Revised runoff curve number for runoff prediction in the Loess Plateau of China

The soil conservation service (now Natural Resources Conservation Service) Curve Number (SCS-CN), one of the most commonly used methods for surface runoff prediction. The runoff calculated by this method was very sensitive to CN values. In this study, CN values were calculated by both arithmetic mean (CN_C) and least square fit method (CN_F) using observed rainfall-runoff data from 43 sites in the Loess Plateau region, which are considerably different from the CN₂ values obtained from the USDA-SCS handbook table (CN_T). The results showed that using CN_C instead of CN_T for each watershed produce little improvement, while replacing CN_T with CN_F improves the performance of the original SCS-CN method, but still performs poorly in most study sites. This is mainly due to the SCS-CN method using a constant CN value and discounting of the temporal variation in rainfall-runoff process. Therefore, three factors—soil moisture, rainfall depth and intensity—affecting the surface runoff variability are considered to reflect the variation of CN in each watershed, and a new CN value was developed. The reliability of the proposed method was tested with data from 38 watersheds, and then applied to the remaining five typical watersheds using the optimized parameters. The results indicated that the proposed method, which boosted the model efficiencies to 81.83% and 74.23% during calibration and validation cases, respectively, performed better than the original SCS-CN and the Shi and Wang (2020b) method, a modified SCS-CN method based on tabulated CN value. Thus, the proposed method incorporating the influence of the temporal variability of soil moisture, rainfall depth, and intensity factors suggests an accurate runoff prediction for general applications under different hydrological and climatic conditions on the Loess Plateau region.     

Halin图的色数问题

Halin图G=T∪C,其中T为每一非悬挂点(内点)度数至少为3的平面树,C为连接T的所有悬挂点的圈.文章分别讨论了Halin图的星色数、面色数及分数色数.     

天津城区春节期间大气气溶胶污染特征 和数浓度分布

利用天津城区2009-2014年春节期间大气气溶胶观测资料和相关气象资料,重点分析2013和2014年春节期间气溶胶污染特征,探求燃放烟花爆竹以及气象条件对春节期间大气气溶胶的影响。结果表明,受燃放烟花爆竹影响,春节期间PM_(2.5)质量浓度最高值均发生在除夕夜间;持续雾霾天气条件下燃放烟花爆竹,造成2013年除夕夜间PM_(2.5)质量浓度峰值达到1240μg·m～(-3),是近年来最严重的一次;2014年春节期间烟花爆竹燃放量有所减少,加之空气扩散条件较为有利,PM_(2.5)质量浓度显著低于2013年;不同天气条件下,气溶胶数浓度谱分布特征存在明显差异,燃放烟花爆竹期间气溶胶数浓度水平与严重雾-霾天气相当。     

SAR图像海岸线检测的区域距离正则化几何主动轮廓模型

合成孔径雷达(SAR)卫星遥感图像可以极大地提高全国海岸线覆盖频率,然而受到海洋波浪所引起的随机海水表面粗糙度的影响,海岸目标与海水背景边界易混淆不清,因此本文提出了基于区域距离正则化几何主动轮廓模型(RDRGAC),引入距离正则项,解决重复初始化水平集函数为符号距离函数的问题,提高了算法收敛速度。此外,将区域面积项系数与SAR图像等效视数(ENL)建立非线性拟合关系,实现RDRGAC模型根据不同SAR遥感图像的自适应调整,改善海岸线自动提取精度。通过河北省北戴河和大连市金州湾SAR数据海岸线提取对比试验,验证了所提方法的有效性。     

微动技术在堤坝渗漏探测中的应用

堤坝是重要的水利工程,其安全性至关重要。坝体渗漏是常见的安全隐患之一,对坝体渗漏位置、程度以及坝体结构变化的探测一直是重要的物探课题。微动勘探作为一种新兴的物探手段,应用范围正逐步拓展,通过某水库大坝渗漏检测实例,展示频率-波数法微动线性点阵剖面测量进行大坝渗漏检测的效果,该技术通过提取频散曲线及视S波速度成像,刻画地层速度结构并圈定异常,可实现对大坝渗漏快速精确的无损探测,具有一定的方法优势和广泛的应用前景。     

单一地震事件与多个地震事件的定位方法及应用

主要介绍各种地震定位方法,概述各种地震定位方法的基本原理,重点介绍Geiger的经典方法以及在此基础上建立的各种线性方法:单一地震事件定位法与多个地震事件定位法以及对每一种地震定位方法的应用情况,尤其是国内的应用情况做了总结;同时指出各种方法的特点,并进行相应的比较.     

