Multilayer analytic element modeling of radial collector wells

A new multilayer approach is presented for the modeling of ground water flow to radial collector wells. The approach allows for the inclusion of all aspects of the unique boundary condition along the lateral arms of a collector well, including skin effect and internal friction losses due to flow in the arms. The hydraulic conductivity may differ between horizontal layers within the aquifer, and vertical anisotropy can be taken into account. The approach is based on the multilayer analytic element method, such that regional flow and local three-dimensional detail may be simulated simultaneously and accurately within one regional model. Horizontal flow inside a layer is computed analytically, while vertical flow is approximated with a standard finite-difference scheme. Results obtained with the proposed approach compare well to results obtained with three-dimensional analytic element solutions for flow in unconfined aquifers. The presented approach may be applied to predict the yield of a collector well in a regional setting and to compute the origin and residence time, and thus the quality, of water pumped by the collector well. As an example, the addition of three lateral arms to a collector well that already has three laterals is investigated. The new arms are added at an elevation of 2 m above the existing laterals. The yield increase of the collector well is computed as a function of the lengths of the three new arms.     

A new framework for modeling the migration of meandering rivers

Many models of river meander migration rely upon a simple formalism, whereby the eroding bank is cut back at a rate that is dictated by the flow, and the depositing bank then migrates passively in response, so as to maintain a constant bankfull channel width. Here a new model is presented, in which separate relations are developed for the migration of the eroding bank and the depositing bank. It is assumed that the eroding bank consists of a layer of fine‐grained sediment that is cohesive and/or densely riddled with roots, underlain by a purely noncohesive layer of sand and/or gravel. Following erosion of the noncohesive layer, the cohesive layer fails in the form of slump blocks, which armor the noncohesive layer and thereby moderate the erosion rate. If the slump block material breaks down or is fluvially entrained, the protection it provides for the noncohesive layer diminishes and bank erosion is renewed. Renewed bank erosion, however, rejuvenates slump block armoring. At the depositing bank, it is assumed that all the sediment delivered to the edge of vegetation due to the transverse component of sediment transport is captured by encroaching vegetation, which is not removed by successive floods. Separate equations describing the migration of the eroding and depositing banks are tied to a standard morphodynamic formulation for the evolution of the flow and bed in the central region of the channel. In this model, the river evolves toward maintenance of roughly constant bankfull width as it migrates only to the extent that the eroding bank and depositing bank ‘talk’ to each other via the medium of the morphodynamics of the channel center region. The model allows for both (a) migration for which erosion widens the channel, forcing deposition at the opposite bank, and (b) migration for which deposition narrows the channel forcing erosion at the opposite bank. Copyright © 2010 John Wiley & Sons, Ltd.     

A multivariate design framework for river confluences

ABSTRACT

Throughout the last decade copula functions were widely used to assess a wide range of hydrological problems, often focusing on two distinct variables. In many of these studies it was ignored whether the two variables of interest actually occurred simultaneously (e.g. two annual maximum time series were analysed in a multivariate statistical framework). Here we introduce a novel approach to derive bivariate design events using copula functions allowing both simultaneous and non-simultaneous occurrence of the variables to be modelled. The methodology is exemplarily applied to assess the combined flood occurrence at the confluence of the rivers Rhine and Sieg (Germany). The results underline the validity of the methodology. Employing a hydrodynamic numerical model furthermore shows that commonly used statistical approaches to select a single design event out of a vast number of possible combinations can be critical for practical design purposes.

Editor Z.W. Kundzewicz; Associate editor S. Grimaldi     

A probabilistic framework for floodplain mapping using hydrological modeling and unsteady hydraulic modeling

ABSTRACT

Prediction of design hydrographs is key in floodplain mapping using hydraulic models, which are either steady state or unsteady. The former, which require only an input peak, substantially overestimate the volume of water entering the floodplain compared to the more realistic dynamic case simulated by the unsteady models that require the full hydrograph. Past efforts to account for the uncertainty of boundary conditions using unsteady hydraulic modeling have been based largely on a joint flood frequency–shape analysis, with only a very limited number of studies using hydrological modeling to produce the design hydrographs. This study therefore presents a generic probabilistic framework that couples a hydrological model with an unsteady hydraulic model to estimate the uncertainty of flood characteristics. The framework is demonstrated on the Swannanoa River watershed in North Carolina, USA. Given its flexibility, the framework can be applied to study other sources of uncertainty in other hydrological models and watersheds.     

