Design and implementation of a general software library for using NSGA-II with SWAT for multi-objective model calibration

Calibrating watershed-scale hydrologic models remains a critical but challenging step in the modeling process. The Soil and Water Assessment Tool (SWAT) is one example of a widely used watershed-scale hydrologic model that requires calibration. The calibration algorithms currently available to SWAT modelers through freely available and open source software, however, are limited and do not include many multi-objective genetic algorithms (MOGAs). The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) has been shown to be an effective and efficient MOGA calibration algorithm for a wide variety of applications including for SWAT model calibration. Therefore, the objective of this study was to create an open source software library for multi-objective calibration of SWAT models using NSGA-II. The design and implementation of the library are presented, followed by a demonstration of the library through a test case for the Upper Neuse Watershed in North Carolina, USA using six objective functions in the model calibration.     

Data assimilation framework: Linking an open data assimilation library (OpenDA) to a widely adopted model interface (OpenMI)

Data assimilation optimally merges model forecasts with observations taking into account both model and observational uncertainty. This paper presents a new data assimilation framework that enables the many Open Model Interface (OpenMI) 2.0 .NET compliant hydrological models already available, access to a robust data assimilation library. OpenMI is an open standard that allows models to exchange data during runtime, thus transforming a complex numerical model to a ‘plug and play’ like component. OpenDA is an open interface standard for a set of tools, filters, and numerical techniques to quickly implement data assimilation. The OpenDA–OpenMI framework is presented and tested on a synthetic case that highlights the potential of this new framework. MIKE SHE, a distributed and integrated hydrological model is used to assimilate hydraulic head in a catchment in Denmark. The simulated head over the entire domain were significantly improved by using an ensemble based Kalman filter.     

Toward improved calibration of watershed models: Multisite multiobjective measures of information

This paper presents a computational framework for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. The framework consists of three components: 1) an a-priori characterization of system behavior; 2) a formal and statistically valid formulation of objective function(s) of model errors; and 3) an optimization engine to determine the Pareto-optimal front for the selected objectives. The proposed framework was applied for calibration of the Soil and Water Assessment Tool (SWAT) in the Eagle Creek Watershed, Indiana, USA using three single objective optimization methods [Shuffled Complex Evolution (SCE), Dynamically Dimensioned Search (DDS), and DiffeRential Evolution Adaptive Metropolis (DREAM)], and one multiobjective optimization method. Solutions were classified into behavioral and non-behavioral using percent bias and Nash–Sutcliffe model efficiency coefficient. The results showed that aggregation of streamflow and NO_x (NO₃-N + NO₂-N) information measured at multiple locations within the watershed into a single measure of weighted errors resulted in faster convergence to a solution with a lower overall objective function value than using multiple measures of information. However, the DREAM method solution was the only one among the three single objective optimization methods considered in this study that satisfied the conditions defined for characterizing system behavior. In particular, aggregation of streamflow and NO_x responses undermined finding “very good” behavioral solutions for NO_x, primarily because of the significantly larger number of observations for streamflow. Aggregation of only NO_x responses into a single measure expedited finding better solutions although aggregation of data from nested sites appeared to be inappropriate because of correlated errors. This study demonstrates the importance of hydrologic and water quality data availability at multiple locations, and also highlights the use of multiobjective approaches for proper calibration of watershed models that are used for pollutant source identification and watershed management.     

From qualitative to quantitative environmental scenarios: Translating storylines into biophysical modeling inputs at the watershed scale

Scenarios are increasingly used for envisioning future social-ecological changes and consequences for human well-being. One approach integrates qualitative storylines and biophysical models to explore potential futures quantitatively and maximize public engagement. However, this integration process is challenging and sometimes oversimplified. Using the Yahara Watershed (Wisconsin, USA) as a case study, we present a transparent and reproducible roadmap to develop spatiotemporally explicit biophysical inputs [climate, land use/cover (LULC), and nutrients] that are consistent with scenario narratives and can be linked to a process-based biophysical modeling suite to simulate long-term dynamics of a watershed and a range of ecosystem services. Our transferrable approach produces daily weather inputs by combining climate model projections and a stochastic weather generator, annual narrative-based watershed-scale LULC distributed spatially using transition rules, and annual manure and fertilizer (nitrogen and phosphorus) inputs based on current farm and livestock data that are consistent with each scenario narrative.     

