Stochastic multi-site generation of daily rainfall occurrence in south Florida

This paper presents a stochastic model to generate daily rainfall occurrences at multiple gauging stations in south Florida. The model developed in this study is a space–time model that takes into account the spatial as well as temporal dependences of daily rainfall occurrence based on a chain-dependent process. In the model, a Markovian method was used to represent the temporal dependence of daily rainfall occurrence and a direct acyclic graph (DAG) method was introduced to encode the spatial dependence of daily rainfall occurrences among gauging stations. The DAG method provides an optimal sequence of generation by maximizing the spatial dependence index of daily rainfall occurrences over the region. The proposed space–time model shows more promising performance in generating rainfall occurrences in time and space than the conventional Markov type model. The space–time model well represents the temporal as well as the spatial dependence of daily rainfall occurrences, which can reduce the complexity in the generation of daily rainfall amounts.     

Which catchment characteristics control the temporal dependence structure of daily river flows?

Hydrological classification systems seek to provide information about the dominant processes in the catchment to enable information to be transferred between catchments. Currently, there is no widely agreed‐upon system for classifying river catchments. This paper develops a novel approach to classifying catchments based on the temporal dependence structure of daily mean river flow time series, applied to 116 near‐natural ‘benchmark’ catchments in the UK. The classification system is validated using 49 independent catchments. Temporal dependence in river flow data is driven by the flow pathways, connectivity and storage within the catchment and can thus be used to assess the influence catchment characteristics have on moderating the precipitation‐to‐flow relationship. Semi‐variograms were computed for the 116 benchmark catchments to provide a robust and efficient way of characterising temporal dependence. Cluster analysis was performed on the semi‐variograms, resulting in four distinct clusters. The influence of a wide range of catchment characteristics on the semi‐variogram shape was investigated, including: elevation, land cover, physiographic characteristics, soil type and geology. Geology, depth to gleyed layer in soils, slope of the catchment and the percentage of arable land were significantly different between the clusters. These characteristics drive the temporal dependence structure by influencing the rate at which water moves through the catchment and/or the storage in the catchment. Quadratic discriminant analysis was used to show that a model with five catchment characteristics is able to predict the temporal dependence structure for un‐gauged catchments. This method could form the basis for future regionalisation strategies, as a way of transferring information on the precipitation‐to‐flow relationship between gauged and un‐gauged catchments. © 2014 The Authors. Hydrological Processes by published by John Wiley & Sons, Ltd.     

Making the transition from discrete shot records to continuous seismic records and source wavefields,and its potential impact on survey efficiency and environmental footprint

A marine seismic method based on continuous source and receiver wavefields has been developed. The method requires continuous recording of the seismic data. The source that may consist of multiple source elements can emit signals continuously while moving. The ideal source wavefield to be used with this method should be as white as possible both in a temporal and a spatial sense to avoid deep notches in the spectrum enabling a stable multi-dimensional deconvolution. White noise has such properties. However, equipment that can generate white noise does not exist. In order to generate a continuous source wavefield that is approaching the properties of white noise using existing equipment onboard marine seismic vessels, individual air-guns can be triggered with short randomized time intervals in a near-continuous fashion. The main potential benefits with the method are to reduce the environmental impact of marine seismic surveys and to improve acquisition efficiency. The peak sound pressure levels are significantly reduced by triggering one air-gun at a time compared to conventional marine seismic sources. Sound exposure levels are also reduced in most directions. Since the method is based on continuous recording of seismic data and the air-guns are triggered based on time and not based on position, there are less vessel speed limitations compared to conventional marine seismic data acquisition. Also, because the source wavefield is spread out in time, the wavefields emitted from source elements in different cross-line positions can be designed such that the emitted wavefield is spatially white in this direction. This means that source elements in multiple cross-line positions can be operated simultaneously, potentially improving the cross-line sampling and/or the acquisition efficiency.     

Numerical viscoelastic modelling by the spectral Laguerre method

Seismic wave propagation in a viscoelastic media can be described by a system of integro-differential equations. The solution of such equations requires special methods when using finite-difference techniques in the time domain. In the frequency domain, the integral terms are represented by complex elastic parameters. This paper presents an efficient algorithm for viscoelastic modelling based on the integral Laguerre transform for the approximation of temporal derivatives and for the calculation of convolution integrals. For the calculation of spatial derivatives, it is possible to use various methods: finite-difference and finite-element techniques, spectral and pseudo-spectral methods. We then obtain a system of algebraic equations with a matrix independent of the parameter m , i.e. the degree of the Laguerre polynomials. In this case, only the right-hand side of the system has recurrent dependence on the parameter m , which is an analogue of the temporal frequency in the frequency domain. The obtained system with a large number of right-hand sides can be solved using fast methods, where the matrix is transformed only once, as opposed to the frequency-domain approach, when the matrix is transformed for each temporal frequency.     

