RESUMEN La presencia de uranio en los reservorios carbonatados de petróleo se ha relacionado con zonas de buena permeabilidad, por la existencia de fracturas abiertas por donde han circulado aguas ricas en sales de uranio. Por otra parte, el uranio se relaciona con la materia orgánica en ambientes reductores. Este trabajo se propone arrojar luz sobre la naturaleza del uranio en los reservorios carbonatados que aparecen en las formaciones gasopetrolíferas cubanas. Para ello se seleccionaron, de la Provincia Gasopetrolífera Norte Cubana, pozos contentivos de estos reservorios que poseyeran registros geofísicos de pozo con imágenes eléctricas de pared de pozo, radiactividad natural de muestras medidas en cámara de bajo fondo y contenido de carbono orgánico total por interpretación de registros de pozo. Se evidenció que la presencia de uranio no puede considerarse un índice directo de permeabilidad al aparecer este asociado lo mismo a fracturas abiertas que cerradas. También se reveló su asociación con la materia orgánica en zonas donde no hay fracturación; de ahí que, en el modelo resultante no pueda ser considerada la presencia de uranio como índice de fracturación y permeabilidad en los carbonatos cubanos. La integración de los datos de los registros geofísicos de pozo convencionales, la herramienta de imágenes de pared de pozo FMI junto a los trabajos de laboratorio, conforma la clave para definir la naturaleza del uranio en los carbonatos.

ABSTRACT Presence of uranium in carbonated petroleum reservoirs has been linked to areas of good permeability, due to the existence of open fractures through which uranium-rich salt waters have circulated. Moreover, uranium is related to organic matter in reducing environments. This paper aims to shed light on nature of uranium in carbonated reservoirs that appear in Cuban gas-controlled formations. For this purpose, wells containing these reservoirs possessing geophysical well logs with electrical images of well wall, natural radioactivity of samples measured in low bottom chamber and total organic carbon content by interpretation of well logs were selected in the North Cuban Petroleum Gas Province. There is evidence that the presence of uranium cannot be considered a direct index of permeability when it appears associated with open fractures as well as closed. It was also showed its association with organic matter in areas where there is no fracturing; hence, in the resulting model, the presence of uranium cannot be considered as index of fracturing and permeability in Cuban carbonates. Integrating data from conventional geophysical well logs, the FMI well wall-imaging tool alongside laboratory work, forms the key to defining the nature of uranium in carbonates.

Resumen En la exploración geofísica, el análisis del terreno es fundamental para planificar la adquisición de datos de gravimetría y magnetometría. No obstante, en la actualidad dichos análisis requieren el uso supervisado de información secundaria extensa. Por este motivo, en este estudio se propone una metodología que utiliza el aprendizaje profundo para evaluar el impacto de la cobertura vegetal y la topografía en la adquisición geofísica. Se usó una red neuronal artificial perceptrón multicapa para considerar cinco variables terrestres, y una red neural convolucional para la clasificación automatizada de coberturas vegetales sobre imágenes satelitales. A partir de esto, se obtuvieron puntos para la localización de estaciones de levantamiento geofísico que cumplen con un criterio de favorabilidad por accesibilidad, distancias, restricciones por cuerpos de agua y coberturas boscosas. La geometría obtenida se evaluó en la exploración del Granito de Durania en Colombia, y los resultados se analizaron utilizando transectas de adquisición y modelado computacional de anomalías magnéticas y de gravedad. Finalmente, se aplicaron técnicas de interpolación donde el método Ponderación de Distancia Inversa (IDW) mostró la mejor imagen para interpretar la delimitación del cuerpo intrusivo.

Abstract In geophysical exploration, terrain analysis is fundamental for planning the gravity and magnetic surveys. However, current analyses necessitate supervised use of extensive secondary information. Consequently, this study proposes a methodology that leverages deep learning to assess the impact of vegetation coverage and topography in geophysical acquisition. An artificial neural network multilayer perceptron was used to consider five terrain-related variables, while a convolutional neural network is used for automated classification of vegetation cover on satellite imagery. From this, geophysical acquisition points are obtained, adhering to criteria involving accessibility favourability, distances, restrictions imposed by bodies of water, and forested cover. The obtained geometry was tested in the exploration of the Granito de Durania in Colombia, and the results were analysed using acquisition transects and computational modelling of gravity and magnetic anomalies. Interpolation techniques were applied, with the Inverse Distance Weighting (IDW) method yielding the most informative map for interpreting the delineation of the intrusive body.

