Review of snow water equivalent microwave remote sensing

Accurate quantitative global scale snow water equivalent information is crucial for meteorology, hydrology, water cycle and global change studies, and is of great importance for snow melt-runoff forecast, water resources management and flood control. With land surface process model and snow process model, the snow water equivalent can be simulated with certain accuracy, with the forcing data as input. However, the snow water equivalent simulated using the snow process models has large uncertainties spatially and temporally, and it may be far from the needs of practical applications. Thus, the large scale snow water equivalent information is mainly from remote sensing. Beginning with the launch of Nimbus-7 satellite, the research on microwave snow water equivalent remote sensing has developed for more than 30 years, researchers have made progress in many aspects, including the electromagnetic scattering and emission modeling, ground and airborne experiments, and inversion algorithms for future global high resolution snow water equivalent remote sensing program. In this paper, the research and progress in the aspects of electromagnetic scattering/emission modeling over snow covered terrain and snow water equivalent inversion algorithm will be summarized.     

Effect of tidal stress on fault nucleation and failure of the 2007 Ms6.4 Ning’er earthquake

Based on calculations of the tidal Coulomb failure stress and investigations of the correlation between the Earth tide and the Ning’er earthquake sequence, the processes of fault nucleation and failure were simulated. In these simulations we consider the influence of tidal stresses using the rate- and state-dependent friction laws. Furthermore, the effects on tidal triggering due to the stress amplitude and periodic oscillation properties were investigated, and the triggering effects between the tidal normal and tidal shear stresses were compared. The results showed that the Ning’er earthquake sequence was a physical consequence of tidal effects. A transition period T₀ exists between the nucleation and failure processes of a seismic fault. When the period T of stress is equal to or becomes larger than T₀, the fault response becomes dependent on the periodic features of the loading stress; however, for T < T₀, the response of the fault is nearly independent of the period. Both the tidal normal and tidal shear stresses have similar effect in the nucleation and failure processes; the clock changes generally increase with the maximum amplitudes of the tidal stresses. Tidal normal and tidal shear stresses with positive amplitudes mainly induce earthquake triggering; however, the triggering effects induced by negative tidal stresses are smaller and faults are not sensitive to negative tidal stresses. Our results primarily reveal the physical mechanisms of tidal stress triggering.     

旧石器时期以来新疆文化遗址分布特征及驱动因素

运用最近邻指数和耦合分析方法,研究了旧石器时期至近现代新疆432处文化遗址时空分布特征及驱动因素。结果表明：（1）新疆文化遗址属于聚集分布模式,集中分布在以12个聚集区为主的丝绸之路南道、中道、北道和塔城-阿勒泰地区4个带。中道和北道的遗址数量约占总量的80.11%。（2）新疆文化遗址可划分为旧石器-商朝、西周-秦朝、汉代-南北朝、隋唐-五代、宋元明、清朝-近现代6个时期,不同时期遗址分布重心经历了塔城-阿勒泰→丝绸之路南道和中道→丝绸之路中道和北道→丝绸之路中道的演变。（3）文化遗址的格局演化与历史时期新疆自然和人文因素等有很好的耦合关系,文化遗址的快速发展期（如西汉、隋唐）与气候的相对凉湿期、中原政权的强盛、屯垦的高潮期、丝绸之路的繁荣期相对应。（4）文化遗址空间分布主要受控于自然因素,而时间变迁更多的是受人文因素的影响。早期自然因素的影响大,而后期人文力量起主导作用,是新疆文化遗址变迁与自然和人文耦合关系的总规律。     

RBF神经网络在电路故障诊断中的应用研究

电路系统在工业控制中起着极其重要的应用,随着电路越来越复杂,电路各节点间的关系呈现非线性关系,若节点发生故障,如何确定故障发生在何处成为一大难题。利用RBF（radical basis function）神经网络可以快速逼近任意非线性函数及良好分类能力的特点,来实现对电路系统的故障分类。通过RBF与BP方法的比较及实例分析可得出结论,RBF可以很精确地确定电路中的故障来源,在对电路故障诊断能力方面具有较多的优越性。     

采用多项式拟合修正法提高CCD垂线仪的测量精度

通过分析CZ型CCD垂线坐标仪的标定数据,提出了使用3段2次多项式拟合修正法减小仪器非线性误差,提高测量精度的方法。在实际应用中明显提高了该产品的测量精度。     

措勤地区竟柱山组沉积特征及构造意义

上白垩统竟柱山组在西藏措勤地区主要沿班公湖-怒江缝合带、且坎-古昌-阿索断裂带和塔若错北-达瓦错南-秋措麦凹陷带断续分布。主要为一套磨拉石的紫红色碎屑岩,其沉积环境以扇三角洲和三角洲为主。扇三角洲和三角洲的前积层理指示了其进积方向,表明早期物源来自北部,而晚期来自南部的陆源物质增加。竞柱山组磨拉石沉积的发育,是班公湖-怒江缝合带造山运动的证据。     

半参数p-范极大似然回归

应用核权函数,在观测为误差单峰、对称的情况下,得到了一元p-范分布的半参数模型的计算公式.详细推导了p已知时一元p-范分布极大似然方程的解算公式,将半参数回归模型应用到极大似然平差的参数估计理论中,得到了一个比较好的算法.最后,构造了两个模拟平差问题,说明了此方法的优越性.     

