河流封冻日期长期预报方法的研究

根据吉林省自然地理特征,我们采用大气环流指数、降温日期、旬平均气温和初霜日期等要素作指标,编制了河流封冻日期的预报方案。在编制过程中,为提高方案精度,我们首先点绘了吉林省冰情多年平均等值线图,根据冰情分布的规     

黄河内蒙古段冰情预报系统的开发

为了预报黄河内蒙古段的流凌和封开河日期,以多元线性回归理论与人工神经网络理论为基础,设计开发了黄河内蒙古段冰情预报系统预报内蒙古段各个站点的流凌和封开河日期。选用黄河内蒙古段水文、气象和冰情信息建立数据库,应用ADO OLEDB技术调用数据库,建立符合相关性要求的人工神经网络模型和多元线性回归模型,从而实现预报识别检验。使用2003—2004年度至2007—2008年度5年的资料进行预报检验,并与实际开河日期对比分析,预报结果合格率为80%和67.7%,分别达到甲等和丙等预报精度,表明系统可以应用于黄河内蒙古段的冰情预报。     

基于GASS-BPEE交叉训练算法的河道冰情预报组合模型

在文章的河道冰情预报的组合模型中,首先在成因分析的基础上,采用逐步回归算法对预报因子进行有效的筛选,然后采用GASS-BPEE交叉训练算法对冰情要素进行预报.利用该组合模型对凌汛灾害多发的松花江依兰、佳木斯江段开河日期进行了预报,结果表明所建立的河道冰情预报组合模型结构简单、预报精度较高,具有实用价值.     

黄河内蒙古段开河日期预报模型及应用

对黄河内蒙古段的冰情特点进行分析,选用1970—1971年度至2007—2008年度共38个冬季的冰情资料,提取合适的预报因子,分别采用人工神经网络模型和多元线性回归模型,对黄河内蒙古段的开河日期进行预报。结果表明,神经网络模型和多元线性回归模型预报样本合格率分别为86.7%和80.0%,神经网络模型的预报精度高于多元线性回归模型,更适用于黄河内蒙古段开河日期预报。     

克孜加尔水库上游冰情特征分析与预报

以野外实地观测为依据,对克孜加尔水库上游河段2010年～2015年的冰情进行分析,采用人工神经网络模型对克孜加尔水库上游河段的封河历时、开河历时、开河日期等进行测算与预报。结果表明,该预报方法的预测合格率高达93.33%,预测精度较高。人工神经网络模型对克孜加尔水库上游河段冰情的特征分析与预报适用性很强,可有效解决流域冰情预报问题。     

黄河宁蒙河段冰情预报决策支持系统的设计与开发

以黄河宁蒙河段为例，在对河段历史冰情变化规律及其影响因素分析的基础上，建立冰情预报数据库，进行数据挖掘，并以地理信息系统（GIS）为平台，以水文学流量演算、热力学、冰水力学等原理为基础，结合相关经验预报模型，建立用实测资料进行参数率定的冰情预报概念性数学模型和人工神经网络模型，初步探讨了集信息查询、模型参数率定、气温预报、冰情预报等功能为一体的冰情预报决策支持系统的设计与开发。     

神经网络算法在南水北调冰期输水中的应用

通过分析南水北调沿线气候和气温特点,用LevenbergMarquart算法改进传统BP神经网络算法进行气温稳定转负日期的预报。把该模型应用到南水北调沿线新乡、安阳、邢台和石家庄2003—2006年气温稳定转负日期预报中,取得良好效果。立冬日作为气温转负日期统计的基准点,提高了预报精度,说明中国传统二十四节气对于冰情预报及其它同气温和气候相关的预报有重要的参考价值。     

东北地区水利水电工程施工期冰情预报及度凌措施

东北地区河流均存在不同程度冰情,河流封江期和开江期冰情对工程安全施工存在一定风险。文章根据东北地区莲花水电站、尼尔基水利枢纽工程施工期渡凌实践,通过冰情预报方案编制、工程渡凌措施和非工程渡凌措施等方面的论述,对施工期冰情预报方案编制和渡凌措施的技术问题进行了总结,提出了比较合理的建议。     

黄河宁蒙河段冰情预报方法分析

黄河宁蒙河段冰情预报影响因素多、预报难度大。通过分析黄河宁蒙河段冰情特点,冰情预报任务,阐述了宁蒙河段目前的冰情预报方法;同时,依据当前防汛形势对冰情预报的新要求,提出了未来冰情预报需要开展的工作。     

小山水电站施工期冰情预报方案编制及其应用

小山水电站坝址位于抚江县河水文站以下１５．４ｋｍ处，该电站于１９９２年动工兴建，小山电站施工期冰情报途径为：首先预报松江河水文站冰情，再预报小山电站工地的冰情，根据施工需要，编制开江日期，开江形势和开江景最水位预报方案，１９９５年导流洞排冰，预报与实际开江情况基本一致。     

