Person: Giménez Díaz, Rafael
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Giménez Díaz
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Rafael
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Ingeniería
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IS-FOOD. Research Institute on Innovation & Sustainable Development in Food Chain
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0000-0003-3210-0578
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Publication Open Access Factors controlling sediment export in a small agricultural watershed in Navarre (Spain)(Elsevier, 2012) Giménez Díaz, Rafael; Casalí Sarasíbar, Javier; Grande Esteban, Ildefonso; Díez Beregaña, Javier; Campo-Bescós, Miguel; Álvarez Mozos, Jesús; Goñi Garatea, Mikel; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak; Gestión de Empresas; Enpresen Kudeaketa; Gobierno de Navarra / Nafarroako GobernuaIt is recognised that the hydrological and erosion processes in watersheds are very much conditioned by the (inter)action of a number of variables. This paper covers a 15-year period of studying those factors that have a major influence on the sediment yield and transport during individual hydrological events in a small Mediterranean agricultural watershed. Multivariate statistical techniques such as cluster analysis and principal component analysis were applied for the interpretation of datasets. In addition, the relationships between suspended sediment concentration and discharge (hysteretic loops) were also analysed. The hydrological response of the studied watershed is mainly controlled by the antecedent condition of the flow. Most of the runoff and sediment are generated during the wet season when vegetation cover is scant and saturation overland flow occurs promptly as a response to almost any rainfall events. In contrast, during the dry seasons even if high-intensity rainfalls normally occur, very scant runoffs are, however recorded, at the exit of the watershed. Most of the eroded sediment seems to come from riparian areas. The discharge registered at the watershed outlet up to 1 h prior to the flood is a very good surrogate for antecedent soil moisture.Publication Open Access Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter(Elsevier, 2016) Martínez de Aguirre Escobar, Alejandro; Álvarez Mozos, Jesús; Giménez Díaz, Rafael; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta ProiektuakSurface roughness crucially affects the hydrological and erosive behaviours of soils. In agricultural areas surface roughness is directly related to tillage, whose action strongly affects the key physical properties of soils and determines the occurrence and fate of several processes (e.g., surface storage, infiltration, etc.). The characterisation of surface roughness as a result of tillage operations is not straightforward, and numerous parameters and indices have been proposed for quantifying it. In this article, a database of 164 profiles (each 5 m long), measured in 5 different roughness classes, was analysed. Four roughness classes corresponded to typical tillage operations (i.e., mouldboard, harrow, seedbed, etc.), and the fifth represented a seedbed soil that was subject to rainfall. The aim of the research was to evaluate and select the surface roughness parameters that best characterised and quantified the surface roughness caused by typical tillage operations. In total, 21 roughness parameters (divided into 4 categories) were assessed. The parameters that best separated and characterised the different roughness classes were the limiting elevation difference (LD) and the Mean Upslope Depression index (MUD); however, the parameters most sensitive to rainfall action on seedbed soils were limiting slope (LS) and the crossover lengths measured with the semivariogram method (lSMV) and the root mean square method (lRMS). Many parameters had high degrees of correlation with each other, and therefore gave almost identical information. The results of this study may contribute to the understanding of the surface roughness phenomenon and its parameterisation in agricultural soils.Publication Open Access Influence of surface roughness sample size for C-band SAR backscatter applications on agricultural soils(IEEE, 2017) Martínez de Aguirre Escobar, Alejandro; Álvarez Mozos, Jesús; Lievens, Hans; Verhoest, Niko E. C.; Giménez Díaz, Rafael; Landa Ingeniaritza eta Proiektuak; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Proyectos e Ingeniería RuralSoil surface roughness determines the backscatter coefficient observed by radar sensors. The objective of this letter was to determine the surface roughness sample size required in synthetic aperture radar applications and to provide some guidelines on roughness characterization in agricultural soils for these applications. With this aim, a data set consisting of ten ENVISAT/ASAR observations acquired coinciding with soil moisture and surface roughness surveys has been processed. The analysis consisted of: 1) assessing the accuracies of roughness parameters s and l depending on the number of 1-m-long profiles measured per field; 2) computing the correlation of field average roughness parameters with backscatter observations; and 3) evaluating the goodness of fit of three widely used backscatter models, i.e., integral equation model (IEM), geometrical optics model (GOM), and Oh model. The results obtained illustrate a different behavior of the two roughness parameters. A minimum of 10-15 profiles can be considered sufficient for an accurate determination of s, while 20 profiles might still be not enough for accurately estimating l. The correlation analysis revealed a clear sensitivity of backscatter to surface roughness. For sample sizes >15 profiles, R values were as high as 0.6 for s and ~0.35 for l, while for smaller sample sizes R values dropped significantly. Similar results were obtained when