A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations

Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software framework for assisting with numerical experiments in computational turbulence. The framework targets Reynolds-averaged Navier-Stokes models, discretized by finite element methods. The novel implementation makes use of Python and the FEniCS package, the combination of which leads to compact and reusable code, where model- and solver-specific code resemble closely the mathematical formulation of equations and algorithms. The presented ideas and programming techniques are also applicable to other fields that involve systems of nonlinear partial differential equations. We demonstrate the framework in two applications and investigate the impact of various linearizations on the convergence properties of nonlinear solvers for a Reynolds-averaged Navier-Stokes model.     

A GIS tool for spatiotemporal modeling under a knowledge synthesis framework

In recent years, there has been a fast growing interest in the space–time data processing capacity of Geographic Information Systems (GIS). In this paper we present a new GIS-based tool for advanced geostatistical analysis of space–time data; it combines stochastic analysis, prediction, and GIS visualization technology. The proposed toolbox is based on the Bayesian Maximum Entropy theory that formulates its approach under a mature knowledge synthesis framework. We exhibit the toolbox features and use it for particulate matter spatiotemporal mapping in Taipei, in a proof-of-concept study where the serious preferential sampling issue is present. The proposed toolbox enables tight coupling of advanced spatiotemporal analysis functions with a GIS environment, i.e. QGIS. As a result, our contribution leads to a more seamless interaction between spatiotemporal analysis tools and GIS built-in functions; and utterly enhances the functionality of GIS software as a comprehensive knowledge processing and dissemination platform.     

基于ARM9地震电磁信息数据服务器的设计与实现

分析地震电磁信息仪器对信号处理和采集中存在的问题,提出基于ARM9的地震电磁信息数据服务器的解决方案,成功实现了对地震电磁信息的高速采集、海量存储和网络传输。文中介绍地震电磁信息数据服务器设计思路及基本构架,对各个模块给出硬件设计,并介绍系统的软件流程。     

An interactive multi-objective optimization framework for groundwater inverse modeling

The groundwater inverse problem of estimating heterogeneous groundwater model parameters (hydraulic conductivity in this case) given measurements of aquifer response (such as hydraulic heads) is known to be an ill-posed problem, with multiple parameter values giving similar fits to the aquifer response measurements. This problem is further exacerbated due to the lack of extensive data, typical of most real-world problems. In such cases, it is desirable to incorporate expert knowledge in the estimation process to generate more reasonable estimates. This work presents a novel interactive framework, called the ‘Interactive Multi-Objective Genetic Algorithm’ (IMOGA), to solve the groundwater inverse problem considering different sources of quantitative data as well as qualitative expert knowledge about the site. The IMOGA is unique in that it looks at groundwater model calibration as a multi-objective problem consisting of quantitative objectives – calibration error and regularization – and a ‘qualitative’ objective based on the preference of the geological expert for different spatial characteristics of the conductivity field. All these objectives are then included within a multi-objective genetic algorithm to find multiple solutions that represent the best combination of all quantitative and qualitative objectives. A hypothetical aquifer case-study (based on the test case presented by Freyberg [Freyberg DL. An exercise in ground-water model calibration and prediction. Ground Water 1988;26(3)], for which the ‘true’ parameter values are known, is used as a test case to demonstrate the applicability of this method. It is shown that using automated calibration techniques without using expert interaction leads to parameter values that are not consistent with site-knowledge. Adding expert interaction is shown to not only improve the plausibility of the estimated conductivity fields but also the predictive accuracy of the calibrated model.     

A new collector for sampling volcanic aerosols

A new apparatus, Venturi Effect System (VES), designed for sampling volcanic plumes is described and tested at Vulcano (Italy). This device, together with purified basic NH₄OH solutions, supplies optimal conditions to obtain reliable S_total/Cl/F ratios and enrichment factors for metallic trace elements (MTE). Good concordance for acid gas ratios and metal enrichment factors in both the gas phase and the related plume allows the procedure to be validated. The VES appears in Vulcano conditions as a simple, robust and easily portable apparatus that allows reliable collection of both acid gases and MTE within a single sample and the analysis with current chemical methods (High Pressure Liquid Chromatography, Inductively Coupled Plasma–Mass Spectrometry). This apparatus may be suitable for more difficult volcanoes where only the plume can be sampled.     

A design procedure for suspended zipper‐braced frames in the framework of Eurocode 8

In the recent past, suspended zipper‐braced frames were proposed to avoid one‐storey collapse mechanisms and dynamic instability under severe ground motions. In this paper, the design procedure suggested by Yang et al. is first slightly modified to conform to the design approach and capacity design rules stipulated in Eurocode 8 for concentrically braced frames. The procedure is applied to a set of suspended zipper‐braced frames with different number of storeys and founded on either soft or rock soil. The structural response of these frames is analysed to highlight qualities and deficiencies and to assess the critics reported by other researchers with regard to the design procedure by Yang et al. Then, improvements are proposed to this procedure to enhance the energy dissipation of the chevron braces and the response of the structural system as well. The effectiveness of the design proposals is evaluated by incremental dynamic analysis on structures with different geometric properties, gravity loads and soil of foundation. Copyright © 2017 John Wiley & Sons, Ltd.     

