A case for a reassessment of the risks of extreme hydrological hazards in the Caribbean

There is an urgent need for the development and implementation of modern statistical methodology for long-term risk assessment of extreme hydrological hazards in the Caribbean. Notwithstanding the inevitable scarcity of data relating to extreme events, recent results and approaches call into question standard methods of estimation of the risks of environmental catastrophes that are currently adopted. Estimation of extreme hazards is often based on the Gumbel model and on crude methods for estimating predictive probabilities. In both cases the result is often a remarkable underestimation of the predicted probabilities for disasters of large magnitude. Simplifications do not stop here: assumptions of data homogeneity and temporal independence are usually made regardless of potential inconsistencies with genuine process behaviour and the fact that results may be sensitive to such mis-specifications. These issues are of particular relevance for the Caribbean, given its exposure to diverse meteorological climate conditions.In this article we present an examination of predictive methodologies for the assessment of long-term risks of hydrological hazards, with particular focus on applications to rainfall and flooding, motivated by three data sets from the Caribbean region. Consideration is given to classical and Bayesian methods of inference for annual maxima and daily peaks-over-threshold models. We also examine situations where data non-homogeneity is compromised by an unknown seasonal structure, and the situation in which the process under examination has a physical upper limit. We highlight the fact that standard Gumbel analyses routinely assign near-zero probability to subsequently observed disasters, and that for San Juan, Puerto Rico, standard 100-year predicted rainfall estimates may be routinely underestimated by a factor of two.     

Decoupling between the middle and upper crust during transpression-related lateral flow: Variscan evolution of the Aston gneiss dome (Pyrenees, France)

We present a structural, AMS, microstructural and kinematic study of the Aston gneiss dome (French Pyrenees), which consists of a core made up of orthogneiss and paragneiss intruded by numerous sills of Carboniferous peraluminous granite. The orthogneiss corresponds to a former Ordovician granitic laccolith. Four Variscan events have been evidenced in this gneiss dome: (i) D1 deformation observed only as relics in the orthogneisses and their country-rocks located above the sillimanite isograd, and characterized by a NS to NE–SW non coaxial stretch associated to top to the south motions (NS convergence); (ii) D2-a deformation observed in the orthogneisses and their country-rocks, mainly migmatitic paragneisses, located below the sillimanite isograd and in the peraluminous granites whatever their structural level, and characterized by an EW to N120°E stretch associated to a top to the east flat shearing (lateral flow in the hot middle crust in a transpressive regime); (iii) D2-b deformation characterized by EW-trending megafolds corresponding to the domes in the middle crust and by EW-trending tight folds with subvertical axial planes in the metasedimentary upper crust; (iv) subvertical medium-temperature mylonitic bands developed by the end of the transpression.The Aston massif is a good example of decoupling between a cold upper crust and a hotter middle crust overheated by a thermal event originated in the upper mantle. This decoupling allowed the lateral flow of the migmatitic middle crust along a direction at high angle with respect to the more or less NS-trending direction of convergence. We suggest that the HT-LP metamorphism developed before the formation of the domes during D2-a, coevally with the emplacement of numerous sills of peraluminous granite, whereas the emplacement of the large calc-alkaline plutons in the upper crust occurred by the end of D2-b. Our data invalidate the previous geodynamical models based on either early or late extensional regime to explain the development of the HT-LP metamorphism. This new interpretation of the dynamics of the Variscan crust of the Pyrenees is consistent with recent studies conducted in Archaean and Palaeoproterozoic hot continental crusts having undergone oblique convergence, and characterized by a competition between vertical thickening and lateral flow induced by the important rheological contrast between two thermally different levels.     

基于贝叶斯模型的器测、古气候重建与气候模拟数据的融合试验

气象部门馆藏的西部最早的器测气象资料始于20世纪30年代,不能满足建立20世纪以来中国气候变化序列的需求,而古气候重建或气候模拟资料则可以延伸到器测时代以前。为了探讨长序列多源气候资料序列融合方法,采用贝叶斯方法对中国北疆地区8条树轮气温重建资料、器测资料与国际耦合模式比较计划第5阶段（CMIP5）模式模拟资料进行了融合试验。首先利用器测资料对气温代用资料进行校验与网格重建,并以此作为贝叶斯模型的先验分布,然后,用泰勒图选出了该区域气候模拟效果最佳的几个模式;最后将网格重建和气候模拟序列用贝叶斯模型进行了融合试验。结果表明,贝叶斯融合模型能有效提取各种数据来源的有用信息进行融合,融合结果的长期变化（线性）趋势更接近器测气候序列,并在一定程度上提高了序列的精度,减小了结果的不确定性;并且,融合结果能够纠正先验分布及气候模拟数据的明显偏差,为长年代气候序列重建提供了一个可行的思路。      

