986 resultados para field capacity


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Das wichtigste Oxidationsmittel für den Abbau flüchtiger Kohlenwasserstoffverbindungen (VOC, engl.: volatile organic compounds) in der Atmosphäre ist das Hydroxylradikal (OH), welches sich in einem schnellen chemischen Gleichgewicht mit dem Hydroperoxylradical (HO2) befindet. Bisherige Messungen und Modellvergleiche dieser Radikalspezies in Waldgebieten haben signifikante Lücken im Verständnis der zugrundeliegenden Prozesse aufgezeigt.rnIm Rahmen dieser Doktorarbeit wurden Messungen von OH- und HO2-Radikalen mittelsrnlaserinduzierten Fluoreszensmesstechnik (LIF, engl.: laser-induced fluorescence) in einem Nadelwald in Süd-Finnland während der Messkampagne HUMPPA–COPEC–2010 (Hyytiälä United Measurements of Photochemistry and Particles in Air – Comprehensive Organic Precursor Emission and Concentration study) im Sommer 2010 durchgeführt. Unterschiedliche Komponenten des LIF-Instruments wurden verbessert. Eine modifizierte Methode zur Bestimmung des Hintergrundsignals (engl.: InletPreInjector technique) wurde in den Messaufbaurnintegriert und erstmals zur Messung von atmosphärischem OH verwendet. Vergleichsmessungen zweier Instrumente basierend auf unterschiedlichen Methoden zur Messung von OH-Radikalen, chemische Ionisationsmassenspektrometrie (CIMS - engl.: chemical ionization mass spectrometry) und LIF-Technik, zeigten eine gute Übereinstimmung. Die Vergleichsmessungen belegen das Vermögen und die Leistungsfähigkeit des modifizierten LIF-Instruments atmosphärische OH Konzentrationen akkurat zu messen. Nachfolgend wurde das LIF-Instrument auf der obersten Plattform eines 20m hohen Turmes positioniert, um knapp oberhalb der Baumkronen die Radikal-Chemie an der Schnittstelle zwischen Ökosystem und Atmosphäre zu untersuchen. Umfangreiche Messungen - dies beinhaltet Messungen der totalen OH-Reaktivität - wurden durchgeführt und unter Verwendung von Gleichgewichtszustandsberechnungen und einem Boxmodell, in welches die gemessenen Daten als Randbedingungen eingehen, analysiert. Wenn moderate OH-Reaktivitäten(k′(OH)≤ 15 s−1) vorlagen, sind OH-Produktionsraten, die aus gemessenen Konzentrationen von OH-Vorläuferspezies berechnet wurden, konsistent mit Produktionsraten, die unter der Gleichgewichtsannahme von Messungen des totalen OH Verlustes abgeleitet wurden. Die primären photolytischen OH-Quellen tragen mit einem Anteil von bis zu einem Drittel zur Gesamt-OH-Produktion bei. Es wurde gezeigt, dass OH-Rezyklierung unter Bedingungen moderater OH-Reaktivität hauptsächlich durch die Reaktionen von HO2 mit NO oder O3 bestimmt ist. Während Zeiten hoher OH-Reaktivität (k′(OH) > 15 s−1) wurden zusätzliche Rezyklierungspfade, die nicht über die Reaktionen von HO2 mit NO oder O3, sondern direkt OH bilden, aufgezeigt.rnFür Hydroxylradikale stimmen Boxmodell-Simulationen und Messungen gut übereinrn(OHmod/OHobs=1.04±0.16), während HO2-Mischungsverhältnisse in der Simulation signifikant unterschätzt werden (HO2mod/HO2obs=0.3±0.2) und die simulierte OH-Reaktivität nicht mit der gemessenen OH-Reaktivität übereinstimmt. Die gleichzeitige Unterschätzung der HO2-Mischungsverhältnisse und der OH-Reaktivität, während OH-Konzentrationen von der Simulation gut beschrieben werden, legt nahe, dass die fehlende OH-Reaktivität in der Simulation eine noch unberücksichtigte HO2-Quelle darstellt. Zusätzliche, OH-unabhängigernRO2/HO2-Quellen, wie z.B. der thermische Zerfall von herantransportiertem peroxyacetylnitrat (PAN) und die Photolyse von Glyoxal sind indiziert.

