Spatial variability patterns of some Vertisol properties at a field scale using standardized data

Spatial variability of Vertisol properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns. The objectives of the present work were (i) to quantify the spatial structure of different physical properties collected from a Vertisol, (ii) to search for potential correlations between different spatial patterns and (iii) to identify relevant components through multivariate spatial analysis. The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years. We used six soil properties collected from a squared grid (225 points) (penetrometer resistance (PR), total porosity, fragmentation dimension (Df), vertical electrical conductivity (ECv), horizontal electrical conductivity (ECh) and soil water content (WC)). All the original data sets were z-transformed before geostatistical analysis. Three different types of semivariogram models were necessary for fitting individual experimental semivariograms. This suggests the different natures of spatial variability patterns. Soil water content rendered the largest nugget effect (C0 = 0.933) while soil total porosity showed the largest range of spatial correlation (A = 43.92 m). The bivariate geostatistical analysis also rendered significant cross-semivariance between different paired soil properties. However, four different semivariogram models were required in that case. This indicates an underlying co-regionalization between different soil properties, which is of interest for delineating management zones within sugarcane fields. Cross-semivariograms showed larger correlation ranges than individual, univariate, semivariograms (A ≥ 29 m). All the findings were supported by multivariate spatial analysis, which showed the influence of soil tillage operations, harvesting machinery and irrigation water distribution on the status of the investigated area.

Spatial variability of seed depth placement of maize under no tillage.

Among the various factors that contribute towards producing a successful maize crop, seed depth placement is a key determinant, especially in a no-tillage system. The main objective of this work was to evaluate the spatial variability of seed depth placement and crop establishment in a maize crop under no-tillage conditions, using precision farming technologies. The obtained results indicate that seed depth placement was significantly affected by soil moisture content, while a very high coefficient of variation of 39% was found for seed depth. Seeding depth had a significant impact on mean emergence time and percentage of emerged plants. Shallow average depth values and the high coefficient of variation suggest a need for improvement in controlling the seeder sowing depth.

A partial study of vertical distribution of conventional no-till seeders and spatial variability of seed depth placement of maize in the Alentejo region, Portugal

The requirements for a good stand in a no-till field are the same as those for conventional planting as well as added field and machinery management. Among the various factors that contribute towards producing a successful maize crop, seed depth placement is a key determinant. Although most no-till planters on the market work well under good soil and residue conditions, adjustments and even modifications are frequently needed when working with compacted or wet soils or with heavy residues. The main objective of this study, carried out in 2010, 2011 and 2012, was to evaluate the vertical distribution and spatial variability of seed depth placement in a maize crop under no-till conditions, using precision farming technologies and conventional no-till seeders. The results obtained indicate that the seed depth placement was affected by soil moisture content and forward speed. The seed depth placement was negatively correlated with soil resistance and seeding depth had a significant impact on mean emergence time and the percentage of emerged plants. Shallow average depth values and high coefficients of variation suggest a need for improvements in controlling the seeders’ sowing depth mechanism or more accurate calibration by operators in the field.

Spatial variability of seed depth placement of maize under no tillage in Alentejo, Portugal

Among the various factors that contribute towards producing a successful maize crop, seed depth placement is a key determinant, especially in a no-tillage system. The main objective of this work was to evaluate the spatial variability of seed depth placement and crop establishment in a maize crop under no-tillage conditions, using precision farming technologies. The obtained results indicate that seed depth placement was significantly affected by soil moisture content, while a very high coefficient of variation of 39% was found for seed depth. Seeding depth had a significant impact on mean emergence time and percentage of emerged plants. Shallow average depth values and the high coefficient of variation suggest a need for improvement in controlling the seeders sowing depth.

Contribute to the Study of Vertical Distribution of Conventional No-Till Seeders and Spatial Variability of Seed Depth Placement of Maize in Alentejo, Portugal

Entre os vários fatores que contribuem para a produção de uma cultura de milho, a distribuição vertical dos semeadores avaliada através da localização da semente em profundidade é um fator-chave, especialmente na técnica de sementeira direta. Simultaneamente, dada a complexidade dos ecossistemas naturais e agrícolas em sistemas de agricultura de conservação, a gestão diferenciada e localizada das parcelas assume um importante papel na análise e gestão da variabilidade das propriedades do solo e estabelecimento das culturas, nomeadamente utilizando informação geo referenciada e tecnologia expedita. Assim, o principal objetivo desta Tese foi a avaliação em culturas de milho da variabilidade espacial da localização de semente em profundidade e estabelecimento da cultura em sementeira direta usando sistemas convencionais de controlo de profundidade, tendo-se comparado com diferentes sistemas de mobilização e recorrendo a tecnologias de agricultura de precisão. Os ensaios decorreram na região Mediterrânea do Alentejo, em propriedades agrícolas no decorrer das campanhas de 2010, 2011, 2012 e 2015 em 6 diferentes campos experimentais. O trabalho experimental consistiu em ensaios com avaliações in loco do solo e cultura, consumo de combustível das operações e deteção remota. Os resultados obtidos indicam que não só o sistema de mobilização afetou a localização da semente em profundidade, como em sementeira direta a profundidade de sementeira foi afetada pelo teor de humidade do solo, resistência do solo à profundidade e velocidade da operação de sementeira. Adicionalmente observaram-se condições heterogéneas de emergência e estabelecimento da cultura afetadas por condições físicas de compactação do solo. Comparando os diferentes sistemas de mobilização, obteve-se uma significativa redução de combustível para a técnica de sementeira direta, apesar de se terem observado diferenças estatísticas significativas considerando diferentes calibrações de profundidade de sementeira Do trabalho realizado nesta Tese ressalva-se a importância que as tecnologias de agricultura de precisão podem ter no acompanhamento e avaliação de culturas em sementeira direta, bem como a necessidade de melhores procedimentos no controlo de profundidade dos semeadores pelo respetivos operadores ou ao invés, a adoção de semeadores com mecanismos ativos de controlo de profundidade. ABSTRACT Among the various factors that contribute towards producing a successful maize crop, seeders vertical distribution evaluated through seed depth placement is a key determinant, especially under a no-tillage technique. At the same time in conservation agriculture systems due to the complexity of natural and agricultural ecosystems site specific management became an important approach to understand and manage the variability of soil properties and crop establishment, especially when using geo spatial information and affording readily technology Thus, the main objective of this Thesis was to evaluate the spatial variability of seed depth placement and crop establishment in maize crops under no-tillage conditions compared to different tillage systems, using conventional seed depth control no till seeders and precision farming technologies. Trials were carried out in the Mediterranean region of Alentejo, in private farms along the sowing operations season over the years 2010, 2011, 2012 and 2015 in 6 different experimental fields. Experimental work covered field tests with in loco soil and crop evaluations, fuel operation evaluations and aerial sensing. The results obtained indicate that not only tillage system affected seed depth placement but under no till conditions seed depth was affected by soil moisture content, soil resistance to penetration and seeders forward speed. In addition uneven crop seedling and establishment depended on seed depth placement and could be affected by physical problems of compaction layers. Significant reduction in fuel consumption was observed for no till operations although significant differences observed according to different setting calibrations of seed depth control. According to the results, precision agriculture is an important tool to evaluate crops under no till conditions and seed depth mechanisms should be more accurate by the operators or is determinant the adoption of new active depth control technology to improve seeders performance.

