Typhoon Events Research Articles

Nonlinear Tide‐River‐Surge Interactions and Their Impacts on Compound Flooding During Typhoon Hato in the Pearl River Delta

AbstractIn coastal areas, multiple hydrodynamic processes co‐occur, including the astronomical tide, river discharge, and storm surge. Their propagation and interaction within coastal tidal river result in strong nonlinear behavior in inland areas. This study employed a hydrodynamic model and continuous wavelet transform analysis to investigate the complex tide‐river‐surge interactions and their impacts on compound flooding in the West River of the Pearl River Delta during an extreme typhoon event. Validated model outputs provided insights into the spatial and temporal variations of river discharge, water levels, and currents. Wavelet analysis revealed river discharge modulates tidal properties, causing nonstationary tides and asymmetries, with high flows suppressing tidal ranges but facilitating energy transfers to overtides. During Typhoon Hato, storm surges dominated high‐frequency water level fluctuations that rapidly propagated upstream. Crucially, strong high‐frequency tide‐river‐surge coupling induced significant water level amplifications, with interaction intensities increasing landward. In upstream areas where riverine and coastal drivers converged, flood risks exceeded typical estimates due to this vigorous multi‐driver compounding. Findings highlighted how existing flood mitigation approaches over simplistically superposing individual sources may severely underestimate flood levels by neglecting such nonlinear interactions. A comprehensive accounting of the cumulative, multiplicative effects of tides, discharge, storm surge, and sea level rise is imperative. This quantitative unraveling of key physical drivers offers transferable insights applicable to compound flood risk evaluations and policy guidance for enhancing resilience in other estuary and delta regions. Future work should focus on holistically modeling multivariate extremes and their interactions.

Analysis of the Response Relationship Between PWV and Meteorological Parameters Using Combined GNSS and ERA5 Data: A Case Study of Typhoon Lekima

Precipitable water vapor (PWV) is a crucial parameter of Earth’s atmosphere, with its spatial and temporal variations significantly impacting Earth’s energy balance and weather patterns. Particularly during meteorological disasters such as typhoons, PWV and other meteorological parameters exhibit dramatic changes. Studying the response relationship between PWV and typhoon events, alongside other meteorological parameters, is essential for meteorological and climate analysis and research. To this end, this paper proposes a method for analyzing the response relationship between PWV and meteorological parameters based on Wavelet Coherence (WTC). Specifically, PWV and relevant meteorological parameters were obtained using GNSS and ERA5 data, and the response relationships between PWV and different meteorological parameters before and after typhoon events were studied in time–frequency domain. Considering that many GNSS stations are not equipped with meteorological monitoring equipment, this study interpolated meteorological parameters based on ERA5 data for PWV retrieval. In the experimental section, the accuracy of ERA5 meteorological parameters and the accuracy of PWV retrieval based on ERA5 were first analyzed, verifying the feasibility and effectiveness of this approach. Subsequently, using typhoon Lekima as a case study, data from six GNSS stations affected by the typhoon were selected, and the corresponding PWV was retrieved using ERA5. The WTC method was then employed to analyze the response relationship between PWV and meteorological parameters before and after the typhoon’s arrival. The results show that the correlation characteristics between PWV and pressure can reveal different stages before and after the typhoon passes, while the local characteristics between PWV and temperature better reflect regional precipitation trends.