Abstract Iron ore tailings dams must be constantly monitored for safety purposes. Among the aspects traditionally monitored are geotechnical protocols, such as piezometric levels along the dam. Recently, geophysics, a science that studies, among other things, dynamic processes in the Earth, has contributed to non-invasive monitoring using electro-resistivity methods. Geophysical methods provide a large amount of data in relatively quick samples, but there is little information on the integration of traditional geotechnical and geophysical techniques. Therefore, this work aimed to evaluate the relationship between geophysical data, monitored every 15 days between May 2022 and March 2023, and geotechnical data from an iron ore tailings dam located in the Iron Quadrangle. The geophysical method used was two-dimensional electrical imaging with a Schlumberger array. Analysis of variance and multiple regression allowed us to evaluate the relationship between resistivity values, piezometer level, sampling time, and rainfall. Piezometry data explained the electro-resistivity significantly, while sampling time and rainfall did not significantly explain electro-resistivity. Therefore, the dam's electro-resistivity patterns have not changed significantly over the period, and local rainfall does not imply an immediate response in resistivity. These conclusions can support new directions in decisions about monitoring iron ore tailings dams and may contribute to advances in dam safety in the mining sector. purposes protocols Recently geophysics studies things Earth noninvasive non invasive electroresistivity electro samples techniques Therefore 1 202 2023 Quadrangle twodimensional two dimensional array values level electroresistivity. s period sector 20 2

Abstract In the past decade, machine learning techniques were responsible for a revolution in classification and regression tasks, making it possible to automate some laborious activities, saving time and reducing errors. It is known that the geological logging process is one of the most time-consuming activities accomplished by mining companies. Additionally, it is a subjective activity, and changes in the staff directly affect the geological databases due to different human log interpretation. By developing an automatic log classifier, a company can avoid problems related to the turnover of the staff by standardizing the criteria used to label an interval and can save time by avoiding manual log description. The proposed solution is: given the well log data containing the coordinates, resistivity and natural gamma, the model will be able to predict the presence or absence of coal, and its lithology. The innovation of the methodology proposed, considers not only the geophysical logging values, but additionally inserts the neighbourhood of a given depth as valuable input information, using Fully Convolutional Network. It performs a semantic segmentation using the well log data, which means that model´s input is the complete well log data curve and the trained model will return an output curve giving the probability of the presence of coal, by interval. The results showed good prediction for the binary problem (F1-score 0.79). The multi-class modelling suffers from the lack of data for each class, resulting in a F1-score from 0.38 for the worst result to 0.76 for the best. decade tasks errors timeconsuming consuming companies Additionally activity interpretation classifier description coordinates gamma coal lithology values information Network models s F1score Fscore F1 score F 0.79. 079 0.79 . 0 79 0.79) multiclass multi class 038 38 0.3 076 76 0.7 best 07 7 03 3 0.

Resumen La aplicación de las técnicas geofísicas en la investigación de la obra civil, como el estudio de las presas de relaves mineras en todas sus fases, ha sido actualizada en Ecuador con el ACUERDO Nº MERNNR-MERNNR-2020-0043-AM y su Anexo II. Se realiza una revisión de las mismas, su utilidad y los parámetros que aportan para cada parte de la construcción de una balsa de relves mineros. Se hace una revisión también de las que han sido incluidas en el Acuerdo Ministerial y la posibilidad de incluir más técnicas que las que se indican en dicha normativa. Se concluye con la importancia de estas técnicas en la investigación complementaria previa y en el monitoreo durante la vida y cierre del repositorio y la solución de problemas geotécnicos variados. También se recomienda un análisis y la inclusión de más técnicas de investigación geofísica en este Acuerdo Ministerial y en la normativa minera de Ecuador.

Abstract The application of geophysical techniques in the investigation of civil works, such as the study of mining tailings dams in all its phases, has been updated in Ecuador with Nº MERNNR-MERNNR-2020-0043-AM AGREEMENT, and its Annex II. A review of them, their usefulness, and the parameters they provide for each part of constructing a mining tailings pond are carried out. A review is also made of those that have been included in the Ministerial Agreement and the possibility of including more techniques than those indicated in said regulations. It concludes with the importance of these techniques in the previous complementary investigation, monitoring during the life and closure of these repositories and the solution of various geotechnical problems. An analysis including more geophysical investigation techniques in this Ministerial Agreement and Ecuador's mining regulations is also recommended.