Desarrollo de un modelo de formación del valor inmobiliario en áreas de crecimiento suburbano. Aplicación a la comarca de la Vega Baja del Segura en el litoral alicantino

Una de las principales líneas de investigación de la economía urbana es el comportamiento del mercado inmobiliario y sus relaciones con la estructura territorial. Dentro de este contexto, la reflexión sobre el significado del valor urbano, y abordar su variabilidad, constituye un tema de especial importancia, dada la relevancia que ha supuesto y supone la actividad inmobiliaria en España. El presente estudio ha planteado como principal objetivo la identificación de aquellos factores, ligados a la localización que explican la formación del valor inmobiliario y justifican su variabilidad. Definir este proceso precisa de una evaluación a escala territorial estableciendo aquellos factores de carácter socioeconómico, medioambiental y urbanístico que estructuran el desarrollo urbano, condicionan la demanda de inmuebles y, por tanto, los procesos de formación de su valor. El análisis se centra en valores inmobiliarios residenciales localizados en áreas litorales donde la presión del sector turístico ha impulsado un amplio. Para ello, el ámbito territorial seleccionado como objeto de estudio se sitúa en la costa mediterránea española, al sur de la provincia de Alicante, la comarca de la Vega Baja del Segura. La zona, con una amplia diversidad ecológica y paisajística, ha mantenido históricamente una clara distinción entre espacio urbano y espacio rural. Esta dicotomía ha cambiado drásticamente en las últimas décadas, experimentándose un fuerte crecimiento demográfico y económico ligado a los sectores turístico e inmobiliario, aspectos que han tenido un claro reflejo en los valores inmobiliarios. Este desarrollo de la comarca es un claro ejemplo de la política expansionista de los mercados de suelo que ha tenido lugar en la costa española en las dos últimas décadas y que derivado en la regeneración de un amplio tejido suburbano. El conocimiento del marco territorial ha posibilitado realizar un análisis de variabilidad espacial mediante un tratamiento masivo de datos, así como un análisis econométrico que determina los factores que se valoran positivamente y negativamente por el potencial comprador. Estas relaciones permiten establecer diferentes estructuras matemáticas basadas en los modelos de precios hedónicos, que permiten identificar rasgos diferenciales en los ámbitos económico, social y espacial y su incidencia en el valor inmobiliario. También se ha sistematizado un proceso de valoración territorial a través del análisis del concepto de vulnerabilidad estructural, entendido como una situación de fragilidad debida a circunstancias tanto sociales como económicas, tanto actual como de tendencia en el futuro. Actualmente, esta estructura de demanda de segunda residencia y servicios ha mostrado su fragilidad y ha bloqueado el desarrollo económico de la zona al caer drásticamente la inversión en el sector inmobiliario por la crisis global de la deuda. El proceso se ha agravado al existir un tejido industrial marginal al que no se ha derivado inversiones importantes y un abandono progresivo de las explotaciones agropecuarias. El modelo turístico no sería en sí mismo la causa del bloqueo del desarrollo económico comarcal, sino la forma en que se ha implantado en la Costa Blanca, con un consumo del territorio basado en el corto plazo, poco respetuoso con aspectos paisajísticos y medioambientales, y sin una organización territorial global. Se observa cómo la vinculación entre índices de vulnerabilidad y valor inmobiliario no es especialmente significativa, lo que denota que las tendencias futuras de fragilidad no han sido incorporadas a la hora de establecer los precios de venta del producto inmobiliario analizado. El valor muestra una clara dependencia del sistema de asentamiento y conservación de las áreas medioambientales y un claro reconocimiento de tipologías propias del medio rural aunque vinculadas al sector turístico. En la actualidad, el continuo descenso de la demanda turística ha provocado una clara modificación en la estructura poblacional y económica. Al incorporar estas modificaciones a los modelos especificados podemos comprobar un verdadero desmoronamiento de los valores. Es posible que el remanente de vivienda construida actualmente vaya dirigido a un potencial comprador que se encuentra en retroceso y que se vincula a unos rasgos territoriales ya no existentes. Encontrar soluciones adaptables a la oferta existente, implica la viabilidad de renovación del sistema poblacional o modificaciones a nivel económico. La búsqueda de respuestas a estas cuestiones señala la necesidad de recanalizar el desarrollo, sin obviar la potencialidad del ámbito. SUMMARY One of the main lines of research regarding the urban economy focuses on the behavior of the real estate market and its relationship to territorial structure. Within this context, one of the most important themes involves considering the significance of urban property value and dealing with its variability, particularly given the significant role of the real estate market in Spain, both in the past and present. The main objective of this study is to identify those factors linked to location, which explain the formation of property values and justify their variability. Defining this process requires carrying out an evaluation on a territorial scale, establishing the socioeconomic, environmental and urban planning factors that constitute urban development and influence the demand for housing, thereby defining the processes by which their value is established. The analysis targets residential real estate values in coastal areas where pressure from the tourism industry has prompted large-scale transformations. Therefore, the focal point of this study is an area known as Vega Baja del Segura, which is located on the Spanish Mediterranean coast in southern Alicante (province). Characterized by its scenic and ecological diversity, this area has historically maintained a clear distinction between urban and rural spaces. This dichotomy has drastically changed in past decades due to the large increase in population attributed to the tourism and real estate markets – factors which have had a direct effect on property values. The development of this area provides a clear example of the expansionary policies which have affected the housing market on the coast of Spain during the past two decades, resulting in a large increase in suburban development. Understanding the territorial framework has made it possible to carry out a spatial variability analysis through massive data processing, as well as an econometric analysis that determines the factors that are evaluated positively and negatively by potential buyers. These relationships enable us to establish different mathematical systems based on hedonic pricing models that facilitate the identification of differential features in the economic, social and spatial spheres, and their impact on property values. Additionally, a process for land valuation was established through an analysis of the concept of structural vulnerability, which is understood to be a fragile situation resulting from either social or economic circumstances. Currently, this demand structure for second homes and services has demonstrated its fragility and has inhibited the area’s economic development as a result of the drastic fall in investment in the real estate market, due to the global debt crisis. This process has been worsened by the existence of a marginal industrial base into which no important investments have been channeled, combined with the progressive abandonment of agricultural and fishing operations. In and of itself, the tourism model did not inhibit the area’s economic development, rather it is the result of the manner in which it was implemented on the Costa Brava, with a land consumption based on the short-term, lacking respect for landscape and environmental aspects and without a comprehensive organization of the territory. It is clear that the link between vulnerability indexes and property values is not particularly significant, thereby indicating that future fragility trends have not been incorporated into the problem in terms of establishing the sale prices of the analyzed real estate product in question. Urban property values are clearly dependent on the system of development and environmental conservation, as well as on a clear recognition of the typologies that characterize rural areas, even those linked to the tourism industry. Today, the continued drop in tourism demand has provoked an obvious modification in the populational and economic structures. By incorporating these changes into the specified models, we can confirm a real collapse in values. It’s possible that the surplus of already-built homes is currently being marketed to a potential buyer who is in recession and linked to certain territorial characteristics that no longer exist. Finding solutions that can be adapted to the existing offer implies the viability of renewing the population system or carrying out modifications on an economic level. The search for answers to these questions suggests the need to reform the development model, without leaving out an area’s potentiality.