Tracking the impact of typhoons on maize growth and recovery using Sentinel-1 and Sentinel-2 data: A case study of Northeast China

The increasing frequency of typhoon events, attributed to global climate change, has significantly affected agricultural production, predominantly resulting in substantial negative consequences. Accurate and timely assessment of crop damage is crucial for understanding economic implications, devising effective agricultural strategies, and enhancing resilience amid mounting climate uncertainties. This study investigates the utility of Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) data in tracking maize damage severity following typhoon events. By employing continuous field sampling techniques and conducting visual interpretation of high-resolution remote sensing imagery, sample sets representing a spectrum of maize damage severity were systematically established. The application of time series analysis on Sentinel data enables a comprehensive exploration of spectral and polarization responses, providing insights into the correlation with maize damage severity. Segmentation of the maize damage timeline into pre-disaster, disaster, and recovery periods, coupled with optimization of relevant feature parameters, was undertaken to bolster monitoring precision. Leveraging the Google Earth Engine (GEE) cloud platform, a Random Forest algorithm was used to develop a model for monitoring maize damage severity across different post-typhoon periods, yielding maps delineating the distribution and magnitude of maize damage in Northeast China. Results indicate that integrating spectral indices from the pre-disaster phase with backscatter variations of polarization bands during various post-typhoon periods enhances maize damage assessment. Maize damage severity is notably elevated during the disaster period, achieving an overall accuracy of 87.22 %. While mitigated during the recovery phase, localized exacerbation occurs in severely affected regions, yielding an overall accuracy of 88.54 %. Analysis incorporating terrain and meteorological data reveals that post-typhoon maize disasters predominantly occur in low-lying and flat areas, with meteorological factors, particularly maximum wind speed and daily cumulative precipitation, exerting significant influence on damage severity. This study underscores the critical role of SAR and optical data fusion in elucidating typhoon-induced crop damage dynamics, thereby providing essential insights for proactive mitigation strategies against future agricultural losses.

Stochastic processes driving cyanobacterial temporal succession in response to typhoons in a coastal reservoir

Typhoons associated with heavy rainfall events, potentially triggering harmful algal blooms (cyanoHABs) dominated by cyanobacteria in coastal reservoirs. These blooms deteriorate water quality and produce toxins, posing a threat to aquatic ecosystems. However, the ecological mechanisms driving cyanobacteria communities in response to typhoons remain unclear. To address this gap, we investigated a coastal reservoir with high-frequency sampling during two typhoon seasons. We employed comprehensive statistical methods under neutral and evolutionary theories to analyze environmental dynamics and cyanobacterial genus succession. Our findings revealed a significant increase in nutrient loads following typhoons, with concentrations of total nitrogen (TN), total phosphorus (TP), and ammonia-nitrogen (NH4+-N) rising from 0.4 mg/L to 1.0 mg/L, 0.02 mg/L to 0.63 mg/L, and 0.03 mg/L to 0.26 mg/L, respectively. These changes coincided with fluctuations in other physicochemical parameters under changing hydrometeorological conditions. Despite significant environmental disturbances, the cyanobacterial community exhibited a remarkable recovery within 15–25 days following the typhoons. This recovery progressed through four distinct successional phases, with a notable shift in community composition from Raphidiopsis and Pseudoanabaena to Aphanocapsa, subsequently replaced by Raphidiopsis and Microcystis, before reverting to the pre-typhoon community structure. During the entire successional phase, the availability of TN and the TN/TP ratio played a dominant role, as indicated by PLS-PM analysis (total effects = -0.6; p < 0.05). Pre-typhoon, environmental factors primarily influenced community structure (54 %) based on modified stochasticity ratio. However, following the typhoons, stochastic fluctuations took precedence (71 %-91 %). The rapid recovery of cyanobacterial communities and the shift in driving mechanisms from deterministic to stochastic processes underscore the complex ecological responses to typhoon events. This study provides essential insights for biodiversity preservation and ecosystem restoration, emphasizing the need to consider both stochastic and deterministic processes in ecological management strategies.

