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161.
    
This study develops improved Soil Moisture Proxies (SMP) based suspended sediment yield (SMPSY) models corresponding to three antecedent moisture conditions (AMCs) (i.e., AMC-I-AMC-III) by coupling the improved initial abstraction (Ia-λ) model, the SMA procedure and the SMP concept for modelling the rainfall generated suspended sediment yield. The SMPSY models specifically incorporate a watershed storage index (S) model to accentuate the transformation from storm to storm and to avoid the sudden jumps in sediment yield computation. The workability of the SMPSY models is tested using a large dataset of rainfall and sediment yield (98 storm events) from twelve small watersheds and a comparison has been made with the existing MSY model. The goodness-of-fit (GOF) statistics is evaluated in terms of the Nash Sutcliffe efficiency (NSE), and error indices, i.e., root mean square error (RMSE), normalized root mean square error (nRMSE), standard error (SE), mean absolute error (MAE), and RMSE-observations standard deviation ratio (RSR). The NSE values vary from 74.31% to 96.57% and from 75.21% to 91.78%, respectively for the SPMSY and MSY model. The NSE statistics indicate that the SMPSY model has lower uncertainty in simulating sediment yield as compared to the MSY model. The error indices are lower for the SMPSY model than the MSY model for most of the watersheds. These results show that the SMPSY model has less uncertainty and performs better than the MSY model. A sensitivity analysis of the SMPSY model shows that the parameter β is most sensitive followed by parameter S, α and A. Overall, the results show that the characterization of soil moisture variability in terms of SMPs and incorporation of improved delivery ratio and runoff coefficient relationship improves the simulation of the erosion and sediment yield generation process.  相似文献   
162.
  总被引:1,自引:0,他引:1  
Diagnostic analyses of hydrological models intend to improve the understanding of how processes and their dynamics are represented in models. Temporal patterns of parameter dominance could be precisely characterized with a temporally resolved parameter sensitivity analysis. In this way, the discharge conditions are characterized, that lead to a parameter dominance in the model. To achieve this, the analysis of temporal dynamics in parameter sensitivity is enhanced by including additional information in a three‐tiered framework on different aggregation levels. Firstly, temporal dynamics of parameter sensitivity provide daily time series of their sensitivities to detect variations in the dominance of model parameters. Secondly, the daily sensitivities are related to the flow duration curve (FDC) to emphasize high sensitivities of model parameters in relation to specific discharge magnitudes. Thirdly, parameter sensitivities are monthly averaged separately for five segments of the FDC to detect typical patterns of parameter dominances for different discharge magnitudes. The three methodical steps are applied on two contrasting catchments (upland and lowland catchment) to demonstrate how the temporal patterns of parameter dynamics represent different hydrological regimes. The discharge dynamic in the lowland catchment is controlled by groundwater parameters for all discharge magnitudes. In contrast, different processes are relevant in the upland catchment, because the dominances of parameters from fast and slow runoff components in the upland catchment are changing over the year for the different discharge magnitudes. The joined interpretation of these three diagnostic steps provides deeper insights of how model parameters represent hydrological dynamics in models for different discharge magnitudes. Thus, this diagnostic framework leads to a better characterization of model parameters and their temporal dynamics and helps to understand the process behaviour in hydrological models. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   
163.
    
Prediction intervals (PIs) are commonly used to quantify the accuracy and precision of a forecast. However, traditional ways to construct PIs typically require strong assumptions about data distribution and involve a large computational burden. Here, we improve upon the recent proposed Lower Upper Bound Estimation method and extend it to a multi‐objective framework. The proposed methods are demonstrated using a real‐world flood forecasting case study for the upper Yangtze River Watershed. Results indicate that the proposed methods are able to efficiently construct appropriate PIs, while outperforming other methods including the widely used Generalized Likelihood Uncertainty Estimation approach. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
164.
    
The chronology of the Solar System, particularly the timing of formation of extra‐terrestrial bodies and their features, is an outstanding problem in planetary science. Although various chronological methods for in situ geochronology have been proposed (e.g., Rb‐Sr, K‐Ar), and even applied (K‐Ar), the reliability, accuracy, and applicability of the 40Ar/39Ar method makes it by far the most desirable chronometer for dating extra‐terrestrial bodies. The method however relies on the neutron irradiation of samples, and thus a neutron source. Herein, we discuss the challenges and feasibility of deploying a passive neutron source to planetary surfaces for the in situ application of the 40Ar/39Ar chronometer. Requirements in generating and shielding neutrons, as well as analysing samples are described, along with an exploration of limitations such as mass, power and cost. Two potential solutions for the in situ extra‐terrestrial deployment of the 40Ar/39Ar method are presented. Although this represents a challenging task, developing the technology to apply the 40Ar/39Ar method on planetary surfaces would represent a major advance towards constraining the timescale of solar system formation and evolution.  相似文献   
165.
    