Soil fragmentation study applying different tillage systems

Runoff generation depends on rainfall, infiltration, interception, and surface depressional storage. Surface depressional storage depends on surface microtopography, usually quantified trough soil surface roughness (SSR). SSR is subject to spatial and temporal changes that create a high variability. In an agricultural environment, tillage operations produce abrupt changes in roughness. Subsequent rainfall gradually decreases roughness. Beside it, local variation in soil properties and hydrology cause its SSR to vary spatially at different scales. The methods commonly used to measure it involve collecting point elevations in regular grids using laser profilers or scanners, digital close range stereo-photogrammetry and terrestrial laser scanning or LIDAR systems. In this case, a laser-scanning instrument was used to obtain representative digital elevation models (DEMs) at a grid resolution of 7.2x7.2mm that cover an area of 0.9x0.9m. The DEMs were obtained from two study sites with different soils. The first study site was an experimental field on which five conventional tillage methods were applied. The second study site was a large olive orchard with trees planted at 7.5x5.0m and bare soils between rows. Here, three tillage treatments were applied. In this work we have evaluated the spatial variability of SSR at several scales studying differences in height calculated from points separated by incremental distances h were raised to power values q (from 0 to 4 in steps of 0.1). The q = 2 data were studied as a semivariogram model. The logarithm of average differences plotted vs. log h were characterized by their slope, ?(q). Structure functions [?(q) vs. q] were fitted showing that data had nonlinear structure functions typical of multiscale phenomena. Comparisson of the two types of soil in their respective structure functions are shown.

Aplicaciones de interés forestal de las imágenes obtenidas con el sensor Multi-angle Imaging SpectroRadiometer (MISR)

