Partial Duration Research Articles

Frequency analysis of the extreme streamflow by the threshold level method in semi-arid region: Case study of Wadi Mekerra catchment in the North-West of Algeria

Abstract Extreme streamflow drought is the direct problem of serious on damaging and on social impacts, so the frequency analysis of hydrological drought is an important work can be done to studying the drought phenomenon in catchments. So the hydrometric data for a river conducts to the establishment of the flow duration curve (FDC) as an important index of streamflow drought regime, from this characteristic, a threshold level can be defined for both perennial or intermittent streams. Well, two partial duration series can be derived for each year; the deficit volume and drought duration series. In the catchment of Wadi Mekerra in the North-West of Algeria, the minimum value estimated from the Pareto’s annual maximum instantaneous flood population (0.60 m3∙s−1) is considered as the threshold level index where, the largest deficit volume and the largest drought duration occurring in a given year are taken into consideration. Hence, the frequency analysis of the streamflow drought regime of the catchment is analysed with Weibull distribution for both deficit volume and drought duration combined with the probability of occurrence which is determined under some criterion in order to forecasting the streamflow drought in the catchment.

Spatio-temporal consideration of the impact of flood event types on flood statistic

Flood events can have very different generating processes. Floods may originate from high intensity rainfall, long-duration rainfall or snowmelt. Other factors, e.g. initial soil moisture conditions, also affect the spatial and temporal characteristics of floods. Hence, a typology for floods is often used to classify floods according to their runoff generating processes. Having in mind the changing circumstances for floods over the years, like climatic or anthropogenic changes, the question arises in how far these changes affect the occurrence of certain flood types. This does not only concern a change of frequency of flood event types over time, but also spatial changes resulting in different regional patterns. We investigate the changes of the frequency of occurrence of flood event types, their spatial patterns and the consequences for estimating extreme events. Many watershed characteristics are strongly related with specific flood types, e.g. elevation with snowmelt. Short-rain events are limited in their spatial extension and cause floods in smaller catchments, whereas in large river basins a large flood peak requires a long and spatially extended rain event. In this study, the flood typology is based on analyses of the peak-volume relationship allowing to consider long periods of observation with partially only few meteorological data, e.g. snow height. For the resulting flood types, temporal changes and spatial patterns are detected and connected with the generating processes as well as catchment characteristics. Finally, the impact of changes on the flood statistic is investigated by using a seasonal mixture model of partial duration series that is able to model event types and seasons separately and combines them in an annual model.

Biomechanical investigation of the type and configuration of screws used in high tibial osteotomy with titanium locking plate and screw fixation

BackgroundTo maintain the corrected alignment after high tibial osteotomy (HTO), fixation with titanium locking plate and screws is widely used in current practice; however, screw breakage is a common complication. Thus, this study was to investigate the mechanical stability of HTO with locking plate and various screw fixations, including the length as well as the type.MethodsA finite element (FE) model involving a distal femur, meniscus, and a proximal tibia with HTO fixed with a titanium locking plate and screws was created. The angle of the medial open wedge was 12°, and bone graft was not used. Two types of screws, namely conventional locking and far-cortical locking screws, with various lengths and configurations were used. At the proximal tibia, conventional locking screws with different lengths, 30 and 55 mm, were used; at the tibia shaft, different screw fixations including one-cortical, two-cortical, and far-cortical locking screws were used.ResultsThe use of far-cortical locking screw generated the highest equivalent stress on the screws, which was four times (from 137.3 to 541 MPa) higher than that of the one-cortical screw. Also, it led to the maximum deformation of the tibia and a greater gap deformation at the osteotomy site, which was twice (from 0.222 to 0.442 mm) larger than that of the one-cortical screw. The effect of different locking screw length on tibia deformation and implant stress was minor.ConclusionThus, far-cortical locking screws and plates increase interfragmentary movement but the screw stress is relatively high. Increasing the protection time (partial weight duration) is suggested to decrease the risk of screw breakage in HTO through fixation with titanium far-cortical locking screws and plates.

