The efficiency of different estimation methods of hydro-physical limits

The soil water available to crops is defined by specific values of water potential limits. Underlying the estimation of hydro-physical limits, identified as permanent wilting point (PWP) and field capacity (FC), is the selection of a suitable method based on a multi-criteria analysis that is not always clear and defined. In this kind of analysis, the time required for measurements must be taken into consideration as well as other external measurement factors, e.g., the reliability and suitability of the study area, measurement uncertainty, cost, effort and labour invested. In this paper, the efficiency of different methods for determining hydro-physical limits is evaluated by using indices that allow for the calculation of efficiency in terms of effort and cost. The analysis evaluates both direct determination methods (pressure plate - PP and water activity meter - WAM) and indirect estimation methods (pedotransfer functions - PTFs). The PTFs must be validated for the area of interest before use, but the time and cost associated with this validation are not included in the cost of analysis. Compared to the other methods, the combined use of PP and WAM to determine hydro-physical limits differs significantly in time and cost required and quality of information. For direct methods, increasing sample size significantly reduces cost and time. This paper assesses the effectiveness of combining a general analysis based on efficiency indices and more specific analyses based on the different influencing factors, which were considered separately so as not to mask potential benefits or drawbacks that are not evidenced in efficiency estimation.

Estimation of soil moisture in the root-zone from remote sensing data

Field-based soil moisture measurements are cumbersome. Thus, remote sensing techniques are needed because allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. The objective of the study was to evaluate the accuracy of an empirical relationship to calculate soil moisture from remote sensing data of irrigated soils of the Apodi Plateau, in the Brazilian semiarid region. The empirical relationship had previously been tested for irrigated soils in Mexico, Egypt, and Pakistan, with promising results. In this study, the relationship was evaluated from experimental data collected from a cotton field. The experiment was carried out in an area of 5 ha with irrigated cotton. The energy balance and evaporative fraction (Λ) were measured by the Bowen ratio method. Soil moisture (θ) data were collected using a PR2 - Profile Probe (Delta-T Devices Ltd). The empirical relationship was tested using experimentally collected Λ and θ values and was applied using the Λ values obtained from the Surface Energy Balance Algorithm for Land (SEBAL) and three TM - Landsat 5 images. There was a close correlation between measured and estimated θ values (p<0.05, R² = 0.84) and there were no significant differences according to the Student t-test (p<0.01). The statistical analyses showed that the empirical relationship can be applied to estimate the root-zone soil moisture of irrigated soils, i.e. when the evaporative fraction is greater than 0.45.

Detection and Characterization of Preferential Flow Paths in the Downstream Area of a Hazardous Landfill

We have used surface-based electrical resistivity tomography to detect and characterize preferential hydraulic pathways in the immediate downstream area of an abandoned, hazardous landfill. The landfill occupies the void left by a former gravel pit and its base is close to the groundwater table and lacking an engineered barrier. As such, this site is remarkably typical of many small- to medium-sized waste deposits throughout the densely populated and heavily industrialized foreland on both sides of the Alpine arc. Outflows of pollutants lastingly contaminated local drinking water supplies and necessitated a partial remediation in the form of a synthetic cover barrier, which is meant to prevent meteoric water from percolating through the waste before reaching the groundwater table. Any future additional isolation of the landfill in the form of lateral barriers thus requires adequate knowledge of potential preferential hydraulic pathways for outflowing contaminants. Our results, inferred from a suite of tomographically inverted surfaced-based electrical resistivity profiles oriented roughly perpendicular to the local hydraulic gradient, indicate that potential contaminant outflows would predominantly occur along an unexploited lateral extension of the original gravel deposit. This finds its expression as a distinct and laterally continuous high-resistivity anomaly in the resistivity tomograms. This interpretation is ground-truthed through a litholog from a nearby well. Since the probed glacio-fluvial deposits are largely devoid of mineralogical clay, the geometry of hydraulic and electrical pathways across the pore space of a given lithological unit can be assumed to be identical, which allows for an order-of-magnitude estimation of the overall permeability structure. These estimates indicate that the permeability of the imaged extension of the gravel body is at least two to three orders-of-magnitude higher than that of its finer-grained embedding matrix. This corroborates the preeminent role of the high-resistivity anomaly as a potential preferential flow path.

