流域水文信息系统研究与实践综述

流域水文信息系统是地理信息系统、互联网和数据库等技术与水文学研究的结合,集成观测和环境信息的水文信息系统已经成为“数字地球”技术在流域科学方面的重要应用。研究回顾了流域科学的研究方法、发展现状和技术背景,提出当前流域科学研究迫切需要建立水文信息系统,而水文信息系统的重点任务是流域数据建模与数据共享服务。针对目前Arc Hydro水文地理数据模型和开源“协同促进水文科学发展大学联盟”--水文信息系统(CUAHSI\|HIS)的研究进展,提出了一个适合于黑河流域的在线流域水文信息系统设计即“数字黑河”在线门户,集成流域地理数据、观测数据和数据共享服务于一体的流域水文信息系统将有效推动流域科学各方面的研究。     

黑河流域自动观测数据下载系统的改进与应用

黑河流域生态水文WSN观测数据自动综汇系统于2012年7月正式发布。随着数据申请人数骤增,之前采用的权限管理模式、下载流程已经无法满足需求。针对黑河流域自动观测数据共享应用过程中的具体需求,将黑河计划数据管理中心下载系统与黑河流域生态水文WSN观测数据自动综汇下载系统进行对接,对下载系统的权限粒度、授权方式、数据生成及获取方式进行优化改进,极大地提高了数据共享效率,对于自动观测数据的在线共享具有重要意义。     

黑河综合遥感联合试验数据发布

“黑河综合遥感联合试验”(Watershed Allied Telemetry Experimental Research,WATER)是在我国第二大内陆河流域-黑河流域开展的大型航空、卫星遥感和地面同步观测试验。在试验加强观测期结束两年之际,试验数据集正式发布,实现了发展多尺度、多分辨率、高质量并最终完全共享的综合数据集的目标。本文是“黑河综合遥感联合试验”数据专栏的序言,概述了试验数据信息系统的意义、数据集的构成、数据质量控制的基本措施和流程,以及数据共享政策。我们热情邀请国内外同行在内陆河水文与生态研究、定量遥感研究等多方面使用该数据集,共同推进其广泛应用。     

基于Web的科学数据可视化在数据共享中的应用

从数据可视化处理的角度出发,对黑河流域e-Science生态-水文数据共享平台中的所有数据按其各自特点进行归类,大致分为矢量数据、栅格数据、自动气象站观测数据(AWS)、通量数据(FLUX)、普通文档数据和图片数据6种类型;然后通过比较研究,最终选择开源的WebGIS地图发布工具MapServer、基于Flash的Web图表曲线工具Amcharts、开源文档工具OpenOffice/unoconv以及数据格式转换工具SWFTools等制作对应的可视化处理模块,实现科学数据共享平台中多种类型单体数据的Web可视化和数据集的Web可视化,并完成一个实际应用系统。     

面向黑河无线传感网络观测数据的质量控制方法研究

“黑河流域生态水文传感器网络”试验是无线传感器网络技术在近地表观测领域的一次成功应用,通过分析该试验所采集的观测数据的特点,首次给出WSN数据的质量元素的规范内容,并设计出每种质量元素的判定算法,用于解决WSN数据的质量控制问题。之后提供了两个评价实例,其结果表明将这些质量元素判定算法应用到黑河观测数据自动综汇系统中,能够高效、合理地完成“黑河流域生态水文传感器网络”野外观测数据的质量控制工作。     

面向黑河流域生态水文过程集成研究的科学数据汇交与管理

科学数据汇交是科学数据共享的重要数据支撑,在重大科学研究计划中更需要考虑数据的汇交与共享。国家自然科学基金委员会于2010年正式启动了“黑河流域生态-水文过程集成研究”重大研究计划(以下简称“黑河计划”)后,就将黑河计划的数据汇交与管理进行了多次讨论,于2012年推出《黑河计划数据汇交与共享管理条例》(以下简称“管理条例”),由黑河计划数据管理中心负责具体执行。黑河计划数据管理中心基于管理条例,设计并实现了面向黑河计划的科学数据汇交管理系统。回顾了科学数据汇交的发展现状,介绍了管理条例的核心内容,设计了黑河计划数据汇交的技术流程,并将数据提供者的权益保护嵌入到数据服务流程中,并根据黑河计划特点进行数据共享管理。针对数据汇交系统在实现中的关键技术问题进行了讨论,包括集成GeoNetwork系统实现元数据的撰写、以提高数据质量为目标的数据审核、高效的数据服务以及数据的知识挖掘4个方面。     