利用水位变化的黑龙江开河方式和开河日期预报

天然河道发生武开河时容易产生冰塞冰坝,造成凌汛灾害。在分析破冰水位和实测日水位的基础上,提前准确预报开河方式和开河日期并及时采取相应防范技术,是防凌减灾的一项重要非工程措施。基于冰盖挠度破坏原理,在利用水位变化判断开河模式的研究基础上将一维冰厚模型的度日法进行优化,计算河道冰厚变化,预报2015—2018年黑龙江开河方式及开河日期。结果表明:开河日期预报除2017年预报值和实测值误差1天,其余年份均完全相同;开河方式预报除因2018年开河水位过低导致水动力不足影响到预报的准确度外,其余年份预报值和实测值相同。     

黄河头道拐站开河日期预测的LSSVM方法

根据实测冰情数据分析发现,可将冰盖厚度演变过程作为预测头道拐站的开河日期的主要依据,同时还应考虑封冻期气温、流量等对冰盖厚度的持续性和累积性影响。据此提出了一种应用数据挖掘技术和LSSVM进行头道拐站开河日期预测的新方法。应用LSSVM模型对头道拐站2010年、2011年和2012年开河日期的预测结果表明,可在封冻期内任一冰盖厚度测量日期利用上述方法对该站的开河日期进行预测,有效延长了预见期,且在3月6日前的预测值均满足许可误差合格率的要求。根据LSSVM模型预测误差呈波动性变化的特点,提出了预测开河日期的均值法,可使开河日期预测精度得到显著提高。     

基于BP神经网络的黑龙江漠河段冰坝预测

黑龙江干流上游在开江流凌期经常出现冰坝,并产生凌汛灾害。为预测黑龙江漠河段的开江日期和冰坝发生情况,利用黑龙江漠河段1960—2010年的水文气象数据建立基于BP神经网络的冰坝预测模型,预测该河段2011—2015年的冰坝发生情况及开江日期,并和实际情况进行比较。研究结果表明:该模型的预测精度较高;通过对27年的气温转正日期和开江日期的分析发现,二者的日期均趋于稳定,且在气温转正后的15 d左右黑龙江漠河段会顺利进入开江阶段;预测2011—2015年开江日期的最大误差为3 d,根据水文情报预报规范,此次预测为甲等预测方案且预测结果均合格。     

基于BP-DEMATEL算法的冰情预报因子敏感性分析

冰情发展受到水文、气象、水力、河道条件和人类活动等多因子相互作用的影响,获得各影响因子的权重关系是进一步明晰冰情发展演变规律和提高预报精度的基础。本研究提出了基于BP-DEMATEL算法的冰情预报因子敏感性分析模型,应用于黄河内蒙古河段巴彦高勒水文站流凌、封河及开河冰情影响因子的分析中,得到影响冰情演变各因子的权重和不同因子之间的相互耦合关系,明确了冰情预报中关键的影响因子。采用不同权重的因子开展流凌、封河和开河的预报,结果显示利用权重值大、相关性强的预报因子开展冰情预报的预报值与实测值吻合较好。因此本研究提出的BP-DEMATEL模型开展冰情预报因子敏感性分析能够得到合理的权重值。     

Lake bathymetry from Indian Remote Sensing (P6‐LISS III) satellite imagery using artificial neural network model

The remote sensing technique provides a rapid and relatively inexpensive means of identifying silted areas in large water bodies, in order that desilting activities can be effectively conducted. This study developed lake bathymetry for a selected lake system (Akkulam–Veli Lake, Kerala, India) from the Indian Remote Sensing (IRS P6‐LISS III) satellite imagery, using an artificial neural network (ANN) model. The water depth was measured for 17 months at different points in the lake on the same date of overpass of the IRS satellite. The satellite imageries obtained for 12 December 2007 and 16 February 2009 were identified as cloud‐free images. ANN models were developed with the four input series of radiance values from green, red, NIR and MIR bands observed for the satellite imagery obtained on 12 December 2007 at the sampling sites, with actual water depth measurements also being taken on the same date. A three‐layered feed forward neural network with back propagation training algorithm was developed for this study. To train the model, it was run several times by changing the number of neurons, learning rate and the momentum constants until the mean square error was minimum. When the number of neurons is increased to 35, and the logsig function is used as ANN transfer function, the error becomes minimum. To test the model, the developed ANN was run for a new set of input from the satellite imagery taken on 16 February 2009. Comparing the predicted and measured values for the same sites for the same day, it was found that the model is best suited for predicting water depth using ANN and the radiance values for four bands of IRS satellite imagery. The results of this study indicated that, for the shallow lake with lower depth, the difference between the actual and predicted value was considerable. In contrast, this was not the case where the lake water depth was greater, indicating an increased prediction accuracy with ANN with increasing depths for shallow lakes. A bathymetry map prepared with ANN indicated only the lake shoreline, as well as the shallow littoral zones. The approach used in this study requires further refinement, including further of the model based on using more field measurements to obtain a better bathymetry map.     