A new perspective to understand public response to the Typhoon Doksuri from coastal and inland regions

Massive amounts of data from social media possess the potential to rapidly identify the primary issues of concern in emergency disaster management. In summer 2023, Super Typhoon Doksuri which was an exceptionally special typhoon disaster that caused severe damage to China's coastal areas and disastrous impacts in inland regions, particularly triggered the most severe rainstorm in Beijing area in over a century. To enhance typhoon hazard reduction in both coastal and interior locations, it is crucial to examine public response to these events. This study uses microblog text data from July 27 to August 3 of 2023 to map the public response to Typhoon Doksuri. The Support Vector Machine (SVM) algorithm was used to classify the microblog text in combination with the typhoon path to analyze the spatial and temporal variations of the emotions of the affected individuals. The relationship between changes in public opinion, the distribution of topics, and the major disasters triggered by the residual circulation of Typhoon Doksuri in the Beijing-Tianjin-Hebei region is discussed. The Mentougou mega-storm in Beijing area that occurred in July 2023 is a typical case. The findings demonstrate that during the typhoon event, the focus of public attention changed with the movement of the typhoon path, and various public opinion topics exhibited temporal synchronization. Public sentiment indicates that the overall supportive sentiment is higher than is fearful sentiment. Based on this, it is crucial to strengthen the Beijing-Tianjin-Hebei cooperative emergency response, and response measures were proposed related to urban flood control and drainage construction, public awareness, backward areas, secondary disasters, resident relocation, and social media technology.

Natural coral recovery despite negative population growth.

Demographic processes that ensure the recovery and resilience of marine populations are critical as climate change sends an increasing proportion on a trajectory of decline. Yet for some populations, recovery potential remains high. We conducted annual monitoring over 9 years (2012-2020) to assess the recovery of coral populations belonging to the genus Pocillopora. These populations experienced a catastrophic collapse following a severe typhoon in 2009. From the start of the monitoring period, high initial recruitment led to the establishment of a juvenile population that rapidly transitioned to sexually mature adults, which dominated the population within 6 years after the disturbance. As a result, coral cover increased from 1.1% to 20.2% during this time. To identify key demographic drivers of recovery and population growth rates (λ), we applied kernel-resampled integral projection models (IPMs), constructing eight successive models to examine annual change. IPMs were able to capture reproductive traits as key demographic drivers over the initial 3 years, while individual growth was a continuous key demographic driver throughout the entire monitoring period. IPMs further detected a pulse of reproductive output subsequent to two further Category 5 typhoon events during the monitoring period, exemplifying key mechanisms of resilience for coral populations impacted by disturbance. Despite rapid recovery, (i.e., increased coral cover, individual colony growth, low mortality), IPMs estimated predominantly negative values of λ, indicating a declining population. Indeed, while λ translates to a change in the number of individuals, the recovery of coral populations can also be driven by an increase in the size of surviving colonies. Our results illustrate that accumulating long-term data on historical dynamics and applying IPMs to extract demographic drivers are crucial for future predictions that are based on comprehensive and robust understandings of ecological change.

Do typhoon disasters foster climate change concerns? Evidence from public discussions on social media in China

Combating the adverse impacts of extreme climate events through adaptation depends on climate change awareness from both governments and the public. It has long been discussed that historical experiences of climatic hazards might help to foster and raise public concerns about climate change, and consequently contribute to climate actions. However, current studies have reached no consensus on the impacts of the occurrence of extreme climatic hazards on the public's climate change awareness. This study provides a national-level analysis of climate change-related posts accompanying extreme typhoon events in China from 2011 to 2022, based on social media big data and machine learning, to discern the relationship between occurrences of typhoon disasters and climate change concerns on Weibo—in terms of the volume, contents and sentiment expressed in climate change-related posts. Our analysis found that the volume of climate change-related posts generally did not significantly increase during or after typhoon disasters. In terms of contents, though, the proportion of contents about climate change impacts did significantly increase during typhoon events, from 41.74 % to 48.97 %, and these disasters also significantly provoked negative sentiment toward climate change, which increased from 62.47 % to 70.18 %. Contents about climate change impacts and negative sentiment, however, were observed to bounce back to pre-disaster levels within about twelve days after typhoon events. Our study emphasizes the importance of learning from previous climatic disasters, to foster public concerns about climate change and thereby to promote climate actions.