2013 年3 月27 日台湾南投MW 6. 0 地震震源机制解与发震构造研究

采用基于近远震波形的CAPjoint 方法,对2013 年3 月27 日台湾南投MW6. 0 地震分别进行了单独反演和联合反演,获得了各自的震源机制解及震源深度。其中,联合反演所得的最优双力偶机制解参数为,节面Ⅰ:方位角0°,倾角30°,滑动角78°;节面Ⅱ:方位角193°,倾角60°,滑动角96°;震源深度18km。为了验证联合反演的有效性和可靠性,采用由重抽样理论发展而来的Bootstrap 方法,对近远震数据分别进行了重采样,并对其单独反演和联合反演所得的参数进行了统计,验证了联合反演的有效性及稳定性,并发现远震反演震源深度的结果一定程度上受台站分布的影响,若要获得精确的震源深度则需要方位角分布较好的远震台站记录。根据前人对集集地震及车笼埔断层的研究成果以及南投地震的发震断层性质接近车笼埔断层的认识,推测此次地震可能发生在车笼埔断层上。     

A Gridded Daily Min/Max Temperature Dataset With 0.1° Resolution for the Yangtze River Valley and its Error Estimation

The minimum/maximum (Min/Max) temperature in the Yangtze River valley is decomposed into the climatic mean and anomaly component. A spatial interpolation is developed which combines the 3D thin-plate spline scheme for climatological mean and the 2D Barnes scheme for the anomaly component to create a daily Min/Max temperature dataset. The climatic mean field is obtained by the 3D thin-plate spline scheme because the relationship between the decreases in Min/Max temperature with elevation is robust and reliable on a long time-scale. The characteristics of the anomaly field tend to be related to elevation variation weakly, and the anomaly component is adequately analyzed by the 2D Barnes procedure, which is computationally efficient and readily tunable. With this hybridized interpolation method, a daily Min/Max temperature dataset that covers the domain from 99°E to 123°E and from 24°N to 36°N with 0.1° longitudinal and latitudinal resolution is obtained by utilizing daily Min/Max temperature data from three kinds of station observations, which are national reference climatological stations, the basic meteorological observing stations and the ordinary meteorological observing stations in 15 provinces and municipalities in the Yangtze River valley from 1971 to 2005. The error estimation of the gridded dataset is assessed by examining cross-validation statistics. The results show that the statistics of daily Min/Max temperature interpolation not only have high correlation coefficient (0.99) and interpolation efficiency (0.98), but also the mean bias error is 0.00 °C. For the maximum temperature, the root mean square error is 1.1 °C and the mean absolute error is 0.85 °C. For the minimum temperature, the root mean square error is 0.89 °C and the mean absolute error is 0.67 °C. Thus, the new dataset provides the distribution of Min/Max temperature over the Yangtze River valley with realistic, successive gridded data with 0.1° × 0.1° spatial resolution and daily temporal scale. The primary factors influencing the dataset precision are elevation and terrain complexity. In general, the gridded dataset has a relatively high precision in plains and flatlands and a relatively low precision in mountainous areas.     

Flood season segmentation based on the probability change-point analysis technique

Abstract

The segmentation of flood seasons has both theoretical and practical importance in hydrological sciences and water resources management. The probability change-point analysis technique is applied to segmenting a defined flood season into a number of sub-seasons. Two alternative sampling methods, annual maximum and peaks-over-threshold, are used to construct the new flow series. The series is assumed to follow the binomial distribution and is analysed with the probability change-point analysis technique. A Monte Carlo experiment is designed to evaluate the performance of proposed flood season segmentation models. It is shown that the change-point based models for flood season segmentation can rationally partition a flood season into appropriate sub-seasons. China's new Three Gorges Reservoir, located on the upper Yangtze River, was selected as a case study since a hydrological station with observed flow data from 1882 to 2003 is located 40 km downstream of the dam. The flood season of the reservoir can be reasonably divided into three sub-seasons: the pre-flood season (1 June–2 July); the main flood season (3 July–10 September); and the post-flood season (11–30 September). The results of flood season segmentation and the characteristics of flood events are reasonable for this region.

Citation Liu, P., Guo, S., Xiong, L. & Chen, L. (2010) Flood season segmentation based on the probability change-point analysis technique. Hydrol. Sci. J. 55(4), 540–554.