Las aplicaciones de la teledetección al seguimiento de lo que ocurre en la superficie terrestre se han ido multiplicando y afinando con el lanzamiento de nuevos sensores por parte de las diferentes agencias espaciales. La necesidad de tener información actualizada cada poco tiempo y espacialmente homogénea, ha provocado el desarrollo de nuevos programas como el Earth Observing System (EOS) de la National Aeronautics and Space Administration (NASA). Uno de los sensores que incorpora el buque insignia de ese programa, el satélite TERRA, es el Multi-angle Imaging SpectroRadiometer (MISR), diseñado para capturar información multiangular de la superficie terrestre. Ya desde los años 1970, se conocía que la reflectancia de las diversas ocupaciones y usos del suelo variaba en función del ángulo de observación y de iluminación, es decir, que eran anisotrópicas. Tal variación estaba además relacionada con la estructura tridimensional de tales ocupaciones, por lo que se podía aprovechar tal relación para obtener información de esa estructura, más allá de la que pudiera proporcionar la información meramente espectral. El sensor MISR incorpora 9 cámaras a diferentes ángulos para capturar 9 imágenes casi simultáneas del mismo punto, lo que permite estimar con relativa fiabilidad la respuesta anisotrópica de la superficie terrestre. Varios trabajos han demostrado que se pueden estimar variables relacionadas con la estructura de la vegetación con la información que proporciona MISR. En esta Tesis se ha realizado una primera aplicación a la Península Ibérica, para comprobar su utilidad a la hora de estimar variables de interés forestal. En un primer paso se ha analizado la variabilidad temporal que se produce en los datos, debido a los cambios en la geometría de captación, es decir, debido a la posición relativa de sensores y fuente de iluminación, que en este caso es el Sol. Se ha comprobado cómo la anisotropía es mayor desde finales de otoño hasta principios de primavera debido a que la posición del Sol es más cercana al plano de los sensores. También se ha comprobado que los valores máximo y mínimo se van desplazando temporalmente entre el centro y el extremo angular. En la caracterización multiangular de ocupaciones del suelo de CORINE Land Cover que se ha realizado, se puede observar cómo la forma predominante en las imágenes con el Sol más alto es convexa con un máximo en la cámara más cercana a la fuente de iluminación. Sin embargo, cuando el Sol se encuentra mucho más bajo, ese máximo es muy externo. Por otra parte, los datos obtenidos en verano son mucho más variables para cada ocupación que los de noviembre, posiblemente debido al aumento proporcional de las zonas en sombra. Para comprobar si la información multiangular tiene algún efecto en la obtención de imágenes clasificadas según ocupación y usos del suelo, se han realizado una serie de clasificaciones variando la información utilizada, desde sólo multiespectral, a multiangular y multiespectral. Los resultados muestran que, mientras para las clasificaciones más genéricas la información multiangular proporciona los peores resultados, a medida que se amplían el número de clases a obtener tal información mejora a lo obtenido únicamente con información multiespectral. Por otra parte, se ha realizado una estimación de variables cuantitativas como la fracción de cabida cubierta (Fcc) y la altura de la vegetación a partir de información proporcionada por MISR a diferentes resoluciones. En el valle de Alcudia (Ciudad Real) se ha estimado la fracción de cabida cubierta del arbolado para un píxel de 275 m utilizando redes neuronales. Los resultados muestran que utilizar información multiespectral y multiangular puede mejorar casi un 20% las estimaciones realizadas sólo con datos multiespectrales. Además, las relaciones obtenidas llegan al 0,7 de R con errores inferiores a un 10% en Fcc, siendo éstos mucho mejores que los obtenidos con el producto elaborado a partir de datos multiespectrales del sensor Moderate Resolution Imaging Spectroradiometer (MODIS), también a bordo de Terra, para la misma variable. Por último, se ha estimado la fracción de cabida cubierta y la altura efectiva de la vegetación para 700.000 ha de la provincia de Murcia, con una resolución de 1.100 m. Los resultados muestran la relación existente entre los datos espectrales y los multiangulares, obteniéndose coeficientes de Spearman del orden de 0,8 en el caso de la fracción de cabida cubierta de la vegetación, y de 0,4 en el caso de la altura efectiva. Las estimaciones de ambas variables con redes neuronales y diversas combinaciones de datos, arrojan resultados con R superiores a 0,85 para el caso del grado de cubierta vegetal, y 0,6 para la altura efectiva. Los parámetros multiangulares proporcionados en los productos elaborados con MISR a 1.100 m, no obtienen buenos resultados por sí mismos pero producen cierta mejora al incorporarlos a la información espectral. Los errores cuadráticos medios obtenidos son inferiores a 0,016 para la Fcc de la vegetación en tanto por uno, y 0,7 m para la altura efectiva de la misma. Regresiones geográficamente ponderadas muestran además que localmente se pueden obtener mejores resultados aún mejores, especialmente cuando hay una mayor variabilidad espacial de las variables estimadas. En resumen, la utilización de los datos proporcionados por MISR ofrece una prometedora vía de mejora de resultados en la media-baja resolución, tanto para la clasificación de imágenes como para la obtención de variables cuantitativas de la estructura de la vegetación. ABSTRACT Applications of remote sensing for monitoring what is happening on the land surface have been multiplied and refined with the launch of new sensors by different Space Agencies. The need of having up to date and spatially homogeneous data, has led to the development of new programs such as the Earth Observing System (EOS) of the National Aeronautics and Space Administration (NASA). One of the sensors incorporating the flagship of that program, the TERRA satellite, is Multi-angle Imaging Spectroradiometer (MISR), designed to capture the multi-angle information of the Earth's surface. Since the 1970s, it was known that the reflectance of various land covers and land uses varied depending on the viewing and ilumination angles, so they are anisotropic. Such variation was also related to the three dimensional structure of such covers, so that one could take advantage of such a relationship to obtain information from that structure, beyond which spectral information could provide. The MISR sensor incorporates 9 cameras at different angles to capture 9 almost simultaneous images of the same point, allowing relatively reliable estimates of the anisotropic response of the Earth's surface. Several studies have shown that we can estimate variables related to the vegetation structure with the information provided by this sensor, so this thesis has made an initial application to the Iberian Peninsula, to check their usefulness in estimating forest variables of interest. In a first step we analyzed the temporal variability that occurs in the data, due to the changes in the acquisition geometry, i.e. the relative position of sensor and light source, which in this case is the Sun. It has been found that the anisotropy is greater from late fall through early spring due to the Sun's position closer to the plane of the sensors. It was also found that the maximum and minimum values are displaced temporarily between the center and the ends. In characterizing CORINE Land Covers that has been done, one could see how the predominant form in the images with the highest sun is convex with a maximum in the camera closer to the light source. However, when the sun is much lower, the maximum is external. Moreover, the data obtained for each land cover are much more variable in summer that in November, possibly due to the proportional increase in shadow areas. To check whether the information has any effect on multi-angle imaging classification of land cover and land use, a series of classifications have been produced changing the data used, from only multispectrally, to multi-angle and multispectral. The results show that while for the most generic classifications multi-angle information is the worst, as there are extended the number of classes to obtain such information it improves the results. On the other hand, an estimate was made of quantitative variables such as canopy cover and vegetation height using information provided by MISR at different resolutions. In the valley of Alcudia (Ciudad Real), we estimated the canopy cover of trees for a pixel of 275 m by using neural networks. The results showed that using multispectral and multiangle information can improve by almost 20% the estimates that only used multispectral data. Furthermore, the relationships obtained reached an R coefficient of 0.7 with errors below 10% in canopy cover, which is much better result than the one obtained using data from the Moderate Resolution Imaging Spectroradiometer (MODIS), also onboard Terra, for the same variable. Finally we estimated the canopy cover and the effective height of the vegetation for 700,000 hectares in the province of Murcia, with a spatial resolution of 1,100 m. The results show a relationship between the spectral and the multi-angle data, and provide estimates of the canopy cover with a Spearman’s coefficient of 0.8 in the case of the vegetation canopy cover, and 0.4 in the case of the effective height. The estimates of both variables using neural networks and various combinations of data, yield results with an R coefficient greater than 0.85 for the case of the canopy cover, and 0.6 for the effective height. Multi-angle parameters provided in the products made from MISR at 1,100 m pixel size, did not produce good results from themselves but improved the results when included to the spectral information. The mean square errors were less than 0.016 for the canopy cover, and 0.7 m for the effective height. Geographically weighted regressions also showed that locally we can have even better results, especially when there is high spatial variability of estimated variables. In summary, the use of the data provided by MISR offers a promising way of improving remote sensing performance in the low-medium spatial resolution, both for image classification and for the estimation of quantitative variables of the vegetation structure.