Proposal of design rules for ductile X-CBFS in the framework of EUROCODE 8

Cross concentrically braced frames (X-CBFs) are commonly used as primary seismic resisting system, owing to their large lateral stiffness, simplicity of design, and relatively low constructional cost. Current EN 1998-1 provides design rules theoretically aiming at developing ductile global plastic mechanism, namely enforcing plastic deformations in the diagonal members, while the remaining structural members and connections should elastically behave. However, as widely demonstrated by many existing studies, the design and the corresponding seismic performance of EC8-compliant X-CBFs are generally affected by several criticisms, eg, difficulties in sizing of diagonal members, massive and non-economical structures, and poor seismic behavior. In light of these considerations, the research activity presented in this paper is addressed to revise the design rules and requirements given EN 1998-1 for X-CBFs to simplify the design process and to improve the ductility and the dissipative capacity of this structural system. Hence, design rules are proposed for the next version of EN 1998-1 and numerically validated by means of nonlinear dynamic analyses.     

A unified approach for the design of high ductility steel frames with concentric braces in the framework of Eurocode 8

Eurocode 8 (EC8) stipulates design methods for frames with diagonal braces and for chevron braced frames, which differ as regards the numerical model adopted, the value of the behavior factor q and the estimation of the lateral strength provided by braces. Instead, in this paper, the use of the same design method is suggested for both types of concentrically braced frames. The design method is a generalization of the one proposed for chevron braced frames in a previous study. A numerical investigation is conducted to assess the reliability of this design method. A set of concentrically braced frames is designed according to the EC8 and proposed design methods. The seismic response of these frames is determined by nonlinear dynamic analysis. Finally, it is demonstrated that the proposed design method is equivalent to those provided by EC8, because it can ensure the same level of structural safety which would be expected when using EC8. Copyright © 2013 John Wiley & Sons, Ltd.     

Simulation/optimization modeling for robust pumping strategy design

A new simulation/optimization modeling approach is presented for addressing uncertain knowledge of aquifer parameters. The Robustness Enhancing Optimizer (REO) couples genetic algorithm and tabu search as optimizers and incorporates aquifer parameter sensitivity analysis to guide multiple-realization optimization. The REO maximizes strategy robustness for a pumping strategy that is optimal for a primary objective function (OF), such as cost. The more robust a strategy, the more likely it is to achieve management goals in the field, even if the physical system differs from the model. The REO is applied to trinitrotoluene and Royal Demolition Explosive plumes at Umatilla Chemical Depot in Oregon to develop robust least cost strategies. The REO efficiently develops robust pumping strategies while maintaining the optimal value of the primary OF-differing from the common situation in which a primary OF value degrades as strategy reliability increases. The REO is especially valuable where data to develop realistic probability density functions (PDFs) or statistically derived realizations are unavailable. Because they require much less field data, REO-developed strategies might not achieve as high a mathematical reliability as strategies developed using many realizations based upon real aquifer parameter PDFs. REO-developed strategies might or might not yield a better OF value in the field.     

Integration of the radiation belt environment model into the space weather modeling framework

We have integrated the Fok radiation belt environment (RBE) model into the space weather modeling framework (SWMF). RBE is coupled to the global magnetohydrodynamics component (represented by the Block-Adaptive-Tree Solar-wind Roe-type Upwind Scheme, BATS-R-US, code) and the Ionosphere Electrodynamics component of the SWMF, following initial results using the Weimer empirical model for the ionospheric potential. The radiation belt (RB) model solves the convection–diffusion equation of the plasma in the energy range of 10 keV to a few MeV. In stand-alone mode RBE uses Tsyganenko's empirical models for the magnetic field, and Weimer's empirical model for the ionospheric potential. In the SWMF the BATS-R-US model provides the time dependent magnetic field by efficiently tracing the closed magnetic field-lines and passing the geometrical and field strength information to RBE at a regular cadence. The ionosphere electrodynamics component uses a two-dimensional vertical potential solver to provide new potential maps to the RBE model at regular intervals. We discuss the coupling algorithm and show some preliminary results with the coupled code. We run our newly coupled model for periods of steady solar wind conditions and compare our results to the RB model using an empirical magnetic field and potential model. We also simulate the RB for an active time period and find that there are substantial differences in the RB model results when changing either the magnetic field or the electric field, including the creation of an outer belt enhancement via rapid inward transport on the time scale of tens of minutes.     

