Modeling non-stationary extreme waves using a point process approach and wavelets

In the present paper a statistical model for extreme value analysis is developed, considering seasonality. The model is applied to significant wave height data from the N. Aegean Sea. To build this model, a non-stationary point process is used, which incorporates apart from a time varying threshold and harmonic functions with a period of one year, a component μ _w(t) estimated through the wavelet transform. The wavelet transform has a dual role in the present study. It detects the significant “periodicities” of the signal by means of the wavelet global and scale-averaged power spectra and then is used to reconstruct the part of the time series, μ _w(t), represented by these significant features. A number of candidate models, which incorporate μ _w(t) in their location and scale parameters are tried. To avoid overparameterisation, an automatic model selection procedure based on the Akaike information criterion is carried out. The best obtained model is graphically evaluated by means of diagnostic plots. Finally, “aggregated” return levels with return periods of 20, 50 and 100 years, as well as time-dependent quantiles are estimated, combining the results of the wavelet analysis and the Poisson process model, identifying a significant reduction in return level estimation uncertainty, compared to more simple non-stationary models.     

Estimation of the generalized logistic distribution of extreme events using partial L-moments

Abstract

Statistical analysis of extreme events is often carried out to predict large return period events. In this paper, the use of partial L-moments (PL-moments) for estimating hydrological extremes from censored data is compared to that of simple L-moments. Expressions of parameter estimation are derived to fit the generalized logistic (GLO) distribution based on the PL-moments approach. Monte Carlo analysis is used to examine the sampling properties of PL-moments in fitting the GLO distribution to both GLO and non-GLO samples. Finally, both PL-moments and L-moments are used to fit the GLO distribution to 37 annual maximum rainfall series of raingauge station Kampung Lui (3118102) in Selangor, Malaysia, and it is found that analysis of censored rainfall samples of PL-moments would improve the estimation of large return period events.

Editor D. Koutsoyiannis; Associate editor K. Hamed

Citation Zakaria, Z.A., Shabri, A. and Ahmad, U.N., 2012. Estimation of the generalized logistic distribution of extreme events using partial L-moments. Hydrological Sciences Journal, 57 (3), 424–432.     

A bivariate analysis of the volume and duration of low-flow events

: The knowledge of the volume and duration of low-flow events in river channels is essential for water management and the design of hydraulics structures. In this study, both preceding characteristics, X ₁ and X ₂, are considered simultaneously via two types of bivariate distributions whose marginals are exponential. One of these bivariate distributions has been presented by Nagao and Kadoya (1971) and the other has been used by Singh and Singh (1991) to the study of rainfall intensity and rainfall depth. The results are applied to the low-flow series (“peaks-below-threshold”) of Lepreau River (station 01AQ001) in New Brunswick, Canada. These results show that the model that was successfully employed by Singh and Singh (1991) to study rainfall, presents certain difficulties when a very strong correlation, ρ, between the two random variables X ₁ and X ₂, exists. The model by Nagao and Kadoya (1971) seems to be more satisfactory for such situations, although this model seems also to be quite sensitive to variations in ρ.     

A bivariate analysis of the volume and duration of low-flow events

: The knowledge of the volume and duration of low-flow events in river channels is essential for water management and the design of hydraulics structures. In this study, both preceding characteristics, X ₁ and X ₂, are considered simultaneously via two types of bivariate distributions whose marginals are exponential. One of these bivariate distributions has been presented by Nagao and Kadoya (1971) and the other has been used by Singh and Singh (1991) to the study of rainfall intensity and rainfall depth. The results are applied to the low-flow series (“peaks-below-threshold”) of Lepreau River (station 01AQ001) in New Brunswick, Canada. These results show that the model that was successfully employed by Singh and Singh (1991) to study rainfall, presents certain difficulties when a very strong correlation, ρ, between the two random variables X ₁ and X ₂, exists. The model by Nagao and Kadoya (1971) seems to be more satisfactory for such situations, although this model seems also to be quite sensitive to variations in ρ.     

