Revisiting Field Capacity (FC): variation of definition of FC and its estimation from pedotransfer functions

Taking into account the nature of the hydrological processes involved in in situ measurement of Field Capacity (FC), this study proposes a variation of the definition of FC aiming not only at minimizing the inadequacies of its determination, but also at maintaining its original, practical meaning. Analysis of FC data for 22 Brazilian soils and additional FC data from the literature, all measured according to the proposed definition, which is based on a 48-h drainage time after infiltration by shallow ponding, indicates a weak dependency on the amount of infiltrated water, antecedent moisture level, soil morphology, and the level of the groundwater table, but a strong dependency on basic soil properties. The dependence on basic soil properties allowed determination of FC of the 22 soil profiles by pedotransfer functions (PTFs) using the input variables usually adopted in prediction of soil water retention. Among the input variables, soil moisture content θ (6 kPa) had the greatest impact. Indeed, a linear PTF based only on it resulted in an FC with a root mean squared residue less than 0.04 m³ m-3 for most soils individually. Such a PTF proved to be a better FC predictor than the traditional method of using moisture content at an arbitrary suction. Our FC data were compatible with an equivalent and broader USA database found in the literature, mainly for medium-texture soil samples. One reason for differences between FCs of the two data sets of fine-textured soils is due to their different drainage times. Thus, a standardized procedure for in situ determination of FC is recommended.

Estimation of field capacity from ring infiltrometer-drainage data

Field capacity (FC) is a parameter widely used in applied soil science. However, its in situ method of determination may be difficult to apply, generally because of the need of large supplies of water at the test sites. Ottoni Filho et al. (2014) proposed a standardized procedure for field determination of FC and showed that such in situ FC can be estimated by a linear pedotransfer function (PTF) based on volumetric soil water content at the matric potential of -6 kPa [θ(6)] for the same soils used in the present study. The objective of this study was to use soil moisture data below a double ring infiltrometer measured 48 h after the end of the infiltration test in order to develop PTFs for standard in situ FC. We found that such ring FC data were an average of 0.03 m³ m- 3 greater than standard FC values. The linear PTF that was developed for the ring FC data based only on θ(6) was nearly as accurate as the equivalent PTF reported by Ottoni Filho et al. (2014), which was developed for the standard FC data. The root mean squared residues of FC determined from both PTFs were about 0.02 m³ m- 3. The proposed method has the advantage of estimating the soil in situ FC using the water applied in the infiltration test.

EFFECTS OF COMPACTION DUE TO MACHINERY TRAFFIC ON SOIL PORE CONFIGURATION

Soil compaction has been recognized as a severe problem in mechanized agriculture and has an influence on many soil properties and processes. Yet, there are few studies on the long-term effects of soil compaction, and the development of soil compaction has been shown through a limited number of soil parameters. The objectives of this study were to evaluate the persistence of soil compaction effects (three traffic treatments: T0, without traffic; T3, three tractor passes; and T5, five tractor passes) on pore system configuration, through static and dynamic determinations; and to determine changes in soil pore orientation due to soil compaction through measurement of hydraulic conductivity of saturated soil in samples taken vertically and horizontally. Traffic led to persistent changes in all the dynamic indicators studied (saturated hydraulic conductivity, K0; effective macro- and mesoporosity, εma and εme), with significantly lower values of K0, εma, and εme in the T5 treatment. The static indicators of bulk density (BD), derived total porosity (TP), and total macroporosity (θma) did not vary significantly among the treatments. This means that machine traffic did not produce persistent changes on these variables after two years. However, the orientation of the soil pore system was modified by traffic. Even in T0, there were greater changes in K0 measured in the samples taken vertically than horizontally, which was more related to the presence of vertical biopores, and to isotropy of K0 in the treatments with machine traffic. Overall, the results showed that dynamic indicators are more sensitive to the effects of compaction and that, in the future, static indicators should not be used as compaction indicators without being complemented by dynamic indicators.

