The USLE soil erodibility nomograph revisited

The nomograph by Wischmeier et al. (1971) for calculating the K-factor in the USLE was extremely useful when there was low access to calculators. However, the generalised calculation of this factor requires the development of analytic procedures. This paper presents a detailed analysis of the nomograph and its underlying equation, which is applicable only when the silt plus very find sand fraction does not exceed 70%. We also examined the quality of fit on the nomograph of the adaptations to the equation that have been proposed, as a means of dealing with those areas where the original equation is not applicable. All models are shown to have areas where the fit is deficient or even unacceptable. Besides, the family of curves on the nomograph for the various values taken by the organic matter are not coincident with the mathematical function from which they presumably derive. The study also identifies those areas of the textural triangle in which the soils originally used in developing the USLE are located, with a view to according a lower predictive value to the contrasting areas in which calculations of the K-factor will necessarily be extrapolations. Finally, a new equation for calculating the K-factor is presented, which accurately reproduces the different sections of the nomograph, and allows the poorly functioning graph to be dispensed with. The paper ends with a link to a tool in R for simplifying the procedure for calculating the K-factor, taking into account varying situations of data availability.Funding for Open Access charges: Universidad de Huelv

Estimating textural fractions of the USDA using those of the International System: A quantile approach

Este artículo forma parte de una trilogía centrada en la revisión de los principales problemas que tiene uno de los factores más importantes de la Ecuación Universal de Pérdidas de Suelo (USLE), en concreto el Factor K de erosionabilidad del suelo. Se plantea un enfoque para solucionar la falta de correspondencias directas entre clasificaciones texturales de suelos.In soil science, the two most frequently used classification systems for the soil particle size distribution are the schemes by the United States Department of Agriculture (USDA) and the so-called International System (IS), whose difference is the upper particle size limit of the silt fraction, namely, 0.02 mm for the IS and 0.05 mm for the USDA system. The existence of these and other systems creates a disparity that hinders and prevents the use and exchange of soil information worldwide. To solve this problem, it is necessary to devise methodologies for the conversion of textural fractions between the different classification systems. This work focuses on the estimation of the USDA silt fraction from the basic textural fractions (sand, silt and clay) in the IS. Five models are currently available for that purpose: the log-linear interpolation method, the Minasny-McBratney-Bristow regression formula, the Shirazi-Boersma-Johnson interpolation method, the Minasny-McBratney regression formula, and the Padarian-Minasny-McBratney regression formula. The accuracy of some of these methods has already been assessed, but in this work we develop a new methodology, based on a local quantile regression, which improves and enriches this evaluation, providing both the regions of the textural triangle where the predictions of the models are acceptable, and the regions where each model is most appropriate. The data used were taken from the publicly available National Cooperative Soil Survey Soil Characterization Database, from which more than 270,000 soil horizon samples were selected for having valid texture data. The analysis carried out concludes that the Padarian-Minasny-McBratney regression formula is the best model of those evaluated. In addition, the tool developed for the evaluation of the models becomes a new model that provides point estimates of the USDA silt fraction from the basic textural fractions in the IS, with further improvement, compared to the 5 models evaluated, as it also provides a prediction interval for those estimates.Funding for open access charge: Universidad de Huelva / CBU

Use of TanDEM-X and Sentinel Products to Derive Gully Activity Maps in Kunene Region (Namibia) Based on Automatic Iterative Random Forest Approach

