127 research outputs found

    Mapping infiltration in an urbanizing mixed-land-use watershed with multi-temporal satellite imagery

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    Digital soil mapping (DSM) is a field of soil science that aims to improve traditional soil maps by producing higher resolution predictive maps of soil properties using spatial environmental data. DSM has historically relied primarily on static environmental covariates—such as slope gradient, slope aspect, and other topographic variables derived from digital terrain models—for predicting static soil properties, like soil texture. Advancements in satellite imagery and statistical modeling improve the accuracy of digital soil maps by incorporating multi-temporal data that can capture landscape-scale change over relatively short periods of time. Adding these dynamic environmental covariates may be especially useful for spatial prediction of dynamic soil properties, like infiltration rate, that are strongly affected by phenomenon that satellite imagery can detect, like land use that changes rapidly due to human activity. Infiltration strongly impacts soil health and hydrologic characteristics in a watershed. Understanding infiltration for sustainable land management is vital for making best management decisions in urbanizing environments like the West Run Watershed in Morgantown, West Virginia. We hypothesized that infiltration could be predicted at a higher accuracy and a finer spatiotemporal scale using digital soil mapping techniques than is currently provided by the current official soil data and maps produced by the National Cooperative Soil Survey. Spatial predictions of infiltration rate were produced for the West Run watershed using both static and dynamic environmental covariates as inputs into multiple linear regression (MLR) and random forest (RF) models, each of which were made using 10-fold cross validation. Training and independent validation sampling locations were selected using a conditioned Latin hypercube sampling scheme and observed saturated hydraulic conductivity of the soil surface was collected using automated dual-head infiltrometers. The MLR and RF models had R 2 of 0.302 and 0.201, respectively. Validation sampling was stratified by the predicted infiltration values of the MLR model. Validation R 2 values for the MLR and RF models were 0.080 and 0.103. The results from this study will benefit the development of a dynamic soil survey and will improve hydrologic models in this and potentially other mixed-land-use watersheds

    Soil Erosion and Sustainable Land Management (SLM)

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    This Special Issue titled “Soil Erosion and Sustainable Land Management” presents 13 chapters organized into four main parts. The first part deals with assessment of soil erosion that covers historical sediment dating to understand past environmental impacts due to tillage; laboratory simulation to clarify the effect of soil surface microtopography; integrated field observation and the random forest machine learning algorithm to assess watershed-scale soil erosion assessment; and developing the sediment delivery distributed (SEDD) model for sub-watershed erosion risk prioritization. In Part II, the factors controlling soil erosion and vegetation degradation as influenced by topographic positions and climatic regions; long-term land use change; and improper implementation of land management measures are well dealt with. Part III presents different land management technologies that could reduce soil erosion at various spatial scales; improve land productivity of marginal lands with soil microbes; and reclaim degraded farmland using dredged reservoir sediments. The final part relates livelihood diversification to climate vulnerability as well as the coping strategy to the adverse impacts of soil erosion through sustainable land management implementation which opens prospects for policy formulation. The studies cover regions of Africa, Europe, North America and Asia, being dominantly conducted under the framework of international scientific collaborations through employing a range techniques and scales, from the laboratory to watershed scales. We believe those unique features of the book could attract the interest of the wider scientific community worldwide

    Assessing soil redistribution and sediment apportationment from different land uses: geospatial analysis and modelling in a mountain agroecosystem