Forecasting sea surface temperature during typhoon events in the Bohai Sea using spatiotemporal neural networks

Advanced neural network methods can effectively combine temporal and spatial information, allowing us to exploit complex relationships in the prediction of sea surface temperature (SST). Therefore, the authors have developed an attention-based context fusion network model recently, known as ACFN, to enhance the underlying spatiotemporal correlations in SST data. In a previous preliminary long-term evaluation, ACFN has demonstrated substantial improvements over several state-of-the-art baseline models, such as Convolutional Long-Short Term Memory (ConvLSTM) and Predictive Recurrent Neural Network (PredRNN). However, these methods have not been widely used for predicting SST during typhoons, and their performance has not been thoroughly evaluated. This study focuses on three specific typhoons, In-fa (2021), Lekima (2019), and Rumbia (2018), as case studies. The results show that ACFN consistently outperforms ConvLSTM and PredRNN, as demonstrated during Typhoon In-fa with a mean absolute error of 0.27 °C and a root-mean-square error of 0.33 °C for a 1-day forecast time. This study also examines the impact of forecast time on predictive skill, revealing that the performance of ACFN, as expected, gradually decreases with longer forecast times. This thorough evaluation of the ACFN model provides a valuable reference for using deep learning in predicting regional typhoon SST. Plain language summaryIn previous work, we developed an attention-based context fusion network model. This spatiotemporal neural network model has been successfully applied to short-term sea surface temperature (SST) prediction in the Bohai Sea, utilizing only current and previous 1- to 10-day SST data as input to forecast SST for the subsequent 1- to 10-day period. In this study, we further evaluated the capability of the model to predict SST during typhoons in the Bohai Sea, and the results were very promising. When predicting SST during Typhoon In-fa, the present spatiotemporal neural network model had a mean absolute error of only 0.27 °C for a 1-day forecast time, and a correlation coefficient of 0.74. On the other hand, comparison with baseline spatiotemporal neural network models shows that the present model is more effective in extracting input information. The current model has resolved the constraint that its predictive capability does not diminish as the forecast time increases, thereby enhancing the rationality of the prediction outcomes. In conclusion, the present spatiotemporal neural network model demonstrates its efficacy in forecasting typhoon-induced SST in the Bohai Sea, offering valuable insights for applications in meteorology and oceanography.

Field measurement of entrapped pore‐air pressure and the effect of rising groundwater level in the soil layer

AbstractUnsaturated soil contains pore air, some of which becomes entrapped in the soil layer during the infiltration process. Such entrapped pore air in the soil layer inhibits infiltration, decreases hydraulic conductivity, and causes erroneous estimates of groundwater response. Experimental studies suggest an effect of compressed entrapped pore air on stream discharge. However, few studies have investigated the behaviour of pore air in the field, and no method for measurement of pore‐air behaviour has been established. We measured pore‐air pressure (Pair) with a simple handmade probe, combined with atmospheric pressure (Patm) and groundwater level. The entrapment and compression of pore air were detected based on the pressure difference (ΔP = Pair – Patm). Observations were conducted for approximately 1 year in two small headwater catchments (TC and HA, which have differences in soil depth and groundwater level dynamics) in Ibaraki Prefecture, Japan. Positive responses of ΔP during some rainfall events were confirmed at both TC and HA. Pore‐air entrapment occurred even during weak rainfall events with rainfall intensity of &lt;10 mm/h. During a typhoon event in October 2019, a maximum ΔP of 3.9 kPa was observed at HA. The pore pressure increase recorded by the tensiometer was mostly explained by the increase in ΔP, which was supported by the soil moisture data. Therefore, we concluded that our handmade measurement system could successfully measure Pair and detect pore‐air entrapment in the field. This showed that Pair is not negligible. Total event rainfall was related to the maximum ΔP. It also showed that the rise in the groundwater level plays a significant role in pressurization of the entrapped pore air. We present the first field data demonstrating the effect of groundwater level rise on the pressurization of entrapped Pair.