Abstract The characterization of unsaturated soils using hydromechanical methods is an essential requirement in soil science. However, current laboratory techniques used to obtain soil water retention and unsaturated hydraulic conductivity curves are time-consuming. To address this issue, a method based on indirect measures (electrical resistivity/electrical conductivity) was developed to quantitatively characterize soils. A novel unsaturated semi-empirical hydrogeophysical model of soils was developed by incorporating the hydrodynamic, geophysical, and petrophysical characteristics of soils. The model assumes that the parameters influencing the variation in the volumetric water content with matric suction and electrical resistivity are the same. The electrical resistivity characteristic curve (ERCC) defines a function that correlates environmental variables, electrical resistivity, soil water status, matric suction, hydraulic and petrophysical parameters, and fluid electrical resistivity. Model validation confirmed that the proposed approach can estimate the soil water retention curve (SWRC) via the indirect measures, and the results agreed with the experimental data. This indicates that it is possible to determine the SWRC and unsaturated hydraulic conductivity function of soil using the described approach. science However timeconsuming. timeconsuming time consuming. consuming time-consuming issue resistivityelectrical semiempirical semi empirical hydrodynamic geophysical same ERCC (ERCC variables status (SWRC data

ABSTRACT In this work, we have applied two geophysical techniques in two different areas of potential interest for paleoseismological assessment of the active faults of the Acambay graben. The main goal was to localize segments of buried faults suspected to break the surface during the 1912 Acambay Earthquake, in order to (1) identify favorable sites for paleoseismological investigation purpose and (2) extrapolate the data obtained with a paleoseismic trenching. On the one hand, Electromagnetic Induction (EMI) Method was used to map the horizontal variation of the apparent resistivity in order to detect the 1912 surface rupture of the Temascalcingo fault in the alluvial plain of the Lerma River. On the other hand, within a volcanic edifice, the Electrical Resistivity Tomography (ERT) technique was used to characterize the electrical resistivity distribution along a profile in order to detect and localize the San Pedro fault, partially buried in a Holocene sedimentary filling of a small endorheic basin. Results of these studies allow defining location and orientation of the structures that potentially broke the surface during the 1912 earthquake and are partially hidden by recent deposits filling the tectonic depressions. Good correlation between ERT subsurface to deep imagery of faults and a trench survey which cuts across the San Pedro fault trace, illustrate the pertinence to use such techniques for paleoseismological investigation purpose in volcano-sedimentary environments.

RESUMEN En este trabajo, aplicamos dos técnicas geofísicas en dos áreas diferentes de potencial interés para la evaluación paleosismológica de las fallas activas del graben de Acambay. El objetivo principal es localizar dos segmentos de fallas parcialmente anegadas por la sedimentación que posiblemente rompieron la superficie durante el terremoto de Acambay de 1912, para (1) identificar sitios propicios para fines de investigación paleosismológica y (2) extrapolar los datos encontrados en excavación paleosísmica. Por un lado, se utilizó el método de Inducción Electromagnética (EMI por sus siglas en inglés) para mapear la variación ¡horizontal de la resistividad aparente con el fin de localizar en subsuperficie la ruptura de 1912 de la falla Temascalcingo en la llanura aluvial del río Lerma. Por otro lado, dentro de un edificio volcánico se utilizó la técnica de Tomografía de Resistividad Eléctrica (ERT por sus siglas en inglés) para caracterizar la distribución de resistividad eléctrica a lo largo de un perfil con el fin de detectar y localizar la falla San Pedro parcialmente sepultada por un relleno sedimentario holoceno en una pequeña cuenca endorreica. Los resultados de estos estudios permiten definir la ubicación y orientación de las estructuras que rompieron potencialmente durante el terremoto de 1912y están parcialmente ocultas por depósitos recientes que llenan las depresiones tectónicas. La buena correlación entre las imágenes ERT del subsuelo y un levantamiento en trincheras cortando la traza de la falla de San Pedro, ilustra la pertinencia de usar tales técnicas para complementar la investigación paleosismológica en ambientes volcánico-sedimentarios.

