Short Return Periods Research Articles

Wave Height Estimation with a Short Return Period

Bisection and grid search methods are proposed as wave height estimation techniques for short return periods (hereafter RP; reference, one year) using long-term wave monitoring data. The proposed method is compared and evaluated with the estimation results using GP (generalized Pareto) and GEV (generalized extreme value) distribution functions, which are widely used as extreme value analysis methods. The wave height data used for the estimation were KMA Ulleungdo Ocean Buoy’s wave height data observed for 12 years from 2012 to 2023. The estimation results show that the annual frequency wave height is 4.55 m, the 90% confidence interval (±5%) is [4.18, 4.69] (m), and the confidence interval for the RP is [0.58, 1.42] (years). The difference from the GP and GEV estimation results (4.61 m and 4.53 m, respectively) was statistically ‘no significance difference.’ The method proposed in this study can estimate design variables for RPs without assumptions on candidate extreme distribution functions or parameter estimation procedures, so it can be used to estimate wave heights for short RPs of one year or less when observation data of approximately ten years or more are available.

Multi-round decentralized dataset distillation with federated learning for Low Earth Orbit satellite communication

Satellite communication and Low Earth Orbit (LEO) satellites are important components of the 6G network, widely used for Earth observation tasks due to their low cost and short return period, making them a key technology for 6G network connectivity. Due to limitations in satellite system technology and downlink bandwidth, it is not feasible to download all high-resolution image information to ground stations. Even in existing federated learning (FL) methods, sharing well-trained parts of the model can still bottleneck with increasing model size. To address these challenges, we propose a new federated learning framework (FL-M3D) for LEO satellite communication that employs multi-round decentralized dataset distillation techniques. It allows satellites to independently extract local datasets and transmit them to ground stations instead of exchanging model parameters. Communication costs depend only on the size of the synthesized dataset and do not increase with larger models. However, the heterogeneity of satellite datasets can lead to sample ambiguity and decreased model convergence speed. Therefore, we propose distilling the datasets to mitigate the negative effects of data heterogeneity. Through experiments using real-world image datasets, FL-M3D reduces communication volume in simulated satellite networks by approximately 49.84% and achieves improved model performance.

Evaluations of storm tide hazard along the coast of China using synthetic dynamic tropical cyclone events

Concurring with high astronomical tides, storm surges have caused devastating damage in low-lying areas along the Chinese coastal regions. However, accurately calculating tropical cyclone (TC) storm tide hazards, especially those with long return periods, has proven challenging due to limited temporal and spatial information on TCs. In this study, we adopt the Synthetic Dynamic TC Method (SDTM), which enables a more robust estimation of storm tide hazards by generating a large number of synthetic TCs based on historical best track data and ocean-atmosphere environmental data. Within the SDTM framework, synthetic TCs corresponding to 10,000 years are validated using several statistical metrics, and the associated storm tides are simulated. For comparison, we employ the Historical Storm Method (HSM) to simulate storm tides for historical TCs from 1950 to 2019. Storm tide hazard curves are calculated and compared using these two methods. Our results demonstrate that the SDTM can robustly estimate storm tide hazards for both short and long return periods, whereas the HSM performs well for short return periods but struggles to reliably assess storm tide hazards for long return periods. Notably, within the SDTM, storm tide height exhibits nonlinear growth with increasing return periods in the Gumbel plot, a phenomenon not observed in the HSM due to the limited time span of TC records. With sufficient TC data, the spatial storm tide hazard maps obtained from the SDTM can serve as a robust foundation for developing disaster prevention and mitigation policies.

