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Liquefaction is a significant geotechnical hazard in seismically active regions like Taiwan, threatening infrastructure and public safety. Accurate prediction models are essential for assessing soil susceptibility to liquefaction during seismic events. This study evaluates liquefaction potential in central Taiwan using the random forest (RF) method. The RF models were developed with a dataset of 540 soil and seismic parameter sets, including depth, effective and total overburden stresses, SPT-N values, fine soil content, earthquake magnitude, peak ground acceleration, and historical liquefaction occurrences. Rigorous validation techniques, such as cross-validation and comparisons with observed liquefaction events, confirm the RF model’s effectiveness, achieving an accuracy of 98.89%. The model also quantifies predictor importance, revealing that the SPT-N value is the most critical soil factor, while peak ground acceleration is the key seismic factor for liquefaction prediction. Notably, the RF model outperforms simplified procedures in accuracy, even with fewer input factors. Our case studies show that an accuracy of over 95% can still be achieved, highlighting the RF model’s superior performance compared to conventional methods, which struggle to reach similar levels.

Traditional urban stormwater management systems are increasingly strained by expanding impervious ground cover and intense precipitation associated with climate change. Low-impact Development (LID) has emerged as a vital strategy to mitigate these impacts. This study assessed Taiwan’s first large-scale integrated LID installation—the Taoyuan Water Recycling Center, which incorporates bioretention cells, permeable pavements, and green roofs. Simulations performed using the Storm Water Management Model (SWMM) calibrated using field data collected in 2021–2024 demonstrated that these LID facilities reduced runoff volume by as much as 88%, with peak flow reductions reaching 90%. Under short-duration rainfall conditions, LID also reduced the risk of urban flooding by delaying the onset of peak flows. Analysis of six sub-catchments subjected to 24 synthetic storm scenarios revealed facility layout, storage capacity, and contributing drainage area as the principal determinants of LID performance. These findings underscore the need to scale up LID infrastructure—by increasing storage depth as well as spatial coverage—when seeking to enhance the resilience of urban centers to extreme rainfall.

Identifying locations of landslide slip surfaces provides critical information for understanding the volume of landslides and the scale of disasters, both of which are essential for formulating disaster preparedness and mitigation strategies. Based on hydrogeological survey data from 24 deep-seated landslide-prone sites in Taiwan’s mountainous regions, this study developed the hydraulic conductivity potential index (HCPI) using principal component analysis to quantify the hydraulic properties of disturbed rock formations with six geological factors. Then, regression analysis was performed to construct a permeability estimation model for the geological environment of landslides. Finally, the established model was utilized to develop an identification method for potential slip depths in landslide-prone sites. Results indicated a strong relation between HCPI and hydraulic conductivity with a determination coefficient of 0.895. The relation equation confirmed that the data it generated concerning the depths of significant changes in hydraulic conductivity could be used to identify potential slip surfaces. Additionally, this study successfully established a rule for identifying potential slip zones by summarizing data concerning the generated hydraulic conductivity profiles, stratigraphic lithology, existing inclinometer slip depth records, and groundwater level of landslide sites. This identification method was then applied to predict potential slip depths for ten landslide sites where slip surfaces have not yet occurred. These findings offer a new alternative to having early information on potential sliding depths for timely disaster management and control implementation.

This study introduces a deep neural network approach that utilizes radial basis functions (RBFs) to solve forward and inverse problems in the process of diffusion. The input layer incorporates multiquadric (MQ) RBFs, symbolizing the radial distance between the boundary points on the spacetime boundary and the source points positioned outside the spacetime boundary. The output layer is the initial and boundary data given by analytical solutions of the diffusion equation. Utilizing the concept of the spacetime coordinates, the approximations for forward and backward diffusion problems involve assigning initial data on the bottom or top spacetime boundaries, respectively. As the need for discretization of the governing equation is eliminated, our straightforward approach uses only the provided boundary data and MQ RBFs. To validate the proposed method, various diffusion scenarios, including forward, backward, and inverse problems with noise, are examined. Results indicate that the method can achieve high-precision numerical solutions for solving diffusion problems. Notably, only 1/4 of the initial and boundary conditions are known, yet the method still yields precise results.