Abstract The application of geophysical detection techniques to mapping the underground of agricultural and forest fields has accelerated in recent years. Geophysical imaging provides an alternative or complement to traditional methods of collecting subsurface variables over time and space. Where previously the standard was soil sampling and laboratory analysis to assess the condition of a soil for its various purposes, in situ detection techniques are proving to be a very effective way to assess variation in soil / underground properties. This work is a review of the state of the art related to the most applied geophysical techniques in the detection of underground components and processes that can influence the productivity and functioning of forest ecosystems and agricultural systems. This review highlights the opportunities, applications and challenges presented by geophysical images (radargrams and tomograms) in the multidisciplinary fields of Biogeosciences. Both geophysical research techniques are very attractive to the scientific community, allowing the underground to be accurately mapped, plot rooting, monitor water content, identify sales movement and agrochemicals. Agronomists, foresters, and the scientific community would benefit from adopting these minimally invasive, scalable imaging technologies to the underground and advance our collective research.

Resumen La aplicación de técnicas de detección geofísica para mapear el subsuelo de campos agrícolas y forestales se ha acelerado en los últimos años. La obtención de imágenes geofísicas proporciona una alternativa o complemento a los métodos tradicionales para recopilar variables subsuperficiales a lo largo del tiempo y el espacio. Donde anteriormente el estándar era el muestreo de suelos y el análisis de laboratorio para evaluar la condición de un suelo para diversos propósitos, las técnicas de detección in situ están demostrando ser una forma muy efectiva para evaluar la variación de las propiedades del suelo / subsuelo. Este trabajo es una revisión del estado del arte relacionada con las técnicas geofísicas más aplicadas en la detección de las características y propiedades del subsuelo que influyen en la productividad y el funcionamiento de los ecosistemas forestales y sistemas agrícolas. En esta revisión se destacan las oportunidades, aplicaciones y retos que presentan las imágenes geofísicas (radargramas y tomogramas) en los campos multidisciplinarios de las biogeociencias. Las dos técnicas de investigación geofísica son muy atractivas para la comunidad científica, pues permiten mapear con precisión el subsuelo, graficar enraizamiento y monitorear contenidos de agua, identificar movimiento de sales y agroquímicos. Los agrónomos, silvicultores y la comunidad científica, podrían beneficiarse de la adopción de estas tecnologías de imágenes escalables y mínimamente invasivas para explorar el subsuelo y avanzar en nuestra investigación colectiva.

ABSTRACT In this study, three geophysical techniques were used to identify, localize, and characterize a partly blind fault in the Llano Grande basin within the Agua Fría Graben. This tectonic basin is located in the Los Azufres Volcanic Complex, one of the major silicic volcanic centers in the Trans-Mexican Volcanic Belt. The 1 km wide Agua Fría graben could be considered as an analogous of the larger graben structures bounded by the Morelia-Acambay Fault System. Since it is filled by recent sediments, it represents a challenge for the recognition and characterization of active faults that lack clear surface expression. Newly collected magnetic data led to the identification of lineaments interpreted as structural discontinuities. Ground penetrating radar and seismic refraction surveys were carried out across one of these magnetic lineaments crossing the basin to characterize the nature and geometry of the inferred discontinuity. The ground penetrating radar profiles allowed the identification of buried deformational structures interpreted as the northern segment of the Agua Fría fault. The subsurface reflectors displaced 1 to 1.5 m by the fault indicate that this structure is potentially active. The opening of trenches based on these results makes it possible to confirm the interpretation of the geophysical profiles, to discuss the precision of the data and to validate their use for such studies. On seismic refraction profiles, the deformation zones are related to low P-wave velocity zones. These geophysical studies demonstrate the potential of such techniques to locate faults in the subsurface, partially characterize the width of the fault zone and the associated displacement within the uppermost of the subsurface. Our results may be applied to define ideal sites for paleoseismic excavations which are essential for the identification and description of historical and prehistoric earthquakes, and thus, for the characterization of the local seismic hazard.