Identification of extreme events using drought indices and their impact on the Danube lower basin discharge

In this study extreme droughts and extremely wet periods in the Danube upper and middle basin (DUMB) have been highlighted with specific indices. The most widely used indices have been considered to estimate both the dry and wet phenomena severity and the frequency or spatio‐temporal extension. The climatic condition of 15 meteorological stations situated in the Danube basin has been evaluated using four indices: Palmer Drought Severity Index (PDSI), Palmer Hydrological Drought Index (PHDI), Weighted PDSI (WPLM) and Palmer Z‐index (ZIND). The four indices have been analysed separately for each of the four seasons between 1901 and 2000. First the internal structure of the time series of the four indices has been analysed separately. Then the overall temporal characteristic has been analysed by means of the principal component of the Multivariate Empirical Orthogonal Functions decomposition of the four indices (PC1‐MEOF). For the discharge in the Danube lower basin, station Orsova has been chosen, representing an integrator of the discharges from the DUMB. A very close connection has been found between Palmer indices and Danube discharge in all seasons (with correlation coefficients greater then 0.80) excepting the spring season. A classification in five classes of both the four indices separately and the PC1‐MEOF has been achieved in order to highlight extreme events. The impact of phenomena quantified by Palmer indices in DUMB upon discharges in Danube lower basin is evident. It was demonstrated in this study that the Greenland‐Balkan Oscillation (GBO) influences the south‐east European hydro‐climatic regime more than the North Atlantic Oscillation (NAO) Index. Copyright © 2016 John Wiley & Sons, Ltd.     

利用贝叶斯极值分布函数估算河套断陷带的发震概率

正Campbell(1982,1983)将贝叶斯概率理论和极值概率模型相结合,发展出一种估算地震发生概率的贝叶斯极值分布模型。在此模型中,地震活动的先验估计值是基于地震矩、滑动速率、地震复发率和震级等数据计算得到的,而后将估计值用于贝叶斯理论的后验估算,或者用于研究区的历史地震活动性的评估方面(李拴虎等,2016)。     

Effects of extreme climate events on the macrobenthic communities' structure and functioning of a temperate estuary

The Mondego estuary (Portugal) experienced profound structural and functional modifications due to eutrophication, which was exacerbated by consecutive weather extremes that compromised a previous restoration project. This work explores multiple climate impacts on macrobenthic communities’ structure and functioning and its implications on ecosystem’s recovery. Floods and heat waves had a stronger negative effect on macrobenthic assemblages than the droughts, imposing a total abundance decline. Contrarily, biomass was not so affected by climate events, being stable and even increased in a mudflat area, where seagrass is re-colonizing. Bivalves and oligochaetes decreased with the flooding episodes, likewise subsurface-deposit feeders and suspension feeders, while crustaceans were particularly sensitive to heat waves. Species richness declined with the floods and heat waves, whilst evenness increased in sandflat area, constituting a positive sign towards recovery. Succession of different climate extremes affected ecosystem structure and functioning, delaying its recovery with possible consequent effects at higher trophic levels.     

Reconstructing extreme post‐wildfire floods: a comparison of convective and mesoscale events

In much of western United States destructive floods after wildfire are frequently caused by localized, short‐duration convective thunderstorms; however, little is known about post‐fire flooding from longer‐duration, low‐intensity mesoscale storms. In this study we estimate and compare peak flows from convective and mesoscale floods following the 2012 High Park Fire in the ungaged 15.5 km² Skin Gulch basin in the northcentral Colorado Front Range. The convective storm on 6 July 2012 came just days after the wildfire was contained. Radar data indicated that the total rainfall was 20–47 mm, and the maximum rainfall intensities (upwards of 50 mm h^?1) were concentrated over portions of the watershed that burned at high severity. The mesoscale storm on 9–15 September 2013 produced 220–240 mm of rain but had maximum 15‐min intensities of only 25–32 mm h^?1. Peak flows for each flood were estimated using three independent techniques. Our best estimate using a 2D hydraulic model was 28 m³ s^?1 km^?2 for the flood following the convective storm, placing it among the largest rainfall‐runoff floods per unit area in the United States. In contrast, the flood associated with the mesoscale flood was only 6 m³ s^?1 km^?2, but the long‐duration flood caused extensive channel incision and widening, indicating that this storm was much more geomorphically effective. The peak flow estimates for the 2013 flood had a higher relative uncertainty and this stemmed from whether we used pre‐ or post‐flood channel topography. The results document the extent to which a high and moderate severity forest fire can greatly increase peak flows and alter channel morphology, illustrate how indirect peak flow estimates have larger errors than is generally assumed, and indicate that the magnitude of post‐fire floods and geomorphic change can be affected by the timing, magnitude, duration, and sequence of rainstorms. Copyright © 2017 John Wiley & Sons, Ltd.     

Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed

Future climate projections of Global Climate Models (GCMs) under different emission scenarios are usually used for developing climate change mitigation and adaptation strategies. However, the existing GCMs have only limited ability to simulate the complex and local climate features, such as precipitation. Furthermore, the outputs provided by GCMs are too coarse to be useful in hydrologic impact assessment models, as these models require information at much finer scales. Therefore, downscaling of GCM outputs is usually employed to provide fine-resolution information required for impact models. Among the downscaling techniques based on statistical principles, multiple regression and weather generator are considered to be more popular, as they are computationally less demanding than the other downscaling techniques. In the present study, the performances of a multiple regression model (called SDSM) and a weather generator (called LARS-WG) are evaluated in terms of their ability to simulate the frequency of extreme precipitation events of current climate and downscaling of future extreme events. Areal average daily precipitation data of the Clutha watershed located in South Island, New Zealand, are used as baseline data in the analysis. Precipitation frequency analysis is performed by fitting the Generalized Extreme Value (GEV) distribution to the observed, the SDSM simulated/downscaled, and the LARS-WG simulated/downscaled annual maximum (AM) series. The computations are performed for five return periods: 10-, 20-, 40-, 50- and 100-year. The present results illustrate that both models have similar and good ability to simulate the extreme precipitation events and, thus, can be adopted with confidence for climate change impact studies of this nature.     

Complex active regions as the main source of extreme and large solar proton events

A study of solar proton sources indicated that solar flare events responsible for ≥2000 pfu proton fluxes mostly occur in complex active regions (CARs), i.e., in transition structures between active regions and activity complexes. Different classes of similar structures and their relation to solar proton events (SPEs) and evolution, depending on the origination conditions, are considered. Arguments in favor of the fact that sunspot groups with extreme dimensions are CARs are presented. An analysis of the flare activity in a CAR resulted in the detection of “physical” boundaries, which separate magnetic structures of the same polarity and are responsible for the independent development of each structure.     

German tanks and historical records: the estimation of the time coverage of ungauged extreme events

The use of historical data can significantly reduce the uncertainty around estimates of the magnitude of rare events obtained with extreme value statistical models. For historical data to be included in the statistical analysis a number of their properties, e.g. their number and magnitude, need to be known with a reasonable level of confidence. Another key aspect of the historical data which needs to be known is the coverage period of the historical information, i.e. the period of time over which it is assumed that all large events above a certain threshold are known. It might be the case though, that it is not possible to easily retrieve with sufficient confidence information on the coverage period, which therefore needs to be estimated. In this paper methods to perform such estimation are introduced and evaluated. The statistical definition of the problem corresponds to estimating the size of a population for which only few data points are available. This problem is generally refereed to as the German tanks problem, which arose during the second world war, when statistical estimates of the number of tanks available to the German army were obtained. Different estimators can be derived using different statistical estimation approaches, with the maximum spacing estimator being the minimum-variance unbiased estimator. The properties of three estimators are investigated by means of a simulation study, both for the simple estimation of the historical coverage and for the estimation of the extreme value statistical model. The maximum spacing estimator is confirmed to be a good approach to the estimation of the historical period coverage for practical use and its application for a case study in Britain is presented.     

Modelling the effects of fire and rainfall regimes on extreme erosion events in forested landscapes

Existing models of post-fire erosion have focused primarily on using empirical or deterministic approaches to predict the magnitude of response from catchments given some initial rainfall and burn conditions. These models are concerned with reducing uncertainties associated with hydro-geomorphic transfer processes and typically operate at event timescales. There have been relatively few attempts at modelling the stochastic interplay between fire disturbance and rainfall as factors which determine the frequency and severity with which catchments are conditioned (or primed) for a hazardous event. This process is sensitive to non-stationarity in fire and rainfall regime parameters and therefore suitable for evaluating the effects of climate change and strategic fire management on hydro-geomorphic hazards from burnt areas. In this paper we ask the question, “What is the first-order effect of climate change on the interaction between fire disturbance and storms?” The aim is to isolate the effects of fire and rainfall regimes on the frequency of extreme erosion events. Fire disturbance and storms are represented as independent stochastic processes with properties of spatial extent, temporal duration, and frequency of occurrence, and used in a germ–grain model to quantify the annual area affected by extreme erosion events due to the intersection of fire disturbance and storms. The model indicates that the frequency of extreme erosion events will increase as a result of climate change, although regions with frequent storms were most sensitive.     