Variations of compound warm, dry, wet, and cold climate extremes in India during 1951 to 2014

The simultaneous occurrence of climate extremes significantly impacts ecosystems, increasing the vulnerability to physical risks. Despite extensive research on hot extremes and droughts globally, there remains a significant gap in comprehending the occurrence, magnitude, spatial extent, and associated risks of compound extremes, encompassing scenarios like warm/dry, cold/dry, warm/wet, and cold/wet. This study investigates various compound extreme scenarios by examining combinations of maximum temperature (Tx) and the Standardized Precipitation Evapotranspiration Index (SPEI) using monthly data from 1951 to 2014 acquired from the India Meteorological Department (IMD) for Indian landmass. From the results, the spatial extent of warm/dry events has increased at 1.8 % per decade, while cold/wet events decreased by 1.1 % over India. The warm/wet events have shown an increased trend of about 0.3 %, and cold/dry events at modest rise of 0.7 % per decade. Furthermore, compound warm/dry and cold/wet extremes over India exhibit extreme frequency and shorter return periods, posing greater risk. Conversely, compound cold/dry and warm/wet extremes occur less often, indicating longer return periods and lower risk. Across much of the country, the frequency of warm/dry, cold/dry, warm/wet, and cold/wet extremes ranges from 30 to 45, 15–30, 20–30, and 25–45 months, respectively. Notably, warm/dry conditions exhibit increased frequency in the recent period (1983–2014) with 31 years compared to the base period (1951–1982) which had approximately 24 years for a spatial extent exceeding 5 %. The findings of this study contribute to an enhanced understanding of the changes in compound climate extremes from a multivariate perspective.

Method for analyzing urban waterlogging mechanisms based on a 1D-2D water environment dynamic bidirectional coupling model

Urban waterlogging is a significant global issue. To achieve precisely control urban waterlogging and enhance our understanding of its causes, a novel study method was introduced. This method is based on a dynamic bidirectional coupling model that combines 1D-2D hydrodynamic and water quality simulations. The waterlogging phenomenon in densely populated metropolitan areas of Changzhi city, China, was studied. This study focused on investigating the process involved in waterlogging formation, particularly overflow at nodes induced by the design of the topological structure of the pipe network, constraints on the capacity of the underground drainage system, and the surface runoff accumulation. The complex interplay among these elements and their possible influences on waterlogging formation were clarified. The results indicated notable spatial and temporal variation in the waterlogging formation process in densely populated urban areas. Node overflow in the drainage system emerged as the key influencing factor in the waterlogging formation process, accounting for up to 71% of the total water accumulation at the peak time. The peak lag time of waterlogging during events with short return periods was primarily determined by the rainfall peak moment. In contrast, the peak time of waterlogging during events with long return periods was influenced by the rainfall peak moment, drainage capacity and topological structure of the pipe network. Notably, the access of inflow from both upstream and downstream segments of the pipe network drainage system significantly impacted the peak time of waterlogging, with upstream water potentially delaying the peak time substantially. This study not only provides new insights into urban waterlogging mechanisms but also provides practical guidance for optimizing urban drainage systems, urban planning, and disaster risk management.

Urbanization Further Intensifies Short‐Duration Rainfall Extremes in a Warmer Climate

AbstractIntensification of short‐duration rainfall extremes contributes to increased urban flood risk. Yet, it remains unclear how upper‐tail rainfall statistics could change with regional warming. Here, we characterize the non‐stationarity of rainfall extremes over durations of 1–24 hr for the rapidly developing coastal megalopolis of the Greater Bay Area, China. Using high‐resolution, multi‐source, merged and gridded data we observe greater increases in rainfall intensities over the north‐central part of the region compared with the southern coastal region. Our results show, for the first time, that urbanization nonlinearly increases rainfall intensities at different durations and return periods. Over short durations (≤3‐hr) and short return periods (2‐yr), urban areas have the greatest scaling rates (≥19.9%/°C). However, over longer durations (≥9‐hr) rural areas have greater scaling rates, with a lower degree of dependency on both durations and return periods.

Assessing Benzene and TVOC Pollution and the Carcinogenic and Noncarcinogenic Risks to Workers in an Industrial Plant in Southeastern Romania.