The use of direct boundary element method for gaining insight into complex seismic site response

The boundary element method is specially well suited for the analysis of the seismic response of valleys of complicated topography and stratigraphy. In this paper the method’s capabilities are illustrated using as an example an irregularity stratified (test site) sedimentary basin that has been modelled using 2D discretization and the Direct Boundary Element Method (DBEM). Site models displaying different levels of complexity are used in practice. The multi-layered model’s seismic response shows generally good agreement with observed data amplification levels, fundamental frequencies and the high spatial variability. Still important features such as the location of high frequencies peaks are missing. Even 2D simplified models reveal important characteristics of the wave field that 1D modelling does not show up.

Effects of different soil management practices on soil mechanic resistance and seed depth placement in a maize crop in Alentejo, Portugal Mediterranean region.

No tillage, minimum tillage and conventional tillage practices are commonly used in maize crops in Alentejo, affecting soil physic conditions and determining seeders performance. Seeders distribution can be evaluated in the longitudinal and vertical planes. Vertical plane is specified by seeding depth (Karayel et al., 2008). If, in one hand seeding depth uniformity is a goal for all crop establishment , in the other hand, seeders furrow openers depth control is never constant depending on soil conditions. Seed depth uniformity affects crop emergence, Liu et al. (2004) showed an higher correlation between crop productivity and emergence uniformity than with longitudinal plants distribution. Neto et al. (2007) evaluating seed depth placement by measuring maize mesocotyl length under no tillage conditions in 38 farms concluded that 20% of coefficient of variation suggests the need of improvement seeders depth control mechanisms. The objective of this study was to evaluate casual relationships and create spatial variability maps between soil mechanic resistance and vertical distribution under three different soil practices to improve seed depth uniformity.

Modelling of Topographic Irregularities for Seismic Site Response

Seismic evaluation methodology is applied to an existing viaduct in the south of Spain, near Granada, which is a medium seismicity region. The influence of both geology and topography in the spatial variability of ground motion are studied as well as seismic hazard analysis and ground motion characterization. Artificial hazard-consistent ground motion records are synthesised applying seismic hazard analysis and site effects are estimated through a diffraction study. Direct BEM is used to calculate the valley displacement response to vertically propagating SV waves and transfer functions are generated allowing the transformation of free field motion to motion at each support. A closed formulae is used to estimate these transfer function. Finally, the results obtained are compared.

Heterogeneity of atmosfpheric ammonia at the landscape scale and consequences for environmental impact assessment.

We examined the consequences of the spatial heterogeneity of atmospheric ammonia (NH3) by measuring and modelling NH3 concentrations and deposition at 25 m grid resolution for a rural landscape containing intensive poultry farming, agricultural grassland, woodland and moorland. The emission pattern gave rise to a high spatial variability of modelled mean annual NH3 concentrations and dry deposition. Largest impacts were predicted for woodland patches located within the agricultural area, while larger moorland areas were at low risk, due to atmospheric dispersion, prevailing wind direction and low NH3 background. These high resolution spatial details are lost in national scale estimates at 1 km resolution due to less detailed emission input maps. The results demonstrate how the spatial arrangement of sources and sinks is critical to defining the NH3 risk to semi-natural ecosystems. These spatial relationships provide the foundation for local spatial planning approaches to reduce environmental impacts of atmospheric NH3.