Classification of yearly extreme precipitation events and associated flood risk in the Yangtze-Huaihe River Valley

Fifty cases of regional yearly extreme precipitation events(RYEPEs)were identified over the Yangtze-Huaihe River Valley(YHRV)during 1979–2016 applying the statistical percentile method.There were five types of RYEPEs,namely Yangtze Meiyu(YM-RYEPE),Huaihe Meiyu(HM-RYEPE),southwest-northeast-oriented Meiyu(SWNE-RYEPE)and typhoon I and II(TC-RYEPE)types of RYEPEs.Potential vorticity diagnosis showed that propagation trajectories of the RYEPEs along the Western Pacific Subtropical High and its steering flow were concentrated over the southern YHRV.As a result,the strongest and most frequently RYEPEs events,about 16–21 cases with average rainfall above 100 mm,occurred in the southern YHRV,particularly in the Nanjing metropolitan area.There have been 14 cases of flood-inducing RYEPEs since 1979,with the submerged area exceeding 120 km~2as simulated by the Flood Area hydraulic model,comprising six HM-RYEPEs,five YM-RYEPEs,two TC-RYEPEs,and one SWNE-RYEPE.The combination of evolving RYEPEs and rapid expansion of urban agglomeration is most likely to change the flood risk distribution over the Nanjing metropolitan area in the future.In the RCP6.0(RCP8.5)scenario,the built-up area increases at a rate of about 10.41 km~2(10 yr)~(-1)(24.67 km~2(10 yr)~(-1))from 2010 to 2100,and the area of high flood risk correspondingly increases from 3.86 km~2(3.86 km~2)to 9.00 km~2(13.51 km~2).Areas of high flood risk are mainly located at Chishan Lake in Jurong,Lukou International Airport in Nanjing,Dongshan in Jiangning District,Lishui District and other low-lying areas.The accurate simulation of flood scenarios can help reduce losses due to torrential flooding and improve early warnings,evacuation planning and risk analysis.More attention should be paid to the projected high flood risk because of the concentrated population,industrial zones and social wealth throughout the Nanjing metropolitan area.     

地下流体对地震孕育发生过程的影响研究综述

地下流体对地震的孕育、发生过程起着重要作用.本文简述了近年来国内外关于地下流体影响地震的研究进展,对流体诱发地震的物理机制进行了深入介绍,主要有孔隙压的增加对有效应力的降低、流体受热膨胀扩容以及对岩石的润滑和软化作用;同时介绍了一些典型的流体触发地震模式,包括地震泵、断层阀、膨胀—扩散模式等,并讨论了目前存在的主要问题...     

Modeling of occurrence frequencies of ion conics as a function of altitude and conic angle

The occurrence frequencies of dayside ion conics with various conic angles are obtained as a function of altitude from Exos-D (Akebono) observations. We made a model calculation of ion conic evolution to match the observation results. The observed occurrence frequencies of ion conics with 80° to 90° conic angle are used as an input to the model and the occurrence frequencies of ion conics with smaller conic angles are numerically calculated at higher altitudes. The calculated occurrence frequencies are compared with the observed ones of ion conics with smaller conic angles. We take into account conic angle variation with altitude in both adiabatic and non-adiabatic cases, horizontal extension of ion conics due to E × B drift, and evolution to elevated conics and ion beams in the model. In the adiabatic case, the conic angle decreases with increasing altitude much faster than was observed. The occurrence frequency of small-angle conics is much larger than the observed value without E × B drift and evolution to the other UFIs. An agreement is obtained by assuming non-adiabatic variation of conic angles with altitude and an ion E × B drift to gyro velocity ratio of 0.08 to 0.6, depending on geomagnetic activities.     

Contemporary versus long‐term denudation along a passive plate margin: the role of extreme events

Short‐term (contemporary) and long‐term denudation rates were determined for the Blue Mountains Plateau in the western Sydney Basin, Australia, to explore the role of extreme events (wildfires and catastrophic floods) in landscape denudation along a passive plate margin. Contemporary denudation rates were reconstructed using 40 years of river sediment load data from the Nattai catchment in the south‐west of the basin, combined with an analysis of hillslope erosion following recent wildfires. Long‐term denudation rates (10 kyr–10 Myr) were determined from terrestrial cosmogenic nuclides, apatite fission track thermochronology and post‐basalt flow valley incision. Contemporary denudation rates average several times lower than the long‐term average (5·5 ± 4 mm kyr^?1 versus 21·5 ± 7 mm kyr^?1). Erosion of sediment following wildfires accounts for only a small proportion (5%) of the contemporary rate. Most post‐fire sediment is stored on the lower slopes and valley floor, with the amount transported to the river network dependent on rainfall–run‐off conditions within the first few years following the fire. Historical catastrophic floods account for a much larger proportion (35%) of the contemporary erosion rate, and highlight the importance of these events in reworking stored material. Evidence for palaeofloods much larger than those experienced over the past 200 years suggests even greater sediment export potential. Mass movement on hillslopes along valleys incised into softer lithology appears to be a dominant erosion process that supplies substantial volumes of material to the valley floor. It is possible that a combination of infrequent mass movement events and high fluvial discharge could account for a significant proportion of the discrepancy between the contemporary and long‐term denudation rates. Copyright © 2006 John Wiley & Sons, Ltd.     