RESUMEN En este estudio/ .se emplearon tres técnicas geofísicas para identificar, localizar y caracterizar una falla parcialmente ciega en la cuenca de Llano Grande dentro del graben de Agua Fría. Esta cuenca tectónica se encuentra en el complejo volcánico Los Azufres, uno de los principales centros silícicos del Cinturón Volcánico Transmexicano. El graben de Agua Fría de 1 km de ancho, podría considerarse como análogo a las estructuras de graben más grandes delimitadas por el sistema de fallas Morelia-Acambay. Dado que está lleno de sedimentos recientes, presenta un desafío en cuanto a la identificación y caracterización de fallas activas que carecen de clara expresión superficial. Los datos magnéticos obtenidos para este trabajo nos permitieron identificar lineamientos interpretados como discontinuidades estructurales. Levantamientos con georadar y refracción sísmica se realizaron sobre uno de estos lineamientos magnéticos que cruzan la cuenca, para caracterizar la naturaleza y geometría de la discontinuidad inferida. Los perfiles de georadar permitieron la identificación de estructuras de deformación las cuales son interpretadas como el segmento norte de la falla Agua Fría. Los reflectores desplazados entre 1 y 1.5 m por la falla, indican que esta estructura es potencialmente activa. La apertura de trincheras con base en estos resultados confirma la interpretación de perfiles geofísicos y permite validar su precisión y su uso para este tipo de estudios. En los perfiles de refracción sísmica, las zonas de deformación están relacionadas con zonas de baja velocidad de ondas P. Estos estudios geofísicos demuestran la potencialidad de estas técnicas para localizar fallas en subsuelo a poca profundidad, caracterizar parcialmente el ancho de su zona de influencia y el desplazamiento asociado en los primeros metros del subsuelo. Nuestros resultados podrían ser aplicados para definir sitios ideales para excavaciones paleosísmicas que son esenciales para la identificación y descripción de terremotos históricos o prehistóricos y, por lo tanto, para la caracterización del peligro sísmico local.

Resumen En la presente investigación se aplicaron técnicas geofísicas y geotécnicas para caracterizar el subsuelo a la altura del Km 68+500 del municipio de Pamplona, definir la resistividad eléctrica, velocidad sísmica tipo P y S, parámetros dinámicos del suelo, tipo de perfil de suelo y curva de espectro de aceleración mediante la NSR10 título A, llevando a cabo dos fases: una de campo, donde se realizó levantamiento topográfico, dos (2) ensayos de SPT, cuatro (4) de SEV, dos (2) líneas de TRS, dos (2) de MASW 1D y 2D; y la fase de procesamiento de datos para generar imágenes 2D del perfil, interpretar y correlacionar, dando como resultados, velocidades de onda P entre 499m/s y 1714m/s, velocidades de onda S entre 210m/s y 466m/s y resistividades entre 6.06 Ω-m y 581.05 Ω-m., perfiles de suelo Tipo D, compuestos de materiales rígidos, arenas con presencia de arcilla y arcilla limosa saturada.

Abstract In the present investigation, geophysical and geotechnical techniques were applied to characterize the subsoil at the height of Km 68 + 500 in the municipality of Pamplona, define the electrical resistivity, seismic velocity type P and S, dynamic parameters of the soil, type of soil profile and acceleration spectrum curve using NSR10 title A, carrying out two phases: one in the field, where topographic survey was performed, two (2) SPT tests, four (4) SEV, two (2) TRS lines, two (2) of MASW 1D and 2D; and the data processing phase to generate 2D images of the profile, interpret and correlate, resulting in P wave velocities between 499m / s and 1714m / s, S wave velocities between 210m / s and 466m / s and resistivities between 6.06 Ω -m and 581.05 Ω-m., Type D soil profiles composed of rigid materials, sands with the presence of clay and saturated silty clay.

Abstract Landslides can substantially impact the fluvial systems, which is why the continuous mapping of their extent, evolution and stability assessment is crucial. However, in such environments, material identification (e.g. colluvium) and subsurface characterization by the methods used for geologic mapping and geotechnical investigation is often a challenging task. Thus, these classical invasive methods may benefit from geophysical techniques to enable and enhance our understanding of the subsurface in these areas. To examine such integrated approach, Multi-Channel Analysis of Surface Waves (MASW) combined with Electrical Resistivity Tomography (ERT) were applied on a geomorphologically active fluvial valley in Sobradinho (the Federal District of Brazil). The subsurface materials showed a specific range of resistivity values as dry soil, saprolite, and landslide slip surface. The 1D shear wave velocity (Vs) model showed an increasing trend of Vs with depth at a location away from the landslide mass, while the longitudinal profile (over the landslide) showed an anomalous change in Vs (~ 250 to 400 m/sec). Based on the existing information about the landslide, the ERT appeared to be an effective method over MASW. This study shows how the integration of geophysical data with the geological and geotechnical investigation helps to obtain a more realistic or unambiguous model of the subsurface.

