Typhoon-induced storm surges are catastrophic disasters in coastal areas worldwide, although typhoon surges are not extremely high in Taiwan. However, the rising water level around an estuary could be a block that obstructs the flow of water away from the estuary and indirectly forms an overflow in the middle or lower reaches of a river if the occurrence of the highest storm surge (HSS) coincides with the highest astronomical tide (HAT). Therefore, assessing the highest storm tide (HST, a combination of the HSS and HAT) hazard level along the coast of Taiwan is particularly important to an early warning of riverine inundation. This study hindcasted the storm surges of 122 historical typhoon events from 1979 to 2018 using a high-resolution, unstructured-grid, surge-wave fully coupled model and a hybrid typhoon wind model. The long-term recording measurements at 28 tide-measuring stations around Taiwan were used to analyze the HAT characteristics. The hindcasted HSSs of each typhoon category (the Central Weather Bureau of Taiwan classified typhoon events into nine categories according to the typhoon’s track) were extracted and superposed on the HATs to produce the individual potential HST hazard maps. Each map was classified into six hazard levels (I to VI). Finally, a comprehensive potential HST hazard map was created based on the superposition of the HSSs from 122 typhoon events and HATs.

In Taiwan, the coastal hazard from typhoon-induced storm waves poses a greater threat to human life and infrastructure than storm surges. Therefore, there has been increased interest in assessing the storm wave hazard levels for the nearshore waters of Taiwan. This study hindcasted the significant wave heights (SWHs) of 124 historical typhoon events from 1978 to 2017 using a fully coupled model and hybrid wind fields (a combination of the parametric typhoon model and reanalysis products). The maximum SWHs of each typhoon category were extracted to create individual storm wave hazard maps for the sea areas of the coastal zones (SACZs) in Taiwan. Each map was classified into five hazard levels (I to V) and used to generate a comprehensive storm wave hazard map. The results demonstrate that the northern and eastern nearshore waters of Taiwan are threatened by a hazard level IV (SWHs ranging from 9.0 to 12.0 m) over a SACZ of 510.0 km² and a hazard level V (SWHs exceeding 12.0 m) over a SACZ of 2152.3 km². The SACZs threatened by hazard levels I (SWHs less than 3.0 m), II (SWHs ranging from 3.0 to 6.0 m), and III (SWHs ranging from 6.0–9.0 m) are of 1045.2 km², 1793.9 km², and 616.1 km², respectively, and are located in the western waters of Taiwan.

The tidal current power (TCP) resource, the impact of TCP extraction on hydrodynamics and the influence of sea-level rise (SLR) on TCP output in the coastal waters of Kinmen Island (Taiwan) are investigated using a state-of-the-art unstructured-grid depth-integrated numerical model. The model was driven by eight tidal constituents extracted from a global tidal prediction model and verified with time series of measured data for tide level and depth-averaged current. The simulations showed reasonable agreement with the observations; the skill index was in the excellent (0.71–0.93) range with regard to simulating tide level and currents. Model predictions indicated that the channel between Kinmen and Lieyu serves as an appropriate site for deploying the tidal turbines because of its higher tidal current and deeper water depth. The bottom friction approach was utilized to compute the average TCP over a spring-neap cycle (i.e., 15 days). Mean TCP reached its maximum to 45.51 kW for a coverage area of 0.036 km² when an additional turbine friction coefficient (C_t) increased to 0.08, and a cut-in speed of 0.5 m/s was used. The annual TCP output was estimated to be 1.08 MW. The impact of TCP extraction on the change in current is significant, with a maximum reduction rate of instant current exceeding 60%, and the extent of influence for the average current is 1.26 km in length and 0.30 km in width for the −0.05 m/s contour line. However, the impact of TCP extraction on the change in tide level is insignificant; the maximum change in amplitude is only 0.73 cm for the K₂ tide. The influence of SLR on the TCP output in Kinmen waters was also estimated. Modeling assessments showed that due to SLR produces faster tidal current, the annual TCP output increased to 1.52 MW, 2.01 MW, 2.48 MW and 2.97 MW under the same cut-in speed and coverage area conditions when SLR 0.25 m, SLR 0.5 m, SLR 0.75 m and SLR 1.0 m were imposed on the model.

A pluvial flash flood is rapid flooding induced by intense rainfall associated with a severe weather system, such as thunderstorms or typhoons. Additionally, topography, ground cover, and soil conditions also account for the occurrence of pluvial flash floods. Pluvial flash floods are among the most devastating natural disasters that occur in Taiwan, and these floods always /occur within a few minutes or hours of excessive rainfall. Pluvial flash floods usually threaten large plain areas with high population densities; therefore, there is a great need to implement an operational high-performance forecasting system for pluvial flash flood mitigation and evacuation decisions. This study developed a high-performance two-dimensional hydrodynamic model based on the finite-element method and unstructured grids. The operational high-performance forecasting system is composed of the Weather Research and Forecasting (WRF) model, the Storm Water Management Model (SWMM), a two-dimensional hydrodynamic model, and a map-oriented visualization tool. The forecasting system employs digital elevation data with a 1-m resolution to simulate city-scale pluvial flash floods. The extent of flooding during historical inundation events derived from the forecasting system agrees well with the surveyed data for plain areas in southwestern Taiwan. The entire process of the operational high-performance forecasting system prediction of pluvial flash floods in the subsequent 24 h is accomplished within 8–10 min, and forecasts are updated every six hours.

Flash floods are different from common floods because they occur rapidly over short time scales, and they are considered to be one of the most devastating natural hazards worldwide. Mountainous areas with high population densities are particularly threatened by flash floods because steep slopes generate high flow velocities. Therefore, there is a great need to develop an operational forecasting system (OFS) for better flash flood prediction and warning in mountainous regions. This study developed an OFS through the integration of meteorological, hydrological, and hydrodynamic models. Airborne light detection and ranging (LiDAR) data were used to generate a digital elevation model (DEM). The OFS employs high-density and high-accuracy airborne LiDAR DEM data to simulate rapid water level rises and flooding as the result of intense rainfall within relatively small watersheds. The water levels and flood extent derived from the OFS are in agreement with the measured and surveyed data. The OFS has been adopted by the National Science and Technology Center for Disaster Reduction (NCDR) for forecasting flash floods every six hours in a mountainous floodplain in Taiwan. The 1D and 2D visualization of the OFS is performed via the National Center for Atmospheric Research Command Language (NCL).