Prediction uncertainty for tracer migration in random heterogeneities with multifractal character

Travel-time statistics for non-reacting tracers in fractal and multifractal media are addressed through numerical simulations. The logarithm of hydraulic conductivity is modeled using fractional Brownian motion (fBm) and more recently developed multifractal model based on bounded fractional Levy motion (bfLm). These models have been shown previously to accurately reproduce statistical properties of large conductivity datasets. The ensemble-mean travel time increases nearly linearly with travel distance and the variance in the travel time increases nearly parabolically with travel distance. This is consistent with near-field analytical approximations developed for non-fractal media and suggests that these analytical results may have some degree of robustness to non-ideal features in the random-field models. The magnitudes of the travel-time moments are dependent on the system size. For fBm media, this size dependence can be explained using an effective variance that increases with increasing size of the flow system. However, the magnitudes of the travel-time moments are also sensitive to other non-ideal effects such as deviations from Gaussian behavior. This sensitivity illustrates the need for careful aquifer characterization and conditional numerical simulation in practical situations requiring accurate estimates of uncertainty in the plume position.     

Long-range dependence in the Cenozoic reversal record

The frequency distribution of intervals between Cenozoic geomagnetic reversals approximates a power law, while their occurrence over time shows temporal clustering of short and long intervals. Application of the Aggregate Variance and Absolute Value methods suggest long-range dependence in this time series, a possible indication that the geodynamo operates as a self-organised complex system. This hypothesis may allow the Cretaceous superchron to be considered as an integral part of the ordinary reversal regime attested in the Cenozoic record.     

Scale-based statistical analysis of sediment fluxes

The flux of sediments over a line perpendicular to the main flow direction was measured during experiments of weak one-dimensional bed load. The standard definition of solid discharge through a boundary is a straightforward issue, yet the dependence of resulting values on the spatial and temporal scales used as a support for measurement is not. In this work, first- and second-order statistics of sediment transport rates were analyzed as scale-dependent quantities. The spatial scales used were significantly larger than the particle size, while the temporal scales covered a two-orders-of-magnitude range enabling the physical time scales of the single particles to be appreciated. In addition, the relationship between sediment fluxes, process intermittency and particle interarrival times was investigated. Proper knowledge of the scale-dependence of statistical properties of sediment transport fluxes may allow for adequate design of measuring campaigns (both in the laboratory and field) and for sound interpretation of data from multiple sources.     

Analysis of seismic dynamical systems

A procedure is presented for the analysis of complex stationary time series for which the Fourier power spectra reveals broadband noise or broadened pulses. We first determine the Hurst exponent from which we may know whether the time series under study is mainly random or if the data points present correlations. If the data are correlated, a chaotic analysis will reveal whether they may be interpreted as a low dimensional nonlinear system (defined by a low correlation dimension and a finite and positive Kolmogorov entropy and largest positive Lyapunov exponent) or as a stochastic process. We have studied three kind of temporal series: inter-event time series of infrasonic pulses recorded at Stromboli volcano, and, S-coda waves and microseisms, that have been recorded at the eastern Pyrenees. Results show that microseisms and Coda waves can be modeled as a low dimensional deterministic system, Correlation dimensions 2.3, 3.2, respectively. At the contrary infrasonic has resulted stochastic. This chaotic character can be attributed to the medium properties. Coda waves with scattering through a fractal distribution of scatters or to multiple reflection inside resonators (for example sedimentary basins) and microseisms as a propagation of wave guide of variable cross section which have the same temporal characteristics as a nonlinear forced oscillator.     