面向企业的数据集成建模方法研究

针对目前企业普遍存在的信息孤岛林立和数据断层的局面，本文提出了一种进行企业数据集成的模型——企业统一数据模型，应用该模型可以较好地解决企业混乱的数据环境，建立一个统一高效的企业数据平台。同时本文结合在炼化企业建立统一数据模型的经验，详细论述了企业统一数据模型的建模方法。     

Combining watershed models and knowledge-based models to predict local-scale impacts of climate change on endangered wildlife

Climate change is expected to have significant impacts on native, threatened and endangered wildlife. Understanding and modeling these impacts useful for wildlife managers, however, remain difficult due to complex climate change, and costly and high data requirements. Consequently, we proposed an easily-interpretable and data-efficient decision support approach to understand climate change impacts on the abundance of three endangered wetland birds (Hawaiian Stilt, Hawaiian Coot and Hawaiian Moorhen). We coupled a watershed model, AnnAGNPS, and ecological models using fuzzy-cognitive mapping software, Mental Modeler, in Hanalei watershed, Kauaʻi. Results suggested that increased precipitation would increase Stilt abundance, but decrease Coot and Moorhen abundance. Decreasing precipitation might have negative effects for all three species. Moreover, decision-makers should pay equal attention to controlling components (water depth, food availability and disease) with system-wide influence. Finally, besides being adaptable to similar environmental contexts, our approach captured both direct and indirect climate change impacts through ecological connectivity.     

Supporting Semantic Diversity in the Relational Data Model: The Case of Multi-Face Attributes

In recent years various proposals have been offered for increasing the richness of the relational data model by addressing specific user requirements, particularly with regard to structural and behavioral expressiveness. Although there have been some criticisms of the semantic limitations of the model, few proposals have emerged to address them. In this paper we propose an extension of the model to address some of the semantic limitations around the use of multi-face attributes in everyday activity. We present a formal discussion of multi-face attributes and suggest how they can be accommodated in the relational model and relational database software systems. The resulting model offers a higher-level expressiveness and will provide the user with increased flexibility in the input, output and storage of data, and the specification of queries. Finally we outline some of the implications for database design methods that emerge for the extension.     

概率膜系统在大熊猫种群数据建模中的应用

大熊猫种群数据是掌握大熊猫种群动态变化的重要依据,因此大熊猫种群数据建模对保护大熊猫具有重要意义.本文针对现有种群动态性建模方法无法捕获复杂生态系统的随机效应和可扩展性差的问题,提出一种使用概率膜系统对成都大熊猫繁育研究基地大熊猫种群数据建模的方法.基于成都大熊猫繁育研究基地大熊猫谱系数据,设计了一个具有两层膜结构,形式化表示大熊猫生态系统的一系列对象和规则的概率膜系统模型.仿真实验结果表明,该模型能反映大熊猫种群动态变化趋势,给管理者提供参考.     

从知识图谱到数据中台: 华谱系统

针对碎片化的各姓氏家谱数据, 华谱系统通过构建家谱知识图谱的数据中台, 能够解决数据孤岛、烟囱式开发等问题. “数据中台”是一个源自国内的新近技术概念, 在华谱系统建设中, 我们通过家谱知识图谱的构建和应用, 对这个概念进行了正式定义. 基于这个定义和对应的7项核心功能, 本文提出一种用于家谱数据分析的数据中台建设架构Huapu-CP (华谱系统), 并通过该架构详细介绍面向家谱领域的数据中台核心技术, 分析数据中台构建的关键问题.     

Spatio-Temporal Data Types: An Approach to Modeling and Querying Moving Objects in Databases

Spatio-temporal databases deal with geometries changing over time. In general, geometries cannot only change in discrete steps, but continuously, and we are talking about moving objects. If only the position in space of an object is relevant, then moving point is a basic abstraction; if also the extent is of interest, then the moving region abstraction captures moving as well as growing or shrinking regions. We propose a new line of research where moving points and moving regions are viewed as 3-D (2-D space+time) or higher-dimensional entities whose structure and behavior is captured by modeling them as abstract data types. Such types can be integrated as base (attribute) data types into relational, object-oriented, or other DBMS data models; they can be implemented as data blades, cartridges, etc. for extensible DBMSs. We expect these spatio-temporal data types to play a similarly fundamental role for spatio-temporal databases as spatial data types have played for spatial databases. The paper explains the approach and discusses several fundamental issues and questions related to it that need to be clarified before delving into specific designs of spatio- temporal algebras.     

Data model for extensible support of explicit relationships in design databases

We describe the conceptual model of SORAC, a data modeling system developed at the University of Rhode Island. SORAC supports both semantic objects and relationships, and provides a tool for modeling databases needed for complex design domains. SORAC's set of built-in semantic relationships permits the schema designer to specify enforcement rules that maintain constraints on the object and relationship types. SORAC then automatically generates C++ code to maintain the specified enforcement rules, producing a schema that is compatible with Ontos. This facilitates the task of the schema designer, who no longer has to ensure that all methods on object classes correctly maintain necessary constraints. In addition, explicit specification of enforcement rules permits automated analysis of enforcement propagations. We compare the interpretations of relationships within the semantic and object-oriented models as an introduction to the mixed model that SORAC supports. Next, the set of built-in SORAC relationship types is presented in terms of the enforcement rules permitted on each relationship type. We then use the modeling requirements of an architectural design support system, called Arch Objects, to demonstrate the capabilities of SORAC. The implementation of the current SORAC prototype is also briefly discussed.     