A novel symplectic geometry-based modal decomposition technique for accurate modal identification of tall buildings with close-spaced modes

The modal decomposition technique is of crucial importance for accurate modal parameter identification of tall buildings with close-spaced modes. However, most of the existing decomposition techniques are proposed for long-span structures, and the techniques specifically focused on tall buildings have rarely been explored. To this end, this paper proposes a novel modal decomposition technique called Symplectic Geometry Close-Spaced Mode Decomposition (SGCD) for the close-spaced modal identification of tall buildings. A numerical study conducted using a two-degree-of-freedom model is utilized to evaluate the effectiveness of the proposed approach. The results demonstrate that the SGCD method can effectively decompose close-spaced modes, and the modal parameters can be accurately identified with high robustness. Furthermore, the proposed modal decomposition technique is employed to analyze the field measurements obtained during a typhoon event on a 420-m-tall building. The results demonstrate the applicability and efficacy of the proposed modal decomposition technique to field measurement data. The main objective of this paper is to provide an effective modal decomposition technique for accurately identifying close-spaced modes of tall buildings.

Explanations for the positive storm surges on the left side of landfall typhoons in China

The coastal regions of Southeast China frequently experience unusual positive storm surges on the left side of landfalling typhoons, a phenomenon historically overlooked and inadequately explained by conventional circular wind field models. In this study, a high resolution, two-dimensional storm surge model based on ADCIRC along with tide gauge data were used to investigate the spatiotemporal distribution of these surges and proposes underlying mechanisms, informed by a comparative analysis of circular and ERA5 reanalysis wind fields during typical typhoon event 9711 Winnie. Analyzing tide gauge data spanning from 1986 to 2016, the study uncovers a distinct pattern of left-side positive storm surges along the southeastern coast, notably on the Fujian coast and within the Taiwan Strait, which are found to be comparable to those on the cyclone’s right side. The research also documents a significant escalation in both the frequency and intensity of these left-side surges over the past three decades. Simulation results highlights the inadequacies of circular wind field models in operational forecasting and emphasizes the necessity of accounting for topographic influences and the structural complexity of wind fields in storm surge predictions. This is particularly pertinent in semi-enclosed seas with intricate hydrodynamics, such as the Taiwan Strait. The insights gleaned from this study are pivotal for enhancing the real-time simulation and prediction of storm surges, which are vital for coastal safety and disaster prevention measures.

Precipitation Simulation and Dynamic Response of a Transmission Line Subject to Wind-Driven Rain during Super Typhoon Lekima

Typhoons bring great damages to transmission line systems located in coastal areas. Strong wind and extreme precipitation are the main sources of damaging effects. Transmission lines suffered from wind-driven rain exhibit more susceptibility to damage due to the coupled effect of wind and rainwater. This paper presents an integrated numerical simulation framework based on mesoscale WRF model, multiphase CFD model and FEM model to analyze the motions of a transmission line subjected to coupled wind and rain loads during typhoon events. A full-scale transmission line in Zhoushan Island is employed to demonstrate the effectiveness of the proposed framework by simulating typhoon evolution in terms of wind fields and rainfall, solving the coupled wind and rain fields around the conductor and predicting the dynamic responses of the transmission line during Super Typhoon Lekima in 2019. The results show that the horizontal displacements of the transmission line under the joint actions of wind and rain increase approximately 17–18% compared to those of wind loads only. It is important to consider the coupled effects of wind-driven rain on conductors in the design of transmission lines under typhoon conditions.

