东北漫岗黑土区春季冻融期浅沟侵蚀

浅沟侵蚀是东北漫岗黑土区农耕地上常见的水蚀类型,往往对坡耕地造成严重的破坏。2005年春季,通过对两个小流域浅沟侵蚀的调查测量,发现该区浅沟侵蚀相当严重,两流域分别形成浅沟14条、16条,浅沟总长度分别达3 269 m、2 146 m,浅沟密度分别为908 m/km2、766 m/km2,侵蚀深度分别为0.17 mm、0.16 mm,侵蚀模数分别达181.8 t/km2、173.6 t/km2。2005年春季两流域浅沟侵蚀期的径流深分别是6.8 mm、7.7 mm。分析表明,研究区在春季表层土壤解冻、地表裸露和存在季节性冻土层的条件下,春季融雪及强降水易造成强烈的浅沟侵蚀。在分布上,浅沟一般位于坡面的中下部,而且多发育在瓦背状坡面的集流水路上。另外,耕作措施对浅沟的形成和发展也有重要影响。     

Application of back-propagation networks in debris flow prediction

Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.     

Modeling the cyclic swelling pressure of mudrock using artificial neural networks

The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper.     

Deformation-induced garnet zoning

Compositional zoning patterns in garnet porphyroblasts from kyanite-bearing samples of the Devonian Littleton Formation, north-central Massachusetts, reveal complex patterns of growth that are related to multiple deformation and metamorphic events. Garnet porphyroblasts exhibit asymmetrical and irregular zoning patterns in X_Mn, X_Ca and Fe/(Fe + Mg). Zoning reversals in Mn and Fe/(Fe + Mg) and patch distribution in Ca appear to occur around the boundaries of the textural zones. Also, the compositions of the garnet at the textural boundaries are variable for all traverses. These observations suggest that the garnet zoning was not only modified from diffusion processes, but was also influenced by pre-existing microfabrics through the effects of preferential dissolution and resorption in partial disequilibrium. Relationships between chemical and textural truncations indicate that the zoning patterns of garnet were strongly modified from preferential dissolution and precipitation during the development of successive foliations that occurred in zones of high strain/stress (cleavage seams) and zones of low strain/stress, respectively.     

Climate change in Mt. Qomolangma region since 1971

Using monthly average, maximum, minimum air temperature and monthly precipitation data from 5 weather stations in Mt. Qomolangma region in China from 1971 to 2004, climatic linear trend, moving average, low-pass filter and accumulated variance analysis methods, the spatial and temporal patterns of the climatic change in this region were analyzed. The main findings can be summarized as follows: (1) There is obvious ascending tendency for the interannual change of air temperature in Mt. Qomolangma region and the ascending tendency of Tingri, the highest station, is the most significant. The rate of increasing air temperature is 0.234 oC/decade in Mt. Qomolangma region, 0.302 oC/decade in Tingri. The air temperature increases more strongly in non-growing season. (2) Compared with China and the global average, the warming of Mt. Qomolangma region occurred early. The linear rates of temperature increase in Mt. Qomolangma region exceed those for China and the global average in the same period. This is attributed to the sensitivity of mountainous regions to climate change. (3) The southern and northern parts of Mt. Qomolangma region are quite different in precipitation changes. Stations in the northern part show increasing trends but are not statistically significant. Nyalam in the southern part shows a decreasing trend and the sudden decreasing of precipitation occurred in the early 1990s. (4) Compared with the previous studies, we find that the warming of Mt. Qomolangma high-elevation region is most significant in China in the same period. The highest automatic meteorological comprehensive observation station in the world set up at the base camp of Mt. Qomolangma with a height of 5032 m a.s.l will play an important role in monitoring the global climate change.     

InSAR系列讲座4InSAR数据处理及关键算法

作为InSAR系列讲座的第四篇，本文介绍并讨论InSAR数据处理方法和关键算法，并对主要的数据处理流程以数学模型的形式进行了概括。     

华南前汛期不同降水时段的特征分析

利用1957-2001年华南地区74个测站逐日降水资料和同期NCEP／NCAR逐日再分析格点资料，对华南前汛期(4-6月)不同降水时段的特征进行了比较。分析发现，华南前汛期降水由锋面降水和夏季风降水两个时段组成。锋面降水时段主要集中在4月，为典型的由冬到夏过渡的环流形势，华南地区高空为平直的副热带西风急流，大气层结稳定，水汽来源主要是阿拉伯海的西风输送和西太平洋副高南侧东风的转向输送；南海夏季风爆发前，副高仍控制南海地区，华南地区水汽输送主要来源于阿拉伯海的西风输送和西太平洋副高南侧东风的转向输送及孟加拉湾的西南输送；南海夏季风爆发后，副高东撤退出南海地区，南半球越赤道水汽输送加强并与孟加拉湾水汽输送连通，华南区域内对流发展；夏季风降水时段盛期主要集中在6月，此时南亚高压跃上高原，华南地区处于南亚高压东部，对流发展极其旺盛，强大的南半球越赤道水汽输送越过孟加拉湾和南海地区向华南地区输送。     

RegCM3模式对中国东部夏季降水的模拟试验

利用最新发布的区域气候模式RegCM3对1998年5—8月中国东部降水进行了模拟试验，考察了模式对降水和大尺度环流系统的模拟能力。结果表明：不同对流性降水方案对不同月份、不同区域的降水模拟效果差别较大，采用Kuo方案和Grell方案时模拟的降水效果要好于BM方案；RegCM3能较成功地再现异常降水的月际尺度变化和空间分布等基本特征；模式还较好地模拟了西太平洋副高脊线的演变过程和两次向北传播的季节内振荡。该模式可应用于中国东部夏季风降水的研究。     

太阳活动与黄河流域降水关系分析

太阳活动对黄河流域降水有一定影响.引用Morlet小波分析技术,对黄河流域近50年来的降水与太阳黑子的小波系数变化进行分析,表明在1951～1997年期间,黄河流域年降水与太阳黑子在9年时间尺度上呈一定的负相关关系,且降水有1～2年的滞后现象.     

石河子地区降水资源分析

分析了石河子地区位于不同海拔高度的3个观测站的降水资料，结果表明，石河子地区各地降水量分布不均，石河子年降水量最多，其次是炮台，最少是莫索湾。3站季节变化一致，均以春夏季降水量居多，约占全年63％，冬季降水量最少，约占全年的13％。降水量年际变化一致，70年代降水量偏少，80年代以后降水量偏多。出现丰水年和干旱年的降水趋势一致，且出现丰水或干旱时大面积发生的机率较大。