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Für das Vermögen der Atmosphäre sich selbst zu reinigen spielen Stickstoffmonoxid (NO) und Stickstoffdioxid (NO2) eine bedeutende Rolle. Diese Spurengase bestimmen die photochemische Produktion von Ozon (O3) und beeinflussen das Vorkommen von Hydroxyl- (OH) und Nitrat-Radikalen (NO3). Wenn tagsüber ausreichend Solarstrahlung und Ozon vorherrschen, stehen NO und NO2 in einem schnellen photochemischen Gleichgewicht, dem „Photostationären Gleichgewichtszustand“ (engl.: photostationary state). Die Summe von NO und NO2 wird deshalb als NOx zusammengefasst. Vorhergehende Studien zum photostationären Gleichgewichtszustand von NOx umfassen Messungen an unterschiedlichsten Orten, angefangen bei Städten (geprägt von starken Luftverschmutzungen), bis hin zu abgeschiedenen Regionen (geprägt von geringeren Luftverschmutzungen). Während der photochemische Kreislauf von NO und NO2 unter Bedingungen erhöhter NOx-Konzentrationen grundlegend verstanden ist, gibt es in ländlicheren und entlegenen Regionen, welche geprägt sind von niedrigeren NOx-Konzetrationen, signifikante Lücken im Verständnis der zugrundeliegenden Zyklierungsprozesse. Diese Lücken könnten durch messtechnische NO2-Interferenzen bedingt sein - insbesondere bei indirekten Nachweismethoden, welche von Artefakten beeinflusst sein können. Bei sehr niedrigen NOx-Konzentrationen und wenn messtechnische NO2-Interferenzen ausgeschlossen werden können, wird häufig geschlussfolgert, dass diese Verständnislücken mit der Existenz eines „unbekannten Oxidationsmittels“ (engl.: unknown oxidant) verknüpft ist. Im Rahmen dieser Arbeit wird der photostationäre Gleichgewichtszustand von NOx analysiert, mit dem Ziel die potenzielle Existenz bislang unbekannter Prozesse zu untersuchen. Ein Gasanalysator für die direkte Messung von atmosphärischem NO¬2 mittels laserinduzierter Fluoreszenzmesstechnik (engl. LIF – laser induced fluorescence), GANDALF, wurde neu entwickelt und während der Messkampagne PARADE 2011 erstmals für Feldmessungen eingesetzt. Die Messungen im Rahmen von PARADE wurden im Sommer 2011 in einem ländlich geprägten Gebiet in Deutschland durchgeführt. Umfangreiche NO2-Messungen unter Verwendung unterschiedlicher Messtechniken (DOAS, CLD und CRD) ermöglichten einen ausführlichen und erfolgreichen Vergleich von GANDALF mit den übrigen NO2-Messtechniken. Weitere relevante Spurengase und meteorologische Parameter wurden gemessen, um den photostationären Zustand von NOx, basierend auf den NO2-Messungen mit GANDALF in dieser Umgebung zu untersuchen. Während PARADE wurden moderate NOx Mischungsverhältnisse an der Messstelle beobachtet (10^2 - 10^4 pptv). Mischungsverhältnisse biogener flüchtige Kohlenwasserstoffverbindungen (BVOC, engl.: biogenic volatile organic compounds) aus dem umgebenden Wald (hauptsächlich Nadelwald) lagen in der Größenordnung 10^2 pptv vor. Die Charakteristiken des photostationären Gleichgewichtszustandes von NOx bei niedrigen NOx-Mischungsverhältnissen (10 - 10^3 pptv) wurde für eine weitere Messstelle in einem borealen Waldgebiet während der Messkampagne HUMPPA-COPEC 2010 untersucht. HUMPPA–COPEC–2010 wurde im Sommer 2010 in der SMEARII-Station in Hyytiälä, Süd-Finnland, durchgeführt. Die charakteristischen Eigenschaften des photostationären Gleichgewichtszustandes von NOx in den beiden Waldgebieten werden in dieser Arbeit verglichen. Des Weiteren ermöglicht der umfangreiche Datensatz - dieser beinhaltet Messungen von relevanten Spurengasen für die Radikalchemie (OH, HO2), sowie der totalen OH-Reaktivität – das aktuelle Verständnis bezüglich der NOx-Photochemie unter Verwendung von einem Boxmodell, in welches die gemessenen Daten als Randbedingungen eingehen, zu überprüfen und zu verbessern. Während NOx-Konzentrationen in HUMPPA-COPEC 2010 niedriger sind, im Vergleich zu PARADE 2011 und BVOC-Konzentrationen höher, sind die Zyklierungsprozesse von NO und NO2 in beiden Fällen grundlegend verstanden. Die Analyse des photostationären Gleichgewichtszustandes von NOx für die beiden stark unterschiedlichen Messstandorte zeigt auf, dass potenziell unbekannte Prozesse in keinem der beiden Fälle vorhanden sind. Die aktuelle Darstellung der NOx-Chemie wurde für HUMPPA-COPEC 2010 unter Verwendung des chemischen Mechanismus MIM3* simuliert. Die Ergebnisse der Simulation sind konsistent mit den Berechnungen basierend auf dem photostationären Gleichgewichtszustand von NOx.

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Energy crisis and worldwide environmental problem make hydrogen a prospective energy carrier. However, storage and transportation of hydrogen in large quantities at small volume is currently not practical. Lots of materials and devices have been developed for storage hydrogen, but to today none is able to meet the DOE targets. Activated carbon has been found to be a good hydrogen adsorbent due to its high surface area. However, the weak van der Waals force between hydrogen and the adsorbent has limited the adsorption capacity. Previous studies have found that enhanced adsorption can be obtained with applied electric field. Stronger interaction between the polarized hydrogen and the charged sorbents under high voltage is considered as the reason. This study was initiated to investigate if the adsorption can be further enhanced when the activated carbon particles are separated with a dielectric coating. Dielectric TiO2 nanoparticles were first utilized. Hydrogen adsorption measurements on the TiO2-coated carbon materials, with or without an external electric field, were made. The results showed that the adsorption capacity enhancement increased with the increasing amount of TiO2 nanoparticles with an applied electric field. Since the hydrogen adsorption capacity on TiO2 particles is very low and there is no hydrogen adsorption enhancement on TiO2 particles alone when electric field is applied, the effect of dielectric coating is demonstrated. Another set of experiments investigated the behavior of hydrogen adsorption over TiO2-coated activated carbon under various electric potentials. The results revealed that the hydrogen adsorption first increased and then decreased with the increase of electric field. The improved storage was due to a stronger interaction between charged carbon surface and polarized hydrogen molecule caused by field induced polarization of TiO2 coating. When the electric field was sufficient to cause considerable ionization of hydrogen, the decrease of hydrogen adsorption occurred. The current leak detected at 3000 V was a sign of ionization of hydrogen. Experiments were also carried out to examine the hydrogen adsorption performances over activated carbon separated by other dielectric materials, MgO, ZnO and BaTiO3, respectively. For the samples partitioned with MgO and ZnO, the measurements with and without an electric field indicated negligible differences. Electric field enhanced adsorption has been observed on the activated carbon separated with BaTiO3, a material with unusually high dielectric constant. Corresponding computational calculations using Density Functional Theory have been performed on hydrogen interaction with charged TiO2 molecule as well as TiO2 molecule, coronene and TiO2-doped coronene in the presence of an electric field. The simulated results were consistent with the observations from experiments, further confirming the proposed hypotheses.