Analysis and modelling of rainfall fields at different resolutions in southern Italy

Abstract

The spatial and temporal variability of the scaling properties and correlation structure of a data set of rainfall time series, aggregated over different temporal resolutions, and observed in 70 raingauges across the Basilicata and Calabria regions of southern Italy, is investigated. Two types of random cascade model, namely canonical and microcanonical models, were used for each raingauge and selected season. For both models, different hypotheses concerning dependency of parameters on time scale and rainfall height can be adopted. In particular, a new approach is proposed which consists of several combinations of models with a different scale dependence of parameters for different temporal resolutions. The goal is to improve the modelling of the main features of rainfall time series, especially for cases where the variability of rainfall changes irregularly with temporal aggregation. The results obtained with the new methodology showed good agreement with the observed data, in particular, for the summer months. In fact, during this season, rainfall heights aggregated at fine temporal resolutions (from 5 to 20 min) are more similar (relative to the winter season) to the values cumulated on 1 or 3 h (due to convective phenomena) and, consequently, the process of rainfall breakdown is nearly stationary for a range of finer temporal resolutions.

Editor D. Koutsoyiannis; Associate editor A. Montanari     

Spatial and temporal dust source variability in northern China identified using advanced remote sensing analysis

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi‐scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust‐producing sources. The representation of intra‐annual and inter‐annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter‐annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas. Copyright © 2012 John Wiley & Sons, Ltd.     

Kernel distributed residual function in a revised multiple order autoregressive model and its applications in hydrology

ABSTRACT

This paper describes a new approach to fill missing data in hydrologic series. Based on a multiple-order autoregressive model, our algorithm represents the random term with an empirical distribution function that includes different parameters for the low, medium and high ranges of the modelled hydrologic variable. The algorithm involves a corrective mechanism that preserves the original statistical distribution of the series that are filled, while also eliminating the possibility of obtaining negative values for low flows. The algorithm requires multiple correlated hydrologic time series with sufficient data to permit accurate calculation of their statistical properties. It ensures that both the original statistical dependence among the data series and the statistical distribution functions will be preserved after the missing data had been filled. The model has been tested using 15 streamflow series in the Upper Bow River watershed in Alberta, Canada.     

Using slowness and azimuth fluctuations as new observables for four‐dimensional reservoir seismic monitoring

Four‐dimensional imaging using geophysical data is of increasing interest in the oil and gas industries. While travel‐time and amplitude variations are commonly used to monitor reservoir properties at depth, their interpretation can suffer from a lack of information to decipher the parts played by different parameters. In this context, this study focuses on the slowness and azimuth angle measured at the surface using source and receiver arrays as complementary observables. In the first step, array processing techniques are used to extract both azimuth and incidence angles at the source side (departure angles) and at the receiver side (arrival angles). In the second step, the slowness and angle variations are monitored in a laboratory environment. These new observables are compared with traditional arrival‐time variations when the propagation medium is subject to temperature fluctuations. Finally, field data from a heavy‐oil permanent reservoir monitoring system installed onshore and facing steam injection and temperature variations are investigated. The slowness variations are computed over a period of 152 days. In agreement with Fermat's principle, strong correlations between the slowness and arrival‐time variations are highlighted, as well as good consistency with other techniques and field pressure measurements. Although the temporal variations of slowness and arrival time show the same features, there are still differences that can be considered for further characterization of the physical changes at depth.     

Statistical characterization of impact of system variables on temporal dynamics of groundwater in highly weathered regoliths

In situations where the water table fluctuates during the rainy season the characterization of the impact of system variables on the temporal dynamics of the groundwater (GW) is essential to improve the understanding at catchment or regional scale behaviour of GW. In this study the appropriateness of the statistical parameters; mean, median, the 80^th percentile (PC80), coefficient of variation (CV), correlation coefficient (r), and multiple regression models were assessed to characterize the impact of system variables on the temporal dynamics of hydraulic head relative to ground surface (HH) during rainy seasons. The study was conducted from 1999 to 2003 in the wet tropical Johnstone River catchment (JRC) in north‐east Queensland, Australia. Piezometer wells were installed at 32 sites under cropping to 5–90 m depth on different soil types, landscape positions, and varying proximity to surface water bodies (i.e. four system variables). The HH was measured, at least at 10–15 day intervals during 1–5 consecutive rainy seasons. The HH in the 32 wells fluctuated throughout each of the five rainy seasons. The mean HH averaged over the seasons ranged from 1·1 to 17·2 m across the wells, the median from 0·9 to 17·3 m, and the PC80 from 0·3 to 16·1 m. The temporal behaviour of HH characterization by mean of means of HH, the mean of medians of HH, and the mean of PC80 of HH, indicated the HH can be classified to belong to three different groups for each one of these parameters. The impact of the system variables on temporal dynamics, explored using multiple regression procedure, indicated that the model for median was marginally better than mean. The CV was found to be most appropriate parameter to characterize the impact of GW system variable (aquifer type), a component of the system variables, on temporal dynamics. The interactions of GW (i) belonging to different GW system and (ii) at shoulder with footslope in a landscape were best characterized by simple linear correlations. Copyright © 2007 John Wiley & Sons, Ltd.     