Early intervention with cognitive behavioral therapy reduces sick leave duration in people with adjustment, anxiety and depressive disorders

Background: Early intervention in workers diagnosed with mental disorders is associated with a lower incidence of relapse and shorter sick leave. However, no studies have been carried out on the effect of early intervention using an evidence-based therapy, Cognitive Behavioral Therapy (CBT), on people with sick leave.Aims: The objectives of the present study are to study whether the type of intervention (early or late) will affect the total duration of the sick leave, the partial duration of the sick leave, the duration of the psychotherapy and the time until return to work after the psychotherapy ends. The sample was composed of 167 participants who were on sick leave for adjustment disorders, anxiety disorders or depressive disorder.Results: The participants who had early intervention with CBT had a significantly shorter duration of total sick leave and partial sick leave, and a shorter time until returning to work after the psychotherapy ended than those who had late intervention. There were no statistically differences in the duration or efficacy of the psychotherapy.Conclusion: We can suggest that providing early access to CBT significantly reduces the length of sick leave in patients with mental disorders.

Evaluation of Stormwater Infrastructure Design Storms Developed Using Partial Duration and Annual Maximum Series Models

AbstractThis study assesses the advantages and limitations of developing design storms using the partial duration series exceedance-based (PDS-E) rainfall frequency model in comparison with the ann...

Estimation of empirical rainfall thresholds for landslide triggering using partial duration series and their relation with climatic cycles. An application in southern Ecuador

Rainfall-induced landslides constitute a major cause of damage and fatalities throughout the intramontane basins of the Andes. The geological and climatic setting plays a key role in the generation of a high number of landslides in this area. For this reason, a greater understanding of the relationship between landslide frequency and climate conditions is necessary to mitigate human and economic losses. Accordingly, this paper presents an analysis of rainfall variables associated with a series of dated landslides (153 in total) in the southern Ecuador basin of Loja. This analysis was performed by applying an affordable empirical method that enables the calculation of critical rainfall threshold (CRT) curves. This calculation is based on an in-depth examination of rainfall parameters, such as cumulative precipitation and mean intensity, linked to a wide range of rainfall duration (from 1 to 90 days). The inspection of these parameters was addressed considering their frequency, which was calculated by using partial duration series (PDS), taking into account the entire rainfall record. This work has revealed that only 24% of landslides were triggered by rainfall conditions with maximum return periods greater than 1 year, whereas the rest did not exceed that return period. After finding the best correlation between the maximum return periods and the maximum mean intensity, a minimum power law function was adjusted to the CRT curve that correlates duration and cumulative rainfall. The values for this CRT function resulted in 5.14 and 0.83 for its scaling constant (α) and shape parameter (β), respectively. In addition, a spectral analysis was conducted to detect climatic cycles on the entire rainfall record. In general, a clear correlation could not be established between climatic frequencies and significant rainfall events inducing landslides, although similarly return periods were found for a critical rainfall event of March 2015 (10.4 years) and the SUNSPOT cycles (10.5-12 years). The results derived from this research are significantly valuable for the prevention of future mass-movements, although additional data will be crucial to update and calibrate CRT curves to study the influence of climate on landslide event frequency and magnitude in Loja.

Too Cold to Clot? Does Intraoperative Hypothermia Contribute to Bleeding After Aortic Surgery?

We determined the impact of intraoperative hypothermia on postoperative bleeding after thoracic aortic surgery. We retrospectively analyzed 98 consecutive patients who underwent aortic surgery with deep hypothermic circulatory arrest between 2010 and 2014. We evaluated lowest temperature, absolute decrease in temperature, and rewarming rate. Univariate and multivariate regression were used to determine relationships between temperature, clinical characteristics, and measures of postoperative bleeding. The mean age of patients was 60.5 ± 15.1 years, with 64.3% male and 60% Caucasian. The lowest temperatures recorded were 13.5 ± 4.6°C at the bypass circuit. Change in hematocrit was associated with ethnicity, preoperative hematocrit, and rewarming rate. Chest tube output was associated with body mass index, preoperative platelet count, prior cardiac surgery, cardiopulmonary bypass (CPB) duration, intraoperative blood product transfusion, lowest surface temperature, and change in surface temperature. Postoperative packed red blood cell transfusion was associated with ejection fraction, chronic obstructive pulmonary disease (COPD), platelet count, partial thromboplastin time, CPB duration, and lowest blood temperature. Fresh frozen plasma transfusion correlated with COPD, CPB duration, and final blood temperature. Platelet transfusion correlated with body mass index and preoperative platelet count. Unplanned reoperation for bleeding was associated with final temperature and change in temperature. We found no consistent associations between intraoperative temperature and indicators of bleeding. Intraoperative cooling strategies should be based on optimal end-organ protection rather than fear of postoperative bleeding; rewarming strategies may ameliorate the risk of coagulopathy.

