松耦合模型驱动的流域水资源管理决策支持系统研究及应用
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摘要
流域水资源具有发电、供水、航运、灌溉、养殖等多种适用价值和功能，如何合理开发、利用、节约和保护水资源并防治水害是一个事关科学发展的全局性根本性问题，同时也是一个关系国计民生的战略问题。我国水资源相当贫乏，水问题异常突出，且随着人类活动对水资源系统扰动程度的加深以及社会发展进程的高速推进，水资源的供需矛盾将更加严重，另一方面，近些年极端气候事件频发态势进一步增加了流域水资源管理的复杂性与不确定性。如何在流域范围内以最少的水资源、资金和人力的投入获得最大的社会效益、经济效益和环境效益是当前流域水资源管理的首要目标。流域水资源系统是一个受诸多方面因素影响的复杂系统，且流域水资源管理决策过程涉及社会、经济、水文、水动、水工和生态等多个领域，是一个典型半结构化的多层次、多主体、多目标决策问题，以信息管理系统为代表的传统模式已无法适应现代流域水资源管理的需求。基于预报、分析、局部搜索、多目标多属性决策、最优化、模拟、评估、知识、方法、数字化技术等多学科辅助决策运算单元（本文范畴内统称为“模型”，Model）的决策支持系统将辅助流域水资源管理部门更好地开展水资源规划管理工作，其中保证面向决策需求的动态适应性与异质包容性是决定此类决策支持系统性能的关键。本文首次提出了一种以模型为中心，以决策行为优化环与决策技术优化环双层松耦合迭代优化结构为主要特点的决策支持系统建模与设计方法，定义它为松耦合模型驱动决策支持系统（Loose-couplingModel-driven Decision Support System，简称LCMD-DSS），并详细阐述了其决策机理、体系架构以及相关关键技术。近四年来，这一系统方法被成功应用到包括国家973计划项目应用示范在内的水资源管理实际工程应用中，应用效果表明LCMD-DSS具有良好的异质包容性、动态适应性与普适性推广前景。另一方面，随着相关知识产权保护规范与模型应用协议体系的完善，LCMD-DSS将极大地促进科研院所先进的流域水资源管理领域理论算法与实际工程实践相结合的学-研-产新模式的高速发展，为科学地开展流域水资源管理工作，实现“水资源可持续利用”国家战略提供理论基础与技术支撑。本文的主要研究成果和创新点包括：
（1）针对流域水资源管理决策过程多层次、多主体、多目标且半结构化的特点，设计了基于双层迭代优化结构的持续集成松耦合系统体系，明确了系统框架下各相关角色的作用与分工，探讨了这一系统方法在流域水资源管理领域的决策机理，提出了松耦合模型驱动的流域水资源管理决策支持系统方法；
（2）针对LCMD-DSS系统集成所面对的海量多源异构数据集成、网络分布式开放模型集成与基于GIS动态生成交互平台搭建等难题，综合运用地球科学、信息科学、计算机科学、空间科学、通信科学、管理科学、经济人文科学等多学科理论和技术成果，结合数字工程方法克服传统信息系统的物理边缘、技术边缘、功能边缘和逻辑思维边缘，建立了流域水资源管理统一数据共享平台，研发了网络分布式模型驱动的水资源管理智能化开放式模型库，设计并实现了基于WPF与GIS的动态生成交互平台，为LCMD-DSS双层迭代优化机制提供了核心技术支撑；
（3）针对流域水资源管理情景推演需求，综合考虑不规则边界和复杂地形的浅水流动数值计算问题，基于不规则三角形网格单元求解二维浅水方程的高精度Godunov型有限体积模型；研发了一系列用于数据分析与可视化转换的普适性GP服务，以模型的形式集成到系统开放式模型库，实现了流域水资源管理情景推演的数值仿真及可视化模拟；
（4）以国家治水方针、水利部可持续利用治水新思路为指导，以辅助水行政主管部门自上而下调度协调流域水资源为目的，以研究并实现具有普适性意义的流域水资源管理决策支持系统为切入点，以持续优化LCMD方法的系统理论框架（决策行为优化环）与技术储备库（决策技术优化环）为技术路线，开展了LCMD-DSS在流域水资源管理领域的示范推广工作。
Basin water resources have many applicable values and functions, such as flood control,power generation, water supply, navigation, irrigation and aquaculture. The way forrational development, utilization, conservation and protection of water resources asprevention of water disaster is a matter of global fundamental issues to scientificdevelopment, as well as a livelihood strategy. The water resources are very poor in China,exception highlighting on the water problem. With the development of industry andagriculture, as the improving live standards of urban and rural people, the contradictionbetween demand and supply of the water resources will become more serious. On theother hand, frequent extreme weather events during recent years further increase thecomplexity and uncertainty about the basin-water-resources management. Its primaryobjective is the way to use the water resources with minimal input from, financial andhuman resources to maximize social, economic and environmental benefits.Basin-water-resources system is a complex system under the effect on many aspects.Furthermore, the decision-making process of basin-water-resources management involvedmultiple areas, e.g. social, economic, hydrological, water flowing, hydraulic andecological. Therefore, it is a typical half structure problem with multi-levels,multi-department and multi-objective properties. The traditional information managementsystem cannot adapt the needs of modern basin-water-resources management. Based onthe multidisciplinary decision-making operation unit, such as forecast, analysis, localsearch, and multi-objective multi-property decision-making, optimization, simulation,assessment, knowledge search, method and digital technology, which are defined as Modelin this paper, decision support system will help the basin-water-resources manager to becarried out management better. Its key points are dynamic adaptability and heterogeneity.This article proposed a model-centric, two-tier loosely coupled iterative optimizationstructure with Behavior-optimized-ring and Technology-optimized-ring as the mainfeature. We define this new system as