The use of 3D modeling for the prediction of the seismic demands on the gravity dams

Seismic behavior of gravity dams has long been evaluated using a representative two‐dimensional (2D) system. Formulated for the gravity dams built in wide canyons, the assumption is nevertheless utilized extensively for almost all concrete dams due to the established procedures as well as the expected computational costs of a three‐dimensional model. However, a significant number of roller‐compacted concrete dams, characterized as such systems, do not conform to the basic assumptions of these methods by violating the conditions on canyon dimensions and joint‐spacing/details. Based on the premise that the 2D modeling assumption is overstretched for practical purposes in a variety of settings, the purpose of this study is to critically evaluate the use of 2D modeling for the prediction of the seismic demands on these systems. Using a rigorous soil–structure interaction approach, the difference between the two and three‐dimensional response for gravity dams was investigated first in the frequency domain for a range of canyon widths and foundation to dam moduli ratios. Then, the time domain differences between the crest displacements and the maximum principal stress were obtained using 70 different ground motions in order to show the possible bias introduced into the analysis results due to the modeling approach. The results of the study show that even for relatively wide canyons, the 2D analysis can lead to misleading predictions. Copyright © 2017 John Wiley & Sons, Ltd.     

Trend analyses with river sediment rating curves

Sediment rating curves, which are fitted relationships between river discharge (Q) and suspended‐sediment concentration (C), are commonly used to assess patterns and trends in river water quality. In many of these studies, it is assumed that rating curves have a power‐law form (i.e. C = aQ^b, where a and b are fitted parameters). Two fundamental questions about the utility of these techniques are assessed in this paper: (i) how well to the parameters, a and b, characterize trends in the data, and (ii) are trends in rating curves diagnostic of changes to river water or sediment discharge? As noted in previous research, the offset parameter, a, is not an independent variable for most rivers but rather strongly dependent on b and Q. Here, it is shown that a is a poor metric for trends in the vertical offset of a rating curve, and a new parameter, â, as determined by the discharge‐normalized power function [C = â (Q/Q_GM)^b], where Q_GM is the geometric mean of the Q‐values sampled, provides a better characterization of trends. However, these techniques must be applied carefully, because curvature in the relationship between log(Q) and log(C), which exists for many rivers, can produce false trends in â and b. Also, it is shown that trends in â and b are not uniquely diagnostic of river water or sediment supply conditions. For example, an increase in â can be caused by an increase in sediment supply, a decrease in water supply or a combination of these conditions. Large changes in water and sediment supplies can occur without any change in the parameters, â and b. Thus, trend analyses using sediment rating curves must include additional assessments of the time‐dependent rates and trends of river water, sediment concentrations and sediment discharge. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Hydrological Processes published by John Wiley & Sons Ltd.     

Effect of loading duration on uncertainty in creep analysis of clay

Some studies suggest that creep parameters should be determined using a greater quantity of creep test data to provide more reliable prediction regarding the deformation of soft soils. This study aims to investigate the effect of loading duration on model updating. One‐dimensional consolidation data of intact Vanttila clay under different loading durations collected from the literature is used for demonstration. The Bayesian probabilistic method is used to identify all unknown parameters based on the consolidation data during the entire consolidation process, and their uncertainty can be quantified through the obtained posterior probability density functions. Additionally, the optimal models are also determined from among 9 model candidates. The analyses indicate that the optimal models can describe the creep behavior of intact soft soils under different loading durations, and the adopted method can evaluate the effect of loading duration on uncertainty in the creep analysis. The uncertainty of a specific model and its model parameters decreases as more creep data are involved in the updating process, and the updated models that use more creep data can better capture the deformation behavior of an intact sample. The proposed method can provide quantified uncertainty in the process of model updating and assist engineers to decide whether the creep test data are sufficient for the creep analysis.     