The Sheepbed mudstone forms the base of the strata examined by the Curiosity rover in Gale Crater on Mars, and is the first bona fide mudstone known on another planet. From images and associated data, this contribution proposes a holistic interpretation of depositional regime, diagenesis and burial history. A lake basin probably received sediment pulses from alluvial fans. Bed cross‐sections show millimetre to centimetre‐scale layering due to distal pulses of fluvial sediment injections (fine‐grained hyperpycnites), fall‐out from river plumes, and some aeolian supply. Diagenetic features include mineralized synaeresis cracks and millimetre‐scale nodules, as well as stratiform cementation. Clay minerals were initially considered due to in situ alteration, but bulk rock chemistry and mineralogy suggests that sediments were derived from variably weathered source rocks that probably contained pre‐existing clay minerals. X‐ray diffraction analyses show contrasting clay mineralogy in closely spaced samples, consistent with at least partial detrital supply of clay minerals. A significant (ca 30 wt%) amorphous component is consistent with little post‐depositional alteration. Theoretical modelling of diagenetic reactions, as well as kinetic considerations, suggest that the bulk of diagenetic clay mineral formation occurred comparatively late in diagenesis. Diagenetic features (synaeresis cracks and nodules) were previously thought to reflect early diagenetic gas formation, but an alternative scenario of synaeresis crack formation via fabric collapse of flocculated clays appears more likely. The observed diagenetic features, such as solid nodules, hollow nodules, matrix cement and ‘raised ridges’ (synaeresis cracks) can be explained with progressive alteration of olivine/glass in conjunction with centrifugal and counter diffusion of reactive species. Anhydrite‐filled fractures in the Sheepbed mudstone occurred late in diagenesis when fluid pressures built up to exceed lithostatic pressure. Generating fluid overpressure by burial to facilitate hydraulic fracturing suggests a burial depth of at least 1000 m for the underlying strata that supplied these fluids.  相似文献   
166.
Analysis of Earth observation (EO) data, often combined with geographical information systems (GIS), allows monitoring of land cover dynamics over different ecosystems, including protected or conservation sites. The aim of this study is to use contemporary technologies such as EO and GIS in synergy with fragmentation analysis, to quantify the changes in the landscape of the Rajaji National Park (RNP) during the period of 19 years (1990–2009). Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. PCA analysis has produced two principal components (PC) and explained 84.1% of the total variance, first component (PC1) accounted for the 57.8% of the total variance while the second component (PC2) has accounted for the 26.3% of the total variance calculated from the core area metrics, distance metrics and shape metrics. Our results suggested that notable changes happened in the RNP landscape, evidencing the requirement of taking appropriate measures to conserve this natural ecosystem.  相似文献   
167.
Evaluation of maps generated from different conceptual models or data processing approaches at spatial level has importance in many geoenvironmental applications. This paper addresses the spatial comparison of different landslide susceptibility zonation (LSZ) raster maps of the same area derived from various procedures.  相似文献   
168.
Cropping system study is not only useful to understand the overall sustainability of agricultural system, but also it helps in generating many important parameters which are useful in climate change impact assessment. Considering its importance, Space Applications Centre, took up a project for mapping and characterizing major cropping systems of Indo-Gangetic Plains of India. The study area included the five states of Indo-Gangetic Plains (IGP) of India, i.e. Punjab, Haryana, Uttar Pradesh, Bihar and West Bengal. There were two aspects of the study. The first aspect included state and district level cropping system mapping using multi-date remote sensing (IRS-AWiFS and Radarsat ScanSAR) data. The second part was to characterize the cropping system using moderate spatial resolution multi-date remote sensing data (SPOT VGT NDVI) and ground survey. The remote sensing data was used to compute three cropping system performance indices (Multiple Cropping Index, Area Diversity Index and Cultivated Land Utilization Index). Ground survey was conducted using questionnaires filled up by 1,000 farmers selected from 103 villages based on the cropping systems map. Apart from ground survey, soil and water sampling and quality analysis were carried out to understand the effect of different cropping systems and their management practices. The results showed that, rice-wheat was the major cropping system of the IGP, followed by Rice-Fallow-Fallow and Maize-Wheat. Other major cropping systems of IGP included Sugarcane based, Pearl millet-Wheat, Rice-Fallow-Rice, Cotton-Wheat. The ground survey could identify 77 cropping systems, out of which 38 are rice-based systems. Out of these 77 cropping systems, there were 5 single crop systems, occupying 6.5% coverage (of all cropping system area), 56 double crop systems with 72.7% coverage, and 16 triple crop systems with 20.8% coverage. The cropping system performance analysis showed that the crop diversity was found to be highest in Haryana, while the cropping intensity was highest in Punjab state.  相似文献   
169.
A three-step hierarchical Semi Automated Empirical Methane Emission Model (SEMEM) has been used to estimate methane emission from wetlands and waterlogged areas in India using Moderate Resolution Imagine Spectroradiometer (MODIS) sensor data onboard Terra satellite. Wetland Surface Temperature (WST), methane emission fluxes and wetland extent have been incorporated as parameters in order to model the methane emission. Analysis of monthly MODIS data covering the whole of India from November 2004 to April 2006 was carried out and monthly methane emissions have been estimated. Interpolation techniques were adopted to fill the data gaps due to cloudy conditions during the monsoon period. AutoRegressive Integrated Moving Average (ARIMA) model has been fitted to estimate the emitted methane for the months of May 2006 to August 2006 using SPSS software.  相似文献   
170.
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