The article aims to analyze the pollution with Volatile Organic Compounds (VOC) emitted from the biggest refinery in Romania, using the daily and monthly series registered for two years in two sites on the industrial platform, and the carcinogenic and noncarcinogenic risks for workers at the industrial plant. Since the values of the basic statistics (minimum, maximum, and average) and outliers indicate that most recorded values exceed the maximum admissible limits established by law, the Peaks Over Threshold (POT) method was utilized to model the maximum values of the series and determine the return levels for benzene and total VOC (TVOC). Given the high values obtained for relatively short return periods, indicating potential danger for the workers, we assessed the noncarcinogenic and carcinogenic risks to benzene and TVOC exposure by computing the hazard index (HI) and lifetime cancer risk (LCR). The results indicate that 43.75% of the HI values are above 1, indicating a relatively high noncarcinogenic risk for different categories of workers. LRC indicates a high LRC for 93.75% of the workers in all considered categories exposed to TVOC.

Connection-density-aware satellite-ground federated learning via asynchronous dynamic aggregation

With the development of space technology, the use of satellites for Earth observation is becoming more and more common. Among them, low-earth orbit (LEO) satellites have received a lot of attention because of their short return period and low cost. However, traditional satellite systems are unable to process data in orbit due to technical limitations and can only transmit massive amounts of data with useless information back to ground stations and then perform calculations, putting a tremendous strain on downstream bandwidth. Additionally, there are data walls between satellite affiliates, which makes it difficult to share and use data. To address the lack of data processing capabilities and data barriers in conventional satellite systems, as well as to effectively use satellite resources and enhance worldwide collaboration, we proposed a connection density-aware satellite-ground federated learning (FL) framework. According to this structure, satellites serve as workers in federated learning, analyzing data and transmitting the parameters to ground stations for aggregation. The ground station senses the satellite’s connection density during the aggregation process and implements a dynamic aggregation approach for the downstream parameters. Experiments based on real image datasets and on a simulated satellite network validate the effectiveness of the method in terms of execution efficiency and accuracy.

Sediment analysis and historical context of the 2018 Palu-Donggala tsunami deposit, Indonesia

On 28th September 2018, a magnitude 7.5 earthquake occurred on the Palu-Koro strike slip fault near Palu, Indonesia. Shortly after, large tsunami waves generated by the earthquake and the submarine landslides it triggered, washed into Palu Bay. Here, we describe sediment characteristics of the tsunami deposits and present wave height models to provide a modern analogue for tsunamis occurring on strike slip faults. We analyzed 51 sediment samples from 21 sampling points on two transects at Palu City and one transect at Pantaloan. At Palu City, the tsunami inundated between 250 and 270 m inland. Sediments were massive, with landward fining from coarse sands (φ 0) to fine sands (φ 3.7) and weak upward fining sequences (by up to 1 φ). At Pantaloan the tsunami inundated up to 275 m inland. Sediments were massive, with landward fining from a few grains of gravel (φ −2) and coarse sands (φ 0.5) to fine sands (φ 2.5) and weak upward fining sequences (by up to 1 φ). Based on the sediment data the TSUFLIND model predicted: at Palu city flow depths of 1 to 8 m, and flow velocities up to 3.9 m/s; and at Pantoloan flow depths of 2 to 8 m, and flow velocities up 3.8 m/s. The boulder transport model was applied to data from heavy concrete blocks (0.8 to 4.9 tons) deposited by the tsunami between 46 and 125 m inland, and predicted flow depths of 0.8 to 4.3 m and flow velocities up to 5.6 m/s. The rapid attenuation inland of the tsunami flow depth is consistent with the event being partially generated by landslides caused by the Palu-Donggala earthquake. A study of Dutch colonial archives and historical data reveals at least six tsunami events have occurred in or near Palu Bay since 1920, suggesting a very short return period for such events, and a significant tsunami hazard to the area.

Seismic design and performance analysis of perforated rubber buffer layer in tunnel