applying the backscatter models, with enhanced model precision for larger sample sizes. However, IEM and GOM results were poorer than those obtained with the Oh model and more affected by lower sample sizes, probably due to larger uncertainly of l.Publication Open Access Evaluation of 2D models for the prediction of surface depression storage using realistic reference values(Wiley, 2016) Giménez Díaz, Rafael; Mezkiritz Barberena, Irantzu; Campo-Bescós, Miguel; Álvarez Mozos, Jesús; González de Audícana Amenábar, María; Martínez de Aguirre Escobar, Alejandro; Casalí Sarasíbar, Javier; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta ProiektuakDepression storage (DS) is the maximum storage of precipitation and runoff in the soil surface at a given slope. The DS is determined by soil roughness that in agricultural soils is largely affected by tillage. The direct measurement of DS is not straightforward because of the natural permeability of the soil. Therefore, DS has generally been estimated from 2D/3D empirical relationships and numerical algorithms based on roughness indexes and height measurements of the soil surface, respectively. The objective of this work was to evaluate the performance of some 2D models for DS, using direct and reliable measurements of DS in an agricultural soil as reference values. The study was carried out in experimental microplots where DS was measured in six situations resulting from the combination of three types of tillage carried out parallel and perpendicular to the main slope. Those data were used as reference to evaluate four empirical models and a numerical method. Longitudinal altitudinal profiles of the relief were obtained by a laser profilometer. Infiltration measurements were carried out before and after tillage. The DS was largely affected by tillage and its direction. Highest values of DS are found on rougher surfaces mainly when macroforms cut off the dominant slope. The empirical models had a limited performance while the numerical method was the most effective, even so, with an important variability. In addition, a correct hydrological management should take into account that each type of soil tillage affects infiltration rate differently.Publication Open Access On the influence of spatial resolution in soil surface roughness characterization using Tls and Sfm techniques(IEEE, 2018) Martínez de Aguirre Escobar, Alejandro; Álvarez Mozos, Jesús; Giménez Díaz, Rafael; Milenković, Milutin; Pfeifer, Norbert; Ingeniería; IngeniaritzaSoil surface roughness strongly affects the scattering of microwaves and determines the backscattering coefficient observed by SAR (Synthetic Aperture Radar) sensors. The aim of this study is to analyze the influence of the spatial resolution of Terrestrial Laser Scanner (TLS) and Structure from Motion (SfM) techniques to parameterize surface roughness over agricultural soils. Three experimental plots (5 x 5 meters) representing different roughness conditions were measured by TLS and SfM techniques. Roughness parameters (s and l) were calculated from profiles obtained at different spatial resolutions in parallel and in perpendicular to the tillage direction on each plot. The results showed minor differences in the parameters values between both techniques and, in general, a decreasing trend and an increasing trend for lower spatial resolutions for parameter s and l, respectively.Publication Open Access Evaluation of terrestrial laser scanner and structure from motion photogrammetry techniques for quantifying soil surface roughness parameters over agricultural soils(Wiley, 2020) Martínez de Aguirre Escobar, Alejandro; Álvarez Mozos, Jesús; Milenković, Milutin; Pfeifer, Norbert; Giménez Díaz, Rafael; Ingeniería; IngeniaritzaThe surface roughness of agricultural soils is mainly related to the type of tillage performed, typically consisting of oriented and random components. Traditionally, soil surface roughness (SSR) characterization has been difficult due to its high spatial variability and the sensitivity of roughness parameters to the characteristics of the instruments, including its measurement scale. Recent advances in surveying have greatly improved the spatial resolution, extent, and availability of surface elevation datasets. However, it is still unknown how new roughness measurements relates with the conventional roughness measurements such as 2D profiles acquired by laser profilometers. The objective of this study was to evaluate the suitability of Terrestrial Laser Scanner (TLS) and Structure from Motion (SfM) photogrammetry techniques for quantifying SSR over different agricultural soils. With this aim, an experiment was carried out in three plots (5 × 5 m) representing different roughness conditions, where TLS and SfM photogrammetry measurements were co‐registered with 2D profiles obtained using a laser profilometer. Differences between new and conventional roughness measurement techniques were evaluated visually and quantitatively using regression analysis and comparing the values of six different roughness parameters. TLS and SfM photogrammetry measurements were further compared by evaluating multi‐directional roughness parameters and analyzing corresponding Digital Elevation Models. The results obtained demonstrate the ability of both TLS and SfM photogrammetry techniques to measure 3D SSR over agricultural soils. However, profiles obtained with both techniques (especially SfM photogrammetry) showed a loss of high‐frequency elevation information that affected the values of some parameters (e.g. initial slope of the autocorrelation function, peak frequency and tortuosity). Nevertheless, both TLS and SfM photogrammetry provide a massive amount of 3D information that enables a detailed analysis of surface roughness, which is relevant for multiple applications, such as those focused in hydrological and soil erosion processes and microwave scattering.