黑河综合遥感联合试验研究进展:概述

“黑河综合遥感联合试验”是在我国典型的内陆河流域--黑河流域开展的大型航空、卫星遥感和地面同步观测试验。28个单位的280多名科研人员、研究生和工程技术人员参加了试验。介绍了2008年加强试验期以来的研究工作进展。“黑河综合遥感联合试验”最主要的成果是一套多尺度、高质量的综合观测数据集,该数据集已正式对外发布,十分有力地支持了一系列生态、水文、定量遥感模型的发展、改进和验证,试验所期望突破“数据瓶颈”的目标已经实现。此外,已在积雪参数提取、地表冻融微波遥感、森林结构参数的遥感反演、蒸散发观测与遥感估算、土壤水分反演、生物物理参数和生物化学参数反演、水文气象观测、尺度推绎、流域水文模拟和同化应用等方面取得了丰富的研究成果。试验亮点包括蒸散发观测及其遥感模型改进、机载激光雷达的应用、多角度热红外传感器研制和应用;航空遥感在获取高质量、高分辨率数据方面依然具有不可替代的作用。     

黑河综合遥感联合试验的数据管理与共享

“黑河综合遥感联合试验”(Watershed Allied Telemetry Experimental Research,WATER)是在黑河流域开展的以水循环及与之密切联系的生态过程为主要研究对象的大型航空、卫星遥感与地面同步观测科学试验。为了对试验产出和处理后的数据进行统一的管理和共享,促进试验成果在更大范围内的应用,“黑河综合遥感联合试验”建立了数据管理系统,并在中国科学院寒区旱区环境与工程研究所和北京师范大学成立了两个数据服务点负责数据的管理和分发。“黑河综合遥感联合试验”的数据管理系统是一个以元数据为核心的数据管理和发布系统,在数据管理方面介绍了元数据、数据文档和数据实体的组织与管理,在系统功能方面介绍了数据导航和数据可视化。“黑河综合遥感联合试验”目前已发布的原始数据共3.2 TB,预处理的数据2.5 TB,以粗粒度的形式组织了265个数据集,265条元数据与数据报告一起对数据集进行说明。     

异源WSN观测仪器归一化数据接口及自动入库系统的设计与实现

为了远程自动接收黑河流域野外布设的不同类型的WSN观测仪器,并简化后端自动入库程序的复杂度,根据各类仪器的不同特性,对远程接收数据的接口进行了归一化处理;在此基础上,设计实现了数据远程自动入库体系,实现了无人干预的观测数据全自动入库功能,为后续的黑河流域WSN观测数据自动综汇系统应用提供了基础。     

B/S架构下水文模型的构建—以TopModel为例

B/S架构下的水文模型是在线洪水预报预警发布系统的核心功能。首先探讨ASP.NET进行B/S架构水文模型设计的技术原理。继而选择经典的TopModel水文模型作为实验对象,在ASP.NET服务端类型化TopModel,构建了Web SemiTopModel,并简要介绍该模型的实现方式,最后通过实际流域观测数据进行驱动试验,结果较好。     

Data visualization and analysis within a Hydrologic Information System: Integrating with the R statistical computing environment

This paper presents a prototype software system for visualization and analysis of hydrologic data that provides interoperability between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS) and the R statistical computing environment. By linking these two systems within a single desktop software application, an integrated hydrologic data management and analysis environment has been created that simplifies the process used by scientists and engineers to find, access, organize, and analyze the hydrologic data needed in modeling and managing hydrologic and environmental systems. The implementation of this work is a software plug-in for the CUAHSI HIS HydroDesktop software system called HydroR. We describe the design, graphical user interface, and implementation of the HydroR plug-in. An example application of HydroR is presented in which total suspended solids concentrations are modeled for the Little Bear River using a regression developed from turbidity and total suspended solids observations downloaded from the CUAHSI HIS using HydroDesktop. Finally, we conclude with a summary of our experience in developing interoperability between HIS and R and suggest future developments that can extend the capabilities we have developed.     

A watershed data management and visualization system using code-first approach

With rapid growth of population and economic development in northwest China, water resource over-exploitation has led to severe deterioration of watershed ecosystems. In this study, we developed a hydrological information platform (called Watershed Datacenter System) for sharing, managing, analyzing and visualizing a diverse range of hydrologic data collected at watershed scale. This platform can help investigators and geotechnical experts to conduct watershed researches with the intensive data convenience. This Watershed Datacenter system (WDC) is developed with Entity Framework 6 (EF6) approach which based on Model-View-Controller (MVC) architecture pattern and several other useful technologies, such as ArcGIS API and Responsive web design. Observation Database Model (ODM), hydrological model as a service, Web services and time-series analysis tools are seamlessly integrated into our WDC with the help of open source HIS (Hydrologic Information System) from the CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science, Inc.). The results demonstrate that the WDC offers quite a few advantageous features for managing and analyzing of the data for watershed research.     