A stochastic framework to assess the performance of flood warning systems based on rainfall‐runoff modeling

Nowadays, Flood Forecasting and Warning Systems (FFWSs) are known as the most inexpensive and efficient non‐structural measures for flood damage mitigation in the world. Benefit to cost of the FFWSs has been reported to be several times of other flood mitigation measures. Beside these advantages, uncertainty in flood predictions is a subject that may affect FFWS's reliability and the benefits of these systems. Determining the reliability of advanced flood warning systems based on the rainfall–runoff models is a challenge in assessment of the FFWS performance which is the subject of this study. In this paper, a stochastic methodology is proposed to provide the uncertainty band of the rainfall–runoff model and to calculate the probability of acceptable forecasts. The proposed method is based on Monte Carlo simulation and multivariate analysis of the predicted time and discharge error data sets. For this purpose, after the calibration of the rainfall–runoff model, the probability distributions of input calibration parameters and uncertainty band of the model are estimated through the Bayesian inference. Then, data sets of the time and discharge errors are calculated using the Monte Carlo simulation, and the probability of acceptable model forecasts is calculated by multivariate analysis of data using copula functions. The proposed approach was applied for a small watershed in Iran as a case study. The results showed using rainfall–runoff modeling based on real‐time precipitation is not enough to attain high performance for FFWSs in small watersheds, and it seems using weather forecasts as the inputs of rainfall–runoff models is essential to increase lead times and the reliability of FFWSs in small watersheds. Copyright © 2013 John Wiley & Sons, Ltd.     

A simple correction for slug tests in small-diameter wells

A simple procedure is presented for correcting hydraulic conductivity (K) estimates obtained from slug tests performed in small-diameter installations screened in highly permeable aquifers. Previously reported discrepancies between results from slug tests in small-diameter installations and those from tests in nearby larger-diameter wells are primarily a product of frictional losses within the small-diameter pipe. These frictional losses are readily incorporated into existing models for slug tests in high-K aquifers, which then serve as the basis of a straightforward procedure for correcting previously obtained K estimates. A demonstration of the proposed procedure using data from a series of slug tests performed in a controlled field setting confirms the validity of the approach. The results of this demonstration also reveal the detailed view of spatial variations in K that can be obtained using slug tests in small-diameter installations.     

Post-wildfire sediment cascades: A modeling framework linking debris flow generation and network-scale sediment routing

Wildfires represent one of the largest disturbances in watersheds of the Intermountain West. Yet, we lack models capable of predicting post-wildfire impacts on downstream ecosystems and infrastructure. Here we present a novel modeling framework that links new and existing models to simulate the post-wildfire sediment cascade, including spatially explicit predictions of debris flows, storage of debris flow sediment within valleys, delivery of debris flow sediment to active channels, and the downstream routing of sediment through river networks. We apply the model to sediment dynamics in Clear Creek watershed following the 2010 Twitchell Canyon Fire in the Tushar Mountains of southern Utah. The debris flow generation model performed well, correctly predicting 19 out of 20 debris flows from the largest catchments, with only four false positives and two false negatives at observed rainfall intensities. In total, the model predicts the occurrence of 160 post-wildfire debris flows across the Clear Creek watershed, generating more than 650 000 m³ of sediment. Our new storage and delivery model predicts the vast majority of this sediment is stored within valleys, and only 13% is delivered to the river network. The sediment routing model identifies numerous sediment bottlenecks within the network, which alter transport dynamics and may be hotspots for aggradation and aquatic habitat alteration. The volume of sediment exported from the watershed after seven years of simulation totals 17% of that delivered, or 2% of the total generated debris flow sediment. In the case of the Twitchell Canyon Fire, this highlights that significant post-wildfire sediment volumes can be stored in valleys (87%) and within the stream network (11%). Finally, we discuss useful insights that can be gleaned from the model framework, as well as the limitations and need for more monitoring and theory development in order to better constrain essential inputs, process rates, and morphodynamics. © 2019 John Wiley & Sons, Ltd.     

A probabilistic framework to evaluate the uncertainty of design hydrograph: case study of Swannanoa River watershed

ABSTRACT

This study presents a probabilistic framework to evaluate the impact of uncertainty of design rainfall depth and temporal pattern as well as antecedent moisture condition (AMC) on design hydrograph attributes – peak, time to peak, duration and volume, as well as falling and rising limb slopes – using an event-based hydrological model in the Swannanoa River watershed in North Carolina, USA. Of the six hydrograph attributes, falling limb slope is the most sensitive to the aforementioned uncertainties, while duration is the least sensitive. In general, the uncertainty of hydrograph attributes decreases in higher recurrence intervals. Our multivariate analysis revealed that in most of the return periods, AMC is the most important driver for peak, duration and volume, while time to peak and falling limb slope are most influenced by rainfall pattern. In higher return periods, the importance of rainfall depth and pattern increases, while the importance of AMC decreases.