Tunnels may be damaged under earthquakes, which has been observed by many earthquake events, and the buffer layer is proposed and widely investigated as a damping measure. The rubber is considered as a qualified buffer layer material because of its small elastic modulus and super elasticity, but its high price makes it difficult to apply in practical engineering. Therefore, four types of rubber buffer layers are proposed in this study, including the common rubber buffer layer and three types of perforated rubber buffer layers (PRBL), which can reduce the seismic damage and cost of tunnels. A pseudo-static method for calculating the seismic response of tunnels under horizontal and vertical earthquake motions is proposed and verified. Based on proposed pseudo-static method, a seismic design method for the buffer layer is present, and the proposed seismic design process is used to study the seismic mitigation performance of buffer layers. The initial design of the buffer layer under earthquake action E1 is carried out by pseudo-static method, and then the seismic mitigation performance is verified through dynamic time history analysis method under earthquake action E2. The earthquake action E1 and earthquake action E2 are the earthquake actions with short and long return periods of the engineering site, respectively. The results show that the common rubber buffer layer has almost no seismic mitigation performance, and the three types of PRBLs have good seismic mitigation performance. The type IV buffer layer is strip-shaped PRBL and the holes are along the longitudinal direction of the tunnel, and it has optimal seismic mitigation performance. The effects of vertical earthquake motion and peak ground acceleration (PGA) on the seismic mitigation performance of the buffer layer are studied. The results show that vertical earthquake motion has little effect on the seismic mitigation performance of different types of buffer layers. For different PGAs, the type IV buffer layer is able to efficiently decrease the peak internal force of secondary lining. The results also prove the validity of design method.

Flood Retention Lakes in a Rural‐Urban Catchment: Climate‐Dominated and Configuration‐Affected Performances

AbstractFlood retention lakes (RLs) are widely employed in rural‐urban catchments with low impacts on the natural environment. However, insights are lacking regarding the control of climate conditions on RLs' performances and how they are affected by different geographic configurations. This study applies a 2D hydrodynamic model to perform a catchment‐scale performance assessment of RLs beyond the scope of analytical and hydrological models. We conduct extensive numerical experiments of rainstorm‐induced flooding in a rural‐urban catchment with a constructed RL and blueprinted ones upstream. Results demonstrate an L‐shaped band of satisfactory performance of the current RL in the frequency‐duration diagram, which coincides with short return periods (<5 years) and long durations (>4 hr), or short durations (<3 hr) and moderate to long return periods (5–50 years); such L‐shaped pattern is also valid for additional RLs and their combinations. With the increase in event size, the first two modes of RL performance (out of four) correspond to effective flood mitigation. When working jointly, RLs with series configurations are more effective in reducing the mainstream flood peaks, while parallel connections provide a greater spatial extent of flood hazard mitigation. For both series and parallel configurations, the upstream‐weighted settings tend to outperform downstream‐weighted ones under more extreme events; the decentralized arrangement in the urban area yields more benefits in spatial flood hazard mitigation compared to the centralized case. The study highlights the critical role of rainstorm severity (with possible spatiotemporal variabilities) in controlling RL performances despite various configurations and hydraulic settings.

Quantifying uncertainties in tropical cyclone wind hazard assessment due to synthetic track stochastic variability for Southeast Asia

Extreme tropical cyclones (TCs) present serious threat to Southeast Asian communities, causing widespread loss of lives and property damages. This study investigates the uncertainties in probabilistic TC wind hazard assessment due to stochastic variability in the underlying synthetic TC track ensembles. We focus on landfall TCs in the Philippines and Vietnam using multiple realisations from a single synthetic TC generation model. It is found that the maximum 3-s gusts in the Philippines are 233.3 km/h and 301.6 km/h under 100-year and 500-year return periods (RP). The coefficient of variance (CV) for the ensemble means falls within 0.05–0.20 over the main landmass. In Vietnam, the maximum gusts under 100-year and 500-year RPs are 207.6 km/h and 286.1 km/h, respectively, with a CV range of 0.01–0.13. Large uncertainties mainly concentrate in high TC activity zones where the peak gusts from individual synthetic event set can be up to 20% higher than the ensemble outputs. Low TC activity zones are also prone to high ensemble spread in model outputs under short RPs, although these uncertainties tend to decrease as RP increases. The probabilistic hazard model is shown to be most sensitive to TC landfall frequency and maximum intensity. Influence from other track parameters, such as TC size and forward speed, can become important for long exposure of TC trajectories. Such insights enable better understanding on the key drivers of sensitivities in the probabilistic hazard maps. Our study complements the conventional hazard assessment using synthetic TC tracks by explicitly assessing the uncertainties from the underlying stochastic event catalogue. The calculated CVs arising from synthetic track stochastic variability can be compared and/or combined with uncertainty measures on the underlying TC hazard model. This ensures proper quantification and communication of full model uncertainties for more rigorous TC risk assessment and in subsequent risk mitigation.