ABSTRACT: There is an increasing interest in the application of geophysical surveys to assess the soil water content (SWC) variation in both spatial and temporal scales. In this work, a geophysical survey was carried out at an experimental farm in dry and wet conditions. We determined the SWC data measured with the gravimetric method, apparent electrical conductivity by electromagnetic induction (EMI) and amplitude of Ground Penetrating Radar (GPR) data at different frequencies. Geophysical sensors are an efficient tool for soil mapping at high resolution; however; there is a need to improve the knowledge on their capabilities and limitations under field conditions, especially for GPR. The geophysical survey provides an example of the application of these techniques to evaluate the spatial variability of SWC in two different water conditions. The contribution of geophysical data in understanding the spatial variability of SWC was investigated applying both the traditional analysis and spatial techniques. The results indicated that the geophysical data captured the spatial variation of SWC in non-invasively way especially in dry condition. However, they also showed the complex interplay between factors controlling SWC and geophysical responses and the drawbacks of geophysical sensors under inhomogeneous water conditions. Our findings also highlighted that EMI survey provides the potential to map the SWC variability within a relatively short time. The results obtained in this research are important from the agronomical viewpoint, since they allow increasing efficiency of irrigation practices, which is important in times characterized by climate change.

ABSTRACT This article is focused on the importance of remote sensing techniques for archaeological studies, specifically LIDAR, and geophysics techniques, such as ground penetrating radar (GPR). The use of LIDAR has become popular in the last ten years and its use in forested places has been very effective despite the low visibility. In the case of GPR, it is generally used in those places where evidence of structure remains can be found. However, in the sites identified by the Project Costa del Soconusco there are no buildings with these characteristics, but their usefulness for the identification of areas of ceramic production have been decisive for the development of our study. These techniques have provided important data that has allowed us to know more about the settlements located in the eastern region of Soconusco.

RESUMEN Este artículo se enfoca en la importancia de las técnicas para detección remota en los estudios arqueológicos, en específico el LIDAR, y de las técnicas geofísicas, como el georradar (GPR por sus siglas en inglés). El uso de LIDAR se ha popularizado en los últimos diez años y su empleo en lugares boscosos ha resultado muy eficaz a pesar de la poca visibilidad. En el caso del GPR generalmente se emplea en aquellos sitios donde se puede hallar evidencia de restos de estructuras. Aunque en los sitios identificados por el Proyecto Arqueológico Costa del Soconusco no se cuenta con edificaciones de dichas características, su utilidad para la identificación de áreas de producción cerámica ha sido determinante para el desarrollo de nuestro estudio. Esto nos ha permitido conocer más sobre los asentamientos ubicados en la región oriental del Soconusco.

RESUMO O mapeamento de atributos químicos do solo em larga escala pode acarretar em ganhos no planejamento de uso e ocupação do mesmo. Existem diferentes técnicas disponíveis para tal fim, cujos desempenhos devem ser testados para diferentes situações de paisagem. Objetivou-se neste trabalho espacializar atributos químicos do solo, comparando oito métodos para predição. Como variáveis independentes foram utilizados 40 atributos morfométricos gerados a partir do modelo digital de elevação, além de dados geofísicos, imagens do satélite Landsat 8 e o NDVI. Calculou-se todas combinações possíveis entre as bandas do satélite, gerando 28 novas variáveis. Também foram feitas combinações entre as bandas de Th, U e K obtidas dos dados geofísicos, gerando outras três variáveis. As últimas variáveis calculadas foram as distâncias entre os quatro pontos das extremidades da bacia (d1, d2, d3 e d4). As variáveis dependentes do modelo foram teores de Al, Ca, Fe, K, Mg, Na, Si, Ti, Cr, Cu, Mn, Ni, P, Pb, V, Zn, Zr, S e Cl. Foram utilizadas 200 amostras de solo, coletadas em 100 pontos em duas profundidades (0-10 e 10-30 cm), e os elementos totais foram determinados em analisador de fluorescência de raios-X. Random Forest mostrou-se superior aos demais para predizer os atributos químicos do solo nas duas profundidades, sendo indicado para predição dos atributos dos solos da região de estudo. As variavéis espaciais mostraram-se altamente prescindíveis, devendo ser consideradas nas modelagens dos elementos químicos do solo. É possível a predição dos elementos com R2 variando de 0,32 a 0,62 pelos métodos testados.