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A significant cost for foundations is the design and installation of piles when they are required due to poor ground conditions. Not only is it important that piles be designed properly, but also that the installation equipment and total cost be evaluated. To assist in the evaluation of piles a number of methods have been developed. In this research three of these methods were investigated, which were developed by the Federal Highway Administration, the US Corps of Engineers and the American Petroleum Institute (API). The results from these methods were entered into the program GRLWEAPTM to assess the pile drivability and to provide a standard base for comparing the three methods. An additional element of this research was to develop EXCEL spreadsheets to implement these three methods. Currently the Army Corps and API methods do not have publicly available software and must be performed manually, which requires that data is taken off of figures and tables, which can introduce error in the prediction of pile capacities. Following development of the EXCEL spreadsheet, they were validated with both manual calculations and existing data sets to ensure that the data output is correct. To evaluate the three pile capacity methods data was utilized from four project sites from North America. The data included site geotechnical data along with field determined pile capacities. In order to achieve a standard comparison of the data, the pile capacities and geotechnical data from the three methods were entered into GRLWEAPTM. The sites consisted of both cohesive and cohesionless soils; where one site was primarily cohesive, one was primarily cohesionless, and the other two consisted of inter-bedded cohesive and cohesionless soils. Based on this limited set of data the results indicated that the US Corps of Engineers method more closely compared with the field test data, followed by the API method to a lesser degree. The DRIVEN program compared favorably in cohesive soils, but over predicted in cohesionless material.

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There is a need for accurate predictions of ecosystem carbon (C) and water fluxes in field conditions. Previous research has shown that ecosystem properties can be predicted from community abundance-weighted means (CWM) of plant functional traits and measures of trait variability within a community (FDvar). The capacity for traits to predict carbon (C) and water fluxes, and the seasonal dependency of these trait-function relationships has not been fully explored. Here we measured daytime C and water fluxes over four seasons in grasslands of a range of successional ages in southern England. In a model selection procedure, we related these fluxes to environmental covariates and plant biomass measures before adding CWM and FDvar plant trait measures that were scaled up from measures of individual plants grown in greenhouse conditions. Models describing fluxes in periods of low biological activity contained few predictors, which were usually abiotic factors. In more biologically active periods, models contained more predictors, including plant trait measures. Field-based plant biomass measures were generally better predictors of fluxes than CWM and FDvar traits. However, when these measures were used in combination traits accounted for additional variation. Where traits were significant predictors their identity often reflected seasonal vegetation dynamics. These results suggest that database derived trait measures can improve the prediction of ecosystem C and water fluxes. Controlled studies and those involving more detailed flux measurements are required to validate and explore these findings, a worthwhile effort given the potential for using simple vegetation measures to help predict landscape-scale fluxes.

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The goal of the present article is to introduce dual-process theories – in particular the default-interventionist model – as an overarching framework for attention-related research in sports. Dual-process theories propose that two different types of processing guide human behavior. Type 1 processing is independent of available working memory capacity (WMC), whereas Type 2 processing depends on available working memory capacity. We review the latest theoretical developments on dual-process theories and present evidence for the validity of dual-process theories from various domains. We demonstrate how existing sport psychology findings can be integrated within the dual-process framework. We illustrate how future sport psychology research might benefit from adopting the dual-process framework as a meta-theoretical framework by arguing that the complex interplay between Type 1 and Type 2 processing has to be taken into account in order to gain a more complete understanding of the dynamic nature of attentional processing during sport performance at varying levels of expertise. Finally, we demonstrate that sport psychology applications might benefit from the dual-process perspective as well: dual-process theories are able to predict which behaviors can be more successfully executed when relying on Type 1 processing and which behaviors benefit from Type 2 processing.

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Field studies were conducted in walk-in tunnels to determine the flying capacity in the presence and absence of crop, of the parasitoid Psyttalia concolor and the predator Chrysoperla carnea under a UV-absorbent net (Bionet®). Yellow sticky cards were used for insect recovery but neither P. concolor nor C. carnea were very attracted to them, thus captures were too low to permit any meaningful comparisons. Bionet® did not seem to affect the mobility of any natural enemy irrespective of the trap location and monitoring hour. Climatic conditions inside nets were very extreme (average temperatures very high and relative humidity very low) threatening insect survival. New experiments are being developed, trying to find new attractants that permit a significant capture of both natural enemies.