a Loose-coupling Model-driven Decision SupportSystem, referred to LCMD-DSS, and propose its decision-making mechanism, systemarchitecture and key technologies. For nearly four years, this method is widely applied to alarge number of practical applications, represented by the973project. Compared with traditional solutions, we believe that this model-driven method is reasonable, reliable andflexible, thus has bright prospects of application for comprehensive basin-water-resourcesmanagement. On the other hands, with the development of intellectual property protectionand model application agreement, LCMD-DSS will greatly promote the advancement ofthe new learn-Institute-produced mode by combining the theory algorithm and actualengineering practice. It can provide theory and technology support for the sciencebehavior to carry out basin-water-resources management work, as achieve the nationalstrategy which titled Continued Using of Water Resource. This article's main point ofresearch and innovation are as follows:
(1) Focusing the half-structure, multi-levels, multi-department and multi-objectiveproperties of basin-water-resources management, we design a two-tier iterativeoptimization structure for continued integrated loose-coupling system, set up the divisionof the related roles, illustrate the loose-coupling technical framework through identifyingand incorporating the key components, define our LCMD method and propose anarchitecture for designing;
(2) Facing the integration challenges of LCMD-DSS, such as integrating of massmulti-source heterogeneous data, distributed open model gallery and based on GIS-baseddynamic generated interactive platform. Using multi-discipline method, i.e. earth science,information science, computer science, space science, communications science,management science, economic, first, a uniform data platform (as Database Service) ispresented to share multi-source data. Next, an open library (as Multidisciplinary ModelService) is presented to integrate cross-platform models. And, a universal linkage (as GISService) between GIS and models is presented by use of Service-oriented approach.Finally, a flexible interface system (as Interface Service) is presented to help practitionerscustomize the application for decision makers. They can provide technology support fortwo-tier loosely coupled iterative optimization structure of LCMD-DSS;
(3) A well-balanced Godunov-type finite volume algorithm is developed for modelingfree-surface shallow flows over irregular topography with complex geometry. Thealgorithm is based on a new formulation of the classical shallow-water equations inhyperbolic conservation form. Unstructured triangular grids are used to achieve the adaptability of the grid to the geometry of the problem and to facilitate localizedrefinement. The numerical fluxes are calculated using HLLC approximate Riemann solver,and the MUSCL-Hancock predictor-corrector scheme is adopted to achieve thesecond-order accuracy both in space and in time where the solutions are continuous, andto achieve high-resolution results where the solutions are discontinuous. The novelties ofthe algorithm include preserving well-balanced property without any additional correctionterms and the wet/dry front treatments. It provides a platform for numerical simulation andvisual simulation of basin-water-resources management stories;
(4) Following the guide of new basin-water-resources management thought, the targetof supporting water-administrative-sector to coordinate their work, the need of developingthe general suitable decision support system, and the way to continued optimizationLCMD method by the theory framework, referred to Behavior-optimized-ring, andtechnology library, referred to Technology-optimized-ring, the LCMD-DSS was employedto manage the basin-water-resources for experimental detection.