The effect of land cover change on duration and severity of high and low flows

Land cover has been increasingly recognized as an important factor affecting hydrologic processes at the basin and regional level. Therefore, improved understanding of how land cover change affects hydrologic systems is needed for better management of water resources. The objective of this study is to investigate the effects of land cover change on the duration and severity of high and low flows by using the Soil Water Assessment Tool model, Bayesian model averaging and copulas. Two basins dominated by different land cover in the Ohio River basin are used as study area in this study. Two historic land covers from the 1950s and 1990s are considered as input to the Soil Water Assessment Tool model, thereby investigating the hydrologic high and low flow response of different land cover conditions of these two basins. The relationships between the duration and severity of both low and high flow are defined by applying the copula method; changes in the frequency of the duration and severity are investigated. The results show that land cover changes affect both the duration and severity of both high and low flows. An increase in forest area leads to a decrease in the duration and severity during both high and low flows, but its impact is highest during extreme flows. The results also show that the land cover changes have had significant influences on changes in the joint return periods of duration and severity of low and high flows. While this study sheds light on the role of land cover change on severity and duration of high and low flow conditions, more studies using various land cover conditions and climate types are required in order to draw more reliable conclusions in the future. Copyright © 2016 John Wiley & Sons, Ltd.     

Using regional regression within index flood procedures and an empirical Bayesian estimator

Studies have illustrated the performance of at-site and regional flood quantile estimators. For realistic generalized extreme value (GEV) distributions and short records, a simple index-flood quantile estimator performs better than two-parameter (2P) GEV quantile estimators with probability weighted moment (PWM) estimation using a regional shape parameter and at-site mean and L-coefficient of variation (L-CV), and full three-parameter at-site GEV/PWM quantile estimators. However, as regional heterogeneity or record lengths increase, the 2P-estimator quickly dominates. This paper generalizes the index flood procedure by employing regression with physiographic information to refine a normalized T-year flood estimator. A linear empirical Bayes estimator uses the normalized quantile regression estimator to define a prior distribution which is employed with the normalized 2P-quantile estimator. Monte Carlo simulations indicate that this empirical Bayes estimator does essentially as well as or better than the simpler normalized quantile regression estimator at sites with short records, and performs as well as or better than the 2P-estimator at sites with longer records or smaller L-CV.     

Settlement prediction by spatial-temporal random process using Asaoka's method

A methodology was presented for observation-based settlement prediction with consideration of the spatial correlation structure of soil. The spatial correlation is introduced among the settlement model parameters and the settlements at various points are spatially correlated through these geotechnical parameters, which naturally describe the phenomenon. The method is based on Bayesian estimation by considering both prior information, including spatial correlation and observed settlement, to search for the best estimates of the parameters at any arbitrary points on the ground. Within the Bayesian framework, the optimised selection of auto-correlation distance by Akaike's Bayesian Information Criterion (ABIC) is also proposed. The application of the proposed approach in consolidation settlement prediction using Asaoka's method is presented in this paper. Several case studies were carried out using simulated settlement data to investigate the performance the proposed approach. It is concluded that the accuracy of the settlement prediction can be improved by taking into account the spatial correlation structure and the proposed approach gives the rational prediction of the settlement at any location at any time with quantified uncertainty.     

Bayesian Discovery Process Modeling of the Lower and Middle Jurassic Play of the Halten Terrace,Offshore Norway,as Compared with the Previous Modeling

A Bayesian version of the discovery process model was applied to the pre-rift Lower and Middle Jurassic play of the Halten Terrace, Mid-Norway. The Bayesian approach estimates the lognormal parameters, the discoverability parameter, and the distribution of sizes of the undiscovered fields as well as the play potential, conditioned on a discovery sequence averaging for all possible prior choices weighted by their likelihood. This approach avoids the problem of having to make arbitrary choices for the parameters. The estimates of parameters and play potential based upon the present methodology compares well with previous estimates, if the play is divided into two sub-plays representing the overpressured and normally pressured zones. These sub-plays have been estimated independently and aggregated in order to get the total undiscovered resource potential. This study estimates that the expected remaining play potential is 100 × 10⁶Sm³ o.e., about 9% of the total resources in the play. There is however a 90% chance that the remaining potential ranges from 13 to 282× 10⁶ Sm³ o.e. and a 5% possibility of exceeding this value.