South China Sea Typhoon Hagibis enhanced Xinfengjiang Reservoir seismicity

There was an evident increase in the number of earthquakes in the Xinfengjiang Reservoir from June to July 2014 after the landing of Typhoon Hagibis. To understand the spatial and temporal evolution of this microseismicity, we built a high-precision earthquake catalog for 2014 and relocated 2275 events using recently developed methods for event picking and catalog construction. Seismicity occurred in the southeastern part of the reservoir, with the preferred fault plane orientation aligned along the Heyuan Fault. The total seismic energy peaked when the typhoon passed through the reservoir, and seismicity correlated with typhoon energy. In contrast, a limited seismic response was observed during the later Typhoon Rammasun. Combining data regarding the water level in the Xinfengjiang Reservoir and seismicity frequency changes in the Taiwan region during these two typhoon events, we suggest that typhoon activity may increase microseism energy by impacting fault stability around the Xinfengjiang Reservoir. Whether a fault can be activated also depends on how close the stress accumulation is to its failure point.

Reservoir Mud Releasing May Suboptimize Fluvial Sand Supply to Coastal Sediment Budget: Modeling the Impact of Shihmen Reservoir Case on Tamsui River Estuary

AbstractRegular release of sediment from reservoir has been increasingly adopted as a strategy for sustainable management. Here, we use a process‐based morphodynamic model to simulate the estuarine sediment dynamics impacted by turbidity current venting implemented by the Shihmen Reservoir during three typhoon events in 2008. Upon validation with the post‐event bathymetries, the model hindcasts reveal that mud releasing can be effective in mitigating reservoir siltation, yet may be a suboptimal strategy for alleviating coastal sediment deficit. A vast majority of the released muds were delivered through the estuary and exported to offshore by flood advection, wave dispersion, and tidal flushing. The flood‐driven sands, sourced mainly from downstream tributaries, were instead the major contributor to coastal sediment budget. However, mud mantling (covering and immobilizing sand deposits by the reservoir‐released muds) reduced sand availability and thus sand delivery to the coast. For the present case, 25% of the released muds were deposited along the way, presence of these mud covers reduced sand delivery by 15%, compared to a hypothetical scenario of clear‐water flood releases. The relative sand transport deficit is found to increase linearly with the degree of bed mud saturation, 1–D/R, with D/R the ratio of single‐event mud deposit to release. Given broad relevance to global reservoirs encountering the problems of siltation and coastal sediment deficit, our findings highlight that sustainable management needs to look beyond just a bulk amount of sediment, but it is critical to consider how different sediment fractions are interacting and impacted by human activities.

The Limited Effect of Reduced Typhoon Frequency on Stream Hydrochemistry in a Subtropical Forest Watershed

AbstractTropical cyclones are often accompanied by large amount of precipitation potentially impacting stream hydrochemistry. Global warming is altering typhoon disturbance regime. Little is known about how cyclone changes, especially cyclone‐frequency reduction may affect stream hydrochemistry. In this study, we compared water and nutrient input via precipitation and output via streamflow between a frequent‐typhoon period (2013–2017), with 1.2 typhoon yr−1, and a no‐typhoon period (2018–2022) at a long‐term monitoring site, the Fushan Experimental Forest of Taiwan. Precipitation and streamflow quantities were not different between the two periods because typhoons increased the fluctuation but not the mean of monthly precipitation in the major typhoon months (July–September). Inputs of Mg2+, NO3−, and SO42− via precipitation were greater in the frequent‐typhoon period than the no‐typhoon period while inputs of other ions were not different between the two periods. Only the output of Mg2+ was different between the two periods, greater in the frequent‐typhoon period. Output/input ratio of NO3− was greater in the no‐typhoon period than the frequent‐typhoon period despite the greater input in the frequent‐typhoon period, while no differences were found for others. Increases in mineralization rates due to warming is suggested to be the cause of the greater NO3− output/input ratio during the no‐typhoon period. Relationships between stream discharge and ion export were similar between the two periods both with and without removing typhoon events. The limited variation in hydrochemistry between periods of contrasting cyclone activities suggests high resilience of the undisturbed subtropical forests to changes in cyclone frequency at the decadal scale.