Geospatial–temporal dependence among weekly precipitation extremes with applications to observations and climate model simulations in South America

A quantification of the spatio-temporal dependence among precipitation extremes is important for investigating the properties of intense storms as well as flood or flash-flood related hazards. Extreme value theory has been widely applied to the hydrologic sciences and hydraulic engineering. However, rigorous approaches to quantify dependence structures among extreme values in space and time have not been reported in the literature. Previous researchers have quantified the dependence among extreme values through the concept of (pairwise bivariate) tail dependence coefficients. For estimation of the tail dependence coefficients, we apply a recently developed method [Kuhn G. On dependence and extremes. PhD thesis (Advisor: C. Klüppelberg), Munich University of Technology, 2006] which utilized the multivariate tail dependence function of a subclass of elliptical copulas. This study extends the previous approach in the context of space and time by considering pairs of spatial grids in South America and quantifying the dependence among precipitation extremes based on the time series at each spatial grid. In addition, Kendall’s τ is used to estimate the pairwise copula correlation (for an elliptical copula) of precipitation between all grids in South America. The geospatial–temporal dependence measures are applied to precipitation observations from 1940 to 2005 as well as simulations from the Community Climate System Model version 3 (CCSM3) for 1940–2099. New insights are obtained regarding the spatio-temporal dependence structures for precipitation over South America both with regard to correlation as well as tail dependence.     

Transport and delivery of suspended solids, nitrogen and phosphorus from various sources to freshwaters in the UK

Sources of nutrients and suspended solids (SS) are diverse in origin and dynamic with respect to their transport pathways and delivery to surface and groundwaters. Three broad source groups can be identified based on their hydrological and compositional characteristics. Consented discharges from point sources are generally continuous and highly concentrated relative to receiving waters while non-point (diffuse) sources are generally more dilute with SS and phosphorus in particular tending to have a high transport dependence upon hydrological (storm) events. A third group with properties that are intermediate include overflows from septic systems, seepages from farmyards or road/track runoff. This grouping automatically introduces a strong temporal and spatial variability in the relative contribution individual group sources make to the total quantity of nutrients and SS delivered to freshwaters. This spatial or temporal variability in either effluent volumes or composition is generally not considered when predicting impacts, which can be highly significant in headwater streams. Complete compositional data for individual sources (especially the intermediary group) are also often lacking when apportioning source contributions in catchments, being simply lumped into average export coefficients. Better definition of intermediary sources would help to more accurately define the relative contribution of different sources and enable cost-effective river basin management planning as required under the Water Framework Directive.     

Seismic performance of hybrid ductile‐rocking braced frame system

A new hybrid ductile‐rocking seismic‐resistant design is proposed which consists of a code‐designed buckling‐restrained braced frame (BRBF) that yields along its height and also partially rocks on its foundation. The goal of this system is to cost‐effectively improve the performance of BRBFs, by reducing drift concentrations and residual deformations, while taking advantage of their large ductility and their reliable limit on seismic forces and accelerations along a building's height. A lock‐up device ensures that the full code‐compliant lateral strength can be achieved after a limited amount of column uplift, and supplemental energy dissipation elements are used to reduce the rocking response. This paper outlines the mechanics of the system and then presents analyses on rocking frames with both ductile and elastic braces in order to highlight the large higher mode demands on elastic rocking frames. A parametric study using nonlinear time‐history analysis of BRBF structures designed according to the proposed procedure for Los Angeles, California is then presented. This study investigates the system's seismic response and the effect of different energy dissipation element properties and allowable base rotation values before the lock‐up is engaged. Finally, the effect of vertical mass modeling on analysis results was investigated. These studies demonstrated that the hybrid ductile‐rocking system can in fact improve the global peak and residual deformation response as well as reduce brace damage. This enhanced performance could eliminate the need for expensive repairs or demolition that are otherwise to be expected for conventional ductile fixed base buildings that sustain severe damage.     

