矿井涌水量混沌时间序列分析与预测

矿井地下水系统是个非线性系统,由于地下水系统的复杂性,很难完全确定影响矿井涌水量的因素,因此传统的矿井涌水预测表现出较大的局限性。而混沌时间序列分析能够利用单变量处理方法,分析矿井地下水系统中,由于多因素耦合作用所产生的矿井涌水量时间序列。通过对某矿区1985年9月至2005年2月矿井涌水量时间序列资料的分析,显示矿井涌水量时间序列具有混沌特征;通过对比预测值和实测值,表明预测精度高。因此,混沌时间序列分析方法用于矿井涌水量预测是可行的。     

贵州糯东井田水文地质条件分析

通过对井田内泉和暗河流量的调查研究,认为永宁镇组一、三段碳酸盐岩裂隙溶洞水为井田的主要含水层,含水层主要接受大气降水及河流的渗透补给;煤层上覆地层飞仙关组为相对隔水层,厚度大于500m,下覆无强含水层,其地下水对煤层的开采影响不大,井田水文地质条件较简单。采用比拟法对井田的涌水量进行了预算,推算该矿井开采设计涌水量为13 238m^3/d。     

矿井明水注浆技术

明水注浆是在巷道已经发生涌水后进行堵水注浆的一种方法，以开滦东欢坨矿井下明水注浆实践为基础，阐述了明水注浆技术及注浆工艺。大水矿井由于排水电费占生产成本的比例较大，影响企业的经济效益，进行明水注浆有着重要的意义。     

水化学指标表示裘布依公式的应用

从多矿物溶解化学动力学方程出发,推演并建立了由水化学指标表示的承压二维井流裘布依公式。结合水文地质、水文地球化学特征,列举了水文地质单元内不同区带、各种代表性矿物及相应组分化学指标的基本表达式。以山西省太原西峪煤矿所需解决的水文地质问题为例进行了定量研究与评价,其结果与已有的抽水试验资料接近,为矿井涌水量的评价开辟了一条新的道路。从事实上进一步论证了水化学指标表示裘布依公式的理论概括是正确的。     

The influence of marine inflows on the chemical composition of groundwater in small islands: the example of the Cyclades (Greece)

 Marine contamination of groundwater may be caused by seawater intrusion and by salt spray. The role of both processes was studied in the Cyclades archipelago on four small islands (45–195 km²) whose aquifers consist essentially of fractured, weathered metamorphic rocks. Annual rainfall ranges from 400 to 650 mm and precipitation has high total dissolved solids contents of 45–223 mg l^–1. The chemical characteristics of the groundwater, whose salinity is from 0.4 to 22 g l^–1, are strongly influenced by seawater intrusion. However, the effect of atmospheric input is shown in certain water sampling locations on high ground elevation where the dissolved chloride contents may attain 200 mg l^–1. Received: 14 November 1995 · Accepted: 9 September 1996     

黄河上游径流预报的灰色拓扑方法

以龙羊峡水库年平均入库流量预报为例，根据灰色系统理论的建模方法，利用龙羊峡水库入库水量代表站唐乃亥水文站的实测径流资料，建立了一个ＧＭ（１，１）拓扑预测模型，用于黄河上游径流的长期预报，并取得了较为满意的结果。     

The influence of floodplain geohydrology on the distribution of Sarcocornia pillansii in the Olifants Estuary on the West Coast, South Africa

The distribution of Sarcocornia pillansii (Moss) A.J. Scott was determined by water-table depth and electrical conductivity (EC) of the groundwater. Where the groundwater was accessible (<1.5 m) and had a low EC (<80 mS cm⁻¹), S. pillansii extended its roots down to the water-table where a suitable water potential gradient was shown to exist between the soil and roots. In areas where the groundwater was too deep and/or hypersaline, the plants grew on hummocks. The unconfined aquifer below the floodplain is linked to the estuary and although diurnal tidal waves were dampened, water-table level fluctuations were recorded between tidal events. The complex geomorphology of the floodplain influences groundwater flow, in turn affecting the distribution of the salt marsh vegetation.     

Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.     

京津冀地区中α尺度飑线过程中大风特征分析及成因初探

应用常规天气观测资料、地面加密自动气象站资料、大风灾情报资料、京津冀地区7部多普勒天气雷达组网观测资料及VDRAS资料,从多个角度对2013年8月4日京津冀地区一次飑线过程产生的大范围大风天气过程进行了分析,结果显示:此次过程是在高空冷空气南下、低层暖湿气流北上、系统前倾及位势不稳定的有利层结条件下,由多单体风暴演变为中α尺度的强飑线所致。飑线形成于低层垂直切变加强、冷池合并之后;大风主要发生在飑线主体回波中,其次是主体回波前和中前,主体回波后很少发生。大风发生的位置取决于飑线结构中气流的性质,气流的性质与冷池前进的程度和对流的强度关系密切。大风大部分由下沉冷气流产生,少数为近地面上升暖气流导致。大风发生的范围和强度与低层风垂直切变的强度呈正比,大范围低层风垂直切变的加强增强了飑线入流和出流的强度,是大范围大风、局部强风形成的重要原因。大风发生站次与冷池的强度和范围密切相关,冷池的加强和范围的扩大加强了后侧冷入流和前侧暖入流的强度和范围,也是大范围大风形成的重要因素。