Regulation of Flood Dynamics by a Check Dam System in a Typical Ecological Construction Watershed on the Loess Plateau, China

The check dam is the most important engineering measure in place for controlling water and preventing soil loss in the gully on the Loess Plateau. This study assesses Jiuyuangou, a typical governance watershed of the Loess Plateau, and studies the influence that the check dam system has on the dynamics of sub-storm floods over different return periods by coupling the one-dimensional hydrodynamic MIKE 11 model with the distributed hydrological MIKE SHE model. This research demonstrates the following: The check dam system significantly reduces a flood’s peak flow and total volume in the basin and also increases the flood duration. The former effects are greater than the latter effect. The flood peak’s rate of reduction, the flood volume’s rate of reduction and the flood duration’s rate of increase all increase linearly as the number of check dams increase. Of all dam systems, the check dam has the best linear response to a flood peak’s rate of reduction. The check dam system reduces the flow rate of flood runoff in the basin. After the dam is built, the average flow rate in the basin decreases by 54%. The runoff velocity of the flood is reduced by different degrees over different return periods and the average peak value decreases compared with a scenario lacking any kind of dam. The check dams have a greater impact on the runoff velocity over a shorter return period, with the velocity being 58.56% slower. Finally, the check dam system significantly reduces the intensity of erosion in the middle and lower reaches of the watershed, and it changes the distribution of the intensity compared to the original channel runoff. These findings are expected to provide a scientific basis for guiding the construction and high-quality development of check dams on the Loess Plateau. In addition, check dam construction in basins can trap water, sediment and nutrients, and it can also contribute to ecosystem diversity and maintaining ecosystem imbalances around the world.

Assessment of urban flood resilience based on a systematic framework

Urban flooding can seriously threaten urban ecological security and human life, and therefore urban flood resilience (UFR) is important for urban safety and stability. To comprehensively evaluate urban system performance during the entire process of rainfall, runoff, flooding, and drainage, we developed a systematic framework for UFR assessment covering runoff simulation, flood estimation, and resilience assessment, which broadly corresponded to the phases of resistance, adaptation, and recovery. The UFR in the phases of resistance, adaptation, and recovery was simulated and assessed using a system performance curve (SPC) and technically combining with the hybrid flood model while mainly considering the total simulation time and inundated urban proportion in SPC. Because the extent of urban flooding can be influenced by climate change and the rate of urbanization, we chose the corresponding representative factors of precipitation and infiltration rate and considered 21 simulation scenarios (seven rainfall return periods and three infiltration rates) for which UFR was quantified according to urban system performance. The effectiveness of this framework was demonstrated in application to a typical highly urbanized area (i.e., Dongguan, China). The following results were derived: (1) The inundated area under the pessimistic scenario (i.e., S19) would be nearly four times greater than that under the optimistic scenario (i.e., S3); (2) The values of UFR in Dongguan were 0.9494–0.9863, locating at the high and very high level; (3) The lowest UFR value was 0.6552 in the Shuixiang New City district; and (4) The rainfall return period was the main factor influencing UFR under relatively short rainfall return periods (i.e., S1–S9), while infiltration rate was the principal influencing factor under relatively long rainfall return periods (i.e., S10–S21). The proposed systematic framework could be applied in other cities and large-scale regions like urban agglomerations and provinces.