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    Los agroecosistemas Mediterráneos de montaña han experimentado secularmente intervenciones de la actividad humana como la eliminación de bosques y la cubierta vegetal para el desarrollo y la expansión de la agricultura de secano destinada a la subsistencia de las comunidades locales. Su principal impacto ha sido el incremento de las superficies de terreno proclives a la erosión junto con el aumento de la exportación de sedimentos a los cauces acentuada en las últimas décadas con la mecanización agraria. Sin embargo, este proceso se invirtió a mediados del siglo XX debido a diversos cambios socioeconómicos y posteriormente a la política agraria común que provocaron un éxodo rural y el abandono de estos sistemas. Este abandono permitió la recuperación de la vegetación y la consiguiente variación en la cobertera vegetal. Estos factores junto con la intensificación agrícola y la repoblación forestal han afectado de manera significativa al comportamiento hidrológico, las propiedades del suelo y las tasas de exportación de sedimentos en los agroecosistemas de montaña mediterráneos. El objetivo principal de esta investigación es analizar el efecto de los cambios en los usos del suelo junto con el impacto de las diferentes prácticas agrícolas en la conectividad hidráulica, la redistribución del suelo, sus propiedades fisicoquímicas, así como en la procedencia de los sedimentos exportados a los cursos de agua. Para conseguir este objetivo, se seleccionó una cuenca de tamaño medio (23 km2) localizada en la parte central de la cuenca del Ebro (NE España), representativa de los agroecosistemas de las montañas mediterráneas. El área de estudio ha permanecido cultivada casi en su totalidad hasta principios del siglo pasado. Sin embargo, después del abandono acaecido en la década de los 60 sólo el 16.5% de la cuenca se ha mantenido cultivado mientras que las áreas forestales bien de repoblación o de revegetación han pasado a ocupar el 83.5% de la superficie de la cuenca.En esta investigación se han implementado diferentes técnicas y metodologías, las cuales se han agrupado en dos líneas principales. Por un lado aquellas que analizan la variación en la conectividad hidráulica, las propiedades del suelo, los cambios en la cubierta vegetal y las tasas de redistribución del suelo. Por otro, las englobadas en la técnica de fingerprinting para el rastreo de la procedencia de los sedimentos que llegan a los cursos de agua. En el primer grupo cabe destacar la creación de un índice de conectividad hidráulica y su análisis antes y después del abandono de tierras en la cuenca. Además, mediante el uso del radioisótopo 137Cs se han cuantificado las tasas de redistribución del suelo en los distintos usos y se han comparado con propiedades del suelo como el tamaño de partícula o la cantidad de materia orgánica. En tercer lugar, se llevó a cabo un análisis de la distribución espacial de las propiedades fisicoquímicas del suelo junto con algunos nutrientes como el carbono orgánico de suelo o el nitrógeno total. Finalmente, mediante el uso de imágenes de satélite se monitorizó el cambio que la cubierta vegetal ha experimentado en las últimas décadas, correlacionando a su vez estas imágenes con datos del contenido de carbono y nitrógeno.Por otro lado, para obtener la información acerca de cuáles son las áreas que exportan sedimentos a los cursos de agua se han aplicado métodos de vanguardia como la técnica de fingerprinting junto a modelos de desmezcla. Para ello se ha desarrollado un modelo de desmezcla como paquete de R denominado FingerPro. Además, ya que la técnica requiere de diferentes métodos estadísticos para la selección de los trazadores, aquellos más utilizados por la comunidad científica se han incluido en este paquete como funciones adicionales. Sin embargo, los métodos estadísticos clásicos presentan varias limitaciones, siendo la principal que el uso de un método u otro puede dar lugar a la selección de diferentes trazadores, resultando así diferentes resultados de los modelos. Para superar la limitación de los métodos estadísticos clásicos, se ha desarrollado un nuevo método de selección de trazadores que previene la inclusión de trazadores no conservativos y discordantes, mejorando las capacidades de los métodos previos. Finalmente, mediante el uso de estas técnicas con distintos tipos de trazadores tales como radionucleidos, geoquímica elemental, propiedades magnéticas e isótopos estables ha sido posible cuantificar el efecto de eventos extremos de tormenta, las prácticas agrícolas y la tala en los bosques de repoblación, así como su impacto en la variación de los aportes de sedimento y su procedencia.Las diferentes técnicas implementadas para cuantificar y modelar el efecto del abandono de tierras, la distribución espacial de usos del suelo y las prácticas asociadas a estos han dado lugar a conclusiones similares. Una de las principales conclusiones es que son las tierras de cultivo las que presentan menor contenido en nutrientes, experimentan mayores tasas de redistribución de suelo y las que producen una mayor exportación de sedimento a los cursos de agua. Además, se ha comprobado que las prácticas agrícolas son uno de los mayores desencadenantes del aumento en las exportaciones de sedimento y contaminantes a los cauces. También se observó que durante las tareas de clareo de los pinares de repoblación las áreas afectadas producen una mayor contribución de sedimentos a los cauces lo cual se pudo monitorizar gracias al uso pionero de los trazadores CSSI en ambientes Mediterráneos. Por otro lado, los resultados de esta investigación han evidenciado el gran impacto de eventos extremos de tormenta en términos de erosión en toda la cuenca, produciendo además una gran exportación de sedimentos constituyendo uno de los procesos de mayor afectación en los agroecosistemas mediterráneos de montaña.Los resultados obtenidos han permitido comprender el impacto de los cambios de l uso de la tierra en las propiedades del suelo y su redistribución, lo que es esencial para la gestión de la tierra en los frágiles agroecosistemas mediterráneos. La creación de un paquete de software libre junto con un método mejorado de selección de trazadores ha permitido rastrear con éxito la procedencia de los sedimentos exportados, lo cual no podría haberse logrado con los métodos convencionales. Además los resultados de la técnica de fingerprinting, resaltan los peligros de las tormentas excepcionales al incrementar en gran medida la exportación de partículas finas y modificar la contribución de las distintas fuentes de sedimento respaldando así la protección de las tierras de cultivo, especialmente en períodos de ausencia de cobertura vegetal y mayor ocurrencia de tormentas convectivas para evitar la pérdida de suelo fértil y la exportación de contaminantes a los cursos y cuerpos de agua aguas abajo.<br /

