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Intensification of Southern Hemisphere westerly winds 2000–1000 years ago: evidence from the subantarctic Campbell and Auckland Islands (52–50°S) 下载免费PDF全文
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Analysis of the interannual variability of annual daily extreme water levels in the St Lawrence River and Lake Ontario from 1918 to 2010 下载免费PDF全文
We compared the interannual variability of annual daily maximum and minimum extreme water levels in Lake Ontario and the St Lawrence River (Sorel station) from 1918 to 2010, using several statistical tests. The interannual variability of annual daily maximum extreme water levels in Lake Ontario is characterized by a positive long‐term trend showing two shifts in mean (1929–1930 and 1942–1943) and a single shift in variance (in 1958–1959). In contrast, for the St Lawrence River, this interannual variability is characterized by a negative long‐term trend with a single shift in mean, which occurred in 1955–1956. As for annual daily minimum extreme water levels, their interannual variability shows no significant long‐term change in trend. However, for Lake Ontario, the interannual variability of these water levels shows two shifts in mean, which are synchronous with those for maximum water levels, and a single shift in variance, which occurred in 1965–1966. These changes in trend and stationarity (mean and variance) are thought to be due to factors both climatic (the Great Drought of the 1930s) and human (digging of the Seaway and construction of several dams and locks during the 1950s). Despite this change in means and variance, the four series are clearly described by the generalized extreme value distribution. Finally, annual daily maximum and minimum extreme water levels in the St Lawrence and Lake Ontario are negatively correlated with Atlantic multidecadal oscillation over the period from 1918 to 2010. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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Assessing the effects of land cover and future climate conditions on the provision of hydrological services in a medium‐sized watershed of Portugal 下载免费PDF全文
Claudia Carvalho‐Santos João Pedro Nunes António T. Monteiro Lars Hein João Pradinho Honrado 《水文研究》2016,30(5):720-738
The separated and combined effects of land‐cover scenarios and future climate on the provision of hydrological services were evaluated in Vez watershed, northern Portugal. Soil and Water Assessment Tool was calibrated against daily discharge, sediments and nitrates, with good agreements between model predictions and field observations. Four hypothetical land‐cover scenarios were applied under current climate conditions (eucalyptus/pine, oak, agriculture/vine and low vegetation). A statistical downscaling of four General Circulation Models, bias‐corrected with ground observations, was carried out for 2021–2040 and 2041–2060, using representative concentration pathway 4.5 scenario. Also, the combined effects of future climate conditions were evaluated under eucalyptus/pine and agriculture/vine scenario. Results for land cover revealed that eucalyptus/pine scenario reduced by 7% the annual water quantity and up to 17% in the summer period. Although climate change has only a modest effect on the reduction of the total annual discharge (?7%), the effect on the water levels during summer was more pronounced, between ?15% and ?38%. This study shows that climate change can affect the provision of hydrological services by reducing dry season flows and by increasing flood risks during the wet months. Regarding the combined effects, future climate may reduce the low flows, which can be aggravated with eucalyptus/pine scenario. In turn, peak flows and soil erosion can be offset. Future climate may increase soil erosion and nitrate concentration, which can be aggravated with agriculture scenario. Results moreover emphasize the need to consider both climate and land‐cover impacts in adaptation and land management options at the watershed scale. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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Hydrocarbon reservoir modelling and characterisation is a challenging subject within the oil and gas industry due to the lack of well data and the natural heterogeneities of the Earth’s subsurface. Integrating historical production data into the geo-modelling workflow, commonly designated by history matching, allows better reservoir characterisation and the possibility of predicting the reservoir behaviour. We present herein a geostatistical-based multi-objective history matching methodology. It starts with the generation of an initial ensemble of the subsurface petrophysical property of interest through stochastic sequential simulation. Each model is then ranked according the match between its dynamic response, after fluid flow simulation, and the observed available historical production data. This enables building regionalised Pareto fronts and the definition of a large ensemble of optimal subsurface Earth models that fit all the observed production data without compromising the exploration of the uncertainty space. The proposed geostatistical multi-objective history matching technique is successfully implemented in a benchmark synthetic reservoir dataset, the PUNQ-S3, where 12 objectives are targeted. 相似文献
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Numerical representations of a target reservoir can help to assess the potential of different development plans. To be as predictive as possible, these representations or models must reproduce the data (static, dynamic) collected on the field. However, constraining reservoir models to dynamic data – the history-matching process – can be very time consuming. Many uncertain parameters need to be taken into account, such as the spatial distribution of petrophysical properties. This distribution is mostly unknown and usually represented by millions of values populating the reservoir grid. Dedicated parameterization techniques make it possible to investigate many spatial distributions from a small number of parameters. The efficiency of the matching process can be improved from the perturbation of specific regions of the reservoir. Distinct approaches can be considered to define such regions. For instance, one can refer to streamlines. The leading idea is to identify areas that influence the production behavior where the data are poorly reproduced. Here, we propose alternative methods based on connectivity analysis to easily provide approximate influence areas for any fluid-flow simulation. The reservoir is viewed as a set of nodes connected by weighted links that characterize the distance between two nodes. The path between nodes (or grid blocks) with the lowest cumulative weight yields an approximate flow path used to define influence areas. The potential of the approach is demonstrated on the basis of 2D synthetic cases for the joint integration of production and 4D saturation data, considering several formulations for the weights attributed to the links. 相似文献
30.
Giacomo Grassi Roberto Pilli Jo House Sandro Federici Werner A. Kurz 《Carbon balance and management》2018,13(1):8