MODELING OF SOIL LOAD-BEARING CAPACITY AS A FUNCTION OF SOIL MECHANICAL RESISTANCE TO PENETRATION

Estimation of soil load-bearing capacity from mathematical models that relate preconsolidation pressure (σp) to mechanical resistance to penetration (PR) and gravimetric soil water content (U) is important for defining strategies to prevent compaction of agricultural soils. Our objective was therefore to model the σp and compression index (CI) according to the PR (with an impact penetrometer in the field and a static penetrometer inserted at a constant rate in the laboratory) and U in a Rhodic Eutrudox. The experiment consisted of six treatments: no-tillage system (NT); NT with chiseling; and NT with additional compaction by combine traffic (passing 4, 8, 10, and 20 times). Soil bulk density, total porosity, PR (in field and laboratory measurements), U, σp, and CI values were determined in the 5.5-10.5 cm and 13.5-18.5 cm layers. Preconsolidation pressure (σp) and CI were modeled according to PR in different U. The σp increased and the CI decreased linearly with increases in the PR values. The correlations between σp and PR and PR and CI are influenced by U. From these correlations, the soil load-bearing capacity and compaction susceptibility can be estimated by PR readings evaluated in different U.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

From Empirical Bayes to Full Bayes: Methods for Analyzubg Traffic Safey Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this light, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

Iowa Traffic Control Devices and Pavement Markings: A Manual for Cities and Counties April 2001

Iowa Traffic Control Devices and Pavement Markings: A Manual for Cities and Counties has been developed to provide state and local transportation agencies with suggestions and examples related to traffic control devices and pavement markings. Both rural and urban applications are included. The primary source of information for this document is the Manual on Uniform Traffic Control Devices (MUTCD), but many additional references have also been used. A complete listing of these is included in the appendix to this manual, and the reader is invited to consult these references for more in-depth information. The contents of this manual are not intended to represent standard practice or to imply legal requirements for installation in any particular manner. This document should be used as a supplement to the MUTCD, not as a substitute for any requirements contained therein. Engineering judgement should be applied to all decisions regarding traffic control devices and pavement markings. All references to the MUTCD in this manual apply to the millennium edition. The reader should be aware that many millennium revisions are allowed phase-in periods by the Federal Highway Administration (FHWA), ranging from two to ten years. These extended compliance periods should be considered when making decisions regarding traffic control devices and pavement markings. A new addition to the MUTCD, Part 5, “Traffic Control Devices for Low-Volume Roads,” also contains valuable recommendations for signing and marking low volume roads. This manual is presented in an easy to use threering format. Topics included in the complete guide manual may not apply to all jurisdictions and can easily be removed or modified as desired. Desired millennium MUTCD sections may be added for quick reference using the divider at the end of this document. Contents may also be available on CD-ROM in the future.

Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data

Numerous sources of evidence point to the fact that heterogeneity within the Earth's deep crystalline crust is complex and hence may be best described through stochastic rather than deterministic approaches. As seismic reflection imaging arguably offers the best means of sampling deep crustal rocks in situ, much interest has been expressed in using such data to characterize the stochastic nature of crustal heterogeneity. Previous work on this problem has shown that the spatial statistics of seismic reflection data are indeed related to those of the underlying heterogeneous seismic velocity distribution. As of yet, however, the nature of this relationship has remained elusive due to the fact that most of the work was either strictly empirical or based on incorrect methodological approaches. Here, we introduce a conceptual model, based on the assumption of weak scattering, that allows us to quantitatively link the second-order statistics of a 2-D seismic velocity distribution with those of the corresponding processed and depth-migrated seismic reflection image. We then perform a sensitivity study in order to investigate what information regarding the stochastic model parameters describing crustal velocity heterogeneity might potentially be recovered from the statistics of a seismic reflection image using this model. Finally, we present a Monte Carlo inversion strategy to estimate these parameters and we show examples of its application at two different source frequencies and using two different sets of prior information. Our results indicate that the inverse problem is inherently non-unique and that many different combinations of the vertical and lateral correlation lengths describing the velocity heterogeneity can yield seismic images with the same 2-D autocorrelation structure. The ratio of all of these possible combinations of vertical and lateral correlation lengths, however, remains roughly constant which indicates that, without additional prior information, the aspect ratio is the only parameter describing the stochastic seismic velocity structure that can be reliably recovered.

