An extreme wave event in eastern Yucatán,Mexico: Evidence of a palaeotsunami event during the Mayan times

The Yucatán Peninsula, Mexico, has typically been considered a tectonically stable region with little significant seismic activity. The region though, is one that is regularly affected by hurricanes. A detailed survey of ca 100 km of the eastern Yucatán and Cozumel coast identified the presence of ridges containing individual boulders measuring >1 m in length. The boulder ridges reach 5 m in height and their origin is associated with extreme wave event activity. Previously modelled tsunami waves from known seismically active zones in the region (Muertos Thrust Belt and South Caribbean Deformed Belt) are not of sufficient scale in the area of the Yucatán Peninsula to have produced the boulder ridges recorded in this study. The occurrence of hurricanes in this region is more common, but two of the most destructive (Hurricane Gilbert 1988 and Hurricane Wilma 2005) produced coastal waves too small to have created the ridges recorded here. In this paper, a new tsunami model with a source area located on the Motagua/Swan Island Fault System has been generated that indicates a tsunami event may have caused the extreme wave events that resulted in the deposition of the boulder ridges.     

一种基于M估计的Robust-ELM滑坡位移预测方法

采用传统ELM算法进行滑坡位移预测时，其网络输出权值由最小二乘估计得出，导致ELM抗差能力较差，从而造成网络训练参数不准确。为此，将M估计与ELM相结合，提出一种基于M估计的Robust-ELM滑坡变形预测方法。该方法利用加权最小二乘方法来取代最小二乘法计算ELM输出权值，以减少滑坡监测数据中粗差对ELM预测的干扰。分别以链子崖、古树屋滑坡体为例，将Robust-ELM进行了单维、多维粗差的抵御性验证。结果表明，该方法能够有效降低粗差对预测的影响，具有良好的抗差能力。     

袭港热带气旋持续时间长期频率分析

香港经常受到西北太平洋热带气旋的影响,对该地区热带气旋持续时间的研究有助于经济社会的稳定发展。按照气象和天文台警告信号,热带气旋分为不同的强度等级。建立热带气旋持续时间的Poisson-Weibull复合分布模型,相应获得持续时间重现值的求解公式,分别用于不同热带气旋分类下持续时间多年一遇重现值的计算中。基于1987-2016年袭港热带气旋数据的分析结果表明,Poisson-Weibull分布适用于不同的持续时间分类样本;强的热带气旋经常会伴随较长的持续时间,这将会对该地区造成更为严重的破坏,这可为防灾减灾提供参考。     

Regional extreme‐dry‐spell frequency analysis using the L‐moments method in the middle reaches of the Yellow River Basin,China

In this research, the regional extreme‐dry‐spell frequency in the middle reaches of the Yellow River Basin (YRB) is studied by the L‐moments method. The research area has been divided into three subregions (regions 1, 2 and 3), which have been identified as homogenous regions. The results of a goodness‐of‐fit test indicate that a generalized normal distribution is the optimal regional model for regions 1 and 2 whereas a generalized Pareto distribution is the optimal regional model for region 3. The return period analysis figures out that the maximum length‐of‐dry‐spell (MxDS) values increase from south to north in the southern part and increase from northeast to southwest in the northern part of the middle reaches of the YRB under different return periods. The increments of quantiles of dry spell under different return levels indicate that drought risk in region 1 is higher than that in regions 2 and 3. The analysis of the occurrence day of MxDS shows that MxDS mostly occurred during winter of 1998 and spring of 1999 in most stations during the considered period. By comparing summer MxDS events, it can be found that mean MxDS values have slightly increased in regions 1 and 2 during the last five decades. The maximum mean MxDS values appeared in the 2000s for regions 1 and 2 and in the 1990s for region 3. The atmospheric circulation shows that the positive anomaly centre in the west of North China, negative anomaly centre in the east of North China and the strong western Pacific subtropical high led to the decrease of precipitation in North China during the summer of 1997. Copyright © 2013 John Wiley & Sons, Ltd.     