The estimation of PMP and PMF on alpine basins in Switzerland

This paper presents a very fine grid hydrological model based on the spatiotemporal repartition of precipitation and on the topography. The goal is to estimate the flood on a catchment area, using a Probable Maximum Precipitation (PMP) leading to a Probable Maximum Flood (PMF). The spatiotemporal distribution of the precipitation was realized using six clouds modeled by the advection-diffusion equation. The equation shows the movement of the clouds over the terrain and also gives the evolution of the rain intensity in time. This hydrological modeling is followed by a hydraulic modeling of the surface and subterranean flows, done considering the factors that contribute to the hydrological cycle, such as the infiltration, the exfiltration and the snowmelt. This model was applied to several Swiss basins using measured rain, with results showing a good correlation between the simulated and observed flows. This good correlation proves that the model is valid and gives us the confidence that the results can be extrapolated to phenomena of extreme rainfall of PMP type. In this article we present some results obtained using a PMP rainfall and the developed model.

Empirical errors of small area estimates from the multisource National Forest Inventory in Eastern Finland

Abstract

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.

Accuracy of indirect estimation of power output from uphill performance in cycling.

PURPOSE: To use measurement by cycling power meters (Pmes) to evaluate the accuracy of commonly used models for estimating uphill cycling power (Pest). Experiments were designed to explore the influence of wind speed and steepness of climb on accuracy of Pest. The authors hypothesized that the random error in Pest would be largely influenced by the windy conditions, the bias would be diminished in steeper climbs, and windy conditions would induce larger bias in Pest. METHODS: Sixteen well-trained cyclists performed 15 uphill-cycling trials (range: length 1.3-6.3 km, slope 4.4-10.7%) in a random order. Trials included different riding position in a group (lead or follow) and different wind speeds. Pmes was quantified using a power meter, and Pest was calculated with a methodology used by journalists reporting on the Tour de France. RESULTS: Overall, the difference between Pmes and Pest was -0.95% (95%CI: -10.4%, +8.5%) for all trials and 0.24% (-6.1%, +6.6%) in conditions without wind (<2 m/s). The relationship between percent slope and the error between Pest and Pmes were considered trivial. CONCLUSIONS: Aerodynamic drag (affected by wind velocity and orientation, frontal area, drafting, and speed) is the most confounding factor. The mean estimated values are close to the power-output values measured by power meters, but the random error is between ±6% and ±10%. Moreover, at the power outputs (>400 W) produced by professional riders, this error is likely to be higher. This observation calls into question the validity of releasing individual values without reporting the range of random errors.

Gas-liquid mass transfer in bubbly flow: Estimation of mass transfer, bubble size and reactor performance in various applications

Gas-liquid mass transfer is an important issue in the design and operation of many chemical unit operations. Despite its importance, the evaluation of gas-liquid mass transfer is not straightforward due to the complex nature of the phenomena involved. In this thesis gas-liquid mass transfer was evaluated in three different gas-liquid reactors in a traditional way by measuring the volumetric mass transfer coefficient (kLa). The studied reactors were a bubble column with a T-junction two-phase nozzle for gas dispersion, an industrial scale bubble column reactor for the oxidation of tetrahydroanthrahydroquinone and a concurrent downflow structured bed.The main drawback of this approach is that the obtained correlations give only the average volumetric mass transfer coefficient, which is dependent on average conditions. Moreover, the obtained correlations are valid only for the studied geometry and for the chemical system used in the measurements. In principle, a more fundamental approach is to estimate the interfacial area available for mass transfer from bubble size distributions obtained by solution of population balance equations. This approach has been used in this thesis by developing a population balance model for a bubble column together with phenomenological models for bubble breakage and coalescence. The parameters of the bubble breakage rate and coalescence rate models were estimated by comparing the measured and calculated bubble sizes. The coalescence models always have at least one experimental parameter. This is because the bubble coalescence depends on liquid composition in a way which is difficult to evaluate using known physical properties. The coalescence properties of some model solutions were evaluated by measuring the time that a bubble rests at the free liquid-gas interface before coalescing (the so-calledpersistence time or rest time). The measured persistence times range from 10 msup to 15 s depending on the solution. The coalescence was never found to be instantaneous. The bubble oscillates up and down at the interface at least a coupleof times before coalescence takes place. The measured persistence times were compared to coalescence times obtained by parameter fitting using measured bubble size distributions in a bubble column and a bubble column population balance model. For short persistence times, the persistence and coalescence times are in good agreement. For longer persistence times, however, the persistence times are at least an order of magnitude longer than the corresponding coalescence times from parameter fitting. This discrepancy may be attributed to the uncertainties concerning the estimation of energy dissipation rates, collision rates and mechanisms and contact times of the bubbles.