Trends of extreme waves around Hainan Island during typhoon processes

Extreme waves mostly occur during typhoon processes in China Seas. This study statistically shows the trends of extreme wave height over the past several decades around Hainan Island, based on the reconstruction of historical wave processes during the typhoon events from 1949 to 2022. Totally 807 events in the tropical cyclone (TC) best track datasets are numerically simulated by the widely used wave model SWAN. The driving wind fields are reconstructed as a combination of an empirical cyclone wind model with the reanalysis wind field data, in order to better simulate waves near cyclone centers with higher spatial resolution. Based on the reconstructed wave data, the spatial distribution of wave characteristics around Hainan Island has been provided. The Mann-Kendall test shows a descending trend of extreme wave height in the southeast side of Hainan Island, where the maximum descending rate could reach up to 5 cm/yr. The influence of the long-term trend on the design extreme wave height is also discussed. Comparing to the variation of the design extreme wave height with sampling period, the long-term trend is also a significant impact factor.

Temporal and spatial variation of typhoon-induced surges and the impact of rainfall in a tidal river

The Huangpu River, which flows into the Yangtze Estuary, runs through Shanghai Municipality in China. During the flood season, typhoon-induced surges result in extremely high water levels in the Huangpu River, which is the main factor threatening flood control safety in Shanghai. Based on observations of water levels at three stations along the Huangpu River from 2008 to 2021, together with wind and rainfall, this paper investigates: the trends of the annual highest storm surges; the differences in periodic variation and magnitude of surges during the spring-neap cycle; the longitudinal variation of surges; and the impact of rainfall. The results show that the annual highest surges at three stations all show a significant increasing trend, which is caused by the increasing wind speed, and the intensity and duration of rainfall during typhoon events, induced by the increasing frequency of landfall and close-to-YE (Yangtze Estuary) typhoon events, and strong and very strong typhoon events. The periodic variation and magnitude of surges show clear differences during the spring-neap cycle, resulting from the largest nonlinear surge-tide interaction during spring tide and the smallest during neap tide. Heavy rainfall can reduce the probability of 6–7 h and 2.7–3.3 h periods, and change the phase of the periodic variation, inducing partial main peaks and maximum surges during ebb or low tide. The longitudinal variation of storm surge along the Huangpu River can be divided into three types: decreasing upstream, first increasing then decreasing, and increasing upstream. Heavy and long-duration rainfall increases the water discharge from the basin to the river, amplifying the surge, with the largest impact in the upper reach and the smallest in the lower reach, which is the main factor inducing the latter two types, particularly the third type.

Typhoon and flooding occurrences on Chongming Island, Changjiang Estuary, as revealed by a newly acquired sedimentary record

Typhoon-induced storms surges and river flooding events represent two types of natural disasters that affect a wide range, occurring with high frequency and causing serious societal losses. Due to the limited duration of instrumental records, there is an inadequate understanding of the patterns and mechanisms underlying the variations in typhoons and floods. The interpretation of sedimentary records aptly compensates for these deficiencies in terms of the temporal scale, becoming a crucial medium for extending the temporal span of typhoon and flood records. Previous studies in this field have primarily focused on the identification of single types of extreme events. The Changjiang Estuary, particularly Chongming Island, is significantly affected by both typhoons and river floods, making it an excellent area for synchronous comparative studies of these two types of extreme events. Based on the analysis of a core sample, ZP02, collected from Chongming Island, in terms of chronological, sedimentological, and geochemical characteristics, specific tracing fingerprints for event deposits from typhoon and flood events are established. Sediments from typhoon events generally exhibit erosive contact surfaces, coarser grain sizes, and a tendency to become finer upwards, often featuring layers mixed with coarse sand and shell fragments. In contrast, flood event deposits vary in grain size, either coarser or finer, with abrupt contact surfaces compared to normal sediment layers, and are predominantly brownish-yellow in color. The fingerprint tracing results indicate that the typhoon event layers are characterized by high values in principal component 2 (PC2) of the elements, Zr/Fe and Sr/Fe ratios, with low values in principal component 1 (PC1) the elements and Ti/Ca ratio. Flood event deposits are marked by high values in PC1 and Ti/Ca ratio, low values in PC2 and Sr/Fe ratio, and an increase in Zr/Fe ratio in coarser flood layers but no significant change in finer layers. Based on these fingerprints, 19 layers of typhoon and the same number of flood events were identified in core ZP02, which correspond well with documentary records. The establishment of tracing fingerprints for typhoon and flood event deposits provides methodological support for the identification and interpretation of various extreme event deposits.