Gullies are landforms with specific patterns of shape, topography, hydrology, vegetation, and soil characteristics. Remote sensing products (TanDEM-X, Sentinel-1, and Sentinel-2) serve as inputs into an iterative algorithm, initialized using a micromapping simulation as training data, to map gullies in the northwestern of Namibia. A Random Forest Classifier examines pixels with similar characteristics in a pool of unlabeled data, and gully objects are detected where high densities of gully pixels are enclosed by an alpha shape. Gully objects are used in subsequent iterations following a mechanism where the algorithm uses the most reliable pixels as gully training samples. The gully class continuously grows until an optimal scenario in terms of accuracy is achieved. Results are benchmarked with manually tagged gullies (initial gully labeled area <0.3% of the total study area) in two different watersheds (408 and 302 km2, respectively) yielding total accuracies of >98%, with 60% in the gully class, Cohen Kappa >0.5, Matthews Correlation Coefficient >0.5, and receiver operating characteristic Area Under the Curve >0.89. Hence, our method outlines gullies keeping low false-positive rates while the classification quality has a good balance for the two classes (gully/no gully). Results show the most significant gully descriptors as the high temporal radar signal coherence (22.4%) and the low temporal variability in Normalized Difference Vegetation Index (21.8%). This research builds on previous studies to face the challenge of identifying and outlining gully-affected areas with a shortage of training data using global datasets, which are then transferable to other large (semi-) arid regions.This research is part of the DEM_HYDR2024 project sup ported by TanDEM-X Science Team, therefore the authors would like to express thanks to the Deutsches Zentrum für Luft und Raumfahrt (DLR) as the donor for the used TanDEM-X datasets. They acknowledge the financial support provided by the Namibia University of Science and Technology (NUST) within the IRPC research funding programme and to ILMI for the sponsorship of field trips to identify suitable study areas. Finally, they would like to express gratitude toward Heidelberg University and the Kurt-Hiehle-Foundation for facilitating the suitable work conditions during this research

Estimation of water retention capacity in soil: corrections to the CRA pedotransfer formula

El parámetro de capacidad de retención de agua en el suelo (CRA) es un modelo de base física ampliamente utilizado por técnicos forestales e investigadores en ecología forestal del territorio español, como uno de los factores estimadores de las disponibilidades de agua para las plantas y, por ende, de la calidad de estación. Dentro del proyecto Caracterización de suelos forestales de la provincia de Huelva se han apreciado una serie de anomalías en cuanto a los valores obtenidos para el parámetro CRA, especialmente en lo referente a la influencia de la pendiente sobre el modelo para su cálculo, así como en la determinación del agua disponible para la vegetación, en relación a la reserva total. Este trabajo plantea una sencilla modificación del modelo que permite obtener valores de capacidad de retención de agua más acordes con la calidad de la estación, en los terrenos forestales de fuerte pendiente, y también extiende el modelo al cálculo de la máxima reserva de agua disponible en el suelo. La bondad de estos parámetros se contrasta mediante el análisis de correlaciones frente a un índice de calidad de estación, con resultados satisfactorios.In Spain, a physical model to estimate the soil water capacity, which is called the CRA parameter, was implemented by Gandullo (1985). This parameter is broadly used in forest management and forest ecology research in relationship with site index and soil quality variables. While running a soil mapping project in the southwest of Spain some problems related to the CRA model were detected, mainly related to the influence of slope on total soil water capacity, as well as the estimation of available water capacity. A simple correction of the model is proposed in this paper, as well as a complementary parameter for available water capacity. The quality of those new parameters is tested by means of correlation analysis against Site Index variable

Mejoras en la estimación de la textura del suelo y su aplicación al factor K de erosionabilidad: una aproximación cuantílica

