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This study investigates the possible correspondence between catchment structure, as represented by perceptual hydrological models developed from fieldwork investigations, and mathematical model structures, selected on the basis of reproducing observed catchment hydrographs. Three Luxembourgish headwater catchments are considered, where previous fieldwork suggested distinct flow‐generating mechanisms and hydrological dynamics. A set of lumped conceptual model structures are hypothesized and implemented using the SUPERFLEX framework. Following parameter calibration, the model performance is examined in terms of predictive accuracy, quantification of uncertainty, and the ability to reproduce the flow–duration curve signature. Our key research question is whether differences in the performance of the conceptual model structures can be interpreted based on the dominant catchment processes suggested from fieldwork investigations. For example, we propose that the permeable bedrock and the presence of multiple aquifers in the Huewelerbach catchment may explain the superior performance of model structures with storage elements connected in parallel. Conversely, model structures with serial connections perform better in the Weierbach and Wollefsbach catchments, which are characterized by impermeable bedrock and dominated by lateral flow. The presence of threshold dynamics in the Weierbach and Wollefsbach catchments may favour nonlinear models, while the smoother dynamics of the larger Huewelerbach catchment were suitably reproduced by linear models. It is also shown how hydrologically distinct processes can be effectively described by the same mathematical model components. Major research questions are reviewed, including the correspondence between hydrological processes at different levels of scale and how best to synthesize the experimentalist's and modeller's perspectives. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
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Lower Palaeogene extrusive igneous rocks of the Faroe Islands Basalt Group (FIBG) dominate the Faroese continental margin, with flood basalts created at the time of breakup and separation from East Greenland extending eastwards into the Faroe‐Shetland Basin. This volcanic succession was emplaced in connection with the opening of the NE Atlantic; however, consensus on the age and duration of volcanism remains lacking. On the Faroe Islands, the FIBG comprises four main basaltic formations (the pre‐breakup Lopra and Beinisvørð formations, and the syn‐breakup Malinstindur and Enni formations) locally separated by thin intrabasaltic sedimentary and/or volcaniclastic units. Offshore, the distribution of these formations remains ambiguous. We examine the stratigraphic framework of these rocks on the Faroese continental margin combining onshore (published) outcrop information with offshore seismic‐reflection and well data. Our results indicate that on seismic‐reflection profiles, the FIBG can be informally divided into lower and upper seismic‐stratigraphic packages separated by the strongly reflective A‐horizon. The Lower FIBG comprises the Lopra and Beinisvørð formations; the upper FIBG includes the Malinstindur and Enni formations. The strongly reflecting A‐horizon is a consequence of the contrast in properties of the overlying Malinstindur and underlying Beinisvørð formations. Onshore, the A‐horizon is an erosional surface, locally cutting down into the Beinisvørð Formation; offshore, we have correlated the A‐horizon with the Flett unconformity, a highly incised, subaerial unconformity, within the juxtaposed and interbedded sedimentary fill of the Faroe‐Shetland Basin. We refer to this key regional boundary as the A‐horizon/Flett unconformity. The formation of this unconformity represents the transition from the pre‐breakup to the syn‐breakup phase of ocean margin development in the Faroe–Shetland region. We examine the wider implications of this correlation considering existing stratigraphic models for the FIBG, discussing potential sources of uncertainty in the correlation of the lower Palaeogene succession across the Faroe–Shetland region, and implications for the age and duration of the volcanism.  相似文献   
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Diagnosing the source of errors in snow models requires intensive observations, a flexible model framework to test competing hypotheses, and a methodology to systematically test the dominant snow processes. We present a novel process‐based approach to diagnose model errors through an example that focuses on snow accumulation processes (precipitation partitioning, new snow density, and snow compaction). Twelve years of meteorological and snow board measurements were used to identify the main source of model error on each snow accumulation day. Results show that modeled values of new snow density were outside observational uncertainties in 52% of days available for evaluation, while precipitation partitioning and compaction were in error 45% and 16% of the time, respectively. Precipitation partitioning errors mattered more for total winter accumulation during the anomalously warm winter of 2014–2015, when a higher fraction of precipitation fell within the temperature range where partition methods had the largest error. These results demonstrate how isolating individual model processes can identify the primary source(s) of model error, which helps prioritize future research.  相似文献   
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Among other sources of uncertainties in hydrologic modeling, input uncertainty due to a sparse station network was tested. The authors tested impact of uncertainty in daily precipitation on streamflow forecasts. In order to test the impact, a distributed hydrologic model (PRMS, Precipitation Runoff Modeling System) was used in two hydrologically different basins (Animas basin at Durango, Colorado and Alapaha basin at Statenville, Georgia) to generate ensemble streamflows. The uncertainty in model inputs was characterized using ensembles of daily precipitation, which were designed to preserve spatial and temporal correlations in the precipitation observations. Generated ensemble flows in the two test basins clearly showed fundamental differences in the impact of input uncertainty. The flow ensemble showed wider range in Alapaha basin than the Animas basin. The wider range of streamflow ensembles in Alapaha basin was caused by both greater spatial variance in precipitation and shorter time lags between rainfall and runoff in this rainfall dominated basin. This ensemble streamflow generation framework was also applied to demonstrate example forecasts that could improve traditional ESP (Ensemble Streamflow Prediction) method.  相似文献   
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Project INDEPTH (InterNational DEep Profiling of Tibet and the Himalaya) is an interdisciplinary program designed to develop a better understanding of deep structures and mechanics of the Tibetan Plateau. As a component of magnetotelluric (MT) work in the 4th phase of the project, MT data were collected along a profile that crosses the eastern segment of the Altyn Tagh fault on the northern margin of the plateau. Time series data processing used robust algorithms to give high quality responses. Dimensionality analysis showed that 2D approach is only valid for the northern section of the profile. Consequently, 2D inversions were only conducted for the northern section, and 3D inversions were conducted on MT data from the whole profile. From the 2D inversion model, the eastern segment of the Altyn Tagh fault only appears as a crustal structure, which suggests accommodation of strike slip motion along the Altyn Tagh fault by thrusting within the Qilian block. A large-scale off-profile conductor within the mid-lower crust of the Qilian block was revealed from the 3D inversion model, which is probably correlated with the North Qaidam thrust belt. Furthermore, the unconnected conductors from the 3D inversion model indicate that deformations in the study area are generally localized.  相似文献   
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In order to quantify total error affecting hydrological models and predictions, we must explicitly recognize errors in input data, model structure, model parameters and validation data. This paper tackles the last of these: errors in discharge measurements used to calibrate a rainfall‐runoff model, caused by stage–discharge rating‐curve uncertainty. This uncertainty may be due to several combined sources, including errors in stage and velocity measurements during individual gaugings, assumptions regarding a particular form of stage–discharge relationship, extrapolation of the stage–discharge relationship beyond the maximum gauging, and cross‐section change due to vegetation growth and/or bed movement. A methodology is presented to systematically assess and quantify the uncertainty in discharge measurements due to all of these sources. For a given stage measurement, a complete PDF of true discharge is estimated. Consequently, new model calibration techniques can be introduced to explicitly account for the discharge error distribution. The method is demonstrated for a gravel‐bed river in New Zealand, where all the above uncertainty sources can be identified, including significant uncertainty in cross‐section form due to scour and re‐deposition of sediment. Results show that rigorous consideration of uncertainty in flow data results in significant improvement of the model's ability to predict the observed flow. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   
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