CHARACTERIZATION OF HYDROLOGIC CONDITIONS TO SUPPORT PLATTE RIVER SPECIES RECOVERY EFFORTS1

ABSTRACT: Efforts are under way to recover habitat for several threatened and endangered species in and along the Platte River in central Nebraska. A proposed recovery program for these species requires a means of characterizing “wet” versus “normal” versus “dry” hydrologic conditions in order to set corresponding Platte River instream flow targets. Methods of characterizing hydrologic conditions in real time were investigated for this purpose. Initially, 10 watershed variables were identified as potentially valuable indicators of hydrologic conditions. Ultimately, six multiple linear regression equations were developed for six periods of the year using a subset of these variables expressed as frequencies of nonexceedence. The adequacy of these equations for characterizing conditions was assessed by evaluating their historic correlation to subsequent flow in the central Platte River (1947–1994). These equations explained 54 to 82 percent of variability in the observed flow exceedences in the validation datasets, depending upon the period of year evaluated. These equations will provide initial criteria for setting applicable flow targets to determine, in real time, whether water regulation projects associated with the species recovery effort can divert or store flows without conflicting with recovery objectives.     

河冰对桥墩作用的冰荷载计算方法(Ⅰ)——河冰的力学性能试验

通过对松花江河冰的物理力学性能试验和松花江公路大桥桥墩的流冰动压力测量、桥面的脉动测量 ,依据国内外对冰 -结构相互作用的分析 ,提出了适合我国黑龙江冰情特点的春季流冰冰荷载的计算方法。     

国外非工程防洪减灾战略研究(Ⅱ)——减灾实例

讨论了美国等国家在防洪减灾中非工程措施方面的一些做法 ,给出了其中一些实例 ,阐述了防洪减灾工程措施与非工程措施的发展趋势。     

Dynamics of Bacterial Abundance,Biomass, Activity,and Community Composition in the Oligotrophic Traunsee and the Traun River (Austria)

The holomictic Traunsee is the deepest and second largest lakein Austria. The special characteristic of this ecosystem isthe fact that local salt and soda industries presumably alterthe lake by the discharge of waste materials. Since thebeginning of the 20th century salt and soda works areannually releasing up to 50,000 tons of solid wastes and up to150,000 tons of chloride into Traunsee. To assess potentialeffects of these anthropogenic impacts on the bacterioplanktonthree sampling sites, influenced as well as not influenced bythe industrial discharge, were chosen for comparison andsampled monthly from November 1997 to October 1998. Bacterialabundance ranged between 0.4 to 3.0 × 10⁶ cells ml^-1 with decreasing numbers along the depth profile. Theproportion of actively respiring bacteria, i.e. INT [2-(4-iodophenyl)-3-(4-nitrophenyl)-5-phenyltetrazolium chloride]reducing cells, never exceeded 10% of DAPI (4',6'-diamidino-2-phenylindole) stained cells. Fluorescence in situ hybridization (FISH) was used to examine the seasonal and spatial distribution of dominant phylogenetic groups of thebacterioplankton. Up to 84% of bacteria detected with DAPIcould be detected via FISH applying the universal bacterialprobe EUB338. Percentages of alpha- and beta-Proteobacteriaand members of the Cytophaga-Flavobacterium cluster did notexceed 60% of DAPI-stained cells.Beta-Proteobacteriaappeared to be the most abundant group, not only in Traunsee butalso in two reference lakes, Attersee and Hallstättersee. No significant differences in any of the bacterial parameters couldbe detected between the three sampling sites and all measurementswere found in the range reported for oligotrophic lakes. The highdischarge of the Traun River, resulting in a lake water renewaltime of only one year, may diminish possible effects of industrial waste discharge in the pelagic zone.     

太湖流域主要城市洪涝灾害生态风险评价

太湖流域有上海，苏州，无锡，常州，镇江，杭州，嘉兴，湖州八个大中城市，是我国产业最集中，工农业最发达的地区之一，但该地区洪涝灾害频繁，这不仅制约了流域中各城市经济的发展，还严重威胁到该地区城市的生存平衡，本文根据生存风险评价原理，结合太湖流域的自然特点，提出成因分析法的指标模型。并通过分析太湖流域八个大中城市的汛期降雨量和地形地貌因子对洪涝灾害生态风险的影响度，得出各个城市洪涝灾害的生态风险度，最后还根据各城市风险度的大小及其主导因素的不同，提出了如何管理洪涝灾害生态风险的建议。     