数据组合处理方法在数据预测中的应用

数据组合处理方法（GMDH）是20世纪70年代发展起来的一种启发式自组织建立模型的方法;它能充分地、合理地利用数据,自动进行变量组合,筛选以及判断从而得到合适的模型;简单介绍了该方法建模的基本原理和算法实现,给出了仿真算例,并与用相同资料建立的PPR预测模型的预测结果进行了比较;仿真结果表明,用GMDH方法建立非线性系统模型,具有预测精度高、计算稳定性好等优点。     

运用多维数据模型实现油气勘探数据集市

文中首先介绍了数据集市的概念和构建过程,接着以含油气盆地岩性分析为例,阐述了用多维数据模型并基于多种软件工具实现数据集市的方法与过程。最后给出了在二连盆地利用数据集市进行勘探目标分析的实例。实践结果表明,对于油气勘探信息系统建设而言,数据集市比数据仓库更为简洁、更为实用,其推广和应用也更为可行。     

Logical Representation of a Conceptual Model for Spatial Data Warehouses

The MultiDimER model is a conceptual model used for representing a multidimensional view of data for Data Warehouse (DW) and On-Line Analytical Processing (OLAP) applications. This model includes a spatial extension allowing spatiality in levels, hierarchies, fact relationships, and measures. In this way decision-making users can represent in an abstract manner their analysis needs without considering complex implementation issues and spatial OLAP tools developers can have a common vision for representing spatial data in a multidimensional model. In this paper we propose the transformation of a conceptual schema based on the MultiDimER constructs to an object-relational schema. We based our mapping on the SQL:2003 and SQL/MM standards giving examples of commercial implementation using Oracle 10g with its spatial extension. Further we use spatial integrity constraints to ensure the semantic equivalence of the conceptual and logical schemas. We also show some examples of Oracle spatial functions, including aggregation functions required for the manipulation of spatial data. The described mappings to the object-relational model along with the examples using a commercial system show the feasibility of implementing spatial DWs in current commercial DBMSs. Further, using integrated architectures, where spatial and thematic data is defined within the same DBMS, facilitates the system management simplifying data definition and manipulation.

面向路径的测试数据自动生成工具的设计与实现

面向路径的测试数据生成问题是软件测试中的一个基本问题。Gupta等提出一种线性化谓词函数的迭代松驰方法求解该问题。文献[2]改进了该方法，证明改进后的方法与原方法生成的约束系统相同，文章以改进后的方法为核心算法，根据软件工程的思想，采用面向对象的方法，使用UML进行设计，并且在Linux Red Hat7.0操作系统下用C＋＋语言言实现一个为程序路径自动生成测试数据的原型工具，然后将它移植到Windows操作系统。     

基于压缩数据维的城市建筑用地遥感信息提取

通过压缩数据维的方式，研究城市建筑用地信息准确提取的原理和方法。通过对城市土地利用类型的分析，选取了归一化差异建筑指数、修正归一化差异水体指数和土壤调节植被指数来代表城市建成区的3种最主要地类——建筑用地、水体和植被。通过将ETM 影像原有的7个波段压缩为由它们衍生的这3个采用比值运算构成的指数波段，大大压缩了数据维数、减少了数据的相关度并降低了不同地类的光谱混淆性。因此采用简单的最大似然分类和掩膜处理技术，就可以将城市建筑用地信息提取出来，其精度可达91．2％。     

Prediction of sediment,particulate nutrient and dissolved nutrient concentrations in a dry tropical river to provide input to a mechanistic coastal water quality model

A Generalised Additive Modelling (GAM) approach is applied to prediction of both particulate and dissolved nutrient concentrations in a wet-tropical river (the Fitzroy River, Queensland, Australia). In addition to covariant terms considered in previous work (i.e. flow, discounted flow and a rising-falling limb term), we considered several new potential covariates: meteorological and hydrological variables that are routinely monitored, available in near-real time, and were considered to have potential predictive power. Of the additional terms considered, only flows from three tributaries of the Fitzroy River (namely, the Nogoa, Comet and Isaac Rivers) were found to significantly improve the model. Inclusion of one or more of these additional flow terms greatly improved results for dissolved nitrogen and dissolved phosphorus concentrations, which were not otherwise amenable to prediction. In particular, the Nogoa sub-catchment, dominated by pasture for cattle, was found to be important in determining dissolved inorganic nitrogen and phosphorus concentrations reaching the river mouth. This insight may direct further research, including future refinement of processed-based catchment models. The GAMs described here are used to provide near real-time river boundary conditions for a complex coupled hydrodynamic and biogeochemical model of the Great Barrier Reef Lagoon, and can be coupled with a forecasting hydrological model to allow integrated forecasting simulations of the catchment to coast system.