Coupled and Stand-Alone Regional Climate Modeling of Intensive Storms in Western Canada

A coupled atmospheric-hydrologic system models the complex interactions between the land surface and the atmospheric boundary layer and the water-energy cycle from groundwater across the land surface to the top of the atmosphere. A regional climate model called weather research forecasting (WRF) was coupled with a land-surface scheme (Noah) to simulate intensive storms in Alberta of Canada. Accounting for the land-atmosphere feedback enhances the predictability of the fine-tuned WRF-Noah system. Soil moisture, vegetation, and land-surface temperature influence latent and sensible heat fluxes and modulate both thermal and dynamical characteristics of land and the lower atmosphere. WRF was set up in a two-way, 3-domain nested framework so that the output of the outermost domain (D1) was used to run the 2nd domain (D2), and the output of D2 was used to run the innermost, 3rd domain (D3). By this 2-way nesting, D3 and D2 provide the feedback to their outer domains (D2 and D1), respectively. D3 was set at a 3-km resolution adequate to simulate convective storms. WRF-Noah was forced with climate outputs from global climate models (GCMs) for the baseline period 1980–2005. A regional frequency analysis and a quantile-quantile bias correction method were applied to develop intensity-duration-frequency (IDF) curves using precipitation data simulated by WRF-Noah. The simulated baseline precipitation of central Alberta agrees well with observed data from a 13-rain gauge network of the City of Edmonton. The 5th-generation mesoscale atmospheric model (MM5) of National Center for Atmospheric Research was also set up in a 3-domain, but 1-way nesting configuration. As expected, after bias correction, precipitation simulated by MM5 was less accurate than that simulated by WRF-Noah. For storms of short durations and return periods of more than 25 years, both MM5 driven by special reports on emission scenario climate scenarios of coupled model inter-comparison project (CMIP3) and WRF-Noah driven by representative concentration pathway climate scenarios of CMIP5 projected storm intensities in central Alberta to increase from the base period to the 2050s and to the 2080s.

Investigating wind direction influence on wind generated waves using Delft 3D for Gaza Strip Coast

Wind and water levels influence wave overtopping and consequent coastal flood threat, which is especially important in hyper-tidal bays where even modest variations in wave heights may be devastating if they coincide with high tides. The influence of wind and wave characteristics on wave propagation, as well as the sensitivity of significant wave height, are numerically investigated along the Gaza Strip's beachfront as an example. Wind waves with a high amplitude and short duration are susceptible to opposing winds, and their steepening effect varies throughout the bay shoreline, underlining the impact of shoreline geometry and bathymetry on wave hazard. The findings contribute to our existing knowledge of the complex interplay between wind and waves, as well as the crucial variables that maximize danger and hazard variability along the coastline. The findings of this study can assist port and harbor managers prevent financial losses due to downtime, influence sustainable coastal sea defense design, and better understand how wave danger may change in the future owing to shifting storm tracks. The findings can also be used to improve coastal infrastructure design and disaster response planning. Two scenarios were investigated with a wind direction of 330 and 30. It seems that when the wind direction is 330, it produces a higher Hs of 1.2 m and relatively larger wave return period with a range of 12-22 s and a higher wave energy dissipation of 220 N/Ms. In contrast, when the wind direction is 30, it produces a smaller HS of 1m with a short wave return period of 15-17s and smaller wave energy dissipation of 120 N/Ms. Overall, a wind direction of 30 has fewer occurring chances over the year but it seems to produce a destructive wave that are spread over the whole coast with a rapid return period.

Spatial dependence of floods shaped by extreme rainfall under the influence of urbanization.

Weather system are spatially and temporally dependent, and these dependencies can result in flood events with similar behaviors. While it is well known that urbanization profoundly impacts the flood generation process, much less is known about the impacts of urbanization on the spatial dependence of floods, a major determinant of flood risk severity. To this end, a scheme was proposed to detect the flood dependence variations influenced by urbanization. Based on the scheme, we found that 1) the flood dependence can be weakened with extreme rainfall increasing from a short return period to a long return period; 2) The flood dependencies can be amplified in slightly urbanized regions and mitigated in highly urbanized regions due to intensifying urbanization. In addition, the change characteristics of the flood dependencies influenced by urbanization are first identified from the perspective of network structure. We found that urbanization can significantly affect the network structure (i.e., hub and connectivity) of flood dependence, especially in highly urbanized regions. The catchments with high hub and connectivity are prone to widespread floods and should be given more attention in flood warning and control management work, which can contribute to helping defend against floods in hazard-prone areas.

