After the earthquake (Ms = 6.1) occurred in Luquan county of Yunnan province on April 18, 1985, the relationship between major
earthquakes and astronomical time-latitude residuals (ATLR) of a photoelectric astrolabe in Yunnan Observatory was analyzed.
ATLR are the rest after deducting the effects of Earth’s whole motion from the observations of time and latitude. It was found
that there appeared the anomalies of the ATLR before earthquakes which happened in and around Yunnan, a seismic active region.
The reason of the anomalies is possibly from change of the plumb line due to the motion of the groundmass before earthquakes.
Afterwards, using studies of the anomalous characters and laws of ATLR, we tried to provide the warning information prior
to the occurrence of a few major earthquakes in the region. The significant synchronous anomalies of ATLR of the observatory
appeared before the earthquake of magnitude 6.2 in Dayao county of Yunnan province, on July 21, 2003. It has been again verified
that the anomalies possibly provide the prediction information for strong earthquakes around the observatory. 相似文献
The Sebei gasfield is the largest biogas accumulation found in China and many reservoirs and seal rocks superposed on a syndepositional anticline in Quaternary. The biogas charging and dissipating process and its distribution have been a research focus for many years. The authors suggest a diffusing and accumulating model for the biogas, as they find that the shallower the gas producer, the more methane in the biogas, and the lighter stable carbon isotope composition of methane. Based on the diffusing model, diffused biogas is quantitatively estimated for each potential sandy reservoir in the gasfield, and the gas charging quantity for the sandy reservoir is also calculated by the diffused gas quantity plus gas reserve in-place. A ratio of diffusing quantity to charging quantity is postulated to describe biogas accumulating state in a sandy reservoir, if the ratio is less than 0.6, the reservoir forms a good gas-pool and high-production layer in the gasfield, which often occurs in the reservoirs deeper than 900 m; if the ratio is greater than 0.6, a few gas accumulated in the reservoir, which frequently exists in the reservoirs shallower than 900 m. Therefore, a biogas accumulation model is built up as lateral direct charging from gas source for the sands deeper than 900 m and indirect charging from lower gas-bearing sands by diffusion at depth shallower than 900 m. With this charging and diffusion quantitative model, the authors conducted re-evaluation on each wildcat in the central area of the Qaidam Basin, and found many commercial biogas layers.
The competing roles of bedrock uplift and climatic change in the formation of fluvial terraces remain uncertain. Most of recent studies have attributed terrace formation to climatic changes and held that, even in tectonically active settings, climate variations control cycles of terrace planation and abandonment. Based on field investigations of loess-paleosol sequences, magnetostratigraphy and optically stimulated luminescence (OSL) dating, we develop a new chronology for a spectacular flight of terraces along the Yellow River near Lanzhou, China over past 1.24 Ma. All the terraces are strikingly similar in that they have several meters of paleosol developed directly above fluvial deposits on the terrace treads, suggesting that the abandonment of each terrace due to river incision occurs during the transition from glacial to interglacial climates. However, the ages of terraces cluster in two relatively short time periods (1.24–0.86 Ma and 0.13 Ma – present). During the intervening time between 0.86 Ma and 0.13 Ma, terraces either did not form or were not preserved. We suggest that this record indicates that rock uplift rates varied through time and influenced terrace formation/preservation. Thus, our results demonstrate the utility of deep chronologic records from fluvial terraces for deconvolving the effects of tectonics and climate on fluvial incision. 相似文献
The nonlinearity of the relationship between CO2 flux and other micrometeorological variables flux parameters limits the applicability of carbon flux models to accurately estimate the flux dynamics. However, the need for carbon dioxide (CO2) estimations covering larger areas and the limitations of the point eddy covariance technique to address this requirement necessitates the modeling of CO2 flux from other micrometeorological variables. Artificial neural networks (ANN) are used because of their power to fit highly nonlinear relations between input and output variables without explaining the nature of the phenomena. This paper applied a multilayer perception ANN technique with error back propagation algorithm to simulate CO2 flux on three different ecosystems (forest, grassland and cropland) in ChinaFLUX. Energy flux (net radiation, latent heat, sensible heat and soil heat flux) and temperature (air and soil) and soil moisture were used to train the ANN and predict the CO2 flux. Diurnal half-hourly fluxes data of observations from June to August in 2003 were divided into training, validating and testing. Results of the CO2 flux simulation show that the technique can successfully predict the observed values with R2 value between 0.75 and 0.866. It is also found that the soil moisture could not improve the simulative accuracy without water stress. The analysis of the contribution of input variables in ANN shows that the ANN is not a black box model, it can tell us about the controlling parameters of NEE in different ecosystems and micrometeorological environment. The results indicate the ANN is not only a reliable, efficient technique to estimate regional or global CO2 flux from point measurements and understand the spatiotemporal budget of the CO2 fluxes, but also can identify the relations between the CO2 flux and micrometeorological variables.
The feasibility of using fluorescence excitation-emission matrix (EEM) along with parallel factor analysis (PARAFAC) and nonnegative least squares (NNLS) method for the differentiation of phytoplankton taxonomic groups was investigated. Forty-one phytoplankton species belonging to 28 genera of five divisions were studied. First, the PARAFAC model was applied to EEMs, and 15 fluorescence components were generated. Second, 15 fluorescence components were found to have a strong discriminating capability based on Bayesian discriminant analysis (BDA). Third, all spectra of the fluorescence component compositions for the 41 phytoplankton species were spectrographically sorted into 61 reference spectra using hierarchical cluster analysis (HCA), and then, the reference spectra were used to establish a database. Finally, the phytoplankton taxonomic groups was differentiated by the reference spectra database using the NNLS method. The five phytoplankton groups were differentiated with the correct discrimination ratios (CDRs) of 100% for single-species samples at the division level. The CDRs for the mixtures were above 91% for the dominant phytoplankton species and above 73% for the subdominant phytoplankton species. Sixteen of the 85 field samples collected from the Changjiang River estuary were analyzed by both HPLC-CHEMTAX and the fluorometric technique developed. The results of both methods reveal that Bacillariophyta was the dominant algal group in these 16 samples and that the subdominant algal groups comprised Dinophyta, Chlorophyta and Cryptophyta. The differentiation results by the fluorometric technique were in good agreement with those from HPLC-CHEMTAX. The results indicate that the fluorometric technique could differentiate algal taxonomic groups accurately at the division level. 相似文献
Spatial-seasonal patterns in fish diversity in Haizhou Bay were studied based on stratified random surveys conducted in 2011.Principal component analysis was conducted to distinguish different diversity components,and the relationships among 11 diversity indices were explored.Generalized additive models were constructed to examine the environmental effects on diversity indices.Eleven diversity indices were grouped into four components:(1) species numbers and richness,(2) heterogeneous indices,(3) evenness,and(4) taxonomic relatedness.The results show that diversity indices among different components are complementary.Spatial patterns show that fish diversity was higher in coastal areas,which was affected by complex bottom topography and spatial variations of water mass and currents.Seasonal trends could be best explained by the seasonal migration of dominant fish species.Fish diversity generally declined with increasing depth except for taxonomic distinctness,which increased with latitude.In addition,bottom temperature had a significant effect on diversity index of richness.These results indicate that substrate complexity and environmental gradients had important influences on fish diversity patterns,and these factors should be considered in fishery resource management and conservation.Furthermore,diversity in two functional groups(demersal/pelagic fishes) was influenced by different environmental factors.Therefore,the distribution of individual species or new indicators in diversity should be applied to examine spatio-seasonal variations in fish diversity. 相似文献