Nine thousand years of upper montane soil/vegetation dynamics from the summit of Caratuva Peak,Southern Brazil

Biodiversity loss, climate change, and increased freshwater consumption are some of the main environmental problems on Earth. Mountain ecosystems can reduce these threats by providing several positive influences, such as the maintenance of biodiversity, water regulation, and carbon storage, amongst others. The knowledge of the history of these environments and their response to climate change is very important for management, conservation, and environmental monitoring programs. The genesis of the soil organic matter of the current upper montane vegetation remains unclear and seems to be quite variable depending on location. Some upper montane sites in the very extensive coastal Sea Mountain Range present considerable organic matter from the late Pleistocene and other from only the Holocene. Our study was carried out on three soil profiles (two cores in grassland and one in forest) on the Caratuva Peak of the Serra do Ibitiraquire (a sub-range of Sea Mountain Range – Serra do Mar) in Southern Brazil. The δ¹³C isotopic analyses of organic matter in soil horizons were conducted to detect whether C₃ or C₄ plants dominated the past communities. Complementarily, we performed a pollen analysis and ¹⁴C dating of the humin fraction to obtain the age of the studied horizons. Except for a short and probably drier period (between 6000 and 4500 cal yr BP), C₃ plants, including ombrophilous grasses and trees, have dominated the highlands of the Caratuva Peak (Pico Caratuva), as well as the other uppermost summits of the Serra do Ibitiraquire, since around 9000 cal yr BP. The Caratuva region represents a landscape of high altitude grasslands (campos de altitude altomontanos or campos altomontanos) and upper montane rain/cloud forests with soils that most likely contain some organic matter from the late Pleistocene, as has been reported in Southern and Southeastern Brazil for other sites. However, our results indicate that the studied deposits (near the summit) are from the early to late Holocene, when somewhat wetter and warmer conditions (since around 9000 cal yr BP) enabled a stronger colonization of the ridge of Pico Caratuva by mainly C₃ plants, especially grassland species. However, at the same time, even near the summit, the soil core from the forest site already presented the current physiognomy (or a shrubby/elfin or successional forest), indicating that the colonization of the neighboring uppermost saddles and valleys were probably populated mainly by upper montane forest species.     

A nonstationary extreme value distribution for analysing the cessation of karst spring discharge

The effects of climate change and population growth in recent decades are leading us to consider their combined and potentially extreme consequences, particularly regarding hydrological processes, which can be modeled using a generalized extreme value (GEV) distribution. Most of the GEV models were based on a stationary assumption for hydrological processes, in contrast to the nonstationary reality due to climate change and human activities. In this paper, we present the nonstationary generalized extreme value (NSGEV) distribution and use it to investigate the risk of Niangziguan Springs discharge decreasing to zero. Rather than assuming the location, scale, and shape parameters to be constant as one might do for a stationary GEV distribution analysis, the NSGEV approach can reflect the dynamic processes by defining the GEV parameters as functions of time. Because most of the GEV model is designed to evaluate maxima (e.g. flooding, represented by positive numbers), and spring discharge cessation is a ?minima’, we deduced an NSGEV model for minima by applying opposite numbers, i.e. negative instead of positive numbers. The results of the model application to Niangziguan Springs showed that the probability of zero discharge at Niangziguan Springs will be 1/80 in 2025, and 1/10 in 2030. After 2025, the rate of decrease in spring discharge will accelerate, and the probability that Niangziguan Springs will cease flowing will dramatically increase. The NSGEV model is a robust method for analysing karst spring discharge. Copyright © 2013 John Wiley & Sons, Ltd.     

Data-based modelling approach for variable density flow and solute transport simulation in a coastal aquifer

Data-based models, namely artificial neural network (ANN), support vector machine (SVM), genetic programming (GP) and extreme learning machine (ELM), were developed to approximate three-dimensional, density-dependent flow and transport processes in a coastal aquifer. A simulation model, SEAWAT, was used to generate data required for the training and testing of the data-based models. Statistical analysis of the simulation results obtained by the four models show that the data-based models could simulate the complex salt water intrusion process successfully. The selected models were also compared based on their computational ability, and the results show that the ELM is the fastest technique, taking just 0.5 s to simulate the dataset; however, the SVM is the most accurate, with a Nash-Sutcliffe efficiency (NSE) ≥ 0.95 and correlation coefficient R ≥ 0.92 for all the wells. The root mean square error (RMSE) for the SVM is also significantly less, ranging from 12.28 to 77.61 mg/L.     