Integrated modeling within a Hydrologic Information System: An OpenMI based approach

This paper presents a prototype software system for integrated environmental modeling that provides interoperability between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS) and the Open Modeling Interface (OpenMI). The primary motivation for making these two systems interoperable is that the CUAHSI HIS has a primary focus on hydrologic data management and visualization while the OpenMI has a primary focus on integrated environmental modeling. By combining the two systems into a single software application, it is possible to create an integrated environmental modeling environment that scientists and engineers can use to understand and manage environmental systems. Using standards to achieve the steps required to find, gather, integrate, and analyze hydrologic data allows for a wide community of groups to participate because it establishes key rules and protocols that must be followed in order to add to the overarching system. The key contribution of this work, therefore, is an investigation of two standards in the community and exploring ways to provide interoperability between them. HydroModeler is a software implementation of our work and provides an OpenMI-compliant modeling environment embedded within the CUAHSI HIS HydroDesktop software system. We describe the design and implementation of this prototype software system, and then present an example application in which evapotranspiration is modeled using OpenMI components that consume HIS time series data for input. Finally, we conclude with a summary of our experience exploring the potential for interoperability between data and modeling systems, and suggest ways in which future development can better facilitate connections between the various subsystems needed within an integrated environmental modeling system.     

Monthly Runoff Prediction of Zhengyixia in the Heihe River based on Singular Spectrum Analysis-grey Wolf Optimizer-support Vector Regression Hybrid Model

Hydrologic prediction is an important prerequisite for optimal allocation of water resources, but the traditional forecasting methods generally have the problem of low forecasting accuracy. To improve the accuracy of hydrologic prediction, a hybrid data-driven model is proposed for monthly runoff forecasting, namely, Singular Spectrum Analysis-Grey Wolf Optimizer-Support Vector Regression (SSA-GWO-SVR) model. The proposed model uses SSA to denoise the runoff data to improve the stability and predictability of runoff series, and uses GWO to optimize the parameters of SVR model to enhance the generalization ability of the model. This model is validated by monthly runoff prediction of Zhengyixia in the Heihe River Basin, and the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), correlation coefficient (R) and Nash-Sutcliffe Efficiency Coefficien (NSEC) are used as evaluation criteria. The experimental results show that the prediction accuracy of the proposed model is significantly higher than those of Autoregressive Integrated Moving Average model (ARIMA), Persistent Model (PM), Cross Validation(CV)-SVR and GWO-SVR models, and the can predict the runoff peak well, which indicates that the model is a reliable runoff forecasting model, can capture the intrinsic characteristics of hydrologic runoff more deeply, and provides a new method for hydrologic prediction based on data-driven model.     

基于奇异谱分析-灰狼优化-支持向量回归混合模型的黑河正义峡月径流预测

水文预报是水资源优化配置的重要前提,而传统预报方法普遍存在预测精度低的问题,为提高水文预报的准确性,提出了一种混合数据驱动模型用于月径流预测,即奇异谱分析-灰狼优化-支持向量回归(SSA-GWO-SVR)模型。该模型通过SSA对径流数据进行去噪处理来提高径流序列的平稳性和可预测性,采用GWO对SVR模型的参数进行联合选优,从而增强模型的泛化能力。通过黑河正义峡的月径流预测进行模型验证,以平均绝对误差(MAE)、均方根误差(RMSE)、相关系数(R)和纳什效率系数(NSEC)为模型评价标准。实验结果表明该模型的预测精度明显高于自回归积分滑动平均模型(ARIMA)、持续性模型(PM)、交叉验证-SVR(CV-SVR)和GWOSVR模型,并且它能很好地预测径流峰值,说明该模型是一种可靠的径流预测模型,能够更深入地捕获水文径流的内在特性,为基于数据驱动模型的水文预报提供了一种新方法。     

长江流域水文气象信息服务体系设计与实践

长江流域水文气象信息服务体系涵盖水文气象信息收集、预报产品制作、信息管理及成果发布全流程.通过阐述信息服务体系的设计思想、总体框架、系统功能和应用实践,说明水文气象信息服务在防洪减灾、水工程调度、河流水质保护、水资源管理与保护方面的应用情况.信息服务体系以长江流域水库群信息共享平台、水情App和预报调度系统为基础进行融...     

利用MODIS植被指数评估分水对黑河中游的影响

为缓解黑河下游额济纳旗生态恶化的现状,国家对黑河流域实施了分水政策。在下游环境得到了充分改善的同时,中游绿洲地区的发展却受到了不同程度的限制。利用2000~2004年的MODIS归一化植被指数数据,对中游两个绿洲地区连续5 a生长季的植被覆盖面积进行监测。分析并对比其植被覆盖面积的增长趋势,对黑河流域中游地区受分水影响的程度做出评估。