Joint probability density function of the stochastic responses of nonlinear structures

The joint probability density fimction （PDF） of different structural responses is a very important topic in the stochastic response analysis of nonlinear structures. In this paper, the probability density evolution method, which is successfully developed to capture the instantaneous PDF of an arbitrary single response of interest, is extended to evaluate the joint PDF of any two responses. A two-dimensional partial differential equation in terms of the joint PDF is established. The strategy of selecting representative points via the number theoretical method and sieved by a hyper-ellipsoid is outlined. A two-dimensional difference scheme is developed. The free vibration of an SDOF system is examined to verify the proposed method, and a flame structure exhibiting hysteresis subjected to stochastic ground motion is investigated. It is pointed out that the correlation of different responses results from the fact that randomness of different responses comes from the same set of basic random parameters involved. In other words, the essence of the probabilistic correlation is a physical correlation.     

Application of probabilistic neural network to design breakwater armor blocks

This study presents a probabilistic neural network (PNN) technique for predicting the stability number of armor blocks of breakwaters. The PNN is prepared using the experimental data of Van der Meer. The predicted stability numbers of the PNN are compared with those of previous studies, i.e. by an empirical formula and a previous neural network model. The agreement index between the measured and predicted stability numbers by PNN are better than those by the previous studies. The PNN offers a way to interpret the network's structure in the form of a probability density function and it is easy to implement. Therefore, it can be an effective tool for designers of rubble mound breakwaters.     

Shape optimization of two-dimensional cavitators in supercavitating flows, using NSGA II algorithm

The reduction of energy consumption of high speed submersible bodies is an important challenge in hydrodynamic researches. In this paper, shape optimization of two-dimensional cavitators in supercavitating flows is studied. A two dimensional supercavitation potential flow passes a symmetric two dimensional cavitator, which is placed perpendicular to the flow in a channel of infinite length and immediately a cavity is formed behind the cavitator. This is because of the generation of a gas or vapor cavity between the body and the surrounding liquid due to the change in a high speed flow direction passing the cavitator. Drag force acting on this supercavitating body dictates the thrust requirements for the propulsion system, to maintain a required cavity at the operating speed. Therefore, any reduction in the drag force, by modifying the shape of the cavitator, will lead to decrease this force. This study concentrates on the optimization of two dimensional cavitators in order to decrease drag coefficient for a specified after body length and velocity in a potential flow. To achieve this goal a multi-objective optimization problem is defined to optimize cavitator shapes in supercavitating flow. The so-called NSGA II (Non-dominated Sorting Genetic Algorithm) algorithm is used as an optimization method. Design parameters and constraints are obtained according to supercavitating flow characteristics and cavitator modeling and objective functions are generated using Linear Regression Method. The obtained results are compared with other classic optimization methods, like the weighted sum method, for validation.     

Analysis of threshold and incipient conditions for sediment movement

Prediction of threshold conditions and incipient motion is the essential issue for the study of sediment transport. This work compares existing empirical threshold curves proposed for Shields diagram, a method based on the concept of probability of sediment movement, and an empirical method based on movability number. These methods are used to predict the incipient motion conditions for experimental runs taken from various studies. Most of the experimental data, used in this work, have not been used before in derivation of alternative formulations for Shields diagram and other methods. The empirical threshold curves based on the Shields entrainment function was the least successful at predicting the measured incipient motion conditions, while the use of the movability number gives good predictions of critical shear velocity compared with experimental data.