高炮、火箭人工增雨效果统计检验方案设计中的几个问题讨论

基于理想化的人工增雨概念模型,分析了地面增雨作业效果检验试验区设计的基本特征,以及作业轮次、云系移动速度、催化云系对试验区中雨量点的覆盖率等因素对效果评估的影响,主要结果为：1）云系移动速度应该作为目标云选取的一个重要指标,它直接影响试验区的长度和作业点的布局,对效果评估也有很大的影响,不同移动速度的目标云系将人工增加的降水分散到不同的区域,增加了效果评估的难度。2）存在一段最短时间的雨量资料可以用于效果评估,它由试验区长度、作业时间和目标云移动速度共同决定。3）分别给出了作业时间与用于效果统计的雨量时间之比、催化云系对试验区雨量点的覆盖率影响相对增雨率的计算公式,据此定量分析了以色列Ⅰ随机试验资料,结果表明要评估出一定的相对增雨率,需要人工催化云系具有较大的增雨量,即较为显著地改变自然降水。     

吉林省春季人工增雨潜力及指标的数值模拟研究

利用吉林省业务运行的中尺度数值模式WRF3.3.1,分析了2016年4月12日吉林省一次春季降水过程的人工增雨潜力,选取比湿、上升气流、K指数、冰面过饱和度、云水厚度共5种与人工增雨潜力密切相关的指标,作为吉林省春季人工增雨潜力判别的因子。结果表明：吉林省春季850 hPa比湿和K指数与降水量存在相关关系,比湿小于2.9 g·kg^-1几乎不产生降水,产生2 mm以上的降水比湿几乎均大于4.5 g·kg^-1,K指数大于22℃。将850 hPa比湿大于4.5 g·kg^-1、K指数大于22℃、积分云水含量大于0.2 mm、高层冰面过饱和度大于0和低层垂直速度大于0.4 m·s^-1作为强增雨潜力区的指标,并利用春季其他个例对该指标进行检验,发现该指标基本能够表征云内的动力、热力和微物理条件,可以作为人工增雨潜力区的判别指标。     

工程降水中人工回灌综合技术

建筑工程降水往往伴生水资源浪费和地面变形等环境问题,人工回灌是解决这些问题的有效手段之一。影响工程降水中人工回灌的条件有回灌场地水文地质条件、回灌水源水质和水量及回灌方案的经济可行性等因素。就工程降水中出现的问题,提出资源补充型回灌和应力稳定型回灌方法,并给出了适用条件; 根据工程降水水质特点及现有的地下水人工回灌相关水质标准,提出工程降水回灌水质的控制指标主要为悬浮物、浊度、一般污染性指标、微生物指标及重金属等。针对目前人工回灌在工程中存在的可回灌性低的问题,进行了影响入渗速率因素研究,为今后开展促渗关键技术提供理论支持。     

成都锦江下游建立多级复合人工湿地净化污水的可行性研究

锦江是成都市主要污水出口,黄龙溪镇出境断面水质为Ⅴ类或劣Ⅴ类水。本文对采用人工湿地处理锦江江水进行探讨,认为可以在锦江下游建立一系列多级复合人工湿地,湿地面积大约5～7km2,最终可使锦江出水达到Ⅲ类水域水质。     

Use of artificial neural networks to identify the origin of green macroalgae

This study demonstrates application of artificial neural networks (ANNs) for identifying the origin of green macroalgae (Enteromorpha sp. and Cladophora sp.) according to their concentrations of Cd, Cu, Ni, Zn, Mn, Pb, Na, Ca, K and Mg. Earlier studies confirmed that algae can be used for biomonitoring surveys of metal contaminants in coastal areas of the Southern Baltic. The same data sets were classified with the use of different structures of radial basis function (RBF) and multilayer perceptron (MLP) networks. The selected networks were able to classify the samples according to their geographical origin, i.e. Southern Baltic, Gulf of Gdańsk and Vistula Lagoon. Additionally in the case of macroalgae from the Gulf of Gdańsk, the networks enabled the discrimination of samples according to areas of contrasting levels of pollution. Hence this study shows that artificial neural networks can be a valuable tool in biomonitoring studies.     