The exact extreme value distribution – applied study

Extreme value theory is used to develop models for describing the distribution of extreme events. Exact extreme value or compound distri-bution which is based on the theory of the maximum of random variables of random numbers is one of the most important models that are applicable in various situations, for instance of interest, it uses partial duration series (PDF) data to analyze extreme hydrological. As part of our earlier study, the parameters of this model were estimated by two methods, maximum likelihood (ML) and Bayesian- based on non-informative and informative priors. Moreover, a comparative study using simulated data showed that the Bayesian based on informative prior is the best estimation method. In this paper, a real data set taken from records of the largest daily rainfall data of Jeddah city in Saudi Arabia is used to fit the model when the parameters are estimated by Bayesian method. A comparative applied study indicates that the exact extreme value model under Bayesian estimates (BE) of its parameters provides appropriate fit for this data set and it is more applicable than the same model when the parameters are estimated by ML method and other three classical extreme value models.

Evaluating Annual Maximum and Partial Duration Series for Estimating Frequency of Small Magnitude Floods

Understanding the nature of frequent floods is important for characterising channel morphology, riparian and aquatic habitat, and informing river restoration efforts. This paper presents results from an analysis on frequency estimates of low magnitude floods using the annual maximum and partial series data compared to actual flood series. Five frequency distribution models were fitted to data from 24 gauging stations in the Great Barrier Reef (GBR) lagoon catchments in north-eastern Australia. Based on the goodness of fit test, Generalised Extreme Value, Generalised Pareto and Log Pearson Type 3 models were used to estimate flood frequencies across the study region. Results suggest frequency estimates based on a partial series are better, compared to an annual series, for small to medium floods, while both methods produce similar results for large floods. Although both methods converge at a higher recurrence interval, the convergence recurrence interval varies between catchments. Results also suggest frequency estimates vary slightly between two or more partial series, depending on flood threshold, and the differences are large for the catchments that experience less frequent floods. While a partial series produces better frequency estimates, it can underestimate or overestimate the frequency if the flood threshold differs largely compared to bankfull discharge. These results have significant implications in calculating the dependency of floodplain ecosystems on the frequency of flooding and their subsequent management.

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Abstract. The assessment of road infrastructure exposure to extreme weather events is of major importance for scientists and practitioners alike. In this study, we compare the different extreme value approaches and fitting methods with respect to their value for assessing the exposure of transport networks to extreme precipitation and temperature impacts. Based on an Austrian data set from 25 meteorological stations representing diverse meteorological conditions, we assess the added value of partial duration series (PDS) over the standardly used annual maxima series (AMS) in order to give recommendations for performing extreme value statistics of meteorological hazards. Results show the merits of the robust L-moment estimation, which yielded better results than maximum likelihood estimation in 62 % of all cases. At the same time, results question the general assumption of the threshold excess approach (employing PDS) being superior to the block maxima approach (employing AMS) due to information gain. For low return periods (non-extreme events) the PDS approach tends to overestimate return levels as compared to the AMS approach, whereas an opposite behavior was found for high return levels (extreme events). In extreme cases, an inappropriate threshold was shown to lead to considerable biases that may outperform the possible gain of information from including additional extreme events by far. This effect was visible from neither the square-root criterion nor standardly used graphical diagnosis (mean residual life plot) but rather from a direct comparison of AMS and PDS in combined quantile plots. We therefore recommend performing AMS and PDS approaches simultaneously in order to select the best-suited approach. This will make the analyses more robust, not only in cases where threshold selection and dependency introduces biases to the PDS approach but also in cases where the AMS contains non-extreme events that may introduce similar biases. For assessing the performance of extreme events we recommend the use of conditional performance measures that focus on rare events only in addition to standardly used unconditional indicators. The findings of the study directly address road and traffic management but can be transferred to a range of other environmental variables including meteorological and hydrological quantities.

A regional and nonstationary model for partial duration series of extreme rainfall

AbstractRegional extreme value models for estimation of extreme rainfall intensities are widely applied, but their underlying assumption of stationarity is challenged. Many recent studies show that the rainfall extremes worldwide exhibit a nonstationary behavior. This paper presents a spatiotemporal model of extreme rainfall. The framework is built on a partial duration series approach with a nonstationary, regional threshold value. The model is based on generalized linear regression solved by generalized estimation equations. It allows a spatial correlation between the stations in the network and accounts furthermore for variable observation periods at each station and in each year. Marginal regional and temporal regression models solved by generalized least squares are used to validate and discuss the results of the full spatiotemporal model. The model is applied on data from a large Danish rain gauge network for four durations ranging from 10 min to 24 h. The observation period differs between stations, and the number of stations with more than 10 years of observations has increased over the years. A spatiotemporal model for the threshold is suggested, applying the mean annual precipitation and time as the explanatory variables in the regional and temporal domain, respectively. Further analysis of partial duration series with nonstationary and regional thresholds shows that the mean exceedances also exhibit a significant variation in space and time for some rainfall durations, while the shape parameter is found to be constant.