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Aims Agricultural soils in semiarid Mediterranean areas are characterized by low organic matter contents and low fertility levels. Application of crop residues and/or manures as amendments is a cost-effective and sustainable alternative to overcome this problem. However, these management practices may induce important changes in the nitrogen oxide emissions from these agroecosystems, with additional impacts on carbon dioxide emissions. In this context, a field experiment was carried out with a barley (Hordeum vulgare L.) crop under Mediterranean conditions to evaluate the effect of combining maize (Zea mays L.) residues and N fertilizer inputs (organic and/or mineral) on these emissions. Methods Crop yield and N uptake, soil mineral N concentrations, dissolved organic carbon (DOC), denitrification capacity, N2O, NO and CO2 fluxes were measured during the growing season. Results The incorporation of maize stover increased N2O emissions during the experimental period by c. 105 %. Conversely, NO emissions were significantly reduced in the plots amended with crop residues. The partial substitution of urea by pig slurry reduced net N2O emissions by 46 and 39 %, with and without the incorporation of crop residues respectively. Net emissions of NO were reduced 38 and 17 % for the same treatments. Molar DOC:NO 3 − ratio was found to be a robust predictor of N2O and NO fluxes. Conclusions The main effect of the interaction between crop residue and N fertilizer application occurred in the medium term (4–6 month after application), enhancing N2O emissions and decreasing NO emissions as consequence of residue incorporation. The substitution of urea by pig slurry can be considered a good management strategy since N2O and NO emissions were reduced by the use of the organic residue.

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Assuring the sustainability of quality in photovoltaic rural electrification programmes involves enhancing the reliability of the components of solar home systems as well as the characterization of the overall programme cost structure. Batteries and photovoltaic modules have a great impact on both the reliability and the cost assessment, the battery being the weakest component of the solar home system and consequently the most expensive element of the programme. The photovoltaic module, despite being the most reliable component, has a significant impact cost-wise on the initial investment, even at current market prices. This paper focuses on the in-field testing of both batteries and photovoltaic modules working under real operating conditions within a sample of 41 solar home systems belonging to a large photovoltaic rural electrification programme with more than 13,000 installed photovoltaic systems. Different reliability parameters such as lifetime have been evaluated, taking into account different factors, for example energy consumption rates, or the manufacturing quality of batteries. A degradation model has been proposed relating both loss of capacity and time of operation. The user e solar home system binomial is also analysed in order to understand the meaning of battery lifetime in rural electrification.

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Existe una creciente necesidad de hacer el mejor uso del agua para regadío. Una alternativa eficiente consiste en la monitorización del contenido volumétrico de agua (θ), utilizando sensores de humedad. A pesar de existir una gran diversidad de sensores y tecnologías disponibles, actualmente ninguna de ellas permite obtener medidas distribuidas en perfiles verticales de un metro y en escalas laterales de 0.1-1,000 m. En este sentido, es necesario buscar tecnologías alternativas que sirvan de puente entre las medidas puntuales y las escalas intermedias. Esta tesis doctoral se basa en el uso de Fibra Óptica (FO) con sistema de medida de temperatura distribuida (DTS), una tecnología alternativa de reciente creación que ha levantado gran expectación en las últimas dos décadas. Específicamente utilizamos el método de fibra calentada, en inglés Actively Heated Fiber Optic (AHFO), en la cual los cables de Fibra Óptica se utilizan como sondas de calor mediante la aplicación de corriente eléctrica a través de la camisa de acero inoxidable, o de un conductor eléctrico simétricamente posicionado, envuelto, alrededor del haz de fibra óptica. El uso de fibra calentada se basa en la utilización de la teoría de los pulsos de calor, en inglés Heated Pulsed Theory (HPP), por la cual el conductor se aproxima a una fuente de calor lineal e infinitesimal que introduce calor en el suelo. Mediante el análisis del tiempo de ocurrencia y magnitud de la respuesta térmica ante un pulso de calor, es posible estimar algunas propiedades específicas del suelo, tales como el contenido de humedad, calor específico (C) y conductividad térmica. Estos parámetros pueden ser estimados utilizando un sensor de temperatura adyacente a la sonda de calor [método simple, en inglés single heated pulsed probes (SHPP)], ó a una distancia radial r [método doble, en inglés dual heated pulsed probes (DHPP)]. Esta tesis doctoral pretende probar la idoneidad de los sistemas de fibra óptica calentada para la aplicación de la teoría clásica de sondas calentadas. Para ello, se desarrollarán dos sistemas FO-DTS. El primero se sitúa en un campo agrícola de La Nava de Arévalo (Ávila, España), en el cual se aplica la teoría SHPP para estimar θ. El segundo sistema se desarrolla en laboratorio y emplea la teoría DHPP para medir tanto θ como C. La teoría SHPP puede ser implementada con fibra óptica calentada para obtener medidas distribuidas de θ, mediante la utilización de sistemas FO-DTS y el uso de curvas de calibración específicas para cada suelo. Sin embargo, la mayoría de aplicaciones AHFO se han desarrollado exclusivamente en laboratorio utilizando medios porosos homogéneos. En esta tesis se utiliza el programa Hydrus 2D/3D para definir tales curvas de calibración. El modelo propuesto es validado en un segmento de cable enterrado en una instalación de fibra óptica y es capaz de predecir la respuesta térmica del suelo en puntos concretos de la instalación una vez que las propiedades físicas y térmicas de éste son definidas. La exactitud de la metodología para predecir θ frente a medidas puntuales tomadas con sensores de humedad comerciales fue de 0.001 a 0.022 m3 m-3 La implementación de la teoría DHPP con AHFO para medir C y θ suponen una oportunidad sin precedentes para aplicaciones medioambientales. En esta tesis se emplean diferentes combinaciones de cables y fuentes emisoras de calor, que se colocan en paralelo y utilizan un rango variado de espaciamientos, todo ello en el laboratorio. La amplitud de la señal y el tiempo de llegada se han observado como funciones del calor específico del suelo. Medidas de C, utilizando esta metodología y ante un rango