Effects of the 80 km/h and variable speed limits on air pollution in the metropolitan area of Barcelona

In 2008 the regional government of Catalonia (Spain) reduced the maximum speed limit on several stretches of congested urban motorway in the Barcelona metropolitan area to 80 km/h, while in 2009 it introduced a variable speed system on other stretches of its metropolitan motorways. We use the differences-in-differences method, which enables a policy impact to be measured under specific conditions, to assess the impact of these policies on emissions of NOx and PM10. Empirical estimation indicate that reducing the speed limit to 80 km h-1 causes a 1.7 to 3.2% increase in NOx and 5.3 to 5.9% in PM10. By contrast, the variable speed policy reduced NOx and PM10 pollution by 7.7 to 17.1% and 14.5 to 17.3%. As such, a variable speed policy appears to be a more effective environmental policy than reducing the speed limit to a maximum of 80 km/h.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Estimation of transpiration of the 'Valencia' orange young plant using thermal dissipation probe method

Most studies on measures of transpiration of plants, especially woody fruit, relies on methods of heat supply in the trunk. This study aimed to calibrate the Thermal Dissipation Probe Method (TDP) to estimate the transpiration, study the effects of natural thermal gradients and determine the relation between outside diameter and area of xylem in 'Valencia' orange young plants. TDP were installed in 40 orange plants of 15 months old, planted in boxes of 500 L, in a greenhouse. It was tested the correction of the natural thermal differences (DTN) for the estimation based on two unheated probes. The area of the conductive section was related to the outside diameter of the stem by means of polynomial regression. The equation for estimation of sap flow was calibrated having as standard lysimeter measures of a representative plant. The angular coefficient of the equation for estimating sap flow was adjusted by minimizing the absolute deviation between the sap flow and daily transpiration measured by lysimeter. Based on these results, it was concluded that the method of TDP, adjusting the original calibration and correction of the DTN, was effective in transpiration assessment.

Estimation of evaporation in the Banabuiú dam, in the state of Ceará, Brazil, by different combined methods, derived from the Penman equation

The state of Ceará, Brazil, has 75% of its area covered by Brazilian semiarid, with its peculiar features. In this state, the dams are constituted in water structure of strategic importance, ensuring, both in time and space, the development and supply of water to population. However, construction of reservoirs results in various impacts that should be carefully observed when deciding on their implementation. One of the impacts identified as negative is the increased evaporation, which constitutes a major component of water balance in reservoirs, especially in arid regions. Several methods for estimating evaporation have been proposed over time, many of them deriving from the Penman equation. This study evaluated six different methods for estimating evaporation in order to determine the most suitable for use in hydrological models for water balance in reservoirs in the state of Ceará. The tested methods were proposed by Penman, Kohler-Nordenson-Fox, Priestley-Taylor, deBruim-Keijman, Brutsaert-Stricker and deBruim. The methods presented good performance when tested for water balance during the dry season, and the Priestley-Taylor was the most appropriate, since the data from de simulated water balance with evaporation estimated by this method were the closest of the water balance data observed from measures of reservoir level and the elevation-volume curve provided by the Company of Management of Water Resources of the state of Ceará - COGERH.

Estimation of alluvial recharge in the semiarid

In areas where there is irrigated agriculture, the recuperation of water reserves in alluvial aquifers may occur preferentially due to precipitation. Recharging can be evaluated from variation information of water depth measured in piezometers or observation wells. Thus, the aim of this research is to study the recharge in the alluvial aquifer formed by the Mimoso temporary stream in the semiarid region of Pernambuco (PE), Brazil, using the method of the fluctuation of the water level. This system is typical on the Brazilian Northeast semiarid region, using groundwater for domestic supply and for irrigation on small scale agriculture. Monthly potentiometric levels and rainfall data were used. The selected period for the study, from January 2002 to October 2009, involved extreme events of flooding and droughts as well as regular years, providing a better understanding of the behavior of the alluvial recharge. It was found that the system responds significantly to precipitation events. It was also observed that even with different soil textures in the study area, recharge factors were not significantly different. The study provided a better understanding of the behavior of aquifer recharge and its relationship with the soil and the rainfall events in the region.