Decoupled dynamic analysis of combined systems by iterative determination of interface accelerations

A dynamic analysis technique is presented that can be used to determine the response of a discrete model of a large linear structural system composed of multiple substructures. The technique circumvents the costly computation of the modal characteristics of the combined system. This is accomplished by relying on a predictor-corrector scheme to converge iteratively to the interface accelerations of the combined system, while the equations of motions of the individual structures are integrated separately. In this regard, the temporal slopes of the interface accelerations (jerks) are computed at each time point of integration to predict the interface accelerations at the next time point. The proposed technique is exemplified by conducting a space shuttle landing loads analysis; the obtained numerical data demonstrate its reliability and efficiency.     

Multi-site bias correction of climate model outputs for hydro-meteorological impact studies: An application over a watershed in China

Bias correction methods remove systematic differences in the distributional properties of climate model outputs with respect to observations, often as a means of pre-processing model outputs for use in hydrological impact studies. Traditionally, bias correction is applied at each weather station individually, neglecting the dependence that exists between different sites, which could negatively affect simulations from a distributed hydrological model. In this study, three multi-variate bias correction (MBC) methods—initially proposed to correct the inter-variable correlation or multi-variate dependence of climate model outputs—are used to correct biases in distributional properties and spatial dependence at multiple weather stations. To reveal the benefits of correcting spatial dependence, two distribution-based single-site bias correction methods are used for comparison. The effects of multi-site correction on hydro-meteorological extremes are assessed by driving a distributed hydrological model and then evaluating the model performance in terms of several meteorological and hydrological extreme indices. The results show that the multi-site bias correction methods perform well in reducing biases in spatial correlation measures of raw global climate model outputs. In addition, the multi-site methods consistently reproduce watershed-averaged meteorological variables better than single-site methods, especially for extreme values. In terms of representing hydrological extremes, the multi-site methods generally perform better than the single-site methods, although the benefits vary according to the hydrological index. However, when applying the multi-site methods, the original temporal sequence of precipitation occurrence may be altered to some extent. Overall, all multi-site bias correction methods are able to reproduce the spatial correlation of observed meteorological variables over multiple stations, which leads to better hydrological simulations, especially for extremes. This study emphasizes the necessity of considering spatial dependence when applying bias correction to ccc outputs and hydrological impact studies.     

Shaking table test of the effects of multi‐unit particle dampers attached to an MDOF system under earthquake excitation

This paper presents the results of an experimental and analytical/computational study of the performance of multi‐unit particle dampers with an MDOF system. A series of shaking table tests of a three‐storey steel frame with the particle damper system were carried out to evaluate the performance of the system and to verify the analysis method. An analytical solution based on the discrete element method is also presented. A comparison between the experimental and computational results shows that reasonably accurate estimates of the response of a primary system under earthquake excitations can be obtained. These results also indicate that the excitation characterization influences the performance of the particle damper system, for example, particle dampers have good performance in reducing the seismic response of structures and particle movements of plug flow pattern can yield good vibration attenuation effects. It is shown that by using properly designed multi‐unit particle dampers, a lightly damped primary system can achieve a reasonable reduction in its response, with a small weight penalty. Copyright © 2011 John Wiley & Sons, Ltd.     

Simulation and spatio-temporal disaggregation of multi-site rainfall data for urban drainage applications

Abstract

For urban drainage and urban flood modelling applications, fine spatial and temporal rainfall resolution is required. Simulation methods are developed to overcome the problem of data limitations. Although temporal resolution higher than 10–20 minutes is not well suited for detailed rainfall—runoff modelling for urban drainage networks, in the absence of monitored data, longer time intervals can be used for master planning or similar purposes. A methodology is presented for temporal disaggregation and spatial distribution of hourly rainfall fields, tested on observations for a 10-year period at 16 raingauges in the urban catchment of Dalmuir (UK). Daily rainfall time series are simulated with a generalized linear model (GLM). Next, using a single-site disaggregation model, the daily data of the central gauge in the catchment are downscaled to an hourly time scale. This hourly pattern is then applied linearly in space to disaggregate the daily data into hourly rainfall at all sites. Finally, the spatial rainfall field is obtained using inverse distance weighting (IDW) to interpolate the data over the whole catchment. Results are satisfactory: at individual sites within the region the simulated data preserve properties that match the observed statistics to an acceptable level for practical purposes.