variado de contenidos de humedad, sugirieron la idoneidad del método, aunque también se observaron importantes errores en contenidos bajos de humedad de hasta un 22%. La mejora del método requerirá otros modelos más precisos que tengan en cuenta el diámetro del cable, así como la posible influencia térmica del mismo. ABSTRACT There is an increasing need to make the most efficient use of water for irrigation. A good approach to make irrigation as efficient as possible is to monitor soil water content (θ) using soil moisture sensors. Although, there is a broad range of different sensors and technologies, currently, none of them can practically and accurately provide vertical and lateral moisture profiles spanning 0-1 m depth and 0.1-1,000 m lateral scales. In this regard, further research to fulfill the intermediate scale and to bridge single-point measurement with the broaden scales is still needed. This dissertation is based on the use of Fiber Optics with Distributed Temperature Sensing (FO-DTS), a novel approach which has been receiving growing interest in the last two decades. Specifically, we employ the so called Actively Heated Fiber Optic (AHFO) method, in which FO cables are employed as heat probe conductors by applying electricity to the stainless steel armoring jacket or an added conductor symmetrically positioned (wrapped) about the FO cable. AHFO is based on the classic Heated Pulsed Theory (HPP) which usually employs a heat probe conductor that approximates to an infinite line heat source which injects heat into the soil. Observation of the timing and magnitude of the thermal response to the energy input provide enough information to derive certain specific soil thermal characteristics such as the soil heat capacity, soil thermal conductivity or soil water content. These parameters can be estimated by capturing the soil thermal response (using a thermal sensor) adjacent to the heat source (the heating and the thermal sources are mounted together in the so called single heated pulsed probe (SHPP)), or separated at a certain distance, r (dual heated pulsed method (DHPP) This dissertation aims to test the feasibility of heated fiber optics to implement the HPP theory. Specifically, we focus on measuring soil water content (θ) and soil heat capacity (C) by employing two types of FO-DTS systems. The first one is located in an agricultural field in La Nava de Arévalo (Ávila, Spain) and employ the SHPP theory to estimate θ. The second one is developed in the laboratory using the procedures described in the DHPP theory, and focuses on estimating both C and θ. The SHPP theory can be implemented with actively heated fiber optics (AHFO) to obtain distributed measurements of soil water content (θ) by using reported soil thermal responses in Distributed Temperature Sensing (DTS) and with a soil-specific calibration relationship. However, most reported AHFO applications have been calibrated under laboratory homogeneous soil conditions, while inexpensive efficient calibration procedures useful in heterogeneous soils are lacking. In this PhD thesis, we employ the Hydrus 2D/3D code to define these soil-specific calibration curves. The model is then validated at a selected FO transect of the DTS installation. The model was able to predict the soil thermal response at specific locations of the fiber optic cable once the surrounding soil hydraulic and thermal properties were known. Results using electromagnetic moisture sensors at the same specific locations demonstrate the feasibility of the model to detect θ within an accuracy of 0.001 to 0.022 m3 m-3. Implementation of the Dual Heated Pulsed Probe (DPHP) theory for measurement of volumetric heat capacity (C) and water content (θ) with Distributed Temperature Sensing (DTS) heated fiber optic (FO) systems presents an unprecedented opportunity for environmental monitoring. We test the method using different combinations of FO cables and heat sources at a range of spacings in a laboratory setting. The amplitude and phase-shift in the heat signal with distance was found to be a function of the soil volumetric heat capacity (referred, here, to as Cs). Estimations of Cs at a range of θ suggest feasibility via responsiveness to the changes in θ (we observed a linear relationship in all FO combinations), though observed bias with decreasing soil water contents (up to 22%) was also reported. Optimization will require further models to account for the finite radius and thermal influence of the FO cables, employed here as “needle probes”. Also, consideration of the range of soil conditions and cable spacing and jacket configurations, suggested here to be valuable subjects of further study and development.

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La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, altera los regímenes globales de circulación atmosférica por mecanismos de teleconexión. Estos cambios en la circulación general de la atmósfera afectan a la temperatura, precipitación, humedad, viento, etc., a escala regional, los cuales afectan al crecimiento, desarrollo y rendimiento de los cultivos. Para el caso de Europa, esto implica que la variabilidad atmosférica en una región específica se asocia con la variabilidad de otras regiones adyacentes y/o remotas, como consecuencia Europa está siendo afectada por los patrones de circulaciones globales, que a su vez, se ven afectados por patrones oceánicos. El objetivo general de esta tesis es analizar la variabilidad del rendimiento de los cultivos y su relación con la variabilidad climática y teleconexiones, así como evaluar su predictibilidad. Además, esta Tesis tiene como objetivo establecer una metodología para estudiar la predictibilidad de las anomalías del rendimiento de los cultivos. El análisis se centra en trigo y maíz como referencia para otros cultivos de la PI, cultivos de invierno en secano y cultivos de verano en regadío respectivamente. Experimentos de simulación de cultivos utilizando una metodología en cadena de modelos (clima + cultivos) son diseñados para evaluar los impactos de los patrones de variabilidad climática en el rendimiento y su predictibilidad. La presente Tesis se estructura en dos partes: La primera se centra en el análisis de la variabilidad del clima y la segunda es una aplicación de predicción cuantitativa de cosechas. La primera parte está dividida en 3 capítulos y la segundo en un capitulo cubriendo los objetivos específicos del presente trabajo de investigación. Parte I. Análisis de variabilidad climática El primer capítulo muestra un análisis de la variabilidad del rendimiento potencial en una localidad como indicador bioclimático de las teleconexiones de El Niño con Europa, mostrando su importancia en la mejora de predictibilidad tanto en clima como en agricultura. Además, se presenta la metodología elegida para relacionar el rendimiento con las variables atmosféricas y oceánicas. El rendimiento