La estabilidad del frente de excavación de un túnel en terrenos heterogéneos o con un criterio de rotura no-lineal

El frente de un túnel puede colapsar si la presión aplicada sobre el es inferior a un valor limite denominado presión “critica” o “de colapso”. En este trabajo se desarrolla y presenta un mecanismo de rotura rotacional generado punto a punto para el cálculo de la presión de colapso del frente de túneles excavados en terrenos estratificados o en materiales que siguen un criterio de rotura nolineal. La solución propuesta es una solución de contorno superior en el marco del Análisis Límite y supone una generalización del mecanismo de rotura mas reciente existente en la bibliografía. La presencia de un terreno estratificado o con un criterio de rotura no-lineal implica una variabilidad espacial de las propiedades resistentes. Debido a esto, se generaliza el mecanismo desarrollado por Mollon et al. (2011b) para suelos, de tal forma que se puedan considerar valores locales del ángulo de rozamiento y de la cohesión. Además, la estratificación del terreno permite una rotura parcial del frente, por lo que se implementa esta posibilidad en el mecanismo, siendo la primera solución que emplea un mecanismo de rotura que se ajusta a la estratigrafía del terreno. Por otro lado, la presencia de un material con un criterio de rotura no-lineal exige introducir en el modelo, como variable de estudio, el estado tensional en el frente, el cual se somete al mismo proceso de optimización que las variables geométricas del mecanismo. Se emplea un modelo numérico 3D para validar las predicciones del mecanismo de Análisis Limite, demostrando que proporciona, con un esfuerzo computacional significativamente reducido, buenas predicciones de la presión critica, del tipo de rotura (global o parcial) en terrenos estratificados y de la geometría de fallo. El mecanismo validado se utiliza para realizar diferentes estudios paramétricos sobre la influencia de la estratigrafía en la presión de colapso. Igualmente, se emplea para elaborar cuadros de diseño de la presión de colapso para túneles ejecutados con tuneladora en macizos rocosos de mala calidad y para analizar la influencia en la estabilidad del frente del método constructivo. Asimismo, se lleva a cabo un estudio de fiabilidad de la estabilidad del frente de un túnel excavado en un macizo rocoso altamente fracturado. A partir de el se analiza como afectan las diferentes hipótesis acerca de los tipos de distribución y de las estructuras de correlación a los resultados de fiabilidad. Se investiga también la sensibilidad de los índices de fiabilidad a los cambios en las variables aleatorias, identificando las mas relevantes para el diseño. Por ultimo, se lleva a cabo un estudio experimental mediante un modelo de laboratorio a escala reducida. El modelo representa medio túnel, lo cual permite registrar el movimiento del material mediante una técnica de correlación de imágenes fotográficas. El ensayo se realiza con una arena seca y se controla por deformaciones mediante un pistón que simula el frente. Los resultados obtenidos se comparan con las estimaciones de la solución de Análisis Límite, obteniéndose un ajuste razonable, de acuerdo a la literatura, tanto en la geometría de rotura como en la presión de colapso. A tunnel face may collapse if the applied support pressure is lower than a limit value called the ‘critical’ or ‘collapse’ pressure. In this work, an advanced rotational failure mechanism generated ‘‘point-by-point” is developed to compute the collapse pressure for tunnel faces in layered (or stratified) grounds or in materials that follow a non-linear failure criterion. The proposed solution is an upper bound solution in the framework of limit analysis which extends the most advanced face failure mechanism in the literature. The excavation of the tunnel in a layered ground or in materials with a non-linear failure criterion may lead to a spatial variability of the strength properties. Because of this, the rotational mechanism recently proposed by Mollon et al. (2011b) for Mohr-Coulomb soils is generalized so that it can consider local values of the friction angle and of the cohesion. For layered soils, the mechanism needs to be extended to consider the possibility for partial collapse. The proposed methodology is the first solution with a partial collapse mechanism that can fit to the stratification. Similarly, the use of a nonlinear failure criterion introduces the need to introduce new parameters in the optimization problem to consider the distribution of normal stresses along the failure surface. A 3D numerical model is employed to validate the predictions of the limit analysis mechanism, demonstrating that it provides, with a significantly reduced computational effort, good predictions of critical pressure, of the type of collapse (global or partial) in layered soils, and of its geometry. The mechanism is then employed to conduct parametric studies of the influence of several geometrical and mechanical parameters on face stability of tunnels in layered soils. Similarly, the methodology has been further employed to develop simple design charts that provide the face collapse pressure of tunnels driven by TBM in low quality rock masses and to study the influence of the construction method. Finally, a reliability analysis of the stability of a tunnel face driven in a highly fractured rock mass is performed. The objective is to analyze how different assumptions about distributions types and correlation structures affect the reliability results. In addition, the sensitivity of the reliability index to changes in the random variables is studied, identifying the most relevant variables for engineering design. Finally, an experimental study is carried out using a small-scale laboratory model. The problem is modeled in half, cutting through the tunnel axis vertically, so that displacements of soil particles can be recorded by a digital image correlation technique. The tests were performed with dry sand and displacements are controlled by a piston that supports the soil. The results of the model are compared with the predictions of the Limit Analysis mechanism. A reasonable agreement, according to literature, is obtained between the shapes of the failure surfaces and between the collapse pressures observed in the model tests and computed with the analytical solution.

