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21.
ABSTRACT

Evapotranspiration (ET) is one of the most important components in the hydrological cycle, and a key variable in hydrological modelling and water resources management. However, understanding the impacts of spatial variability in ET and the appropriate scale at which ET data should be incorporated into hydrological models, particularly at the regional scale, is often overlooked. This is in contrast to dealing with the spatial variability in rainfall data where existing guidance is widely available. This paper assesses the impacts of scale on the estimation of reference ET (ETo) by comparing data from individual weather stations against values derived from three national datasets, at varying resolutions. These include the UK Climate Impacts Programme 50 km climatology (UKCP50), the UK Met Office 5 km climatology (UKMO5) and the regional values published in the Agricultural Climate of England and Wales (ACEW). The national datasets were compared against the individual weather station data and the UKMO5 was shown to provide the best estimate of ETo at a given site. The potential impacts on catchment modelling were then considered by mapping variance in ETo to show how geographical location and catchment size can have a major impact, with small lowland catchments having much higher variance than those with much larger areas or in the uplands. Some important implications for catchment hydrological modelling are highlighted.
Editor D. Koutsoyiannis; Associate editor L. Ruiz  相似文献   
22.
ABSTRACT

This work explores the ability of two methodologies in downscaling hydrological indices characterizing the low flow regime of three salmon rivers in Eastern Canada: Moisie, Romaine and Ouelle. The selected indices describe four aspects of the low flow regime of these rivers: amplitude, frequency, variability and timing. The first methodology (direct downscaling) ascertains a direct link between large-scale atmospheric variables (the predictors) and low flow indices (the predictands). The second (indirect downscaling) involves downscaling precipitation and air temperature (local climate variables) that are introduced into a hydrological model to simulate flows. Synthetic flow time series are subsequently used to calculate the low flow indices. The statistical models used for downscaling low flow hydrological indices and local climate variables are: Sparse Bayesian Learning and Multiple Linear Regression. The results showed that direct downscaling using Sparse Bayesian Learning surpassed the other approaches with respect to goodness of fit and generalization ability.
Editor D. Koutsoyiannis; Associate editor K. Hamed  相似文献   
23.
Theoretical and Applied Climatology - Disease alert systems (DAS) of the AgroClimate platform are intended to facilitate grower decision-making when planning fungicide applications. These DAS...  相似文献   
24.
Natural disasters, particularly those triggered by heavy rainfall, may cause major damage and death. However, if an accurate early warning is issued, the damage can be mitigated. In Latin America and Brazil, characteristics of socioeconomic development often lead to a disorderly growth of cities and, consequently, occupation and irregular construction in risk areas. Therefore, forecasts of heavy rainfall, as well as preventative and mitigatory actions based on meteorological data/alerts, are essential to saving lives and minimizing material loss. An event that would have benefited from such actions is that which occurred in the mountainous region of Rio de Janeiro in January 2011, when over 800 people lost their lives. This work describes the first research initiative on resilience engineering domain in systems to forecast heavy rains in Rio de Janeiro. The results indicate important sources of brittleness in the system that supports the work of meteorologists, mainly related to the technical and organizational framework, and suggests that the main source of resilience in dealing with critical situations is the tacit knowledge of experts.  相似文献   
25.
Simplified seismic sidesway collapse analysis of frame buildings   总被引:1,自引:0,他引:1       下载免费PDF全文
This paper presents the development and assessment of a simplified procedure for estimating the seismic sidesway collapse margin ratio of building structures. The proposed procedure is based on the development of a robust database of seismic peak displacement responses of nonlinear single‐degree‐of‐freedom systems for various seismic intensities and uses nonlinear static (pushover) analysis without the need for nonlinear time history dynamic analysis. The proposed simplified procedure is assessed by comparing its collapse capacity predictions on 72 different building structures with those obtained by nonlinear incremental dynamic analyses. The proposed simplified procedure offers a simple, yet efficient, computational/analytical tool that is capable of predicting collapse capacities with acceptable accuracy for a wide variety of frame building structures. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
26.
Multidimensional Similarity Measuring for Semantic Trajectories   总被引:1,自引:0,他引:1       下载免费PDF全文
Most existing approaches aiming at measuring trajectory similarity are focused on two‐dimensional sequences of points, called raw trajectories. However, recent proposals have used background geographic information and social media data to enrich these trajectories with a semantic dimension, giving rise to the concept of semantic trajectories. Only a few works have proposed similarity measures for semantic trajectories or multidimensional sequences, having limitations such as predefined weight of the dimensions, sensitivity to noise, tolerance for gaps with different sizes, and the prevalence of the worst dimension similarity. In this article we propose MSM, a novel similarity measure for multidimensional sequences that overcomes the aforementioned limitations by considering and weighting the similarity in all dimensions. MSM is evaluated through an extensive experimental study that, based on a seed trajectory, creates sets of semantic trajectories with controlled transformations to introduce different kinds and levels of dissimilarity. For each set, we compute the similarity between the seed and the transformed trajectories, using different measures. The results showed that MSM was more robust and efficient than related approaches in the domain of semantic trajectories.  相似文献   
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Global climate change induced by the emission of greenhouse gases may pose challenges to energy security. The vulnerability of energy sources, in particular of renewable sources, to climate change raises the need to identify adaptation measures. This paper applies an integrated resource planning approach to calculate least-cost adaptation measures to a set of projected climate impacts on the Brazilian power sector. The methodology used has the advantage of finding optimal solutions that take into consideration the whole energy chain and the interactions between energy supply and demand. Results point in the direction of an increased installed capacity based, mostly, on natural gas, but also sugarcane bagasse, wind power and coal/nuclear plants, to compensate for a lower reliability of hydroelectric production, amongst other impacts. The indirect effect of these results is the displacement of natural gas from other consuming sectors, such as industry, in favor of its use for power generation. Results obtained are, however, based on the techno-economic premises used in the simulation, which may vary in the long term.  相似文献   
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