重污染感潮河道底泥释放特征及其控制技术研究

以珠江三角洲城市重污染感潮河道为对象,研究了底泥污染物(重金属、有机物和营养盐)在静态、潮汐作用影响及人工曝气扰动下的释放特征.在此基础上,采用曝气充氧、重金属化学固定、激活底泥土著微生物等联合技术对底泥释放进行控制,研究其控制效果.结果表明:①感潮作用加速了底泥污染物的释放,与静态释放相比,Cu、Zn、Pb、Cr、COD、NH 4-N和TP的平均释放速率提高了1～4倍,释放量增加了0.3～1.8倍;底泥平均耗氧速率提高了1.28倍.②人工曝气扰动使底泥污染物局部急剧释放,并使泥水界面由弱碱性变成弱酸性;在有氧环境,NH 4-N、TP的释放得到有效抑制.③投加石灰调节pH至8～9,上覆水体Cu、Zn、Pb、Cr的去除率达到85%～98%,同时还可去除92%的TP和86%的浊度;在微碱性好氧条件下,Cu、Zn、Pb和Cr的释放量稳定在300μg·L-1以下.④底泥土著微生物层对水体及底泥污染物有良好的降解作用,通过间歇曝气COD、NH 4-N、TP去除率分别可达到85%、92%和71%;但微生物层具有较高的耗氧速率,达到45g·m-2·d-1.     

长江流域湿地特点及其开发利用

湿地系一种具有多功能的土地资源类型,不仅对农业,而且对水产业均具有开发利用价值,同时还是珍禽栖息地和鱼类繁殖场所。湿地可分为自然湿地和人工湿地两大类型。长江流域湿地分布面积较大,类型较多,具有重要的开发利用价值,尤其人工湿地系我国粮、棉、油生产基地,生产水平高,但仍然具有较大的增产潜力。湿地开发利用应从多目标、多途径进行,出产丰富产品,供应城乡需求,同时为美化环境、保护区域生态环境服务。     

Estimates of Natural Selection in a Salmon Population in Captive and Natural Environments

Abstract:  Captive breeding is a commonly used strategy for species conservation. One risk of captive breeding is domestication selection—selection for traits that are advantageous in captivity but deleterious in the wild. Domestication selection is of particular concern for species that are bred in captivity for many generations and that have a high potential to interbreed with wild populations. Domestication is understood conceptually at a broad level, but relatively little is known about how natural selection differs empirically between wild and captive environments. We used genetic parentage analysis to measure natural selection on time of migration, weight, and morphology for a coho salmon ( Oncorhynchus kisutch ) population that was subdivided into captive and natural components. Our goal was to determine whether natural selection acting on the traits we measured differed significantly between the captive and natural environments. For males, larger individuals were favored in both the captive and natural environments in all years of the study, indicating that selection on these traits in captivity was similar to that in the wild. For females, selection on weight was significantly stronger in the natural environment than in the captive environment in 1 year and similar in the 2 environments in 2 other years. In both environments, there was evidence of selection for later time of return for both males and females. Selection on measured traits other than weight and run timing was relatively weak. Our results are a concrete example of how estimates of natural selection during captivity can be used to evaluate this common risk of captive breeding programs.     

Field‐Scale Application of Three Types of Neural Networks to Predict Ground‐Water Levels1

Abstract: In this paper, a field‐scale applicability of three forms of artificial neural network algorithms in forecasting short‐term ground‐water levels at specific control points is presented. These algorithms are the feed‐forward back propagation (FFBP), radial basis networks (RBN), and generalized regression networks (GRN). Ground‐water level predictions from these algorithms are in turn to be used in an Optimized Regional Operations Plan that prescribes scheduled wellfield production for the coming four weeks. These models are up against each other for their accuracy of ground‐water level predictions on lead times ranging from a week to four weeks, ease of implementation, and execution times (mainly training time). In total, 208 networks of each of the three algorithms were developed for the study. It is shown that although learning algorithms have emerged as a viable solution at field scale much larger than previously studied, no single algorithm performs consistently better than others on all the criteria. On average, FFBP networks are 20 and 26%, respectively, more accurate than RBN and GRN in forecasting one week ahead water levels and this advantage drops to 5 and 9% accuracy in forecasting four weeks ahead water levels, whereas GRN posted a training time that is only 5% of the training time taken by that of FFBP networks. This may suggest that in field‐scale applications one may have to trade between the type of algorithm to be used and the degree to which a given objective is honored.     