Utilization of Remote Traffic Monitoring Devices for Urban Freeway Work Zone Assessment Final Report, January 2012

The objective of this project was to promote and facilitate analysis and evaluation of the impacts of road construction activities in Smart Work Zone Deployment Initiative (SWZDI) states. The two primary objectives of this project were to assess urban freeway work-zone impacts through use of remote monitoring devices, such as radar-based traffic sensors, traffic cameras, and traffic signal loop detectors, and evaluate the effectiveness of using these devices for such a purpose. Two high-volume suburban freeway work zones, located on Interstate 35/80 (I-35/I-80) through the Des Moines, Iowa metropolitan area, were evaluated at the request of the Iowa Department of Transportation (DOT).

Development of a Traffic Control Devices and Pavement Markings Manual for Iowa's Cities and Counties with a Survery of Common Practices, April 2001

Transportation agencies in Iowa are responsible for a significant public investment with the installation and maintenance of traffic control devices and pavement markings. Included in this investment are thousands of signs and other inventory items, equipment, facilities, and staff. The proper application of traffic control devices and pavement markings is critical to public safety on streets and highways, and local governments have a prescribed responsibility under the Code of Iowa to properly manage these assets. This research report addresses current traffic control and pavement marking application, maintenance, and management in Iowa.

Revision to the SUDAS Traffic Signal Standards – Phase 2, Final Report, May 2012

This report provides a summary of the updates to the traffic signal content within the Iowa Statewide Urban Design and Specifications (SUDAS) Design Manual Chapter 13 and Standard Specifications Division 8. Major focal points included pole footing design, cabinets and controllers, monitoring systems, communications systems, and figure updates. This work was completed through a project task force with a variety of participants (contractors, Iowa Department of Transportation, city traffic engineers, consultant, vendors, and University research and support staff).

Concrete Overlay Field Application Program Iowa Task Report US 18 Concrete Overlay Construction Under Traffic, May 2012

The National Concrete Pavement Technology Center, Iowa Department of Transportation, and Federal Highway Administration set out to demonstrate and document the design and construction of portland cement concrete (PCC) overlays on two-lane roadways while maintaining two-way traffic. An 18.82 mile project was selected for 2011 construction in northeast Iowa on US 18 between Fredericksburg and West Union. This report documents planning, design, and construction of the project and lessons learned. The work included the addition of subdrains, full-depth patching, bridge approach replacement, and drainage structural repair and cleaning prior to overlay construction. The paving involved surface preparation by milling to grade and the placement of a 4.5 inch PCC overlay and 4 foot of widening to the existing pavement. In addition, the report makes recommendations on ways to improve the process for future concrete overlays.

Bio-electrical impedance analysis for estimation of fat-free mass and muscle mass in cystic fibrosis patients.

The nutritional status of cystic fibrosis (CF) patients has to be regularly evaluated and alimentary support instituted when indicated. Bio-electrical impedance analysis (BIA) is a recent method for determining body composition. The present study evaluates its use in CF patients without any clinical sign of malnutrition. Thirty-nine patients with CF and 39 healthy subjects aged 6-24 years were studied. Body density and mid-arm muscle circumference were determined by anthropometry and skinfold measurements. Fat-free mass was calculated taking into account the body density. Muscle mass was obtained from the urinary creatinine excretion rate. The resistance index was calculated by dividing the square of the subject's height by the body impedance. We show that fat-free mass, mid-arm muscle circumference and muscle mass are each linearly correlated to the resistance index and that the regression equations are similar for both CF patients and healthy subjects.