This study experimentally and numerically investigated the hydrodynamic characteristics of a 180° curved open channel over rough bed under the condition of constant downstream water depth. Three different sizes of bed particles (the small, middle and big cases based upon the grain size diameter D50) were selected for flume tests. Three-dimensional instantaneous velocities obtained by the acoustic Doppler velocimeter (ADV) were used to analyze hydrodynamic characteristics. Additionally, the Renormalization-Group (RNG) turbulence model was employed for numerical simulations. Experimental results show that rough bed strengthens turbulence and increases turbulent kinetic energy along curved channels. The power spectra of the longitudinal velocity fluctuation satisfy the classic Kolmogorov −5/3 law in the inertial subrange, and the existence of rough bed shortens the inertial subrange and causes the flow reach the viscous dissipation range in advance. The contributions of sweeps and ejections are more important than those of the outward and inward interactions over a rough bed for the middle case. Flow-3D was adopted to simulate flow patterns on two rough bed settings with same surface roughness (skin drag) but different bed shapes (form drag): one is bed covered with thick bottom sediment layers along the curved part of the flume (the big case) as the experimental condition, and the other one is uniform bed along the entire flume (called the big case_flat only for simulations). Numerical simulations reveal that the secondary flow is confined to the near-bed area and the intensity of secondary flow is improved for both rough bed cases, possibly causing more serious bed erosion along a curved channel. In addition, the thick bottom sediments (the big case), i.e., larger form drag, can enhance turbulence strength near bed regions, enlarge the transverse range of secondary flow, and delay the shifting of the core region of maximum longitudinal velocity towards the concave bank.

Large eddy simulation (combined with the mixture model) and laboratory experiment were used to investigate the impact of emergent and rigid vegetation on the dynamics of downslope gravity currents in stratified environments. The reliability of the numerical model was assessed with the corresponding laboratory measurements. The results show that the vegetation cylinders lead to severe lateral non-uniformity of the current front, causing more evident lobe and cleft structures. In stratified environments, the smaller driving force leads to less propagating velocity until the current separates from the slope. The transition point (from acceleration to deceleration phases) of current velocity appears earlier as the vegetation becomes denser. The peak value of the bulk entrainment coefficient Ebuik is inversely proportional to the vegetation density, while the final converged value of Ebuik is proportional to the vegetation density. Vegetation patches make the degree of fluctuation of the instantaneous entrainment coefficient Einst more intense, and even negative values appear locally, indicating that the gravity current is detrained into the ambient fluid. The velocity profiles of gravity current develop multi-peak patterns in stratified environments due to fingering intrusive patterns. Our analysis reveals that as the vegetation density increases, the generated wakes behind vegetation cylinders increase local entrainment and mixing, causing the density of current flow from vegetation to decrease and reach the neutral buoyancy layer of ambient fluids earlier, finally leading to a smaller separation depth.

With larger surface areas and nanochannels for mass delivery and gas diffusion, three-dimensional tubular anodic aluminum oxide (AAO) films have practical advantages over two-dimensional AAO films for medical and energy applications. In this research, we have developed a process for batch production of tubular AAO films using a 6061 Al tube. The tubular AAO films have open nano-channels on both sides, with average pore dimensions of about 60 nm and pore densities of about 108 to 109 pore/cm2. It was found that the porous AAO material with nano-channel structure exhibited dialysis behavior, allowing for liquid/gas exudation through diffusion between the inner and outer surfaces of the tubular AAO films. Ar gas bearing test and aeration test were conducted to find the pressure bearing capacity of tubular AAO films. It was demonstrated that the AAO film with a thickness of 100 μm can resist an argon pressure up to 8 atm; however, 30 μm AAO film can only withstand 3 atm of Ar gas. The tubular AAO films with exudation characteristics have the potential for applications in advanced technologies, such as liquid or gas filters, drug delivery, and energy applications.