甘肃省冬春季人工增雨雪作业指挥系统

为了提高甘肃省人工增雨雪的水平和效果，准确、及时地把握作业气象条件，使人工增雨雪在抗旱减灾中取得更好的社会、经济效益，研制建立了“甘肃省冬春季人工增雨雪作业指挥系统”。该系统包括作业信息系统、作业指挥系统和效果检查系统共3个分系统。详细介绍了各分系统的组成和功能。     

Specificity of Life Conditions for Commercial Invertebrates on Artificial Substrates in the Eutrophicated Amur Bay,the Sea of Japan

The consequences of anthropogenic impact on the water area of Amur Bay (the Sea of Japan) near Vladivostok include the eutrophication of coastal waters and littering with various objects used as artificial substrates, which protect sedentary animals from predators and contribute to the survival of their larvae. An indicator of eutrophication, the diatom Skeletonema costatum accounting for 81–96% of the total abundance of phytoplankton (Stonik and Selina, 1995), is consumed mainly by barnacles and the Pacific oyster. Thus, these animals gain an advantage in the colonization of artificial substrates. The results of the study suggest that eutrophication will lead to changes in the structure of the marine community.     

城市公园湖泊污染治理实践

城市公园湖泊水体保护和水污染治理越来越受到人们的重视。公园内水体往往补充水源不足，自净能力脆弱，当受到污染，湖水会变黑发臭，破坏公园美景。深圳市东湖公园人工湖污染治理过程中结合了水利防洪、环境保护、园林绿化等措施进行综合治理，通过截污、清淤、补充水、湖泊堤岸及拦水橡胶坝的恢复等措施，使湖泊水质得到彻底改善。合理的设计使人工湖具有滞洪防洪功能，还可对公园内地下水起到调节和补充作用，清澈的湖水又使人工湖成为公园内秀丽的景点。该项目为城市公园湖泊污染综合治理进行了一次探索和实践。     

MULTITEMPORAL SCALE HYDROGRAPH PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

Abstract: An artificial neural network (ANN) provides a mathematically flexible structure to identify complex nonlinear relationship between inputs and outputs. A multilayer perceptron ANN technique with an error back propagation algorithm was applied to a multitime-scale prediction of the stage of a hydro-logically closed lake, Devils Lake (DL), and discharge of the Red River of the North at Grand Forks station (RR-GF) in North Dakota. The modeling exercise used 1 year (2002), 5 years (1998–2002), and 27 years (1975–2002) of data for the daily, weekly, and monthly predictions, respectively. The hydrometeorological data (precipitations P_(t), P_(t-1), P_(t-2), P_(t-3), antecedent runoff/lake stage R_(t-1) and air temperature T_(t) were partitioned for training and for testing to predict the current hydro-graph at the selected DL and RR-GF stations. Performance of ANN was evaluated using three combinations of daily datasets (Input I = P_(t)), P_(t-l), P_(t-2), P_(t-3), T_(t) and R_(t-l); Input II = Input-l less P_(t) P_(t-l), P_(t-2), P_(t-3); and Input III = Input-II less T_(t)). Comparison of the model output using Input I data with the observed values showed average testing prediction efficiency (E) of 86 percent for DL basin and 46 percent for RR-GF basin, and higher efficiency for the daily than monthly simulations.     

人工模拟产卵地招引黄脊竹蝗产卵试验

人工模拟产卵地是根据黄脊竹蝗成虫产卵时对自然条件的选择习性,人为造就最适环境,招引成虫集中产卵,避免因林内立竹及植被较密等不利生态因素造成的见缝插针式的散产导致的产卵范围扩大以及给查卵和防治工作带来的困难.试验结果表明,在竹林透光度无差异的情况下,对照区卵块密度平均10.4块/m2,人工模拟产卵地平均为21.2块/m2,是对照的2.04倍,而产卵面积却大为缩小,对照区平均0.038hm2,模拟地均为0.01hm2,仅为对照的l/4.不仅可以诱集成虫集中产卵,便于小面积集中防治,而且还可以省工、省时、省力、省经费.     

INCREASING WATER SUPPLY BY MIXING OF FRESH AND SALINE GROUND WATERS1

ABSTRACT: The quality of ground water in any aquifer takes its final form due to natural mixture of waters, which may originate from different sources. Water quality varies from one aquifer to another and even within the same aquifer itself. Different ground water quality is obtained from wells and is mixed in a common reservoir prior to any consumption. This artificial mixing enables an increase in available ground water of a desired quality for agricultural or residential purposes. The question remains as to what proportions of water from different wells should be mixed together to achieve a desired water quality for this artificial mixture. Two sets of laboratory experiments were carried out, namely, the addition of saline water to a fixed volume of fresh water. After each addition, the mixture volume and the electric conductivity value of the artificially mixed water were recorded. The experiments were carried out under the same laboratory temperature of 20°C. A standard curve was developed first experimentally and then confirmed theoretically. This curve is useful in determining either the volume or discharge ratio from two wells to achieve a predetermined electrical conductivity value of the artificial mixture. The application of the curve is given for two wells within the Quaternary deposits in the western part of the Kingdom of Saudi Arabia.