Generalización de variables medioambientales mediante interpolación GIS

La investigación de esta tesis se centra en el estudio de técnicas geoestadísticas y su contribución a una mayor caracterización del binomio factores climáticos-rendimiento de un cultivo agrícola. El inexorable vínculo entre la variabilidad climática y la producción agrícola cobra especial relevancia en estudios sobre el cambio climático o en la modelización de cultivos para dar respuesta a escenarios futuros de producción mundial. Es información especialmente valiosa en sistemas operacionales de monitoreo y predicción de rendimientos de cultivos Los cuales son actualmente uno de los pilares operacionales en los que se sustenta la agricultura y seguridad alimentaria mundial; ya que su objetivo final es el de proporcionar información imparcial y fiable para la regularización de mercados. Es en este contexto, donde se quiso dar un enfoque alternativo a estudios, que con distintos planteamientos, analizan la relación inter-anual clima vs producción. Así, se sustituyó la dimensión tiempo por la espacio, re-orientando el análisis estadístico de correlación interanual entre rendimiento y factores climáticos, por el estudio de la correlación inter-regional entre ambas variables. Se utilizó para ello una técnica estadística relativamente nueva y no muy aplicada en investigaciones similares, llamada regresión ponderada geográficamente (GWR, siglas en inglés de “Geographically weighted regression”). Se obtuvieron superficies continuas de las variables climáticas acumuladas en determinados periodos fenológicos, que fueron seleccionados por ser factores clave en el desarrollo vegetativo de un cultivo. Por ello, la primera parte de la tesis, consistió en un análisis exploratorio sobre comparación de Métodos de Interpolación Espacial (MIE). Partiendo de la hipótesis de que existe la variabilidad espacial de la relación entre factores climáticos y rendimiento, el objetivo principal de esta tesis, fue el de establecer en qué medida los MIE y otros métodos geoestadísticos de regresión local, pueden ayudar por un lado, a alcanzar un mayor entendimiento del binomio clima-rendimiento del trigo blando (Triticum aestivum L.) al incorporar en dicha relación el componente espacial; y por otro, a caracterizar la variación de los principales factores climáticos limitantes en el crecimiento del trigo blando, acumulados éstos en cuatro periodos fenológicos. Para lleva a cabo esto, una gran carga operacional en la investigación de la tesis consistió en homogeneizar y hacer los datos fenológicos, climáticos y estadísticas agrícolas comparables tanto a escala espacial como a escala temporal. Para España y los Bálticos se recolectaron y calcularon datos diarios de precipitación, temperatura máxima y mínima, evapotranspiración y radiación solar en las estaciones meteorológicas disponibles. Se dispuso de una serie temporal que coincidía con los mismos años recolectados en las estadísticas agrícolas, es decir, 14 años contados desde 2000 a 2013 (hasta 2011 en los Bálticos). Se superpuso la malla de información fenológica de cuadrícula 25 km con la ubicación de las estaciones meteorológicas con el fin de conocer los valores fenológicos en cada una de las estaciones disponibles. Hecho esto, para cada año de la serie temporal disponible se calcularon los valores climáticos diarios acumulados en cada uno de los cuatro periodos fenológicos seleccionados P1 (ciclo completo), P2 (emergencia-madurez), P3 (floración) y P4 (floraciónmadurez). Se calculó la superficie interpolada por el conjunto de métodos seleccionados en la comparación: técnicas deterministas convencionales, kriging ordinario y cokriging ordinario ponderado por la altitud. Seleccionados los métodos más eficaces, se calculó a nivel de provincias las variables climatológicas interpoladas. Y se realizaron las regresiones locales GWR para cuantificar, explorar y modelar las relaciones espaciales entre el rendimiento del trigo y las variables climáticas acumuladas en los cuatro periodos fenológicos. Al comparar la eficiencia de los MIE no destaca una técnica por encima del resto como la que proporcione el menor error en su predicción. Ahora bien, considerando los tres indicadores de calidad de los MIE estudiados se han identificado los métodos más efectivos. En el caso de la precipitación, es la técnica geoestadística cokriging la más idónea en la mayoría de los casos. De manera unánime, la interpolación determinista en función radial (spline regularizado) fue la técnica que mejor describía la superficie de precipitación acumulada en los cuatro periodos fenológicos. Los resultados son más heterogéneos para la evapotranspiración y radiación. Los métodos idóneos para estas se reparten entre el Inverse Distance Weighting (IDW), IDW ponderado por la altitud y el Ordinary Kriging (OK). También, se identificó que para la mayoría de los casos en que el error del Ordinary CoKriging (COK) era mayor que el del OK su eficacia es comparable a la del OK en términos de error y el requerimiento computacional de este último es mucho menor. Se pudo confirmar que existe la variabilidad espacial inter-regional entre factores climáticos y el rendimiento del trigo blando tanto en España como en los Bálticos. La herramienta estadística GWR fue capaz de reproducir esta variabilidad con un rendimiento lo suficientemente significativo como para considerarla una herramienta válida en futuros estudios. No obstante, se identificaron ciertas limitaciones en la misma respecto a la información que devuelve el programa a nivel local y que no permite desgranar todo el detalle sobre la ejecución del mismo. Los indicadores y periodos fenológicos que mejor pudieron reproducir la variabilidad espacial del rendimiento en España y Bálticos, arrojaron aún, una mayor credibilidad a los resultados obtenidos y a la eficacia del GWR, ya que estaban en línea con el conocimiento agronómico sobre el cultivo del trigo blando en sistemas agrícolas mediterráneos y norteuropeos. Así, en España, el indicador más robusto fue el balance climático hídrico Climatic Water Balance) acumulado éste, durante el periodo de crecimiento (entre la emergencia y madurez). Aunque se identificó la etapa clave de la floración como el periodo en el que las variables climáticas acumuladas proporcionaban un mayor poder explicativo del modelo GWR. Sin embargo, en los Bálticos, países donde el principal factor limitante en su agricultura es el bajo número de días de crecimiento efectivo, el indicador más efectivo fue la radiación acumulada a lo largo de todo el ciclo de crecimiento (entre la emergencia y madurez). Para el trigo en regadío no existe ninguna combinación que pueda explicar más allá del 30% de la variación del rendimiento en España. Poder demostrar que existe un comportamiento heterogéneo en la relación inter-regional entre el rendimiento y principales variables climáticas, podría contribuir a uno de los mayores desafíos a los que se enfrentan, a día de hoy, los sistemas operacionales de monitoreo y predicción de rendimientos de cultivos, y éste es el de poder reducir la escala espacial de predicción, de un nivel nacional a otro regional. ABSTRACT This thesis explores geostatistical techniques and their contribution to a better characterization of the relationship between climate factors and agricultural crop yields. The crucial link between climate variability and crop production plays a key role in climate change research as well as in crops modelling towards the future global production scenarios. This information is particularly important for monitoring and forecasting operational crop systems. These geostatistical techniques are currently one of the most fundamental operational systems on which global agriculture and food security rely on; with the final aim of providing neutral and reliable information for food market controls, thus avoiding financial speculation