A multi-step hazard assessment for debris-flow prone areas influenced by hydroclimatic events

Hazard assessment studies are fundamental to identifying disaster-prone areas, especially in locations with high environmental and socioeconomic vulnerability. This study proposes a multi-step debris-flow hazard assessment, based on the combination of Logistic Regression (LR) analysis, numerical simulation and rainfall back-analysis. A landslide-prone area of 84 km2 is chosen as test-site, including 20 river catchments and one of the largest petrochemical plants in Latin America. Rainfall is the main influencing factor in debris-flow initiation, as highlighted by the LR analysis, followed by soil cover and slope. The analysis also indicated the catchments more susceptible to debris flows and the simulation results show that the average runout distance in these catchments is 470 m, with an average peak flow height of 5 m and a peak velocity of 23 m s−1. Debris flows are triggered by short duration (<48 h), high-intensity (>200 mm) precipitation, with return periods that vary from 3 to 10 years. Five levels of hazard (very low to very high) are, then, proposed for the study site, based mainly on 48-h accumulated rainfall and flow properties. Industrial and residential areas in the projected debris-flow route generally exhibit the highest overall hazard levels, as many were developed in the depositional area of debris flows and near fluvial courses, where associated floods and flash floods may occur. As pointed out by recent studies, an increase in the frequency of extreme precipitation events is projected in the Serra do Mar region and when the general short return period of the debris-flow triggering rainfall is considered (<10 years), large magnitude (>105 m3) debris flows are likely to occur in the near future.

Extreme wind speed prediction in mountainous area with mixed wind climates

In addition to common synoptic wind system, the mountainous terrain forms a local thermally driven wind system, which makes the mountain wind system have strong terrain dependence. Therefore, in order to estimate the reliable design wind speeds for structural safety, the samples for extreme wind speeds for certain return periods at mountainous areas can only come from field measurements at construction site. However, wind speeds measuring duration is usually short in real practice. This work proposes a novel method for calculating extreme wind speeds in mountainous areas by using short-term field measurement data and long-term nearby meteorological observatory data. Extreme wind speeds in mountainous area are affected by mixed climates composed by local-scale wind and large-scale synoptic wind. The local winds can be recorded at construction site with short observatory time, while the extreme wind speeds samples from synoptic wind climate from nearby meteorological station with long observatory time is extracted for data augmentation. The bridge construction site at Hengduan Mountains in southwestern China is taken as an example in this study. A 10-month dataset of field measurement wind speeds is recorded at this location. This study firstly provides a new method to extract wind speed time series of windstorms. Based on the different windstorm features, the local and synoptic winds are separated. Next, the synoptic wind speeds from nearby meteorological stations are converted and combined with local winds to derive the extreme wind speeds probability distribution function. The calculation results shows that the extreme wind speed in the short return period is controlled by the local wind system, and the long-period extreme wind speed is determined by the synoptic wind system in the mountain area. The descending slope of the synoptic wind speed exceeding probability exceeds the local wind by about 20%. If the influence of mixed climate is not considered, and the wind speed samples are not divided by category, the decline slope will be 7% lower.

Influence of tidal level on quantifying the probability of nearshore tsunami hazard

Nearshore tsunami hazard can be greatly affected by the tidal level, especially when large tsunami waves meet the high tidal level. This study aims to quantify the probability of the peak nearshore tsunami elevation (PNTE) caused by seismic tsunamis considering the randomness of event occurrence time and the variation of tidal level. The coast around the Pearl River Estuary has been chosen as the study area to show the influence of tidal level on the probability of nearshore tsunami hazard. Two approaches are proposed to calculate the PNTE considering the effect of tide in a probabilistic tsunami assessment framework. One approach is a linear superposition of tsunami wave upon the tidal level, and the other considering the influence of tidal level on tsunami nearshore amplification. The probability of the PNTE along the concern coast is obtained. The results considering the effect of tide show that the PNTE corresponding to short return period is obviously larger than that based on the mean sea level, but no obvious difference in the case of long return period. Moreover, in the study area, the two approaches considering the effect of tide show only slight difference in estimating the probability of PNTE, which suggests the applicability of the linear superposition method in nearshore tsunami hazard assessments.