10 resultados para Input-Output Modelling

em Publishing Network for Geoscientific


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Concentrations and d34S and d13C values were determined on SO4, HCO3, CO2, and CH4 in interstitial water and gas samples from the uppermost 400 m of sediment on the Blake Outer Ridge. These measurements provide the basis for detailed interpretation of diagenetic processes associated with anaerobic respiration of electrons generated by organic- matter decomposition. The sediments are anaerobic at very shallow depths (<1 m) below the seafloor. Sulfate reduction is confined to the uppermost 15 m of sediment and results in a significant outflux of oxidized carbon from the sediments. At the base of the sulfate reduction zone, upward-diffusing CH4 is being oxidized, apparently in conjunction with SO4 reduction. CH4 generation by CO2 reduction is the most important metabolic process below the 15-m depth. CO2 removal is more rapid than CO2 input over the depth interval from 15 to 100 m, and results in a slight decrease in HCO3 concentration accompanied by a 40 per mil positive shift in d13C. The differences among coexisting CH4, CO2, and HCO3 are consistent with kinetic fractionation between CH4 and dissolved CO2, and equilibrium fractionation between CO2 and HCO3. At depths greater than 100 m, the rate of input of CO2 (d13C = -25 per mil) exceeds by 2 times the rate of removal of CO2 by conversion to CH4 (d13C of -60 to -65 per mil). This results in an increase of dissolved HCO3 concentration while maintaining d13C of HCO3 relatively constant at +10 per mil. Non-steady-state deposition has resulted in significantly higher organic carbon contents and unusually high (70 meq/l) pore-water alkalinities below 150 m. These high alkalinities are believed to be related more to spontaneous decarboxylation reactions than to biological processes. The general decrease in HCO3 concentration with constant d13C over the depth interval of 200 to 400 m probably reflects increased precipitation of authigenic carbonate. Input-output carbon isotope-mass balance calculations, and carbonate system equilibria in conjunction with observed CO2-CH4 ratios in the gas phase, independently suggest that CH4 concentrations on the order of 100 mmol/kg are present in the pore waters of Blake Outer Ridge sediments. This quantity of CH4 is believed to be insufficient to saturate pore waters and stabilize the CH4*6H2O gas hydrate. Results of these calculations are in conflict with the physical recovery of gas hydrate from 238 m, and with the indirect evidence (seismic reflectors, sediment frothing, slightly decreasing salinity and chlorinity with depth, and pressure core barrel observations) of gas-hydrate occurrence in these sediments. Resolution of this apparent conflict would be possible if CH4 generation were restricted to relatively thin (1-10 m) depth intervals, and did not occur uniformly at all depths throughout the sediment column, or if another methanogenic process (e.g., acetate fermentation) were a major contributor of gas.

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Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.

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Understanding past human-climate-environment interactions is essential for assessing the vulnerability of landscapes and ecosystems to future climate change. This is particularly important in southern Morocco where the current vegetation is impacted by pastoralism, and the region is highly sensitive to climate variability. Here, we present a 2000-year record of vegetation, sedimentation rate, XRF chemical element intensities, and particle size from two decadal-resolved, marine sediment cores, raised from offshore Cape Ghir, southern Morocco. The results show that between 650 and 850 AD the sedimentation rate increased dramatically from 100 cm/1000 years to 300 cm/1000 years, and the Fe/Ca and pollen flux doubled, together indicating higher inputs of terrestrial sediment. Particle size measurements and end-member modelling suggest increased fluvial transport of the sediment. Beginning at 650 AD pollen levels from Cichorioideae species show a sharp rise from 10% to 20%. Pollen from Atemisia and Plantago, also increase from this time. Deciduous oak pollen percentages show a decline, whereas those of evergreen oak barely change. The abrupt increase in terrestrial/fluvial input from 650 to 850 AD occurs, within the age uncertainty, of the arrival of Islam (Islamisation) in Morocco at around 700 AD. Historical evidence suggests Islamisation led to population increase and development of southern Morocco, including expanded pastoralism, deforestation and agriculture. Livestock pressure may have changed the vegetation structure, accounting for the increase in pollen from Cichorioideae, Plantago, and Artemisia, which include many weedy species. Goats in particular may have played a dominant role as agents of erosion, and intense browsing may have led to the decline in deciduous oak; evergreen oak is more likely to survive as it re-sprouts more vigorously after browsing. From 850 AD to present sedimentation rates, Fe/Ca ratios and fluvial discharge remain stable, whereas pollen results suggest continued degradation. Pollen results from the past 150 years suggest expanded cultivation of olives and the native argan tree, and the introduction of Australian eucalyptus trees. The rapidly increasing population in southern Morocco is causing continued pressure to expand pastoralism and agriculture. The history of land degradation presented here suggests that the vegetation in southern Morocco may have been degraded for a longer period than previously thought and may be particularly sensitive to further land use changes. These results should be included in land management strategies for southern Morocco.