of nourishments of primary necessity. Within this context the present thesis aims to provide an alternative approach to the existing body of research examining the relationship between inter-annual climate and production. Therefore, the temporal dimension was replaced for the spatial dimension, re-orienting the statistical analysis of the inter-annual relationship between crops yields and climate factors to an inter-regional correlation between these two variables. Geographically weighted regression, which is a relatively new statistical technique and which has rarely been used in previous research on this topic was used in the current study. Continuous surface values of the climate accumulated variables in specific phenological periods were obtained. These specific periods were selected because they are key factors in the development of vegetative crop. Therefore, the first part of this thesis presents an exploratory analysis regarding the comparability of spatial interpolation methods (SIM) among diverse SIMs and alternative geostatistical methodologies. Given the premise that spatial variability of the relationship between climate factors and crop production exists, the primary aim of this thesis was to examine the extent to which the SIM and other geostatistical methods of local regression (which are integrated tools of the GIS software) are useful in relating crop production and climate variables. The usefulness of these methods was examined in two ways; on one hand the way this information could help to achieve higher production of the white wheat binomial (Triticum aestivum L.) by incorporating the spatial component in the examination of the above-mentioned relationship. On the other hand, the way it helps with the characterization of the key limiting climate factors of soft wheat growth which were analysed in four phenological periods. To achieve this aim, an important operational workload of this thesis consisted in the homogenization and obtention of comparable phenological and climate data, as well as agricultural statistics, which made heavy operational demands. For Spain and the Baltic countries, data on precipitation, maximum and minimum temperature, evapotranspiration and solar radiation from the available meteorological stations were gathered and calculated. A temporal serial approach was taken. These temporal series aligned with the years that agriculture statistics had previously gathered, these being 14 years from 2000 to 2013 (until 2011 for the Baltic countries). This temporal series was mapped with a phenological 25 km grid that had the location of the meteorological stations with the objective of obtaining the phenological values in each of the available stations. Following this procedure, the daily accumulated climate values for each of the four selected phenological periods were calculated; namely P1 (complete cycle), P2 (emergency-maturity), P3 (flowering) and P4 (flowering- maturity). The interpolated surface was then calculated using the set of selected methodologies for the comparison: deterministic conventional techniques, ordinary kriging and ordinary cokriging weighted by height. Once the most effective methods had been selected, the level of the interpolated climate variables was calculated. Local GWR regressions were calculated to quantify, examine and model the spatial relationships between soft wheat production and the accumulated variables in each of the four selected phenological periods. Results from the comparison among the SIMs revealed that no particular technique seems more favourable in terms of accuracy of prediction. However, when the three quality indicators of the compared SIMs are considered, some methodologies appeared to be more efficient than others. Regarding precipitation results, cokriging was the most accurate geostatistical technique for the majority of the cases. Deterministic interpolation in its radial function (controlled spline) was the most accurate technique for describing the accumulated precipitation surface in all phenological periods. However, results are more heterogeneous for the evapotranspiration and radiation methodologies. The most appropriate technique for these forecasts are the Inverse Distance Weighting (IDW), weighted IDW by height and the Ordinary Kriging (OK). Furthermore, it was found that for the majority of the cases where the Ordinary CoKriging (COK) error was larger than that of the OK, its efficacy was comparable to that of the OK in terms of error while the computational demands of the latter was much lower. The existing spatial inter-regional variability between climate factors and soft wheat production was confirmed for both Spain and the Baltic countries. The GWR statistic tool reproduced this variability with an outcome significative enough as to be considered a valid tool for future studies. Nevertheless, this tool also had some limitations with regards to the information delivered by the programme because it did not allow for a detailed break-down of its procedure. The indicators and phenological periods that best reproduced the spatial variability of yields in Spain and the Baltic countries made the results and the efficiency of the GWR statistical tool even more reliable, despite the fact that these were already aligned with the agricultural knowledge about soft wheat crop under mediterranean and northeuropean agricultural systems. Thus, for Spain, the most robust indicator was the Climatic Water Balance outcome accumulated throughout the growing period (between emergency and maturity). Although the flowering period was the phase that best explained the accumulated climate variables in the GWR model. For the Baltic countries where the main limiting agricultural factor is the number of days of effective growth, the most effective indicator was the accumulated radiation throughout the entire growing cycle (between emergency and maturity). For the irrigated soft wheat there was no combination capable of explaining above the 30% of variation of the production in Spain. The fact that the pattern of the inter-regional relationship between the crop production and key climate variables is heterogeneous within a country could contribute to one is one of the greatest challenges that the monitoring and forecasting operational systems for crop production face nowadays. The present findings suggest that the solution may lay in downscaling the spatial target scale from a national to a regional level.

Spatial and temporal precipitation patterns of the Ebro River Basin, Spain

The Ebro River Basin, with around 85 000 km2 and located in NE Spain, is characterized by the high spatial heterogeneity of its geology, topography, climatology and land use. Rainfall is one of the most important climatic variables studied owing to its non-homogenous behaviour in event and intensity, which creates drought, water runoff and soil erosion with negative environmental and social consequences. In this work we characterized the rainfall variability pattern in the Ebro River Basin using universal multifractal (UM) analysis, which estimates the concentration of the data around the precipitation average (C1, codimension average), the degree of multiscaling behaviour in time (? index) and the maximum probable singularity in the rainfall distribution ( s). A spatial and temporal analysis of the UM parameters is applied to study the possible changes. With this porpoise, 60 daily rainfall series were selected from 132 synthetic series generated by Luna and Balairón (AEMet). These daily rainfall series present a length of 60 years, from 1950 to 2009. Each one of them was subdivided (1950?1970 and 1980?2009) to analyse the difference between the two periods. The range of variation of precipitation amounts and the frequency of dry events between both periods are discussed, as well as the evolution of the UM parameters through the years.