江苏省城市防汛决策支持系统研究

在分析江苏省城市防汛问题的基础上，设计了其防汛决策支持系统；根据江苏省城市洪涝灾情特点研建和选用了适宜的数学模型，该模型可以迅速、可靠和正确地模拟城市雨情、水情、灾情的发展过程和可能后果，为城市防汛决策提供多层次的信息服务和多种支持手段。     

我国农业水旱灾害的时间分布及重灾年景趋势预测

分析了我国 1970～ 1999年农业水旱灾害的时间分布特征。分析结果表明 :在研究时段内 ,我国农业自然灾害总体上呈增长态势。该时段可划分为两个明显的阶段 :80年代中期以前 ,总灾、水灾及旱灾对农业生产的危害较轻 ;80年代中期之后 ,呈现出影响范围广、损失增大的趋势 ,重灾年份明显增加。旱灾和水灾是威胁我国农业生产最为严重的自然灾害 ,尤以旱灾为甚。我国农业遭受旱灾威胁的范围多年基本不变 ,而旱灾受灾率波动明显 ,成灾率逐年增长 ,这与近几年农田水利设施建设缓慢、灌溉能力降低有关 ;水灾受灾率和成灾率具有特别显著的同步特点 ,表明水灾致灾能力强 ,一旦发生 ,极易成灾 ,水灾危害加剧与防洪、抗洪能力低下及生态环境恶化有关。各灾种的受灾率和成灾率呈正相关关系 ,表明我国农业生产系统的抗灾能力总体上较弱。　　本文还用灰色系统理论的建模方法 ,建立了农业总受灾率 -总成灾率、水灾受灾率 -成灾率、旱灾受灾率 -成灾率的重灾年景灰色灾变GM(1,1)预测模型 ,对未来 10年我国农业灾害趋势进行了预测分析。灰色预测结果表明 ,2 0 10年之前 ,除 2 0 0 3,2 0 0 6年水旱灾害危害较小外 ,其它年份均为灾情严重年份 ,其受灾率和成灾率均高于近 30年的平均水平。其中 ,2 0 0 4 ,2 0 0 7年将为水灾重     

基于洪水灾害快速评估的承灾体易损性信息管理系统

洪水灾害易损性信息管理系统是为了开展洪水灾害快速评估,对不同洪水灾害流域和同一洪水灾害流域中的不同地区、不同承灾体(财产分类)、不同致灾因子(水深和历时等)条件,以财产的损失率为核心的综合信息管理系统。本文介绍了洪水灾害易损性信息管理系统的开发与设计的基本原理,阐述了系统的总体结构框架和功能模块划分,并且在系统数据流程图的基础上,对损失率数据库等几个重要的模块进行了详细的分析与设计,给出了系统的部分运行结果。本系统在与GIS、遥感等空间技术结合后,能够高效地完成各种洪水灾害损失的快速评估与预测分析工作,同时,本系统亦可独立作为对区域洪水灾害易损性研究的数据基础和理论支撑。     

鄱阳湖洪灾特征与圩区还湖减灾运用方式研究

根据水文资料,分析了鄱阳湖入湖五大河流来水与长江水情对鄱阳湖洪灾的影响和鄱阳湖洪水位的频率特征,探讨了湖区中小圩区"高水还湖滞洪,低水种植养殖"的减灾运行方式对湖区防洪减灾可以起到的作用。     

FLOOD STAGE FORECASTING WITH SUPPORT VECTOR MACHINES1

ABSTRACT: Machine learning techniques are finding more and more applications in the field of forecasting. A novel regression technique, called Support Vector Machine (SVM), based on the statistical learning theory is explored in this study. SVM is based on the principle of Structural Risk Minimization as opposed to the principle of Empirical Risk Minimization espoused by conventional regression techniques. The flood data at Dhaka, Bangladesh, are used in this study to demonstrate the forecasting capabilities of SVM. The result is compared with that of Artificial Neural Network (ANN) based model for one‐lead day to seven‐lead day forecasting. The improvements in maximum predicted water level errors by SVM over ANN for four‐lead day to seven‐lead day are 9.6 cm, 22.6 cm, 4.9 cm and 15.7 cm, respectively. The result shows that the prediction accuracy of SVM is at least as good as and in some cases (particularly at higher lead days) actually better than that of ANN, yet it offers advantages over many of the limitations of ANN, for example in arriving at ANN's optimal network architecture and choosing useful training set. Thus, SVM appears to be a very promising prediction tool.