Accurate and reliable estimates of sediment yields from a watershed and identification of unstable stream reaches due to sediment-related disaster are crucial for watershed management, disaster prevention, and hazard mitigation purposes. In this study, we added hydrodynamic and sediment transport modules in a recently developed model to estimate sediment yields and identify the unstable stream reaches in a large-scale watershed (> 100km2). The calibrated and verified models can well reproduce the flow discharge and sediment discharge at the study site, the Shihmen Reservoir Watershed in Taiwan, during several typhoon events. For the scenario applications, the results revealed that the contribution (> 96%) of landslides on sediment supply is much more significant than compared to soil erosion (< 4%). The sediment contribution from the upstream of the hydrological station-Yufeng is approximately 36–55% of the total sediment supply for the rainfall events of 25, 50, 100, and 200 years return period. It also indicates that 22–52% of sediment still remain at foot of the slope and the streams, which become a potential source for sediment hazards in the future. Combining with the bed erosion and deposition depths, flow-induced shear stress from the SRH-2D model, and probability of slope failure within 250 m of stream reaches, the relatively stability of stream reaches can be identified. The results could provide the water resource authorities for reference to take precautionary measures in advance on the stream reaches with high-degree instability.

Qualifying sediment dynamic in a reservoir watershed is essential for water resource management. This study proposed an integrated model of Grid-based Sediment Production and Transport Model (GSPTM) at watershed scale to evaluate the dynamic of sediment production and transport in the Shihmen Reservoir watershed in Taiwan. The GSPTM integrates several models, revealing landslide susceptibility and processes of rainfall–runoff, sediment production from landslide and soil erosion, debris flow and mass movement, and sediment transport. For modeling rainfall–runoff process, the tanks model gives surface runoff volume and soil water index as a hydrological parameter for a logistic regression-based landslide susceptibility model. Then, applying landslide model with a scaling relation of volume and area predicts landslide occurrence. The Universal Soil Loss Equation is then used for calculating soil erosion volume. Finally, incorporating runoff-routing algorithm and the Hunt’s model achieves the dynamical modeling of sediment transport. The landslide module was calibrated using a well-documented inventory during 10 heavy rainfall or typhoon events since 2004. A simulation of Typhoon Morakot event was performed to evaluate model’s performance. The results show the simulation agrees with the tendency of runoff and sediment discharge evolution with an acceptable overestimation of peak runoff, and predicts more precise sediment discharge than rating methods do. In addition, with clear distribution of sediment mass trapped in the mountainous area, the GSPTM also showed a sediment delivery ratio of 30% to quantify how much mass produced by landslide and soil erosion is still trapped in mountainous area. The GSPTM is verified to be useful and capable of modeling the dynamic of sediment production and transport at watershed level, and can provide useful information for sustainable development of Shihmen Reservoir watershed.

Carbon-modified titania (C–TiO2) films were easily prepared by using an impregnation process with a glucose-containing TiO2 sol. Through controlling calcination conditions, the as-obtained C–TiO2 products exhibited highly photocatalytic activity for the degradation of gaseous NOx under visible light and ultraviolet illumination. The effects of carbon content and calcination temperature on the photocatalytic performances and their photochemical and physical properties were investigated. Carbonaceous species on the TiO2 surface enhanced the visible-light absorption of TiO2 films; however, an excessive amount of carbon on the TiO2 surface reduced its photocatalytic ability due to the serious coverage effect on active sites. The results show that a suitable glucose addition is about 50–100% of the weight of TiO2 content and the optimized calcination temperature is 300 °C, which leads to better photocatalytic activity under ultraviolet and visible- light irradiations. Accordingly, the simple-prepared C–TiO2 films functioned as visible-light-responsive catalysts, allowing for a feasible producing route for real applications.