de los cultivos es parcialmente determinado por la variabilidad climática atmosférica, que a su vez depende de los cambios en la temperatura de la superficie del mar (TSM). El Niño es el principal modo de variabilidad interanual de la TSM, y sus efectos se extienden en todo el mundo. Sin embargo, la predictibilidad de estos impactos es controversial, especialmente aquellos asociados con la variabilidad climática Europea, que se ha encontrado que es no estacionaria y no lineal. Este estudio mostró cómo el rendimiento potencial de los cultivos obtenidos a partir de datos de reanálisis y modelos de cultivos sirve como un índice alternativo y más eficaz de las teleconexiones de El Niño, ya que integra las no linealidades entre las variables climáticas en una única serie temporal. Las relaciones entre El Niño y las anomalías de rendimiento de los cultivos son más significativas que las contribuciones individuales de cada una de las variables atmosféricas utilizadas como entrada en el modelo de cultivo. Además, la no estacionariedad entre El Niño y la variabilidad climática europea se detectan con mayor claridad cuando se analiza la variabilidad de los rendimiento de los cultivos. La comprensión de esta relación permite una cierta predictibilidad hasta un año antes de la cosecha del cultivo. Esta predictibilidad no es constante, sino que depende tanto la modulación de la alta y baja frecuencia. En el segundo capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de verano en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de maíz en la PI para todo el siglo veinte, usando un modelo de cultivo calibrado en 5 localidades españolas y datos climáticos de reanálisis para obtener series temporales largas de rendimiento potencial. Este estudio evalúa el uso de datos de reanálisis para obtener series de rendimiento de cultivos que dependen solo del clima, y utilizar estos rendimientos para analizar la influencia de los patrones oceánicos y atmosféricos. Los resultados muestran una gran fiabilidad de los datos de reanálisis. La distribución espacial asociada a la primera componente principal de la variabilidad del rendimiento muestra un comportamiento similar en todos los lugares estudiados de la PI. Se observa una alta correlación lineal entre el índice de El Niño y el rendimiento, pero no es estacionaria en el tiempo. Sin embargo, la relación entre la temperatura del aire y el rendimiento se mantiene constante a lo largo del tiempo, siendo los meses de mayor influencia durante el período de llenado del grano. En cuanto a los patrones atmosféricos, el patrón Escandinavia presentó una influencia significativa en el rendimiento en PI. En el tercer capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de invierno en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de trigo en secano del Noreste (NE) de la PI. La variabilidad climática es el principal motor de los cambios en el crecimiento, desarrollo y rendimiento de los cultivos, especialmente en los sistemas de producción en secano. En la PI, los rendimientos de trigo son fuertemente dependientes de la cantidad de precipitación estacional y la distribución temporal de las mismas durante el periodo de crecimiento del cultivo. La principal fuente de variabilidad interanual de la precipitación en la PI es la Oscilación del Atlántico Norte (NAO), que se ha relacionado, en parte, con los cambios en la temperatura de la superficie del mar en el Pacífico Tropical (El Niño) y el Atlántico Tropical (TNA). La existencia de cierta predictibilidad nos ha animado a analizar la posible predicción de los rendimientos de trigo en la PI utilizando anomalías de TSM como predictor. Para ello, se ha utilizado un modelo de cultivo (calibrado en dos localidades del NE de la PI) y datos climáticos de reanálisis para obtener series temporales largas de rendimiento de trigo alcanzable y relacionar su variabilidad con anomalías de la TSM. Los resultados muestran que El Niño y la TNA influyen en el desarrollo y rendimiento del trigo en el NE de la PI, y estos impactos depende del estado concurrente de la NAO. Aunque la relación cultivo-TSM no es igual durante todo el periodo analizado, se puede explicar por un mecanismo eco-fisiológico estacionario. Durante la segunda mitad del siglo veinte, el calentamiento (enfriamiento) en la superficie del Atlántico tropical se asocia a una fase negativa (positiva) de la NAO, que ejerce una influencia positiva (negativa) en la temperatura mínima y precipitación durante el invierno y, por lo tanto, aumenta (disminuye) el rendimiento de trigo en la PI. En relación con El Niño, la correlación más alta se observó en el período 1981 -2001. En estas décadas, los altos (bajos) rendimientos se asocian con una transición El Niño - La Niña (La Niña - El Niño) o con eventos de El Niño (La Niña) que están finalizando. Para estos eventos, el patrón atmosférica asociada se asemeja a la NAO, que también influye directamente en la temperatura máxima y precipitación experimentadas por el cultivo durante la floración y llenado de grano. Los co- efectos de los dos patrones de teleconexión oceánicos ayudan a aumentar (disminuir) la precipitación y a disminuir (aumentar) la temperatura máxima en PI, por lo tanto el rendimiento de trigo aumenta (disminuye). Parte II. Predicción de cultivos. En el último capítulo se analiza los beneficios potenciales del uso de predicciones climáticas estacionales (por ejemplo de precipitación) en las predicciones de rendimientos de trigo y maíz, y explora métodos para aplicar dichos pronósticos climáticos en modelos de cultivo. Las predicciones climáticas estacionales tienen un gran potencial en las predicciones de cultivos, contribuyendo de esta manera a una mayor eficiencia de la gestión agrícola, seguridad alimentaria y de subsistencia. Los pronósticos climáticos se expresan en diferentes formas, sin embargo todos ellos son probabilísticos. Para ello, se evalúan y aplican dos métodos para desagregar las predicciones climáticas estacionales en datos diarios: 1) un generador climático estocástico condicionado (predictWTD) y 2) un simple re-muestreador basado en las probabilidades del pronóstico (FResampler1). Los dos métodos se evaluaron en un caso de estudio en el que se analizaron los impactos de tres escenarios de predicciones de precipitación estacional (predicción seco, medio y lluvioso) en el rendimiento de trigo en secano, sobre las necesidades de riego y rendimiento de maíz en la PI. Además, se estimó el margen bruto y los riesgos de la producción asociada con las predicciones de precipitación estacional extremas (seca y lluviosa). Los métodos predWTD y FResampler1 usados para desagregar los pronósticos de precipitación estacional en datos diarios, que serán usados como inputs en los modelos de cultivos, proporcionan una predicción comparable. Por lo tanto, ambos métodos parecen opciones factibles/viables para la vinculación de los pronósticos estacionales