    Soil threats in Europe

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    Although there is a large body of knowledge available on soil threats in Europe, this knowledge is fragmented and incomplete, in particular regarding the complexity and functioning of soil systems and their interaction with human activities. The main aim of RECARE is to develop effective prevention, remediation and restoration measures using an innovative trans-disciplinary approach, actively integrating and advancing knowledge of stakeholders and scientists in 17 Case Studies, covering a range of soil threats in different bio-physical and socio-economic environments across Europe. Existing national and EU policies will be reviewed and compared to identify potential incoherence, contradictions and synergies. Policy messages will be formulated based on the Case Study results and their integration at European level. A comprehensive dissemination and communication strategy, including the development of a web-based Dissemination and Communication Hub, will accompany the other activities to ensure that project results are disseminated to a variety of stakeholders at the right time and in the appropriate formats to stimulate renewed care for European soils.JRC.H.5-Land Resources Managemen

    The data concept behind the data: From metadata models and labelling schemes towards a generic spectral library

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    Spectral libraries play a major role in imaging spectroscopy. They are commonly used to store end-member and spectrally pure material spectra, which are primarily used for mapping or unmixing purposes. However, the development of spectral libraries is time consuming and usually sensor and site dependent. Spectral libraries are therefore often developed, used and tailored only for a specific case study and only for one sensor. Multi-sensor and multi-site use of spectral libraries is difficult and requires technical effort for adaptation, transformation, and data harmonization steps. Especially the huge amount of urban material specifications and its spectral variations hamper the setup of a complete spectral library consisting of all available urban material spectra. By a combined use of different urban spectral libraries, besides the improvement of spectral inter- and intra-class variability, missing material spectra could be considered with respect to a multi-sensor/ -site use. Publicly available spectral libraries mostly lack the metadata information that is essential for describing spectra acquisition and sampling background, and can serve to some extent as a measure of quality and reliability of the spectra and the entire library itself. In the GenLib project, a concept for a generic, multi-site and multi-sensor usable spectral library for image spectra on the urban focus was developed. This presentation will introduce a 1) unified, easy-to-understand hierarchical labeling scheme combined with 2) a comprehensive metadata concept that is 3) implemented in the SPECCHIO spectral information system to promote the setup and usability of a generic urban spectral library (GUSL). The labelling scheme was developed to ensure the translation of individual spectral libraries with their own labelling schemes and their usually varying level of details into the GUSL framework. It is based on a modified version of the EAGLE classification concept by combining land use, land cover, land characteristics and spectral characteristics. The metadata concept consists of 59 mandatory and optional attributes that are intended to specify the spatial context, spectral library information, references, accessibility, calibration, preprocessing steps, and spectra specific information describing library spectra implemented in the GUSL. It was developed on the basis of existing metadata concepts and was subject of an expert survey. The metadata concept and the labelling scheme are implemented in the spectral information system SPECCHIO, which is used for sharing and holding GUSL spectra. It allows easy implementation of spectra as well as their specification with the proposed metadata information to extend the GUSL. Therefore, the proposed data model represents a first fundamental step towards a generic usable and continuously expandable spectral library for urban areas. The metadata concept and the labelling scheme also build the basis for the necessary adaptation and transformation steps of the GUSL in order to use it entirely or in excerpts for further multi-site and multi-sensor applications

    AMMONIA EMISSIONS FROM ARABLE LANDS IN PO VALLEY: METHODOLOGIES, DYNAMICS AND QUANTIFICATION.