Comparison of the performance of power law and probability distributions in the frequency analysis of flood in Dez Basin, Iran

Determination of the return period of design flood depends on the nature of the project and the consequences of the flood and is based on economic criteria, human casualties, and hydrological factors. Underestimation of flood might result in casualties and economic damages, while the overestimation leads to capital waste. Therefore, in this research, the flood frequency analysis of Dez Basin, Iran was conducted within the period of 1956–2012 using power law approach together with ordinary distributions, including normal, log normal, Pearson type III, exponential, gamma, generalized extreme value, Nakagami, Rayleigh, logistic, generalized logistic, generalized Pareto, and Weibull distributions. The power law comes from the fractal nature of earth science phenomena such as precipitation and runoff. Accordingly, in this research the partial duration flood series of five hydrometric stations in Dez Basin were extracted using power law with the intervals of 7, 14, 30, and 60 days and then compared with the annual maxima. The results indicated that the annual maxima were not suitable for frequency analysis of the flood in Dez Basin, and the 30-day partial duration series obtained from the power law has a better correspondence with the flow and properties of the Dez Basin. The independence and stationarity of the 30-day partial duration series were examined by Wald–Wolfowitz test, confirming the independence of the considered series. Next, the power distribution and the typical statistical distributions were fitted onto the data of the flood in Dez Basin, with the performance of each distribution being investigated using normalized root-mean-square error and Nash–Sutcliffe criteria. The results revealed that in the SDZ and TPB stations, power distribution had a better performance than other considered distributions. Moreover, in the SDS, TPS, and TZ stations the power distribution stood in the second rank in terms of the best distribution. As the performance of power distribution in the estimation of the flood in Dez Basin has been very satisfactory and calculation of its parameters and its application is easier than ordinary probability distributions, thus it can be suggested as the superior distribution for flood frequency analysis in Dez Basin.

Non-Stationary Rainfall Intensity-Duration-Frequency Relationship: a Comparison between Annual Maximum and Partial Duration Series

The rainfall Intensity-Duration-Frequency (IDF) relationship is the primary input for storm water management and other engineering design applications across the world and it is developed by fitting an appropriate theoretical probability distribution to annual maximum (AM) series or partial duration series (PDS) of rainfall. The existing IDF relationship developing methods consider the extreme rainfall series as a stationary series. There exist few studies that compared AM and PDS datasets for developing rainfall IDF relationship in a stationary condition. However, during the last few decades, the intensity and frequency of extreme rainfall events are increasing due to global climate change and creating a non-stationary component in the extreme rainfall series. Therefore, the rainfall IDF relationship developed with the stationary assumption is no longer tenable in a changing climate. Hence, it is inevitable to develop non-stationary rainfall IDF relationship and to understand the differences in non-stationary rainfall IDF relationships derived using AM and PDS datasets. Consequently, the objectives of this study are: (1) to develop non-stationary rainfall IDF relationships using both AM and PDS datasets; (2) to compare them in terms of return level estimation. In particular, the non-linear trend in different durations’ PDS and AM datasets of Hyderabad city (India) rainfall is modeled using Multi-objective Genetic Algorithm (MGA) generated Time based covariate. In this study, the PDS datasets are modeled by the Generalized Pareto Distribution (GPD) while the AM datasets are modeled by the Generalized Extreme Value Distribution (GEVD). The time-varying component is introduced in the scale parameter of the GPD and the location parameter of the GEVD by linking the MGA generated covariate. In addition, the complexity of each non-stationary model is identified using the corrected Akaike Information Criteria (AICc) and the statistical significance of trend parameter in the non-stationary models is estimated using the Likelihood Ratio (LR) test. Upon detecting significant superiority of non-stationary models, the return levels of extreme rainfall event for 2-, 5-, 10- and 25-year return periods are calculated using non-stationary models. From the results, it is observed that the non-stationary return levels estimated with PDS datasets are higher than those estimated with AM datasets for short durations and smaller return periods while the non-stationary return levels estimated with AM datasets are higher than those estimated with PDS datasets for long durations and higher return periods.

