高陡山区开采自然坡失稳分析的神经网络方法

针对山区地下开采自然边坡稳定性分析问题,根据大量工程实测资料,建立了人工神经网络预测模型。通过对人工神经网络算法的改进,选取适当的动量项系数及变步长方法,对已有的实测资料进行了训练和测试,并对丁家河磷矿自然边坡稳定性进行了具体的预测分析,理论计算结果与工程实际情况一致。分析结果表明,所建立的理论模型可用于山区磷矿开采自然边坡稳定性预测分析。     

Microcosm experiments on the effect of nutrient enrichment and a soil layer on the development of freshwater plankton

We investigated the response of phytoplankton and zooplankton to experimental alteration of nitrate and phosphate levels in outdoor enclosures. Experiments were conducted in summer and winter and in the absence and presence of a layer of soil. The tubs (12 in all) except the two plain water controls were manured initially with a mixture of fresh cowdung (50g 1⁻¹), mustard oil cake (25 g l⁻¹) and poultry wastes (25 g l⁻¹; mostly excreta), prior to enrichment. Water samples were collected from the experimental tubs twice a week to measure selected physico-chemical and biological variables. Water temperature in the summer experiments ranged from 20–30 °C and during the winter experiments from 11–15 °C. The pH values ranged from 8.0 to 9.5 and the dissolved oxygen levels from 8.2–10.0 mg l⁻¹. The levels of soluble reactive phosphorus and nitrate nitrogen ranged from undetectable levels to 1800 μg l⁻¹ and 6000 μg l⁻¹, respectively. The increase in chlorophyll-a following enrichment was rapid (3–7 days) during summer, but slower in winter (7–14 days). The predominant phytoplankton species observed in the tubs belong to the genera Sphaerocystis, Chlorella, Scenedesmus, Cosmarium, Ulothrix, Zygnema, Gonium and Pandorina. The rotifer species observed were Brachionus calyciflorus, Rotaria neptunia, Lecane bulla, L. luna, L. unguitata, Euchlanis dilatata, Asplanchna intermedia, Pseudoharringia spp., Eosphora spp., Lepadella ovalis, Epiphanes brachionus, Hexarthra mira and Cephalodella gibba. The cladocerans observed were Macrothrix spp. and Alona spp.     

花鸟山外海域几种形态磷在柱状沉积物中的分布及环境意义

综合运用 SEDEX化学法、ASPILA化学法和 XRF仪器分析法 ,对在东海赤潮多发区花鸟山外海域采集的柱状沉积物进行了总磷及其不同形态磷含量的系统分析。研究表明 ,总磷及其不同形态磷在沉积柱垂向上的分布有一定的变化规律。在采样深度范围内 ,总磷 (TP)、有机磷 (OP)和铁结合态磷 (Fe - P)的含量自下而上增高 ,而吸附态磷 (Ad - P)、自生钙结合态磷 (Ca- P)与碎屑态磷 (De- P)的含量向上递减。样品柱具有较均匀的粒度及矿物、化学组成 ,基本可以排除沉积物质来源和沉积环境变化对沉积物中磷含量的影响 ,而且也不能仅仅用早期成岩作用来解释磷的上述行为。不同形态磷在柱状沉积物中的分布规律 ,在一定程度上反映了近年来陆源区环境污染加剧的趋势。     

Geochemical characteristics of phosphorus near the Huanghe River estuary

INTRODUCTIONPhosphorus (P)isanimportantlimitingelementinglobaloceanicproductivity (Holland ,1 978) ,soknowledgeofPisakeytobetterunderstandingofthecyclingofcarbon ,nitrogen,sulfur,andothernu trientelements.Inasimplemassbalancemodel,thelevelofdissolvedPintheoceanisafunctionoftherateofinputviarivers,andtherateofoutputviadepositioninsediments.Inthepresentstudy,thefocusisontheriverinePinputbytheHuangheRiver (YellowRiver)totheBohaiSea,andespeciallyontheamountofPsolubilizedfromsolidphasesupo…     

Spatial variability of soil nutrients in Punta Fort William,Greenwich Island,maritime Antarctic

This study aims to report baseline soil nutrients, specifically the organic carbon, nitrogen and phosphorus profile, in soil samples collected from Puntta Fort William on Greenwich Island in maritime Antarctic. Samples were collected along two transect lines during the early summer of 2008. Ward＇s method of hierarchical agglomerative clustering was employed to group the sampling points based on their physico-chemical properties. In this context, the soil samples can be grouped into three major clus- ters： （1） Samples with intensive biological activities, （2） samples from the area recently exposed by glacial retreat and （3） samples from barren and dried areas. Nutrient contents in Punta Fort William are driven by the intensity of biological activities as well as melt water from the Qnito glacier.     