ABSTRACT Mapping the chemical attributes of the soil on a large scale can result in gains when planning the use and occupation of the land. There are different techniques available for this purpose, whose performance should be tested for different types of landscapes. The aim of this study was to spatialize chemical attributes of the soil, comparing eight methods of prediction. Forty morphometric attributes, generated from a digital elevation model, were used as independent variables, in addition to geophysical data, images from the Landsat 8 satellite and the NDVI. All possible combinations between the satellite bands were calculated, generating 28 new variables. Combinations between the Th, U and K bands obtained from the geophysical data were also calculated, generating a further three variables. The final variables to be calculated were the distances between the four points of the edges of the basin (d1, d2, d3 and d4). The dependent variables for the model were Al, Ca, Fe, K, Mg, Na, Si, Ti, Cr, Cu, Mn, Ni, P, Pb, V, Zn, Zr, S and Cl. A total of 200 soil samples were used, which were collected from 100 points at two depths (0-10 and 10-30 cm); the total elements were determined using an X-ray fluorescence analyzer. The Random Forest algorithm proved to be superior to the others in predicting the chemical attributes of the soil at both depths, and is suitable for predicting soil attributes in the study region. Spatial variables are essential, and should be considered when modelling chemical elements in the soil. Using the methods under test, it is possible to predict elements with R2 values ranging from 0.32 to 0.62.

RESUMEN Este trabajo presenta la simulación numérica de una avalancha granular a escala experimental basada en elementos de alto orden, con el fin de evaluar el potencial de estas técnicas espectrales para resolver las leyes de conservación en geofísica. La discretización espacial de estas ecuaciones se desarrolló a través del métodos penalizado de multidominios espectrales (SMPM). Los términos temporales se discretizaron utilizando un método Runge-Kutta de preservación de estabilidad fuerte. La estabilidad del esquema numérico se garantiza con el uso de un filtro espectral y un coeficiente de presión lateral de tierras constante o regularizado. El caso de prueba es una avalancha granular que se genera en un canal rectangular de pequeña escala con gradiente topográfico. Se realizó una prueba de independencia de malla para aclarar el orden del error en la conservación de la masa producida por los tratamientos previamente mencionados. Las predicciones numéricas se comparan con las mediciones experimentales realizadas por Denlinger & Iverson (2001). Además, se analizaron las condiciones de contorno, y los parámetros como el coeficiente de presión lateral de tierras y el factor de corrección de momentum para observar su incidencia al resolver las ecuaciones del flujo granular. Este trabajo identifica las bondades y debilidades del SMPM para resolver este conjunto de ecuaciones y es posible concluir que el SMPM proporciona una solución adecuada de las ecuaciones propuestas por Iverson & Denlinger (2001). Además, las predicciones son comparables a los datos experimentales y resultados numéricos dados por otros esquemas.

ABSTRACT This work presents a high-order element-based numerical simulation of an experimental granular avalanche, in order to assess the potential of these spectral techniques to handle geophysical conservation laws. The spatial discretization of these equations was developed via the spectral multidomain penalty method (SMPM). The temporal terms were discretized using a strong-stability preserving Runge-Kutta method. Stability of the numerical scheme is ensured with the use of a spectral filter and a constant or regularized lateral earth pressure coefficient. The test case is a granular avalanche that is generated in a small-scale rectangular flume with a topographical gradient. A grid independence test was performed to clarify the order of the error in the mass conservation produced by the treatments here implemented. The numerical predictions of the granular avalanches are compared with experimental measurements performed by Denlinger and Iverson (2001). Furthermore, the boundary conditions and parameters such as lateral earth pressure coefficients and the momentum correction factor were analyzed in order to observe the incidence of these features when solving the granular flow equations. This work identifies the benefits and weaknesses of the SMPM to solve this set of equations, and thus, it is possible to conclude that the SMPM provides an appropriate solution to the granular flow equations proposed by Iverson and Denlinger (2001) and comparable predictions for the experimental data.