Regional frequency analysis of short duration rainfall extremes using gridded daily rainfall data as co-variate

A regional partial duration series (PDS) model is applied for estimation of intensity duration frequency relationships of extreme rainfalls in Denmark. The model uses generalised least squares regression to relate the PDS parameters to gridded rainfall statistics from a dense network of rain gauges with daily measurements. The Poisson rate is positively correlated to the mean annual precipitation for all durations considered (1 min to 48 hours). The mean intensity can be assumed constant over Denmark for durations up to 1 hour. For durations larger than 1 hour, the mean intensity is significantly correlated to the mean extreme daily precipitation. A Generalised Pareto distribution with a regional constant shape parameter is adopted. Compared to previous regional studies in Denmark, a general increase in extreme rainfall intensity for durations up to 1 hour is found, whereas for larger durations both increases and decreases are seen. A subsample analysis is conducted to evaluate the impacts of non-stationarities in the rainfall data. The regional model includes the non-stationarities as an additional source of uncertainty, together with sampling uncertainty and uncertainty caused by spatial variability.

Flood frequency analysis for a braided river catchment in New Zealand: Comparing annual maximum and partial duration series with varying record lengths

This study addresses technical questions concerning the use of the partial duration series (PDS) within the domain of flood frequency analysis. The recurring questions which often prevent the standardised use of the PDS are peak independence and threshold selection. This paper explores standardised approaches to peak and threshold selection to produce PDS samples with differing average annual exceedances, using six theoretical probability distributions. The availability of historical annual maximum (AMS) data (1930–1966) in addition to systemic AMS data (1967–2015) enables a unique comparison between the performance of the PDS sample and the systemic AMS sample. A recently derived formula for the translation of the PDS into the annual domain, simplifying the use of the PDS, is utilised in an applied case study for the first time. Overall, the study shows that PDS sampling returns flood magnitudes similar to those produced by AMS series utilising historical data and thus the use of the PDS should be preferred in cases where historical flood data is unavailable.

Maternal Nonstandard Work Schedules and Breastfeeding Behaviors

Objectives Although maternal employment rates have increased in the last decade in the UK, there is very little research investigating the linkages between maternal nonstandard work schedules (i.e., work schedules outside of the Monday through Friday, 9–5 schedule) and breastfeeding initiation and duration, especially given the wide literature citing the health advantages of breastfeeding for mothers and children. Methods This paper uses a population-based, UK cohort study, the Millennium Cohort Study (n = 17,397), to investigate the association between types of maternal nonstandard work (evening, night, away from home overnight, and weekends) and breastfeeding behaviors. Results In unadjusted models, exposure to evening shifts was associated with greater odds of breastfeeding initiation (OR 1.71, CI 1.50–1.94) and greater odds of short (OR 1.55, CI 1.32–1.81), intermediate (OR 2.01, CI 1.64–2.47), prolonged partial duration (OR 2.20, CI 1.78–2.72), and prolonged exclusive duration (OR 1.53, CI 1.29–1.82), compared with mothers who were unemployed and those who work other types of nonstandard shifts. Socioeconomic advantage of mothers working evening schedules largely explained the higher odds of breastfeeding initiation and duration. Conclusions Socioeconomic characteristics explain more breastfeeding behaviors among mothers working evening shifts. Policy interventions to increase breastfeeding initiation and duration should consider the timing of maternal work schedules.

Similarity and difference of global reanalysis datasets (WFD and APHRODITE) in driving lumped and distributed hydrological models in a humid region of China

Different conclusions have been drawn in literature as using reanalysis rainfall products to drive hydrological models for the simulation of streamflow, which warrant a need of further investigation before a generalised conclusion can be drawn. This paper assesses the utility of two widely used reanalysis rainfall datasets (WFD (developed by the WATCH project) and APHRODITE (Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation of the water resources)) against the gauged rainfall in terms of flood simulation in lumped (Xinanjiang Model) and distributed (SWAT Model) hydrological models in a tributary basin of Yangtze River with 94,660km2 drainage area in humid region of southern China. Differences in terms of rainfall accumulation, number of rainy days, spatial patterns of the rainfall amount and frequency distribution of the rain rates are evaluated. The APHRODITE product shows high consistency with the gauged rainfall while WFD data gives large errors in various statistical indices in the study region. Simulated discharges from the gauged and reanalysis rainfall data, respectively, are analysed and compared with the observed discharge in basin outlet over the period 1991–2005. The APHRODITE data show relatively high ability in modelling hydrological responses while the WFD data based models give large error in simulating the discharge. For the assessment of the high flows, both datasets exhibit some skills in flood prediction, however, APHRODITE data perform better than the WFD data when forcing into the lumped Xinanjiang Model than into the distributed SWAT Model in terms of flood duration, Probability of Detection, False Alarm Rate, regressions of annual peaks and partial duration series.