A regime shift in sediment export from a coastal watershed during a record wet winter,California: Implications for landscape response to hydroclimatic extremes

Small, steep watersheds are prolific sediment sources from which sediment flux is highly sensitive to climatic changes. Storm intensity and frequency are widely expected to increase during the 21st century, and so assessing the response of small, steep watersheds to extreme rainfall is essential to understanding landscape response to climate change. During record winter rainfall in 2016–2017, the San Lorenzo River, coastal California, had nine flow peaks representing 2–10‐year flood magnitudes. By the third flood, fluvial suspended sediment showed a regime shift to greater and coarser sediment supply, coincident with numerous landslides in the watershed. Even with no singular catastrophic flood, these flows exported more than half as much sediment as had a 100‐year flood 35 years earlier, substantially enlarging the nearshore delta. Annual sediment load in 2017 was an order of magnitude greater than during an average‐rainfall year, and 500‐fold greater than in a recent drought. These anomalous sediment inputs are critical to the coastal littoral system, delivering enough sediment, sometimes over only a few days, to maintain beaches for several years. Future projections of megadroughts punctuated by major atmospheric‐river storm activity suggest that interannual sediment‐yield variations will become more extreme than today in the western USA, with potential consequences for coastal management, ecosystems, and water‐storage capacity. The occurrence of two years with major sediment export over the past 35 years that were not associated with extremes of the El Niño Southern Oscillation or Pacific Decadal Oscillation suggests caution in interpreting climatic signals from marine sedimentary deposits derived from small, steep, coastal watersheds, to avoid misinterpreting the frequencies of those cycles. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.     

A multiscaling‐based intensity–duration–frequency model for extreme precipitation

Rainfall intensity–duration–frequency (IDF) curves are a standard tool in urban water resources engineering and management. They express how return levels of extreme rainfall intensity vary with duration. The simple scaling property of extreme rainfall intensity, with respect to duration, determines the form of IDF relationships. It is supposed that the annual maximum intensity follows the generalized extreme value (GEV) distribution. As well known, for simple scaling processes, the location parameter and scale parameter of the GEV distribution obey a power law with the same exponent. Although, the simple scaling hypothesis is commonly used as a suitable working assumption, the multiscaling approach provides a more general framework. We present a new IDF relationship that has been formulated on the basis of the multiscaling property. It turns out that the GEV parameters (location and scale) have a different scaling exponent. Next, we apply a Bayesian framework to estimate the multiscaling GEV model and to choose the most appropriate model. It is shown that the model performance increases when using the multiscaling approach. The new model for IDF curves reproduces the data very well and has a reasonable degree of complexity without overfitting on the data.     

Continuous real‐time analysis of the isotopic composition of precipitation during tropical rain events: Insights into tropical convection

To investigate stable isotopic variability of precipitation in Singapore, we continuously analysed the δ‐value of individual rain events from November 2014 to August 2017 using an online system composed of a diffusion sampler coupled to Cavity Ring‐Down Spectrometer. Over this period, the average value (δ¹⁸O_Avg), the lowest value (δ¹⁸O_Low), and the initial value (δ¹⁸O_Init) varied significantly, ranging from ?0.45 to ?15.54‰, ?0.9 to ?17.65‰, and 0 to ?13.13‰, respectively. All 3 values share similar variability, and events with low δ¹⁸O_Low and δ¹⁸O_Avg values have low δ¹⁸O_Init value. Individual events have limited intraevent variability in δ‐value (Δδ) with the majority having a Δδ below 4‰. Correlation of δ¹⁸O_Low and δ¹⁸O_Avg with δ¹⁸O_Init is much higher than that with Δδ, suggesting that convective activities prior to events have more control over δ‐value than on‐site convective activities. The d‐excess of events also varies considerably in response to the seasonal variation in moisture sources. A 2‐month running mean analysis of δ¹⁸O reveals clear seasonal and interannual variability. Seasonal variability is associated with the meridional movement of the Intertropical Convergence Zone and evolution of the Asian monsoon. El Niño–Southern Oscillation is a likely driver of interannual variability. During 2015–2016, the strongest El Niño year in recorded history, the majority of events have a δ¹⁸O value higher than the weighted average δ¹⁸O of daily precipitation. δ¹⁸O shows a positive correlation with outgoing longwave radiation in the western Pacific and the Asian monsoon region, and also with Oceanic Niño Index. During El Niño, the convection centre shifts eastward to the central/eastern Pacific, weakening convective activities in Southeast Asia. Our study shows that precipitation δ‐value contains information about El Niño–Southern Oscillation and the Intertropical Convergence Zone, which has a significant implication for the interpretation of water isotope data and understanding of hydrological processes in tropical regions.