（1）针对流域水资源管理决策过程多层次、多主体、多目标且半结构化的特点，设计了基于双层迭代优化结构的持续集成松耦合系统体系，明确了系统框架下各相关角色的作用与分工，探讨了这一系统方法在流域水资源管理领域的决策机理，提出了松耦合模型驱动的流域水资源管理决策支持系统方法；
（2）针对LCMD-DSS系统集成所面对的海量多源异构数据集成、网络分布式开放模型集成与基于GIS动态生成交互平台搭建等难题，综合运用地球科学、信息科学、计算机科学、空间科学、通信科学、管理科学、经济人文科学等多学科理论和技术成果，结合数字工程方法克服传统信息系统的物理边缘、技术边缘、功能边缘和逻辑思维边缘，建立了流域水资源管理统一数据共享平台，研发了网络分布式模型驱动的水资源管理智能化开放式模型库，设计并实现了基于WPF与GIS的动态生成交互平台，为LCMD-DSS双层迭代优化机制提供了核心技术支撑；
（3）针对流域水资源管理情景推演需求，综合考虑不规则边界和复杂地形的浅水流动数值计算问题，基于不规则三角形网格单元求解二维浅水方程的高精度Godunov型有限体积模型；研发了一系列用于数据分析与可视化转换的普适性GP服务，以模型的形式集成到系统开放式模型库，实现了流域水资源管理情景推演的数值仿真及可视化模拟；
（4）以国家治水方针、水利部可持续利用治水新思路为指导，以辅助水行政主管部门自上而下调度协调流域水资源为目的，以研究并实现具有普适性意义的流域水资源管理决策支持系统为切入点，以持续优化LCMD方法的系统理论框架（决策行为优化环）与技术储备库（决策技术优化环）为技术路线，开展了LCMD-DSS在流域水资源管理领域的示范推广工作。
Basin water resources have many applicable values and functions, such as flood control,power generation, water supply, navigation, irrigation and aquaculture. The way forrational development, utilization, conservation and protection of water resources asprevention of water disaster is a matter of global fundamental issues to scientificdevelopment, as well as a livelihood strategy. The water resources are very poor in China,exception highlighting on the water problem. With the development of industry andagriculture, as the improving live standards of urban and rural people, the contradictionbetween demand and supply of the water resources will become more serious. On theother hand, frequent extreme weather events during recent years further increase thecomplexity and uncertainty about the basin-water-resources management. Its primaryobjective is the way to use the water resources with minimal input from, financial andhuman resources to maximize social, economic and environmental benefits.Basin-water-resources system is a complex system under the effect on many aspects.Furthermore, the decision-making process of basin-water-resources management involvedmultiple areas, e.g. social, economic, hydrological, water flowing, hydraulic andecological. Therefore, it is a typical half structure problem with multi-levels,multi-department and multi-objective properties. The traditional information managementsystem cannot adapt the needs of modern basin-water-resources management. Based onthe multidisciplinary decision-making operation unit, such as forecast, analysis, localsearch, and multi-objective multi-property decision-making, optimization, simulation,assessment, knowledge search, method and digital technology, which are defined as Modelin this paper, decision support system will help the basin-water-resources manager to becarried out management better. Its key points are dynamic adaptability and heterogeneity.This article proposed a model-centric, two-tier loosely coupled iterative optimizationstructure with Behavior-optimized-ring and Technology-optimized-ring as the mainfeature. We define this new system as a Loose-coupling Model-driven Decision SupportSystem, referred to LCMD-DSS, and propose its decision-making mechanism, systemarchitecture and key technologies. For nearly four years, this method is widely applied to alarge number of practical applications, represented by the973project. Compared with traditional solutions, we believe that this model-driven method is reasonable, reliable andflexible, thus has bright prospects of application for comprehensive basin-water-resourcesmanagement. On the other hands, with the development of intellectual property protectionand model application agreement, LCMD-DSS will greatly promote the advancement ofthe new learn-Institute-produced mode by combining the theory algorithm and actualengineering practice. It can provide theory and technology support for the sciencebehavior to carry out basin-water-resources management work, as achieve the nationalstrategy which titled Continued Using of Water Resource. This article's main point ofresearch and innovation are as follows:
(1) Focusing the half-structure, multi-levels, multi-department and multi-objectiveproperties of basin-water-resources management, we design a two-tier iterativeoptimization structure for continued integrated loose-coupling system, set up the divisionof the related roles, illustrate the loose-coupling technical framework through identifyingand incorporating the key components, define our LCMD method and propose anarchitecture for designing;
(2) Facing the integration challenges of LCMD-DSS, such as integrating of massmulti-source heterogeneous data, distributed open model gallery and based on GIS-baseddynamic generated interactive platform. Using multi-discipline method, i.e. earth science,information science, computer science, space science, communications science,management science, economic, first, a uniform data platform (as Database Service) ispresented to share multi-source data. Next, an open library (as Multidisciplinary ModelService) is presented to integrate cross-platform models. And, a universal linkage (as GISService) between GIS and models is presented by use of Service-oriented approach.Finally, a flexible interface system (as Interface Service) is presented to help practitionerscustomize the application for decision makers. They can provide technology support fortwo-tier loosely coupled iterative optimization structure of LCMD-DSS;
(3) A well-balanced Godunov-type finite volume algorithm is developed for modelingfree-surface shallow flows over irregular topography with complex geometry. Thealgorithm is based on a new formulation of the classical shallow-water equations inhyperbolic conservation form. Unstructured triangular grids are used to achieve the adaptability of the grid to the geometry of the problem and to facilitate localizedrefinement. The numerical fluxes are calculated using HLLC approximate Riemann solver,and the MUSCL-Hancock predictor-corrector scheme is adopted to achieve thesecond-order accuracy both in space and in time where the solutions are continuous, andto achieve high-resolution results where the solutions are discontinuous. The novelties ofthe algorithm include preserving well-balanced property without any additional correctionterms and the wet/dry front treatments. It provides a platform for numerical simulation andvisual simulation of basin-water-resources management stories;
(4) Following the guide of new basin-water-resources management thought, the targetof supporting water-administrative-sector to coordinate their work, the need of developingthe general suitable decision support system, and the way to continued optimizationLCMD method by the theory framework, referred to Behavior-optimized-ring, andtechnology library, referred to Technology-optimized-ring, the LCMD-DSS was employedto manage the basin-water-resources for experimental detection.
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