Regional Estimation of Floods for Ungauged Sites Using Partial Duration Series and Scaling Approach

AbstractOne of the main obstacles in making reliable predictions of extreme events is the apparent shortness of the time series available in hydrology. There is a common advantage of both regional flood-frequency analysis and partial duration series (PDS) in which both of them allow a reduction of uncertainty by introducing more data to the site of interest. Therefore, a new regional index flood method for ungauged sites based on the PDS model is presented. The PDS model considered in this case assumes a Poisson-distributed number of threshold exceedances and generalized Pareto-distributed peak magnitudes. A new objective approach for the selection of the threshold in the context of regionalization is introduced. This approach estimates a range of reasonable thresholds (or an average annual number of events) for every site. Consequently, the regional average annual number of events can be determined as a common value for all sites in the homogeneous region. The delineation of hydrologically homogeneous re...

Assessing critical rainfall thresholds for landslide triggering by generating additional information from a reduced database: an approach with examples from the Betic Cordillera (Spain)

The denudation of young reliefs prone to landslides can have severe consequences for society and the environment. However, landslide databases and the additional information (landslide type, date and triggering factors) necessary to deal with landslide hazard assessment and the development of effective and reliable landslide warning systems are usually scarce or non-existent. In this way, by taking into account the date of landslide events and by expanding the analysis of cumulative rainfall from these dates to a broader time period that includes the days or months leading up to a landslide, the corresponding triggering rainfall threshold can be assessed more accurately. In this paper, a methodology based on a partial duration series analysis applied to rainfall variables allows the possibility to better understand precipitation patterns. Another advantage of analysing precipitation variables within a broader time period is the ability to identify greater accuracy rainfall anomalies such as extreme rainfalls with their return period related to a low number of dated landslide events (in this case, 20 landslide events). The landslide spatial distribution within a regional area requires the processing and analysis of data from multiple long-term historical daily rainfall records from different rainfall gauges, which notably increase the number of calculations to be dealt with. To overcome this inconvenience, these processes were streamlined by using macro-automation. Additionally, different rainfall durations can be interactively identified from graphical outputs that show anomalies on more than one rainfall variable after applying this methodology. Among these rainfall variables, the antecedent accumulated rainfall (A1) was found to be the most suitable to apply the occurrence probability analysis. When compared to other variables, the return period values of A1 were determined to be conservative, neither too high nor too low. Using this approach, the return period curve was shown to be an important graphic object in detecting uncommon rainfalls that are contemporaneous or previous to landslides. The relevant findings of this research show a power-law trend with α = 88.005 and β = 0.69 in the correlation of intensity and duration associated with antecedent cumulative rainfall (A1) anomalies. The mean return period for these anomalies resulted in 12.4 years, while for 50 % of the landslides, the recurrence interval was estimated in less than or equal to 3.6 years. In addition, significant differences were found between catalogued slope-cut failures and natural landslides. Moreover, differences were also found between simplified types of natural landslides.

Analysis of precipitation extremes in the Taihu Basin of China based on the regional L-moment method

China has suffered from increasingly severe flood events in recent years, most of which are caused by heavy rains. The substantial casualties and damage caused by flooding necessitates a better understanding of precipitation extremes, especially in heavily populated urban areas. Based on L-moments from a regional perspective, this paper analyzes precipitation extremes in the Taihu Basin, utilizing annual maximum daily precipitation and partial duration series at 96 rain gages. The comparison of regional and at-site analysis results shows that the former provides more robust estimates, especially in the upper tail of a distribution (higher quantiles). Also, the use of partial duration series, which captures more information about extreme events, was found to be preferable to describe the extreme precipitation events in the Taihu Basin. Given the recently observed more frequent occurrence and greater magnitude of precipitation extremes, it is suggested that the food design standard used in the basin should be updated, especially for the urbanizing zones.