Orientadores: Paulo Sérgio Graziano Magalhãe, Armando Zaupa Remacre / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola / Made available in DSpace on 2018-08-27T21:34:19Z (GMT). No. of bitstreams: 1 Sanches_GuilhermeMartineli_M.pdf: 13551439 bytes, checksum: 1aa534b602f92044d4ea34bee5e63027 (MD5) Previous issue date: 2015 / Resumo: Umas das ferramentas utilizadas na Agricultura de Precisão (AP) é a geoestatística, cujo principal objetivo é a descrição dos padrões espaciais e a estimativa de dados em locais não amostrados. Um dos fatores limitantes para se fazer um adequado mapeamento do solo e atender os requisitos mínimos dos métodos de interpolação é a necessidade de uma amostragem densa da área, o que inviabiliza muitas vezes o mapeamento do solo, devido ao demorado e custoso processo de retirada de amostras. Dentro deste contexto os métodos de interpolação geoestatísticos vislumbram uma solução para o presente desafio, tornando possível a descrição da variabilidade espacial do solo com uma pequena amostragem da variável a qual se deseja conhecer, utilizando para isto outros atributos que são mais facilmente mensuráveis e a um custo menor. Uma das técnicas possíveis para otimizar a quantidade de pontos amostrais consiste na utilização de dados obtidos através de sensores de solo para orientação da amostragem. Este trabalho tem como hipótese que, utilizando dados provenientes de sensores de Condutividade Elétrica Aparente (CEa) do solo em conjunto com técnicas de geoestatística, é possível, através de uma amostragem direcionada e reduzida, conhecer a descrição da variabilidade espacial da fertilidade e do estado físico dos solos com adequada precisão. A presente pesquisa teve como objetivo obter mapas da variabilidade espacial dos atributos químicos e físicos do solo utilizando um número reduzido de amostras e aplicando métodos de interpolação geoestatísticos (krigagem ordinária e com deriva externa), tendo como base dados de condutividade elétrica aparente do solo. A metodologia utilizada para a obtenção dos mapas de variabilidade espacial dos atributos do solo indicam que é possível prever mapas que podem ser utilizados para recomendação de fertilizantes à taxa variável. Esta abordagem abre novas possibilidades para que atributos agronômicos importantes possam ser estimados em grandes áreas a partir de um número reduzido de amostras, auxiliando os agricultores no manejo da cultura e tomada de decisão / Abstract: One of the tools used in precision agriculture (PA) is geostatistics, which main objective is to describe the spatial patterns and the estimated data on non-sampled locations. One of the limiting factors for making a proper soil mapping and meet the minimum requirements of interpolation methods is the need for a dense sampling grid, which often makes it impossible, as the process are time consuming and expensive. Within this context, the geostatistical interpolation methods envision a solution for this challenge, making it possible to describe the soil spatial variability with a small sampling of the primary variable (which you want to know), using other attributes that are easily measured. One of the possible techniques to optimize the number of soil sampling is the use of data obtained from soil sensors. This work the assumption that, using data from the Apparent Electrical Conductivity (ECa) together with geostatistical techniques, it is possible, through a targeted and reduced sampling, know the spatial variability of soils fertility and physical condition with adequate precision. Therefore, this research aims to obtain maps of the spatial variability of chemical and physical soil properties using a reduced number of samples and applying geostatistical interpolation methods (ordinary kriging and kriging with external drift), based on data of apparent electrical conductivity. The methodology used to obtain the maps of spatial variability of soil attributes indicate that it is possible to provide maps that can be used for fertilizer recommendation to the variable rate. This approach opens new possibilities for important agronomic attributes be estimated in large areas from a small number of samples, assisting farmers in crop management and decision-making / Mestrado / Maquinas Agricolas / Mestre em Engenharia Agrícola

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第22703号 / 工博第4750号 / 新制||工||1743(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 小池 克明, 教授 林 為人, 准教授 柏谷 公希 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