隧道涌水量预测的研究

论述了利用地下水动力学法和模糊数学方法预测隧道涌水量。如果给出施工前和施工初期水文和工程地质参数资料,就可利用地下水动力学中的经验公式,预测隧道涌水量以及涌水量变化过程,该法可以用于指导隧道的总体设计及施工。根据影响隧道涌水量的主要因素,提出运用模糊贴近度预测隧道涌水量的理论,根据计算结果,证明该法预测结果具有一定的参考价值。     

Prediction of climate change effects of fish communities in the Mackinaw River watershed, Illinois, USA.

As part of an integrated assessment of multiple sector impacts produced by predicted changes in climate we have integrated a set of models, which provide predictions of fish populations under changing flow and temperature regimes. The core of the approach is the U. S. Fish and Wildlife Service Physical Habitat Simulation Model (PHABSIM). PHABSIM estimates habitat conditions based on flow, which are life stage specific. The output from PHABSIM is used to model fish populations, considering both flow and a temperature threshold, which affects spawning date. Water temperatures were modelled based on air temperature. The resulting assessment tool provides the means to evaluate the effect of multiple stressors produced by climate change scenarios. The model has been used to estimate smallmouth bass (Micropterus dolomieui) populations for representative reaches of the Mackinaw River, Illinois. The model has been used to illuminate population effects of changing flow and temperature under historical climate/weather conditions, as well as under climate change scenarios. The integrated models in the assessment tool have provided a useful addition to watershed management, improving our capacity to evaluate natural resources impact at temporal scales typical of climate change, and management response systems.     

黄河内蒙古河段冰凌时空分布特性分析

基于黄河内蒙古段系列历史冰情资料,利用小波分析方法对冰期气温、冰期径流、流凌日期、封河日期、开河日期进行了多时间尺度分析。结果表明:巴彦高勒、三湖河口、头道拐三站的冰期气温总体呈上升的变化规律,并且三站的冰期气温变化趋势一致,黄河内蒙古段冰期气温存在15 a左右的周期;实测径流在分析序列中不存在显著周期;三站流凌日期和封河日期整体上推迟,开河日期提前,封冻时间缩短;流凌日期存在12 a左右的周期,封河日期和开河日期不存在显著强周期。     

Observed and predicted occurrence of blackflies (diptera: Simuliidae) at fifty reservoir outlets in Britain

The blackflies present at 50 reservoir outlets throughout mainland Britain were recorded. The observed occurrence of simuliid taxa at sites below upland and lowland reservoirs was compared with the predicted occurrence using predictive equations based on environmental variables. Below the upland reservoirs five simuliid taxa which were predicted to occur were not recorded. Of these S. reptans gp showed the widest discrepancy between predicted and observed occurrences. Four taxa were recorded at significantly fewer sites than predicted and a further four were present at a small number of sites, not differing greatly from the predicted frequency. A similar pattern was observed at the lowland reservoir outlets but S. noelleri, a species frequently associated with lake outlets, was present at more sites than predicted. The influence of a reservoir's presence on the simuliid community is discussed in relation to the known requirements of the species occurring and those predicted to occur.     

Determination of the Influence of Wind on the Keweenaw Current in the Lake Superior Basin as Identified by Advanced Very High Resolution Radiometer (AVHRR) Imagery

The Keweenaw Current is a warm coastal current in Lake Superior that flows northeastward along the northern shore of Michigan's Keweenaw Peninsula. This study focuses on the fate of the current at the tip of the Keweenaw Peninsula. Results of this study suggest that the path of the current beyond the peninsula is primarily controlled by wind.In this study, eleven surface temperature maps derived from Advanced Very High Resolution Radiometric (AVHRR) data using computer assisted image processing techniques were used to identify the Keweenaw Current. Wind data from two moored data buoys, a Coastal Marine Automated Network (CMAN) fixed buoy, and three airport weather stations, collected on the same day as each of the images and for the two days preceding the image date, are used to determine whether wind direction and speed influence the path of the Keweenaw Current past the tip of the peninsula. In nine images the current's path is similar to the surface Ekman transport direction predicted from wind data. All eleven images show a similarity between the current's actual path and a path calculated when net Ekman transport is assumed. Results of this study also show that there may be a possible lag time of one day between a change in wind direction and the current's adjustment to that change.