Spatiotemporal characteristics of precipitation and extreme events on the Loess Plateau of China between 1957 and 2009

Spatiotemporal trends in precipitation may influence vegetation restoration, and extreme precipitation events profoundly affect soil erosion processes on the Loess Plateau. Daily data collected at 89 meteorological stations in the area between 1957 and 2009 were used to analyze the spatiotemporal trends of precipitation on the Loess Plateau and the return periods of different types of precipitation events classified in the study. Nonparametric methods were employed for temporal analysis, and the Kriging interpolation method was employed for spatial analysis. The results indicate a small decrease in precipitation over the Loess Plateau in last 53 years (although a Mann–Kendall test did not show this decrease to be significant), a southward shift in precipitation isohyets, a slightly delayed rainy season, and prolonged return periods, especially for rainstorm and heavy rainstorm events. Regional responses to global climate change have varied greatly. A slightly increasing trend in precipitation in annual and sub‐annual series, with no obvious shift of isohyets, and an evident decreasing trend in extreme precipitation events were detected in the northwest. In the southeast, correspondingly, a more seriously decreasing trend occurred, with clear shifts of isohyets and a slightly decreasing trend in extreme precipitation events. The result suggests that a negative trend in annual precipitation may have led to decreased soil erosion but an increase in sediment yield during several extreme events. These changes in the precipitation over the Loess Plateau should be noted, and countermeasures should be taken to reduce their adverse impacts on the sustainable development of the region. Copyright © 2013 John Wiley & Sons, Ltd.     

Trend and extreme occurrence of precipitation in a mid‐latitude Eurasian steppe watershed at various time scales

The confounding effects of step change invalidate the stationarity assumption of commonly used trend analysis methods such as the Mann–Kendall test technique, so previous studies have failed to explain inconsistencies between detected trends and observed large precipitation anomalies. The objectives of this study were to (1) formulate a trend analysis approach that considers nonstationarity due to step changes, (2) use this approach to detect trends and extreme occurrences of precipitation in a mid‐latitude Eurasian steppe watershed in North China, and (3) examine how runoff responds to precipitation trends in the study watershed. Our results indicate that annual precipitation underwent a marginal step jump around 1995. The significant annual downward trend after 1994 was primarily due to a decrease in summer rainfall; other seasons exhibited no significant precipitation trends. At a monthly scale, July rainfall after 1994 exhibited a significant downward trend, whereas precipitation in other months had no trend. The percentage of wet days also underwent a step jump around 1994 following a significant decreasing trend, although the precipitation intensity exhibited neither a step change nor any significant trend. However, both low‐frequency and high‐frequency precipitation events in the study watershed occurred more often after than before 1994; probably as either a result or an indicator of climate change. In response to these precipitation changes, the study watershed had distinctly different precipitation‐runoff relationships for observed annual precipitations of less than 300 mm, between 300 and 400 mm, and greater than 400 mm. Copyright © 2013 John Wiley & Sons, Ltd.     

The impact of extreme weather events on the seagrass Zostera noltii and related Hydrobia ulvae population

Coastal areas are typically subjected to a range of stressors, but they now face the additional stressor of climate change, manifested in part by an increased intensity and frequency of extreme weather events. Thus, the Mondego estuary (Portugal) has experienced organic enrichment (eutrophication) issues and these are potentially exacerbated by extreme weather events (floods, droughts and heat waves). In this paper, we explore the impact of interactions of these different stressors on the ecology of the system, specifically on the two key components, the seagrass Zostera noltii and the mud snail Hydrobia ulvae. Extreme events affected different components of the estuarine ecosystem (primary producers and macrofauna) differently. Whilst the floods directly impacted on H. ulvae, by wiping out part of its population, they did not directly affect the biomass of Z. noltii. In contrast, drought events, through their effects on salinity, directly impacted the biomass of Zostera, which had knock-on effects on the dynamics of H. ulvae. We conclude that over the period when the estuary experienced eutrophication, extreme weather events contributed to the overall degradation of the estuary, while during the recovery phase following the introduction of a management programme, those extreme weather episodes delayed the recovery process significantly.