Methane emissions from different vegetation zones in a Qinghai-Tibetan Plateau wetland

We measured methane (CH4) emissions in the Luanhaizi wetland, a typical alpine wetland on the Qinghai-Tibetan Plateau, China, during the plant growth season (early July to mid-September) in 2002. Our aim was to quantify the spatial and temporal variation of CH4 flux and to elucidate key factors in this variation. Static chamber measurements of CH4 flux were made in four vegetation zones along a gradient of water depth. There were three emergent-plant zones (Hippuris-dominated; Scirpus-dominated; and Carex-dominated) and one submerged-plant zone (Potamogeton-dominated). The smallest CH4 flux (seasonal mean = 33.1 mg CH4 m(-2) d(-1)) was, observed in the Potamogeton-dominated zone, which occupied about 74% of the total area of the wetland. The greatest CH4 flux (seasonal mean = 214 mg CH4 m(-2) d(-1)) was observed in the Hippuris-dominated zone, in the second-deepest water area. CH4 flux from three zones (excluding the Carex-dominated zone) showed a marked diurnal change and decreased dramatically under dark conditions. Light intensity had a major influence on the temporal variation in CH4 flux, at least in three of the zones. Methane fluxes from all zones increased during the growing season with increasing aboveground biomass. CH4 flux from the Scirpus-dominated zone was significantly lower than in the other emergent-plant zones despite the large biomass, because the root and rhizome intake ports for CH4 transport in the dominant species were distributed in shallower and more oxidative soil than occupied in the other zones. Spatial and temporal variation in CH4 flux from the alpine wetland was determined by the vegetation zone. Among the dominant species in each zone, there were variations in the density and biomass of shoots, gas-transport system, and root-rhizome architecture. The CH4 flux from a typical alpine wetland on the Qinghai-Tibetan Plateau was as high as those of other boreal and alpine wetlands. (C) 2004 Elsevier Ltd. All rights reserved.

小波域地震资料的处理方法（WSSP）研究

The modeling formula based on seismic wavelet can well simulate zero - phase wavelet and hybrid-phase wavelet, and approximate maximal - phase and minimal - phase wavelet in a certain sense. The modeling wavelet can be used as wavelet function after suitable modification item added to meet some conditions. On the basis of the modified Morlet wavelet, the derivative wavelet function has been derived. As a basic wavelet, it can be sued for high resolution frequency - division processing and instantaneous feature extraction, in acoordance with the signal expanding characters in time and scale domains by each wavelet structured. Finally, an application example proves the effectiveness and reasonability of the method. Based on the analysis of SVD (Singular Value Decomposition) filter, by taking wavelet as basic wavelet and combining SVD filter and wavelet transform, a new de - noising method, which is Based on multi - dimension and multi-space de - noising method, is proposed. The implementation of this method is discussed the detail. Theoretical analysis and modeling show that the method has strong capacity of de - noising and keeping attributes of effective wave. It is a good tool for de - noising when the S/N ratio is poor. To give prominence to high frequency information of reflection event of important layer and to take account of other frequency information under processing seismic data, it is difficult for deconvolution filter to realize this goal. A filter from Fourier Transform has some problems for realizing the goal. In this paper, a new method is put forward, that is a method of processing seismic data in frequency division from wavelet transform and reconstruction. In ordinary seismic processing methods for resolution improvement, deconvolution operator has poor part characteristics, thus influencing the operator frequency. In wavelet transform, wavelet function has very good part characteristics. Frequency - division data processing in wavelet transform also brings quite good high resolution data, but it needs more time than deconvolution method does. On the basis of frequency - division processing method in wavelet domain, a new technique is put forward, which involves 1) designing filter operators equivalent to deconvolution operator in time and frequency domains in wavelet transform, 2) obtaining derivative wavelet function that is suitable to high - resolution seismic data processing, and 3) processing high resolution seismic data by deconvolution method in time domain. In the method of producing some instantaneous characteristic signals by using Hilbert transform, Hilbert transform is very sensitive to high - frequency random noise. As a result, even though there exist weak high - frequency noises in seismic signals, the obtained instantaneous characteristics of seismic signals may be still submerged by the noises. One method for having instantaneous characteristics of seismic signals in wavelet domain is put forward, which obtains directly the instantaneous characteristics of seismic signals by taking the characteristics of both the real part (real signals, namely seismic signals) and the imaginary part (the Hilbert transfom of real signals) of wavelet transform. The method has the functions of frequency division and noise removal. What is more, the weak wave whose frequency is lower than that of high - frequency random noise is retained in the obtained instantaneous characteristics of seismic signals, and the weak wave may be seen in instantaneous characteristic sections (such as instantaneous frequency, instantaneous phase and instantaneous amplitude). Impedance inversion is one of tools in the description of oil reservoir. one of methods in impedance inversion is Generalized Linear Inversion. This method has higher precision of inversion. But, this method is sensitive to noise of seismic data, so that error results are got. The description of oil reservoir in researching important geological layer, in order to give prominence to geological characteristics of the important layer, not only high frequency impedance to research thin sand layer, but other frequency impedance are needed. It is difficult for some impedance inversion method to realize the goal. Wavelet transform is very good in denoising and processing in frequency division. Therefore, in the paper, a method of impedance inversion is put forward based on wavelet transform, that is impedance inversion in frequency division from wavelet transform and reconstruction. in this paper, based on wavelet transform, methods of time - frequency analysis is given. Fanally, methods above are in application on real oil field - Sansan oil field.