con modelos de simulación de cultivos para establecer predicciones de rendimiento o las necesidades de riego en el caso de maíz. El análisis del impacto en el margen bruto de los precios del grano de los dos cultivos (trigo y maíz) y el coste de riego (maíz) sugieren que la combinación de los precios de mercado previstos y la predicción climática estacional pueden ser una buena herramienta en la toma de decisiones de los agricultores, especialmente en predicciones secas y/o localidades con baja precipitación anual. Estos métodos permiten cuantificar los beneficios y riesgos de los agricultores ante una predicción climática estacional en la PI. Por lo tanto, seríamos capaces de establecer sistemas de alerta temprana y diseñar estrategias de adaptación del manejo del cultivo para aprovechar las condiciones favorables o reducir los efectos de condiciones adversas. La utilidad potencial de esta Tesis es la aplicación de las relaciones encontradas para predicción de cosechas de la próxima campaña agrícola. Una correcta predicción de los rendimientos podría ayudar a los agricultores a planear con antelación sus prácticas agronómicas y todos los demás aspectos relacionados con el manejo de los cultivos. Esta metodología se puede utilizar también para la predicción de las tendencias futuras de la variabilidad del rendimiento en la PI. Tanto los sectores públicos (mejora de la planificación agrícola) como privados (agricultores, compañías de seguros agrarios) pueden beneficiarse de esta mejora en la predicción de cosechas. ABSTRACT The present thesis constitutes a step forward in advancing of knowledge of the effects of climate variability on crops in the Iberian Peninsula (IP). It is well known that ocean temperature, particularly the tropical ocean, is one of the most convenient variables to be used as climate predictor. Oceans are considered as the principal heat storage of the planet due to the high heat capacity of water. When this energy is released, it alters the global atmospheric circulation regimes by teleconnection1 mechanisms. These changes in the general circulation of the atmosphere affect the regional temperature, precipitation, moisture, wind, etc., and those influence crop growth, development and yield. For the case of Europe, this implies that the atmospheric variability in a specific region is associated with the variability of others adjacent and/or remote regions as a consequence of Europe being affected by global circulations patterns which, in turn, are affected by oceanic patterns. The general objective of this Thesis is to analyze the variability of crop yields at climate time scales and its relation to the climate variability and teleconnections, as well as to evaluate their predictability. Moreover, this Thesis aims to establish a methodology to study the predictability of crop yield anomalies. The analysis focuses on wheat and maize as a reference crops for other field crops in the IP, for winter rainfed crops and summer irrigated crops respectively. Crop simulation experiments using a model chain methodology (climate + crop) are designed to evaluate the impacts of climate variability patterns on yield and its predictability. The present Thesis is structured in two parts. The first part is focused on the climate variability analyses, and the second part is an application of the quantitative crop forecasting for years that fulfill specific conditions identified in the first part. This Thesis is divided into 4 chapters, covering the specific objectives of the present research work. Part I. Climate variability analyses The first chapter shows an analysis of potential yield variability in one location, as a bioclimatic indicator of the El Niño teleconnections with Europe, putting forward its importance for improving predictability in both climate and agriculture. It also presents the chosen methodology to relate yield with atmospheric and oceanic variables. Crop yield is partially determined by atmospheric climate variability, which in turn depends on changes in the sea surface temperature (SST). El Niño is the leading mode of SST interannual variability, and its impacts extend worldwide. Nevertheless, the predictability of these impacts is controversial, especially those associated with European climate variability, which have been found to be non-stationary and non-linear. The study showed how potential2 crop yield obtained from reanalysis data and crop models serves as an alternative and more effective index of El Niño teleconnections because it integrates the nonlinearities between the climate variables in a unique time series. The relationships between El Niño and crop yield anomalies are more significant than the individual contributions of each of the atmospheric variables used as input in the crop model. Additionally, the non-stationarities between El Niño and European climate variability are more clearly detected when analyzing crop-yield variability. The understanding of this relationship allows for some predictability up to one year before the crop is harvested. This predictability is not constant, but depends on both high and low frequency modulation. The second chapter identifies the oceanic and atmospheric patterns of climate variability affecting summer cropping systems in the IP. Moreover, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of simulated crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The third chapter identifies the oceanic and atmospheric patterns of climate variability affecting winter cropping systems in the IP. Also, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of rainfed wheat yield variability in IP. Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In IP, wheat yields are strongly dependent on seasonal rainfall amount and temporal distribution of rainfall during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO) which has been related in part with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). The existence of some predictability has encouraged us to analyze the possible predictability of the wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model with a site specific calibration for the Northeast of IP and reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and relate their variability with SST anomalies. The results show that El Niño and TNA influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold on during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of NAO, which exerts a positive (negative) influence on minimum temperatures (Tmin) and precipitation (Prec) during winter and, thus, yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981-2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures (Tmax) and precipitation experienced by the crop during flowering and grain filling. The co-effects of the two teleconnection patterns help to increase (decrease) the rainfall and decrease (increase) Tmax in IP, thus on increase (decrease) wheat yield. Part II. Crop forecasting The last chapter analyses the potential benefits for wheat and maize yields prediction from using seasonal climate forecasts (precipitation), and explores methods to apply such a climate forecast to crop models. Seasonal climate prediction has significant potential to contribute to the efficiency of agricultural management, and to food and livelihood security. Climate forecasts come in different forms, but probabilistic. For this purpose, two methods were evaluated and applied for disaggregating seasonal climate forecast into daily weather realizations: 1) a conditioned stochastic weather generator (predictWTD) and 2) a simple forecast probability resampler (FResampler1). The two methods were evaluated in a case study where the impacts of three scenarios of seasonal rainfall forecasts on rainfed wheat yield, on irrigation requirements and yields of maize in IP were analyzed. In addition, we estimated the economic margins and production risks associated with extreme scenarios of seasonal rainfall forecasts (dry and wet). The predWTD and FResampler1 methods used for disaggregating seasonal rainfall forecast into daily data needed by the crop simulation models provided comparable predictability. Therefore both methods seem feasible options for linking seasonal forecasts with crop simulation models for establishing yield forecasts or irrigation water requirements. The analysis of the impact on gross margin of grain prices for both crops and maize irrigation costs suggests the combination of market prices expected and the seasonal climate forecast can be a good tool in farmer’s decision-making, especially on dry forecast and/or in locations with low annual precipitation. These methodologies would allow quantifying the benefits and risks of a seasonal weather forecast to farmers in IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. The potential usefulness of this Thesis is to apply the relationships found to crop forecasting on the next cropping season, suggesting opportunity time windows for the prediction. The methodology can be used as well for the prediction of future trends of IP yield variability. Both public (improvement of agricultural planning) and private (decision support to farmers, insurance companies) sectors may benefit from such an improvement of crop forecasting.

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This paper is based on a case study located in Avila, central Spain. Its main objectives are to implement an entrepreneurship program and design a plan of capacity building and education for business in order to promote the development of rural areas. The methodological approach of the program is based on the use of tools that permit involving the various actors of the area from the early planning stages. The university's group that is carrying out the field work has relied on these participatory tools in very different areas and contexts for over 25 years. This has allowed the development of an advanced planning model called ?Working With People? that connects expert and experience knowledge in the territories where it is applied. With this methodological approach, the diagnosis of the territory and the design of the program's strategy has been carried out. Once completed the first phase of the program and in order to ensure the sustainability and applicability of future entrepreneurial initiatives, it is necessary to support and strengthen potential entrepreneurs through training activities and capacity building. It relies on ?How to learn from people who live there? to promote investment projects and to teach them with adequate educational skills. In this context, this article aims to study the implementation strategy of these training and capacity building activities studied from an academic perspective, as well as analyzing the potential effects of these actions in promoting entrepreneurship in the territories

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Photosynthesis and photoinhibition in field-grown rice (Oryza sativa L.) were examined in relation to leaf age and orientation. Two varieties (IR72 and IR65598-112-2 [BSI206]) were grown in the field in the Philippines during the dry season under highly irrigated, well-fertilized conditions. Flag leaves were examined 60 and 100 d after transplanting. Because of the upright nature of 60-d-old rice leaves, patterns of photosynthesis were determined by solar movements: light falling on the exposed surface in the morning, a low incident angle of irradiance at midday, and light striking the opposite side of the leaf blade in the afternoon. There was an early morning burst of CO2 assimilation and high levels of saturation of photosystem II electron transfer as incident irradiance reached a maximum level. However, by midday the photochemical efficiency increased again almost to maximum. Leaves that were 100 d old possessed a more horizontal orientation and were found to suffer greater levels of photoinhibition than younger leaves, and this was accompanied by increases in the de-epoxidation state of the xanthophyll cycle. Older leaves had significantly lower chlorophyll content but only slightly diminished photosynthesis capacity.

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Acclimation of photosynthesis to elevated CO2 has previously been shown to be more pronounced when N supply is poor. Is this a direct effect of N or an indirect effect of N by limiting the development of sinks for photoassimilate? This question was tested by growing a perennial ryegrass (Lolium perenne) in the field under elevated (60 Pa) and current (36 Pa) partial pressures of CO2 (pCO2) at low and high levels of N fertilization. Cutting of this herbage crop at 4- to 8-week intervals removed about 80% of the canopy, therefore decreasing the ratio of photosynthetic area to sinks for photoassimilate. Leaf photosynthesis, in vivo carboxylation capacity, carbohydrate, N, ribulose-1,5-bisphosphate carboxylase/oxygenase, sedoheptulose-1,7-bisphosphatase, and chloroplastic fructose-1,6-bisphosphatase levels were determined for mature lamina during two consecutive summers. Just before the cut, when the canopy was relatively large, growth at elevated pCO2 and low N resulted in significant decreases in carboxylation capacity and the amount of ribulose-1,5-bisphosphate carboxylase/oxygenase protein. In high N there were no significant decreases in carboxylation capacity or proteins, but chloroplastic fructose-1,6-bisphosphatase protein levels increased significantly. Elevated pCO2 resulted in a marked and significant increase in leaf carbohydrate content at low N, but had no effect at high N. This acclimation at low N was absent after the harvest, when the canopy size was small. These results suggest that acclimation under low N is caused by limitation of sink development rather than being a direct effect of N supply on photosynthesis.