The scarcity of housing has led more and more developers to turn to the conversion of former industrial areas into residential areas. Brownfield redevelopment involves the cleanup of contaminated soil to eliminate any health or environmental risk. The quantification of the amount of pollutant in soil is essential to carry out an efficient remediation. It involves sampling and analyzing the soil to determine the concentration of pollutant at a finite number of locations. It is therefore necessary to assess the pollutant amount at unknown locations to estimate the pollution for the whole site. The existing methods used by the depollution actors often lead to underestimation or overestimation of the contamination possibly creating environmental, economic and legal issues. This study aims to compare different methods to assess the mass of pollutant using data from a site contaminated with chlorinated solvents. The methods comprise currently used methods (Mean 1, Mean 2), simple interpolation methods (Thiessen Polygons, Natural Neighbor, Inverse Distance Weighting) and a method based on a complete geostatistical approach (Conditional Simulations). They are compared to determine the variability of the results obtained with a specific set of data depending on the chosen method. The deterministic methods, although easy to apply, will often underestimate the mass of pollutants contained in soil whereas the geostatistical approach can give a more realistic result, but is complex to implement.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / The application of conventional techniques, such as kriging, to model rock mass is limited because rock mass spatial variability and heterogeneity are not considered in such techniques. In this context, as an alternative solution, the application of the Gaussian simulation technique to simulate rock mass spatial heterogeneity based on the rock mass rating (RMR) classification is proposed. This research proposes a methodology that includes a variographic analysis of the RMR in different directions to determine its anisotropic behavior. In the case study of an underground deposit in Peru, the geomechanical record data compiled in the field were used. A total of 10 simulations were conducted, with approximately 6 million values for each simulation. These were calculated, verified, and an absolute mean error of only 3.82% was estimated. It is acceptable when compared with the value of 22.15% obtained with kriging.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19697号 / 工博第4152号 / 新制||工||1641(附属図書館) / 32733 / 京都大学大学院工学研究科都市環境工学専攻 / (主査)教授 米田 稔, 教授 清水 芳久, 准教授 藤川 陽子 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

No description available.

Inorganic contaminants, including potentially toxic metals (PTMs), originating from un-reclaimed abandoned mine areas may accumulate in soils and present significant distress to environmental and public health. The ability to generate realistic spatial distribution models of such contamination is important for risk assessment and remedial planning of sites where this has oc-curred. This study evaluated the prediction accuracy of optimized ordinary kriging compared to spatial regression-informed cokriging for PTMs (Zn, Mn, Cu, Pb, and Cd) in soils near abandoned mines in Bumpus Cove, Tennessee, USA. Cokriging variables and neighborhood sizes were system-atically selected from prior statistical analyses based on the association with PTM transport and soil physico-chemical properties (soil texture, moisture content, bulk density, pH, cation exchange capacity (CEC), and total organic carbon (TOC)). A log transform was applied to fit the frequency histograms to a normal distribution. Superior models were chosen based on six diagnostics (ME, RMS, MES, RMSS, ASE, and ASE-RMS), which produced mixed results. Cokriging models were preferred for Mn, Zn, Cu, and Cd, whereas ordinary kriging yielded better model results for Pb. This study determined that the preliminary process of developing spatial regression models, thus enabling the selection of contributing soil properties, can improve the interpolation accuracy of PTMs in abandoned mine sites.

Lifelines such as highways, pipelines, telecommunication lines, and powerlines provide communities with vital services, and their functionality is dependent upon the foundation soil that supports them. However, when designing the infrastructure, it can be difficult to know where to test the soil in order to give spatially representative sampling, particularly for long, lifeline structures. Finding this distance requires knowledge of the spatial correlation and/or the spatial variability of the soil parameter (stiffness, cohesion, etc.). But this correlation distance is not typically found in practice because it requires large amounts of data and the costs of retrieving that data can be high. Lack of representative sampling can lead to an overly conservative design and too much sampling can create an overly expensive sampling program. In this study, multiple tests using the geophysical method of spatial autocorrelation (SPAC) were conducted to find the soil stiffness along a 310 meter long profile. SPAC records passive surface waves which sample the underlying soil, and these surface waves can be used to create a shear wave velocity profile of the site. The spatial continuity of the stiffness (the soil velocity values) was then found using geostatistics. The geostastical tool primarily used in this study was the (semi-)variogram, but the covariance function and the correlogram are also shown. By using these tools, the spatial correlation/variability can give an estimate of the how far apart to test the foundation soil so that the data is spatially representative. In other words, finding the distance that the soil parameter is minimally correlated with itself. This study found the distance (the range of the semi-variogram) to be 70 meters for 5 meters depth, 100 meters for 10 to 15 meters depth, and 90 meters for 30 meters depth.

