Romanian policy makers have to perceive that human intervention on river basins land cover is influencing rainfall-runoff relation and the used methodology cannot accurately estimate watershed surface flow transformations. Global water cycles and energy fluxes understanding is leading to better predictions of land atmosphere interaction and local hydro-climates evolution. The water transfer time determination from rainfall to runoff needs accurate measurements of river basins hydrological parameters. Here, we analyzed and compared the lag time value results of two different methodologies (curve number and rational methodology) used for 54 Romanian small catchment areas study. The focus of this paper is the lag time evaluation and interpretation for an effective implementation of the best methodology approach in the Romanian geographical space. Our research in small river basins was developed using remote sensing technology maps, GIS and environmental datasets in combination with field work on every drainage basin in order to assess the specific morphological features and validate the land cover typology. We found that Soil Conservation Service - Curve Number (SCS-CN) method is widely used according to USA landscape features classification, but not necessarily applicable to Romanian river basins characteristics. Our results show how the official Romanian rational methodology national standard (RNS) can be improved and the limits of SCS-CN method.
We present a theoretical model for the dark current of bound-to-continuum quantum-well infrared photodetectors (QWIPs), by considering the field-induced mixing effect, tunneling rate and phonon scattering rate between bound and continuum states. Using this model, we can see clearly how these mechanisms significantly influence the Fermi levels of bound and continuum electrons, and thus, the dark current. Nonlinear temperature dependence of the dark current at low temperature is predicted and discussed in detail. The simulated dark currents exhibit good agreement with the experimental results, without use of parameter fitting techniques. 相似文献
First break picking is a pattern recognition problem in seismic signal processing, one that requires much human effort and is difficult to automate. The authors' goal is to reduce the manual effort in the picking process and accurately perform the picking. Feedforward neural network first break pickers have been developed using backpropagation training algorithms applied either to an encoded version of the raw data or to derived seismic attributes which are extracted from the raw data. The authors summarize a study in which they applied a backpropagation fuzzy logic system (BPFLS) to first break picking. The authors use derived seismic attributes as features, and take lateral variations into account by using the distance to a piecewise linear guiding function as a new feature. Experimental results indicate that the BPFLS achieves about the same picking accuracy as a feedforward neural network that is also trained using a backpropagation algorithm; however, the BPFLS is trained in a much shorter time, because there is a systematic way in which the initial parameters of the BPFLS can be chosen, versus the random way in which the weights of the neural network are chosen 相似文献
We introduce a semantic data model to capture the hierarchical, spatial, temporal, and evolutionary semantics of images in pictorial databases. This model mimics the user's conceptual view of the image content, providing the framework and guidelines for preprocessing to extract image features. Based on the model constructs, a spatial evolutionary query language (SEQL), which provides direct image object manipulation capabilities, is presented. With semantic information captured in the model, spatial evolutionary queries are answered efficiently. Using an object-oriented platform, a prototype medical-image management system was implemented at UCLA to demonstrate the feasibility of the proposed approach. 相似文献