The influence of a new artificial structure on fish assemblages of adjacent hard substrata

Deployed for diverse purposes, artificial substrata can, theoretically, act as fish attractors or as fish producers. We tested these hypotheses by comparing fish assemblages on two artificial hard substrata, the Ca’ Roman and Sottomarina jetties, before (1994 and 2003) and after (2005 and 2006) the deployment of a new breakwater in the area. Our results support the fish production hypothesis. A remarkable increase in richness and abundance of sedentary species was observed on the extant substrata with the presence of the new barrier. More mobile species showed less definite trends. The net result has been a total increase in abundance and richness in the area. While fish assemblage showed important temporal variation in composition before deployment (Ca’ Roman, comparison between 1994 and 2003), clear trends of increasing abundance were concurrent with the presence of the new barrier. This increase in abundance, particularly of sedentary species, may be attributed to enhanced connectivity and/or an improvement in larval retention due to the changes in water circulation connected with the new breakwater, or to an increase in juveniles and/or adults promoted by changes in environmental conditions. Indeed, changes in benthic cover were recorded, with an increase of uncovered rock and the appearance of previously unrecorded algae after breakwater deployment.     

Population dynamics of marine ciliate Euplotes vannus (Protozoa, Ciliophora) in different artificial seawaters

To study population dynamics of marine ciliates in different artificial seawaters (ASW), the population growth dynamics of a common marine ciliate Euplotes vannus were investigated using beef extract media and rice media for five types of ASW and natural seawater (NSW). The results show that: (1) the population growth rate was in the order of NSW>Flack ASW>Nakamula ASW>Schmadz ASW>Oshima ASW>Subow ASW and was considerably higher in rice media than in beef extract media (apart from Subow ASW); (2) the maximum density of E. vannus in stationary phase in each treatment was ranked as Flack ASW>Nakamula ASW>Schmadz ASW>NSW>Oshima ASW>Subow ASW, and was again higher in rice media than in beef extract media (except for Subow ASW); (3) the exponential and stationary phases were longer in rice media than in beef extract media; (4) strains of E. vannus that had been domesticated for >1 year in ASW grew significantly slower, with lower maximum density and longer stationary phase than those isolated and maintained in NSW. It was demonstrated that: (1) E. vannus may grow well in Flack, Nakamula and Schmads ASW compared with NSW (mainly in terms of growth rate); and (2) Oshima ASW is the preferred choice for stock cultures of E. vannus, but the ASWs Flack, Nakamula and Schmadz are preferred for mass culture. These findings suggest that these three ASWs are effective for the cultivation of marine protozoa for experimental studies on ecology, toxicology and molecular biology.     

改进BP算法在风暴潮极值水位预报中的应用

提出1种基于改进BP算法的风暴潮极值水位预报方法。首先针对现有人工神经网络BP算法存在的缺陷,引入Cauchy训练方法计算连接权的调整,解决BP算法的局部极小点和网络瘫痪的问题。然后结合山东海区水文观测站每年的台风风暴潮资料,应用该改进算法建立台风强度、风速和台风移速与风暴潮极值水位的非线性网络预报模型,对该站极值水位进行预报。实验结果表明,该算法具有很好的稳定性和准确性,为风暴潮预报分析提供了1种可靠的技术手段。     

湿地植被地上生物量遥感估算模型研究——以洪河湿地自然保护区为例

以洪河湿地自然保护区的TM图像和29个实测样地生物量数据为数据源,采用单变量线性和非线性回归、多元线性逐步回归及人工神经网络(BP网络、RBF网络)技术,构建了研究区内典型湿地植被(草甸和沼泽)的地上生物量干重和湿重的遥感估算模型,并对比得到最优模型。主要结论有:(1)RBF神经网络模型及多元非线性模型是研究区内湿地植被地上生物量遥感估算的最优模型,生物量干重估算值的平均相对误差为2.795%,生物量湿重估算值的平均相对误差为3.399%。(2)比较2004年8月、2006年8月和2008年8月研究区内草甸和沼泽总生物量可得,总生物量干重呈上升趋势,而总生物量湿重呈下降趋势。(3)研究区内生物量极高值和极低值分布较少,且主要集中于混合像元分布的地方,如岛状林、灌丛的周边地区或是沼泽内含水较多的地区。