Production of hot peppers, Capsicum spp., in Jamaica is constrained by the aphid-transmitted potyviruses, tobacco etch virus (TEV) and potato virus Y (PVY). The virus epidemiology was not understood and no effective virus management system existed for these viruses. This study sought to identify possible management strategies for aphid-transmitted viruses of hot peppers in Jamaica, using TEV and Capsicum chinense, var. 'Scotch Bonnet' and 'West Indian Red', as models. Field spread of TEV to pepper was mainly by secondary spread from primary infections. Secondary infections were spatially correlated to primary infections for up to 25 meters. Natural infections of TEV were associated with aphid flight activity. Over 30 species of aphids were collected on pepper farms in St. Catherine parish. These aphids included five known vectors of TEV, Aphis gossypii Glover, A. craccivora Koch, A. spiraecola Patch, Lipaphis erysimi Hille Ris Lambers and M. persicae (Sulzer), and 12 new records for Jamaica, Aphis amaranthi Holman, Brachycaudus helichrysi (Kaltenbach),Capitophorus hippophaes (Walker), Geopemphigus floccosus (Moreira), Hysteroneura setariae (Thomas), Lipaphis erysimi Hille Ris Lambers, Rhopalosiphum padi (Linnaeus), Schizaphis graminum (Rondani), Schizaphis rotundiventris (Signoret), Trichosiphonaphis poligoni (van der Goot), Uroleucon ambrosiae complex (Thomas) and Uroleucon pseudoambrosiae (Olive). A. amaranthi and U. ambrosiae were associated with TEV spread. Weeds on and near farms influenced the abundance and species of aphids captured. West Indian Red pepper showed tolerance to TEV. Scotch Bonnet pepper yield reduction was greater if plants were infected with TEV during the vegetative stage through flower initiation rather than after the start of fruit set. Stylet oil and reflective mulch used together delayed the incidence of TEV in pepper plots for over two months. TEV management programs should aim to delay the virus from infecting peppers during the first two months after transplanting. A risk analysis is proposed for management of TEV and other aphid-borne viruses. / Ph. D.

Wetlands are now recognized for the many social, environmental, ecological, and economic benefits they provide. They improve water quality, support biodiversity, abate floods and storms, and provide local recreational areas. Historically, many wetlands have been drained or altered for residential, commercial, or agricultural use. Effective wetland restoration projects reestablish ecosystem services and mitigate legacy effects of land use change to create self-sustaining systems. However, a persisting lack of scientifically-vetted methodological and evaluation guidelines in the field of restoration ecology has caused many restoration efforts to fail to restore natural wetland hydrologic conditions. By definition, wetlands must be saturated, permanently or seasonally, for durations long or frequent enough to support hydrophilic vegetation. It is therefore critical in planning restoration projects to focus on creating shallow water table conditions and adequate soil moisture retention in the vadose zone. This study quantitatively assesses the efficacy of a process-based ecological restoration technique that has been implemented at a retired cranberry bog in Manomet, Massachusetts. This restoration approach involved the creation of microtopography, ditch filling, and redistribution and mixing of the shallow substrate. The restoration goal for these actions was to bring the water table closer to the surface, increase soil moisture in the root zone, and increase habitat variability at the site. I examined the potential impact of these restorative techniques on groundwater and soil moisture dynamics. I conducted a parametric study using variably saturated groundwater flow modeling, examine the influence of specific restoration parameters (the near surface mixing ratio, anisotropy, and microtopographic geometry) on the restoration outcome. I tested the sensitivity of the water table and soil moisture to alterations in the near surface geologic structure resulting from a pit-and-mound restoration. I hope these findings will inform and optimize these practices for future restoration projects.