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In 2005, the International Ocean Colour Coordinating Group (IOCCG) convened a working group to examine the state of the art in ocean colour data merging, which showed that the research techniques had matured sufficiently for creating long multi-sensor datasets (IOCCG, 2007). As a result, ESA initiated and funded the DUE GlobColour project (http://www.globcolour.info/) to develop a satellite based ocean colour data set to support global carbon-cycle research. It aims to satisfy the scientific requirement for a long (10+ year) time-series of consistently calibrated global ocean colour information with the best possible spatial coverage. This has been achieved by merging data from the three most capable sensors: SeaWiFS on GeoEye's Orbview-2 mission, MODIS on NASA's Aqua mission and MERIS on ESA's ENVISAT mission. In setting up the GlobColour project, three user organisations were invited to help. Their roles are to specify the detailed user requirements, act as a channel to the broader end user community and to provide feedback and assessment of the results. The International Ocean Carbon Coordination Project (IOCCP) based at UNESCO in Paris provides direct access to the carbon cycle modelling community's requirements and to the modellers themselves who will use the final products. The UK Met Office's National Centre for Ocean Forecasting (NCOF) in Exeter, UK, provides an understanding of the requirements of oceanography users, and the IOCCG bring their understanding of the global user needs and valuable advice on best practice within the ocean colour science community. The three year project kicked-off in November 2005 under the leadership of ACRI-ST (France). The first year was a feasibility demonstration phase that was successfully concluded at a user consultation workshop organised by the Laboratoire d'Océanographie de Villefranche, France, in December 2006. Error statistics and inter-sensor biases were quantified by comparison with insitu measurements from moored optical buoys and ship based campaigns, and used as an input to the merging. The second year was dedicated to the production of the time series. In total, more than 25 Tb of input (level 2) data have been ingested and 14 Tb of intermediate and output products created, with 4 Tb of data distributed to the user community. Quality control (QC) is provided through the Diagnostic Data Sets (DDS), which are extracted sub-areas covering locations of in-situ data collection or interesting oceanographic phenomena. This Full Product Set (FPS) covers global daily merged ocean colour products in the time period 1997-2006 and is also freely available for use by the worldwide science community at http://www.globcolour.info/data_access_full_prod_set.html. The GlobColour service distributes global daily, 8-day and monthly data sets at 4.6 km resolution for, chlorophyll-a concentration, normalised water-leaving radiances (412, 443, 490, 510, 531, 555 and 620 nm, 670, 681 and 709 nm), diffuse attenuation coefficient, coloured dissolved and detrital organic materials, total suspended matter or particulate backscattering coefficient, turbidity index, cloud fraction and quality indicators. Error statistics from the initial sensor characterisation are used as an input to the merging methods and propagate through the merging process to provide error estimates for the output merged products. These error estimates are a key component of GlobColour as they are invaluable to the users; particularly the modellers who need them in order to assimilate the ocean colour data into ocean simulations. An intensive phase of validation has been undertaken to assess the quality of the data set. In addition, inter-comparisons between the different merged datasets will help in further refining the techniques used. Both the final products and the quality assessment were presented at a second user consultation in Oslo on 20-22 November 2007 organised by the Norwegian Institute for Water Research (NIVA); presentations are available on the GlobColour WWW site. On request of the ESA Technical Officer for the GlobColour project, the FPS data set was mirrored in the PANGAEA data library.

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The spatial data set delineates areas with similar environmental properties regarding soil, terrain morphology, climate and affiliation to the same administrative unit (NUTS3 or comparable units in size) at a minimum pixel size of 1km2. The scope of developing this data set is to provide a link between spatial environmental information (e.g. soil properties) and statistical data (e.g. crop distribution) available at administrative level. Impact assessment of agricultural management on emissions of pollutants or radiative active gases, or analysis regarding the influence of agricultural management on the supply of ecosystem services, require the proper spatial coincidence of the driving factors. The HSU data set provides e.g. the link between the agro-economic model CAPRI and biophysical assessment of environmental impacts (updating previously spatial units, Leip et al. 2008), for the analysis of policy scenarios. Recently, a statistical model to disaggregate crop information available from regional statistics to the HSU has been developed (Lamboni et al. 2016). The HSU data set consists of the spatial layers provided in vector and raster format as well as attribute tables with information on the properties of the HSU. All input data for the delineation the HSU is publicly available. For some parameters the attribute tables provide the link between the HSU data set and e.g. the soil map(s) rather than the data itself. The HSU data set is closely linked the USCIE data set.

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The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.