Reconstruction of long-term hydrologic change and typhoon-induced flood events over the entire island of Taiwan

Study regionThe island of Taiwan. Study focusThis study presents long-term and high-resolution modeling of flood occurrence, interdecadal patterns of river-floodplain dynamics, and analysis of flooding during two typhoon events—Nari and Morakot over Taiwan. The modeling system combines a hydrological model (HiGW-MAT) and a river hydrodynamics model (CaMa-Flood), simulating hydrologic-hydrodynamic processes at ∼ 5 km resolution with flood occurrences downscaled to ∼ 90 m. New hydrological insights for the regionAs the first investigation to conduct spatially comprehensive and temporally continuous modeling in Taiwan, this study presents important advances on the application of large-scale hydrological-hydrodynamic models in settings like that of Taiwan with important implications on flood prediction under climate change. The assessment of interdecadal changes in streamflow indicates no consistent trends over the past four decades; however, the variabilities in monthly-scale streamflow are significant and regionally diverse across Taiwan. Decadal changes in flood occurrence are also minimal at the island-scale, but the changes vary substantially across different regions and exhibit an increased variability over time. Furthermore, the simulated flood patterns in response to Typhoons Nari and Morakot suggest that the modeling framework can be used to reproduce the spatial dynamics and temporal progression of flooding under extreme events in relatively small regions like Taiwan.

Revealing the Effect of Typhoons on the Stability of Residual Soil Slope by Wind Tunnel Test

Typhoon-induced slope failure is one of the most important geological hazards in coastal areas. However, the specific influence of typhoons on the stability of residual soil slopes still remains an open issue. In this study, the Feiyunjiang catchment in Zhejiang Province of SE China was chosen as the study area, and a downscaling physical model of residual soil slopes in the region was used to carry out the wind tunnel test. Our aim was to answer the question, How does the vegetation on the slope and slope stability respond during a typhoon event? For this purpose, multiple aspects were monitored and observed under four different wind speeds (8.3 m/s, 10.3 m/s, 13.3 m/s, and 17 m/s), including vegetation damage on the slope, macrocracks on the slope surface, wind pressure, wind load, permeability coefficient of the soil layer, and slope stability. The results showed that the plants on the slope could restore to their original states when the wind speeds ranged from 8.3 m/s to 13.3 m/s, but were damaged to the point of toppling when the wind speed increased to 17 m/s. Meanwhile, evident cracks were observed on the ground under this condition, which caused a sharp increase in the soil permeability coefficient, from 1.06 × 10−5 m/s to 6.06 × 10−4 m/s. The monitored wind pressures were larger at the canopy than that at the trunk for most of the trees, and generally larger at the crown of the slope compared with the toe of the slope. Regarding the wind load to the slope ground, the total value increased significantly, from 35.4 N under a wind speed of 8.3 m/s to 166.5 N under a wind speed of 17 m/s. However, the wind load presented different vector directions at different sections of the slope. The quantitative assessment of slope stability considering the wind load effect revealed that the safety factor decreased by 0.123 and 0.1 under the natural state and saturated state, respectively, from no wind to a 17 m/s strong wind. Overall, the present results explained the mechanism of slope failure during typhoon events, which provided theoretical reference for revealing the characteristics of residual soil slope stability under typhoon conditions.