可解释性长短期记忆模型用于预测湖泊总磷浓度变化

对湖泊总磷的变化预测和来源识别对水资源调度和流域生态治理有着重要的意义,然而复杂的生化反应和水动力条件导致的非平稳性给湖泊总磷浓度的准确预测带来极大的困难。为克服这一挑战,本文引入了基于加权回归的季节趋势分解(seasonal and trend decomposition using Loess,STL)技术和夏普利加法(SHapley additive exPlanations,SHAP)结合长短期记忆网络(long short-term memory neural network,LSTM)和门控循环单元(gated recurrent unit,GRU)构建了一个可解释的预测框架,以增强对湖泊总磷浓度演变的预测并提高其可解释性。研究表明:(1)在骆马湖总磷浓度的预测中,该框架拥有较好的预报精度(R²=0.878),优于LSTM和卷积长短期记忆模型(convolutional neural networks and long short term memory network,CNN-LSTM)。当预测时间步长增加到8 h时,该框架有效提高了总磷浓度的预测精度,平均相对误差和均方根误差分别降低了47.1%和33.3%。从预测趋势来看,骆马湖在汛期的总磷平均浓度为0.158 mg/L,相较于非汛期的平均浓度,增加了202.1%。(2)运河来水是骆马湖总磷浓度最重要的影响因素,贡献权重为60.0%,并且不同断面(三湾、三场)的污染源受水动力、气象等因素的影响存在显著的时空差异。本文凸显了神经网络模型在预警水体污染方面的可实施性,并且为提高传统神经网络的学习能力和可解释性的开发与验证提供了重要方向。     

闹德海水库水环境氮磷容量预测及防治对策

为保障饮用水源地闹德海水库的水质安全,通过选取不同氮磷允许负荷量的测算模式进行综合分析。结果表明:闹德海水库实际负荷量总氮为139.98 t/a、总磷为28.28 t/a,目前已处于中—富营养化状态;水库若要达到贫—中营养化状态,应削减总氮129.96 t/a,总磷27.27 t/a。为此,从发展农业节水、综合防治化肥、农药、畜禽养殖业污染及治理水土流失等方面提出了科学的污染防治思路及削减对策。     

元古宙真核藻类演化及环境控制因素

宜居地球、地外生命探索以及资源勘查等的需求使真核生物的早期溯源和演化趋势研究成为国际热点.根据已发现实体化石、分子化石和分子钟证据,将元古宙真核藻类演化划分为环境准备(2.45～1.70 Ga)、缓慢发展(1.70～0.80 Ga)、剧烈波动(0.80～0.64 Ga)、快速辐射(0.64～0.54 Ga)四个阶段.元...     

Evidence for phosphorus limitation in carbonate sediments of the seagrass Syringodium filiforme

The seagrass Syringodium filiforme was examined in an ecological analysis of plant nutrient requirements and nutrient resource availability. Assessment of the sediment geochemistry in a San Salvador Island seagrass bed indicated that phosphorus was not readily accessible to the plants. Ammonium regeneration in the fine-grained carbonate sediments was high, and interstitial concentrations averaged ca. 100 μM while phosphate replenishment to interstitial water was low, and concentrations were generally less than 2 μM. Analysis of the seagrass leaf tissue content (C : N : P = 1390 : 47 : 1, atomic wt) suggested that nitrogen and phosphorus were both depleted relative to carbon. However, this high N : P for S. filiforme and the low concentration of phosphate available in the interstitial water established the likelihood that plant acquisition of phosphorus was limited. The finding of high root biomass relative to leaf biomass in these seagrass beds corroborates this evidence by depicting a method of plant adaptation that increases nutrient absorptive root surface area.     

水环境中氮磷形态分析方法研究进展

归纳总结了近年来国内外水环境中氮、磷形态分析方法的研究新进展,并着重介绍了氮、磷在水环境中赋存形态的分类、分析测定方法,这对于深入揭示水环境中氮、磷的赋存形态及研究环境与生物地球化学循环有着重要的指导意义。