En este trabajo se realiza un análisis de los principales problemas que se padecen para el cálculo del factor K de la USLE y se presenta un conjunto de mejoras tanto para la auto matización de su cálculo como para eliminar errores existentes. Uno de los principales problemas es que los análisis de suelo ordinarios no facilitan un dato fundamental de entrada para calcular el factor K, como es el porcentaje de arena muy fina (AMF). Existen diversos modelos de estimación de la fracción de AMF, que son analizados en este trabajo frente a la mayor base de datos de suelos a escala mundial. Se comprueba que la aceptabilidad de estos modelos es muy baja y se plantea, como alter nativa, el uso de la citada base de datos trasladada al triángulo de textura que ofrece in tervalos cuartílicos de predicción. Se aborda también el problema que plantea la disparidad de intervalos granulométricos según las distintas clasificaciones texturales existentes. La aplicación de fórmulas de eda fotransferencia, como el cálculo del mismo factor K, se ve impedida cuando los datos tex turales aparecen en un sistema distinto del original de la fórmula. El caso más frecuente ocurre con el límite granulométrico de la fracción de limo, el cual en el Sistema USDA abarca el rango de 0,002 a 0,05 mm, mientras que en el Sistema Internacional Simplificado va desde 0,002 hasta 0,02 mm. Con una metodología semejante a la de la AMF se analizan los modelos actuales de conversión entre estos límites texturales; se concluye que uno de estos modelos ofrece resultados aceptables y se indican las regiones del triángulo de tex tura en donde cada modelo tiene un mejor funcionamiento. También se propone una al ternativa para la estimación de la fracción de limo USDA basada en una regresión cuantí lica local. El uso del nomograma de Wischmeier et al. (1971) para el cálculo del factor K resultaba de gran utilidad cuando la disponibilidad de máquinas de cálculo era muy limitada; sin embargo, el cálculo masivo de este factor, para su cartografiado u otras aplicaciones, exige la generación de procedimientos de cálculo analítico. Se ha analizado el nomograma y su ecuación subyacente, así como la calidad del ajuste al nomograma de los modelos analíti cos que tratan de abarcar aquellas regiones donde la ecuación original no era aplicable. Se ha comprobado que todos los modelos tienen zonas de ajuste deficiente o, incluso, inaceptable y que, por las evidencias analizadas, el dibujo de las curvas que ajustaban el factor K en función del contenido en materia orgánica es erróneo en el nomograma. Fi nalmente, se plantea un modelo de cálculo del factor K con un buen ajuste a las distintas partes del nomograma y sin el citado error, que tampoco fue cometido por Wischmeier y Meyer (1973) en su planteamiento analítico. Se muestran también las regiones del trián gulo de textura donde se encuentran los suelos observados por los creadores de la USLE, con vistas a dar una consideración predictiva menor a aquellas regiones en las que los cálculos del factor K estarían extrapolados. Para cerrar el trabajo se ofrece una herramienta que facilita la obtención del factor K para diferentes situaciones de disponibilidad de datos.In this work we perform an analysis of the main problems suffered for the calculation of the K factor of the USLE and a set of improvements is presented, both for the automation of its calculation and to avoid existing errors. One of the main problems is that ordinary soil tests do not provide a basic input to calcu late the K factor, such as the percentage of very fine sand (VFS). There are several models for estimating the fraction of VFS, which are analyzed in this work against the largest soil database worldwide. The acceptability of these models is found to be very low, and we propose, as an alternative, the use of the aforementioned database transferred to texture triangles that offer quartile prediction intervals. The problem posed by the disparity of particle size intervals according to the different existing textural classifications is also addressed. The application of pedotransfer formu las, such as calculating the K factor, is impeded when the textural data appears in a system other than the original of the formula. The most frequent case occurs with the particle size of the silt fraction, which in the USDA System covers the range of 0.002 to 0.05 mm, while in the Simplified International System it ranges from 0.002 to 0.02 mm. Applying a methodology similar to that of the VFS, we analyse the current models of conversion be tween these textural limits; one of these models offers broadly acceptable results; we also indicate the regions of the texture triangle where each model performs better. An alter native for estimating the USDA silt fraction based on a local quantile regression is also proposed. The use of the nomograph of Wischmeier et al. (1971) for the calculation of the K factor was very useful when the access to calculation machines was very limited; However, the massive calculation of this factor, for its mapping or other applications, requires analytical calculation procedures. The nomograph and its underlying equation have been analyzed, as well as the quality of the fit to the nomogram of the analytical models that try to cover those regions where the original equation was not applicable. It has been found that all the models have areas of poor or even unacceptable fit and that, based on the evidence analyzed, the drawing of the curves that adjusted the K factor as a function of the organic matter content is erroneous in the nomograph. Finally, a calculation model for the K factor is proposed with a good fit to the different parts of the nomograph and without the afore mentioned error, which we did not found either in the analytical approach by Wischmeier and Meyer (1973). We also make clear the regions of the texture triangle containing the soils tested by the creators of the USLE in order to give a lower predictive consideration to those regions in which the K factor calculations would be extrapolated. To round off this research, we propose a tool that facilitates obtaining the K factor for different situations of data availability