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    Although the Po Valley (north Italy) is considered one of the most important ammonia (NH3) emitting regions in Europe, few data are available for an evaluation of the ammonia budget at field level in arable lands. Here the NH3 losses were quantify, considering different measurement and estimation approach, fertilisers and agronomic managements. The outputs of two concentration based-inverse dispersion models, together a mechanistic model were assessed with the direct measurements of ammonia fluxes by the micrometeorological technique eddy covariance, at hourly, daily and seasonal scales. A discussion on advantages, disadvantages and performances of each model is given in order to determine the most suitable method able to evaluate the ammonia emission in Po Valley at field scale. The selected inverse dispersion models were assessed in their uncertainty to quantify ammonia emissions rates, and their significance with regards to the Italian context. Moreover emissions from cattle slurry and urea application were performed in seven field trials in three different locations of Po Valley, in order to evaluate the best practices in reducing NH3 loss from arable land. The emission factors relative to different agronomical practices (slurry injection, slurry surface spreading with and without incorporation, urea surface spreading) are given, taking into account the main factors affecting the NH3 volatilization phenomenon and describing its dynamics

    Remote sensing of snow : Factors influencing seasonal snow mapping in boreal forest region

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    Monitoring of snow cover in northern hemisphere is highly important for climate research and for operational activities, such as those related to hydrology and weather forecasting. The appearance and melting of seasonal snow cover dominate the hydrological and climatic patterns in the boreal and arctic regions. Spatial variability (in particular during the spring and autumn transition months) and long-term trends in global snow cover distribution are strongly interconnected to changes in Earth System (ES). Satellite data based estimates on snow cover extent are utilized e.g. in near-real-time hydrological forecasting, water resource management and to construct long-term Climate Data Records (CDRs) essential for climate research. Information on the quantitative reliability of snow cover monitoring is urgently needed by these different applications as the usefulness of satellite data based results is strongly dependent on the quality of the interpretation. This doctoral dissertation investigates the factors affecting the reliability of snow cover monitoring using optical satellite data and focuses on boreal regions (zone characterized by seasonal snow cover). Based on the analysis of different factors relevant to snow mapping performance, the work introduces a methodology to assess the uncertainty of snow cover extent estimates, focusing on the retrieval of fractional snow cover (within a pixel) during the spring melt period. The results demonstrate that optical remote sensing is well suited for determining snow extent in the melting season and that the characterizing the uncertainty in snow estimates facilitates the improvement of the snow mapping algorithms. The overall message is that using a versatile accuracy analysis it is possible to develop uncertainty estimates for the optical remote sensing of snow cover, which is a considerable advance in remote sensing. The results of this work can also be utilized in the development of other interpretation algorithms. This thesis consists of five articles predominantly dealing with quantitative data analysis, while the summary chapter synthesizes the results mainly in the algorithm accuracy point of view. The first four articles determine the reflectance characteristics essential for the forward and inverse modeling of boreal landscapes (forward model describes the observations as a function of the investigated variable). The effects of snow, snow-free ground and boreal forest canopy on the observed satellite scene reflectance are specified. The effects of all the error components are clarified in the fifth article and a novel experimental method to analyze and quantify the amount of uncertainty is presented. The five articles employ different remote sensing and ground truth data sets measured and/or analyzed for this research, covering the region of Finland and also applied to boreal forest region in northern Europe

    The inevitability of arbuscular mycorrhiza for sustainability in organic agriculture—A critical review

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    The arbuscular mycorrhizal fungi (AMF) are significant fertility-promoting microbes in soils. They enable soil fertility, soil-health and boost crop productivity. There are generalist and specialist groups among AMF in natural soils. Optimized use of specific AMF concerning crops and soils can improve agricultural sustainability. Thus, AMF is becoming an inevitable biological tool for improving crop productivity and soil health. Especially in the context of chemicalized agriculture undermining the sustainability of food security, safety, and human and ecosystem health, alternative agricultural means have become inevitable. Therefore, AMF has become essential in nature-friendly, organic agriculture. Of such farm fields, natural biological activity is enhanced to sustain soil fertility. Crops show increased innate immunity against pests and diseases in many such systems. Moreover, ecosystems remain healthy, and the soil is teeming with life in such farms. The primary goal of the review was a thorough critical analysis of the literature on AMF in organic agriculture to assess its efficiency as an ecotechnological tool in sustainable agricultural productivity. The novelty is that this is the first comprehensive review of literature on AMF concerning all aspects of organic agriculture. A vital systematic approach to the exhaustive literature collected using regular databases on the theme is followed for synthesizing the review. The review revealed the essentiality of utilizing specific mycorrhizal species, individually or in consortia, in diverse environmental settings to ensure sustainable organic crop production. However, for the exact usage of specific AMF in sustainable organic agriculture, extensive exploration of them in traditional pockets of specific crop cultivations of both chemical and organic fields and wild environments is required. Moreover, intensive experimentations are also necessary to assess them individually, in combinations, and associated with diverse beneficial soil bacteria
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