内流河流域水资源利用对径流年际年内变化影响的分析——以塔里木河流域为例

以塔里木河流域为例 ,探讨了干旱区内流河流域近 40年来 ,由于人口增长、灌溉面积扩大、河流水资源引用程度日益增加等原因所引起的河流径流多年变化及年内变化等水文效应及其变化的原因。     

Multivariate statistical analysis of deformation tensors: independent vs. correlated tensor observations

In the presence of errors in measuring a random displacement field (under the normal distribution assumption of displacement field), stochastic behaviors of principal components of deformation tensors (strain tensor and tensor of change of curvature (TCC)), based on the intrinsic assumption of geometrical modeling of surface deformation analysis, are discussed. We divided the contents into two parts: In the first, we considered independent random vectors of repeated tensor measurements. In the second step, we considered correlations among repeated measurements. Then, covariance components between tensor elements by Helmert estimator, based on prior information of variance components, are estimated. As a case study, both assumptions are applied to the estimation of principal components of deformation rate tensor observations in Zagros region (Western Iran). The results of numerical analysis showed that greatest shortening is accommodated in oblique orientation (NS) with respect to the Main Recent Fault (MRF), northwest part of North Zagros, Central Iran block and MRF, respectively. Most of the extensions occurred in the east part of the belt. The pattern of eigenspace components of TCC shows highest positive values across the NW region, nearly in orthogonal direction to the MRF and Main Zagros Fault (MZF). The pattern has insignificant values in the Central Zagros. It takes the significant negative values across the SW part, especially along the SPF and Persian Gulf shore. The effect of non-independent observations on the estimation of eigenspace components of deformation tensors (strain tensor and TCC) shows that the estimation of covariance components has influence on the confidence intervals of eigenspace components, especially in seismically active regions of the belt (along the Persian Gulf shore, NW of the belt and region between the Central Iran block and MRF). The results demonstrate the importance of considering the correlation structure among the observations on statistical behavior of principal components of deformation tensors in seismically active regions.     

Seismic risk and damage prediction: case of the buildings in Constantine city (Algeria)

Located at the North-Eastern part of Algeria (Tellian Atlas), Constantine has crucial administrative, economic, scientific and cultural importance. It has continuously experienced significant urban evolutions during the different periods of its history. The city is located in an active seismic region within Algeria and has been struck in the past by several moderate and strong earthquakes. The strongest earthquake recorded since the beginning of instrumental seismology took place on October 27, 1985 with a magnitude M \(_\mathrm{S}=\) 5.9. Constantine presents a high seismic risk, because of its dense housing and high population density (2,374 inhabitants/km \(^{2})\) . This requires a risk assessment in order to take preventive measures and reduce the losses in case of potential major earthquake. For this purpose, a scenario based approach is considered. The building damage assessment methodology adopted for the Algerian context is adapted from HAZUS approach. In the present case, the effective Algerian seismic code response spectrum (RPA 99/2003) is considered as a seismic hazard model. The prediction of the expected damages is performed for a set of almost 29,000 buildings.     

Application of singular value decomposition (SVD) and semi-discrete decomposition (SDD) techniques in clustering of geochemical data: an environmental study in central Iran

Common multivariate clustering techniques are ineffective in identifying subtle patterns of correlation, and clustering of variables or samples within complex geochemical datasets. This study compares the combination of singular value decomposition (SVD) and semi discrete decomposition (SDD), with that of hierarchical cluster analysis (HCA), to examine patterns within a multielement soil geochemical dataset from an agricultural area in the vicinity of Pb–Zn mining operations in central Iran. SVD was used to both identify patterns of correlation between variables and samples and to “denoise” the data, and SDD to simultaneously cluster the samples and variables. The results reveal various spatial associations of mining waste-associated metals As, Ba, Pb and Zn, and within the remaining elements whose distribution is largely controlled by the major oxides. SVD–SDD was found to be superior to HCA, in its ability to detect subtle clusters in soil geochemistry indicative of mine-related contamination in the study area.     

The first electric field pulse of cloud and cloud-to-ground lightning discharges

In this study, the first electric field pulse of cloud and cloud-to-ground discharges were analyzed and compared with other pulses of cloud discharges. Thirty eight cloud discharges and 101 cloud-to-ground discharges have been studied in this analysis. Pulses in cloud discharges were classified as ‘small’, ‘medium’ and ‘large’, depending upon the value of their relative amplitude with respect to that of the average amplitude of the five largest pulses in the flash. We found that parameters, such as pulse duration, rise time, zero crossing time and full-width at half-maximum (FWHMs) of the first pulse of cloud and cloud-to-ground discharges are similar to small pulses that appear in the later stage of cloud discharges. Hence, we suggest that the mechanism of the first pulse of cloud and cloud-to-ground discharges and the mechanism of pulses at the later stage of cloud discharges could be the same.     

Correction of highly noisy strong motion records using a modified wavelet de-noising method

During the past earthquakes, many valuable acceleration time histories were recorded by analog and digital accelerometers. These records are important sources of information in the field of earthquake engineering and engineering seismology. However, a large number of these records are contaminated by noise and it is necessary to correct them for practical applications. On the other hand, only a few records can be corrected using conventional filtering because of mathematical limitations of the method. However, advances in the field of time–frequency analysis and wavelet transform theory provide useful non-linear and adaptive de-noising methods for removing of non-stationary and high-energy noise from the recorded signals. In this paper, the characteristics and capabilities of the modified non-linear adaptive wavelet de-noising method are examined for correction of highly noisy strong motion records. In the frequency domain, it is shown that this method can attenuate the noise in the whole frequency range of engineering interest while in the time domain it can detect and remove non-stationary noise. In addition, the displacement response spectra of these wavelet de-noised records are more stable than conventional filtered records with respect to different correction functions. It is found that a large number of noisy acceleration records that are usually discarded from sets of records used for estimating the ground motions can be corrected using this new method.     

Maritime trade, biological invasions, and the properties of alternate inspection regimes

We analyze the problem of preventing biological invasions caused by ships transporting internationally traded goods between countries and continents. Specifically, we ask the following question: should a port manager have a small number of inspectors inspect arriving ships less stringently or should this manager have a large number of inspectors inspect the same ships more stringently? We use a simple queuing-theoretic framework and show that if decreasing the economic cost of regulation is very important then it makes more sense for the port manager to choose the less stringent inspection regime. In contrast, if reducing the damage from biological invasions is more salient then the port manager ought to pick the more stringent inspection regime.     

Landslide Susceptibility Mapping along Bhalubang–Shiwapur Area of Mid-Western Nepal Using Frequency Ratio and Conditional Probability Models

Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.