997 resultados para Diffuse solar irradiance


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Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data

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The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km(2) grid scale. We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.

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A multi-scale framework for decision support is presented that uses a combination of experiments, models, communication, education and decision support tools to arrive at a realistic strategy to minimise diffuse pollution. Effective partnerships between researchers and stakeholders play a key part in successful implementation of this strategy. The Decision Support Matrix (DSM) is introduced as a set of visualisations that can be used at all scales, both to inform decision making and as a communication tool in stakeholder workshops. A demonstration farm is presented and one of its fields is taken as a case study. Hydrological and nutrient flow path models are used for event based simulation (TOPCAT), catchment scale modelling (INCA) and field scale flow visualisation (TopManage). One of the DSMs; The Phosphorus Export Risk Matrix (PERM) is discussed in detail. The PERM was developed iteratively as a point of discussion in stakeholder workshops, as a decision support and education tool. The resulting interactive PERM contains a set of questions and proposed remediation measures that reflect both expert and local knowledge. Education and visualisation tools such as GIS, risk indicators, TopManage and the PERM are found to be invaluable in communicating improved farming practice to stakeholders. (C) 2008 Elsevier Ltd. All rights reserved.

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Intensive cultivation of fen peat soils (Eutric Histosols) for agricultural purposes, started in Europe about 250 years ago, resulting in decreased soil fertility, increased oxidation of peat and corresponding CO2-emissions to the atmosphere, nutrient transfer to aquatic ecosystems and losses in the total area of the former native wetlands. To prevent these negative environmental effects set-aside programs and rewetting measures were promoted in recent years. Literature results and practical experiences showed that large scale rewetting of intensively used agricultural Histosols may result in the mobilisation of phosphorus (P), its transport to adjacent surface waters and an accelerated eutrophication risk. The paper summarises results from an international European Community sponsored research project and demonstrates how results obtained at different scales and from different scientific disciplines were compiled to derive a strategy to carry out rewetting measures. A decision support system (DSS) for a hydrologically sensitive area in the Droemling catchment in north-eastern Germany was developed and is presented as a tool to regulate rewetting in order to control P release. It is demonstrated that additional laboratory experiments to identify essential processes of P release during rewetting and the site-specific management of the water table, the involvement of specific knowledge and experience of the stakeholders are necessary to develop an applicable DSS. The presented DSS is practically used to prevent freshwater resources from diffuse P pollution.

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This paper provides some insights on the quasi-biennial oscillation (QBO) modulated 11-year solar cycle (11-yr SC) signals in Northern Hemisphere (NH) winter temperature and zonal wind. Daily ERA-40 Reanalysis and ECMWF Operational data for the period of 1958-2006 were used to examine the seasonal evolution of the QBO-solar cycle relationship at various pressure levels up to the stratopause. The results show that the solar signals in the NH winter extratropics are indeed QBO-phase dependent, moving poleward and downward as winter progresses with a faster descent rate under westerly QBO than under easterly QBO. In the stratosphere, the signals are highly significant in late January to early March and have a life span of 30-50 days. Under westerly QBO, the stratospheric solar signals clearly lead and connect to those in the troposphere in late March and early April where they have a life span of 10 days. As the structure changes considerably from the upper stratosphere to the lower troposphere, the exact month when the maximum solar signals occur depends largely on the altitude chosen. For the low-latitude stratosphere, our analysis supports a vertical double-peaked structure of positive signature of the 11-yr SC in temperature, and demonstrates that this structure is further modulated by the QBO. These solar signals have a longer life span (3-4 months) in comparison to those in the extratropics. The solar signals in the lower stratosphere are stronger in early winter but weaker in late winter, while the reverse holds in the upper stratosphere.

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The ground surface net solar radiation is the energy that drives physical and chemical processes at the ground surface. In this paper, multi-spectral data from the Landsat-5 TM, topographic data from a gridded digital elevation model, field measurements, and the atmosphere model LOWTRAN 7 are used to estimate surface net solar radiation over the FIFE site. Firstly an improved method is presented and used for calculating total surface incoming radiation. Then, surface albedo is integrated from surface reflectance factors derived from remotely sensed data from Landsat-5 TM. Finally, surface net solar radiation is calculated by subtracting surface upwelling radiation from the total surface incoming radiation.

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