Estimation des facteurs de risque de la progression de la scoliose idiopathique de l’adolescence

Cette étude a pour but de tester si l’ajout de variables biomécaniques, telles que celles associées à la morphologie, la posture et l’équilibre, permet d’améliorer l’efficacité à dissocier 29 sujets ayant une scoliose progressive de 45 sujets ayant une scoliose non progressive. Dans une étude rétrospective, un groupe d’apprentissage (Cobb: 27,1±10,6°) a été utilisé avec cinq modèles faisant intervenir des variables cliniques, morphologiques, posturales et d’équilibre et la progression de la scoliose. Un groupe test (Cobb: 14,2±8,3°) a ensuite servit à évaluer les modèles dans une étude prospective. Afin d’établir l’efficacité de l’ajout de variables biomécaniques, le modèle de Lonstein et Carlson (1984) a été utilisé à titre d’étalon de mesures. Le groupe d’apprentissage a été utilisé pour développer quatre modèles de classification. Le modèle sans réduction fut composé de 35 variables tirées de la littérature. Dans le modèle avec réduction, une ANCOVA a servit de méthode de réduction pour passer de 35 à 8 variables et l’analyse par composantes principales a été utilisée pour passer de 35 à 7 variables. Le modèle expert fut composé de huit variables sélectionnées d’après l’expérience clinque. L’analyse discriminante, la régression logistique et l’analyse par composantes principales ont été appliquées afin de classer les sujets comme progressifs ou non progressifs. La régression logistique utilisée avec le modèle sans réduction a présenté l’efficience la plus élevée (0,94), tandis que l’analyse discriminante utilisée avec le modèle expert a montré l’efficience la plus faible (0,87). Ces résultats montrent un lien direct entre un ensemble de paramètres cliniques et biomécaniques et la progression de la scoliose idiopathique. Le groupe test a été utilisé pour appliquer les modèles développés à partir du groupe d’apprentissage. L’efficience la plus élevée (0,89) fut obtenue en utilisant l’analyse discriminante et la régression logistique avec le modèle sans réduction, alors que la plus faible (0,78) fut obtenue en utilisant le modèle de Lonstein et Carlson (1984). Ces valeurs permettent d’avancer que l’ajout de variables biomécaniques aux données cliniques améliore l’efficacité de la dissociation entre des sujets scoliotiques progressifs et non progressifs. Afin de vérifier la précision des modèles, les aires sous les courbes ROC ont été calculées. L’aire sous la courbe ROC la plus importante (0,93) fut obtenue avec l’analyse discriminante utilisée avec le modèle sans réduction, tandis que la plus faible (0,63) fut obtenue avec le modèle de Lonstein et Carlson (1984). Le modèle de Lonstein et Carlson (1984) n’a pu séparer les cas positifs des cas négatifs avec autant de précision que les modèles biomécaniques. L’ajout de variables biomécaniques aux données cliniques a permit d’améliorer l’efficacité de la dissociation entre des sujets scoliotiques progressifs et non progressifs. Ces résultats permettent d’avancer qu’il existe d’autres facteurs que les paramètres cliniques pour identifier les patients à risque de progresser. Une approche basée sur plusieurs types de paramètres tient compte de la nature multifactorielle de la scoliose idiopathique et s’avère probablement mieux adaptée pour en prédire la progression.

Estimation des corrélations phylogénétiques entre paramètres d'évolution moléculaire et Traits d'histoire de vie

Depuis quelques années, l'évolution moléculaire cherche à caractériser les variations et l'intensité de la sélection grâce au rapport entre taux de substitution synonyme et taux de substitution non-synonyme (dN/dS). Cette mesure, dN/dS, a permis d'étudier l'histoire de la variation de l'intensité de la sélection au cours du temps ou de détecter des épisodes de la sélection positive. Les liens entre sélection et variation de taille efficace interfèrent cependant dans ces mesures. Les méthodes comparatives, quant a elle, permettent de mesurer les corrélations entre caractères quantitatifs le long d'une phylogénie. Elles sont également utilisées pour tester des hypothèses sur l'évolution corrélée des traits d'histoire de vie, mais pour être employées pour étudier les corrélations entre traits d'histoire de vie, masse, taux de substitution ou dN/dS. Nous proposons ici une approche combinant une méthode comparative basée sur le principe des contrastes indépendants et un modèle d'évolution moléculaire, dans un cadre probabiliste Bayésien. Intégrant, le long d'une phylogénie, sur les reconstructions ancestrales des traits et et de dN/dS nous estimons les covariances entre traits ainsi qu'entre traits et paramètres du modèle d'évolution moléculaire. Un modèle hiérarchique, a été implémenté dans le cadre du logiciel coevol, publié au cours de cette maitrise. Ce modèle permet l'analyse simultané de plusieurs gènes sans perdre la puissance donnée par l'ensemble de séquences. Un travail deparallélisation des calculs donne la liberté d'augmenter la taille du modèle jusqu'à l'échelle du génome. Nous étudions ici les placentaires, pour lesquels beaucoup de génomes complets et de mesures phénotypiques sont disponibles. À la lumière des théories sur les traits d'histoire de vie, notre méthode devrait permettre de caractériser l'implication de groupes de gènes dans les processus biologique liés aux phénotypes étudiés.