the horseshoe vortex system. The large-scale shedding behind the main column greatly influences flow structu...

Scour failures tend to occur suddenly and without warning. Hydraulic scouring is one of the major factors in bridge failure. Bridges that are subject to periodic flooding should be monitored during high‐flow seasons for the safety of the public. Wireless sensor networks have been applied widely, and in many fields. In this study, micro‐electro‐mechanical system (MEMS) pressure sensors are integrated with the wireless Zigbee network on a sensor board for real‐time bridge scour monitoring. A wireless MEMS scour monitoring system has been developed and tested in the laboratory. This system can measure the scouring/deposition process and the variations of water levels at a bridge pier. A scour model is employed to calculate the scour‐depth evolution and validated with real‐time measured data. The results indicate that the proposed system has potential applicability to monitor scour evolution in the field.

Scour around bridge piers remains the leading cause of bridge failure induced in flood. Floods and torrential rains erode riverbeds and damage cross-river structures, causing bridge collapse and a severe threat to property and life. Reductions in bridge-safety capacity need to be monitored during flood periods to protect the traveling public. In the present study, a scour monitoring system designed with vibration-based arrayed sensors consisting of a combination of Internet of Things (IoT) and artificial intelligence (AI) is developed and implemented to obtain real-time scour depth measurements. These vibration-based micro-electro-mechanical systems (MEMS) sensors are packaged in a waterproof stainless steel ball within a rebar cage to resist a harsh environment in floods. The floodwater-level changes around the bridge pier are performed using real-time CCTV images by the Mask R-CNN deep learning model. The scour-depth evolution is simulated using the hydrodynamic model with the selected local scour formulas and the sediment transport equation. The laboratory and field measurement results demonstrated the success of the early warning system for monitoring the real-time bridge scour-depth evolution.

The temporal effect of hydrograph on local scour depth is investigated under clear-water scour condition. By analyzing the characteristics of scour-depth evolutions at bridge piers for different rising hydrographs, a relation for estimating the maximum scour depth in uniform sediment is proposed. In the relation, the flow unsteadiness effect is taken into account by an unsteady flow parameter combining the peak-flow intensity and time-to-peak factors. For nonuniform sediment with $d_{84}$ employed as the effective sediment size, this relation can yield reasonably good results of the maximum scour depth under rising hydrograph.

Sustainable water resources of reservoirs depend on preserving the valuable storage capacity. Sediment management is a crucial task in reservoir operations. Extreme floods caused by typhoon events have brought a massive amount of sediments from the watershed of Shihmen Reservoir in Taiwan. In the case study of Shihmen Reservoir, the primary purpose of the sediment management strategies is to minimize sediment deposition and recover reservoir capacity. Two assessment indexes, the capacity–inflow ratio (CIR) and the capacity–sediment ratio (CSR) are investigated to provide a feasible assessment of desilting techniques. Three desilting projects have been planned and implemented in progress, including one modified power plant penstock and two desilting tunnels. Without effective sediment management strategies, the projected storage capacity may drop to 32.9% of the initial storage capacity in the next fifty years. On the other hand, if sediment management is implemented as per the project schedule, 70.3% of the initial storage capacity may be retained, enabling the provision of sustainable water supplies to meet projected water demands. In investigating the impacts caused by the desilting operations, the floodwater level and riverbed variations along the downstream river of the dam are simulated by the hydromorphological model. From simulated results, the downstream river morphology may adjust toward the equilibrium state under the long-term desilting operations of Shihmen Reservoir. Although relatively high sediment concentration is released during the desilting operation, it decays gradually along the downstream river. In addition, riverbed deposition does not significantly affect the floodwater level caused by the increment of riverbed elevation in desilting operations.