Comparison of Three Algorithms for the Evaluation of TanDEM-X Data for Gully Detection in Krumhuk Farm (Namibia)

Namibia is a dry and low populated country highly dependent on agriculture, with many areas experiencing land degradation accelerated by climate change. One of the most obvious and damaging manifestations of these degradation processes are gullies, which lead to great economic losses while accelerating desertification. The development of standardized methods to detect and monitor the evolution of gully-a ected areas is crucial to plan prevention and remediation strategies. With the aim of developing solutions applicable at a regional or even national scale, fully automated satellite-based remote sensing methods are explored in this research. For this purpose, three di erent algorithms are applied to a Digital Elevation Model (DEM) generated from the TanDEM-X satellite mission to extract gullies from their geomorphological characteristics: (i) Inverted Morphological Reconstruction (IMR), (ii) Smoothing Moving Polynomial Fitting (SMPF) and (iii) Multi Profile Curvature Analysis (MPCA). These algorithms are adapted or newly developed to identify gullies at the pixel level (12 m) in our study site in the Krumhuk Farm. The results of the three methods are benchmarked with ground truth; specific scenarios are observed to better understand the performance of each method. Results show that MPCA is the most reliable method to identify gullies, achieving an overall accuracy of approximately 0.80 with values of Cohen Kappa close to 0.35. The performance of these parameters improves when detecting large gullies (>30 m width and >3 m depth) achieving Total Accuracies (TA) near to 0.90, Cohen Kappa above 0.5, and User Accuracy (UA) and Producer Accuracy (PA) over 0.50 for the gully class. Small gullies (<12 m wide and <2 m deep) are usually neglected in the classification results due to spatial resolution constraints within the input DEM. In addition, IMR generates accurate results for UA in the gully class (0.94). The MPCA method developed here is a promising tool for the identification of large gullies considering extensive study areas. Nevertheless, further development is needed to improve the accuracy of the algorithms, as well as to derive geomorphological gully parameters (e.g., perimeter and volume) instead of pixel-level classification.This research is complementary to the project DEM_HYDR2024, whose donor was the Deutsches Zentrum fur Luft- und Raumfahrt (DLR) for the used TanDEM-Xdatasets. Fieldwork campaigns needed for this research were funded by Integrated Land Management Institute (ILMI) under grant number RY210400 (http://ilmi.nust.na/) and by the Department of Geo-Spatial Science and Technology (http://fnrss.nust.na/?q=department/geo-spatial-technology) at Namibia University of Science and Technology. Financial support was provided by the Deutsche Forschungsgemeinschaft for Open Access Publishing

Reflexiones sobre la idoneidad de los criterios financieros para establecer edades de corta

La ordenación de montes tiene entre sus objetivos la obtención de masas equilibradas con rentas sostenidas. Un cuartel ordenado es una masa forestal de la que se obtienen aprovechamientos y en la que se hacen inversiones de mejora con frecuencias que pueden variar entre uno y diez años, y que, en todo caso, son siempre muy inferiores al turno de la especie. En este contexto resulta inadecuado plantear la obtención del momento óptimo de corta teniendo en cuenta los años que cuesta capitalizar un rodal de la masa y las inversiones y extracciones de este rodal únicamente. El rodal no es la unidad de gestión, ni la unidad productiva, por lo que para masas ordenadas y cercanas a una situación normal, todo cálculo financiero para determinar la edad de madurez debe referirse a las extracciones e inversiones que se hacen sobre el cuartel. La aplicabilidad de los criterios financieros que se han planteado hasta la fecha desde un punto de vista académico quedaría relegada a parcelas forestales cortadas a hecho en su totalidad al final del turno, lo cual no deja de ser un caso particular, aunque en algunas regiones españolas puedan tener importancia económica

Estimation of water retention capacity in soil: corrections to the CRA pedotransfer formula

El parámetro de capacidad de retención de agua en el suelo (CRA) es un modelo de base física ampliamente utilizado por técnicos forestales e investigadores en ecología forestal del territorio español, como uno de los factores estimadores de las disponibilidades de agua para las plantas y, por ende, de la calidad de estación. Dentro del proyecto Caracterización de suelos forestales de la provincia de Huelva se han apreciado una serie de anomalías en cuanto a los valores obtenidos para el parámetro CRA, especialmente en lo referente a la influencia de la pendiente sobre el modelo para su cálculo, así como en la determinación del agua disponible para la vegetación, en relación a la reserva total. Este trabajo plantea una sencilla modificación del modelo que permite obtener valores de capacidad de retención de agua más acordes con la calidad de la estación, en los terrenos forestales de fuerte pendiente, y también extiende el modelo al cálculo de la máxima reserva de agua disponible en el suelo. La bondad de estos parámetros se contrasta mediante el análisis de correlaciones frente a un índice de calidad de estación, con resultados satisfactorios.In Spain, a physical model to estimate the soil water capacity, which is called the CRA parameter, was implemented by Gandullo (1985). This parameter is broadly used in forest management and forest ecology research in relationship with site index and soil quality variables. While running a soil mapping project in the southwest of Spain some problems related to the CRA model were detected, mainly related to the influence of slope on total soil water capacity, as well as the estimation of available water capacity. A simple correction of the model is proposed in this paper, as well as a complementary parameter for available water capacity. The quality of those new parameters is tested by means of correlation analysis against Site Index variable

Problemas, posibilidades y retos para la integración de los cultivos de frutos rojos en el paisaje del suroeste peninsular

Berry crops take a large area in the southern third of the province of Huelva. They feature a high-tech, intensive agriculture that uses tunnel greenhouses to obtain a product with high added value, in terms of price of the products and direct employment, as well as processing and ancillary industrial activities. This value drives to an intensive use of the land, with large earth-moving, straightening and channeling of water streams, and occupations of hydraulic, road and other public domains. Likewise, this activity generates significant amounts of waste whose handling is often inadequate. This set of circumstances produces significant landscape impacts. The present work identifies and describes the named problems, and proposes possible strategies for landscape restoration and integration. Three types of measures are defined: i) those that tackle illegal situations and thus need correction actions by the owners; ii) those that identify non-punishable irregular territorial uses whose correction can be developed by suggesting the owner to resolve them, subsidizing actions when possible; iii) actions for improvement and creation of natural habitats, as well as the enhancement of general visual quality, whose development can be raised through incentives and training the owners about the possibilities of giving a non-farming use to their farms. The integration of the berry landscapes is an important need for the tourist development of Huelva. In addition, it can arise as an opportunity for those farmers who consider hosting tourism to provide visitors with a unique experience that may promote their products abroad even more, and may also project a better image of this crops.Los cultivos de frutos rojos o berries ocupan una gran superficie en el tercio sur de la provincia de Huelva. Se caracterizan por una agricultura tecnificada, intensiva, que se vale de invernaderos en túnel para la obtención de un producto de alto valor añadido. Este valor induce una ocupación casi total del territorio, con grandes movimientos de tierras, rectificaciones y canalizaciones de arroyos, ocupaciones de dominios públicos hidráulico, viario y otros. Así mismo, esta actividad genera importantes cantidades de residuos cuya manipulación es a menudo inadecuada. Este conjunto de circunstancias produce impactos paisajísticos significativos. En el presente trabajo se identifican y describen los problemas señalados, y se plantean posibles estrategias de integración paisajística. Se definen tres tipos de medidas: i) aquellas que deben responder a situaciones ilegales que deben ser corregidas por los propietarios; ii) aquellas que identifiquen usos territoriales irregulares no sancionables cuya corrección puede desarrollarse instando al propietario a su resolución, incluso incentivándole; iii) medidas de mejora y creación de hábitats naturales y de la imagen visual general cuyo desarrollo puede plantearse mediante incentivos y formación a los propietarios sobre las posibilidades de dar un uso terciario a sus explotaciones. La integración paisajística de las explotaciones de frutos rojos es una necesidad importante para el desarrollo turístico de Huelva. Además, puede constituirse en una oportunidad para aquellos agricultores que se planteen generar espacios visitables que proyecten aún más hacia el exterior un producto y una denominación bien conocidos a escala mundial, pero que necesitan consolidar su imagen