Using a data grid to automate data preparation pipelines required for regional-scale hydrologic modeling

Modeling a regional-scale hydrologic system introduces major data challenges related to the access and transformation of heterogeneous datasets into the information needed to execute a hydrologic model. These data preparation activities are difficult to automate, making the reproducibility and extensibility of model simulations conducted by others difficult or even impossible. This study addresses this challenge by demonstrating how the integrated Rule Oriented Data Management System (iRODS) can be used to support data processing pipelines needed when using data-intensive models to simulate regional-scale hydrologic systems. Focusing on the Variable Infiltration Capacity (VIC) model as a case study, data preparation steps are sequenced using rules within iRODS. VIC and iRODS are applied to study hydrologic conditions in the Carolinas, USA during the period 1998–2007 to better understand impacts of drought within the region. The application demonstrates how iRODS can support hydrologic modelers to create more reproducible and extensible model-based analyses.     

Modeling climate change uncertainties in water resources management models

The impact of climate change on hydrologic design and management of hydrosystems could be one of the important challenges faced by future practicing hydrologists and water resources managers. Many water resources managers currently rely on the historical hydrological data and adaptive real-time operations without consideration of the impact of climate change on major inputs influencing the behavior of hydrologic systems and the operating rules. Issues such as risk, reliability and robustness of water resources systems under different climate change scenarios were addressed in the past. However, water resources management with the decision maker’s preferences attached to climate change has never been dealt with. This short paper discusses issues related to impacts of climate change on water resources management and application of a soft-computing approach, fuzzy set theory, for climate-sensitive management of hydrosystems. A real-life case study example is presented to illustrate the applicability of a soft-computing approach for handling the decision maker’s preferences in accepting or rejecting the magnitude and direction of climate change.     

A three-dimensional hydro-geochemical model to assess lake acidification risk

Biogeochemical and hydrological fluxes from riparian zones to lake environments can be significant, particularly for shallow systems experiencing large variations in water level, yet they are not considered in water quality models. To address this challenge we dynamically coupled a three-dimensional surface water model with a soil hydro-geochemical model of the riparian zone and used the coupled system to simulate the impacts of acid sulfate soils on the water quality of a morphologically complex coastal lake system in South Australia. A 3-yr simulation was undertaken to capture a period of exposure and re-flooding of pyrite-bearing sediments and acid fluxes to the lake. Model performance was assessed against data from several acidification events that occurred and the simulations reproduced the observed spatio-temporal variation in the expression of soil and water acidity. The model approach introduced here has potential for simulating systems where the terrestrial–aquatic linkage is important in shaping water quality.     

A multi-scale urban integrated assessment framework for climate change studies: A flooding application

In order to assess the potential future impacts of climate change on urban areas, tools to assist decision-makers to understand future patterns of risk are required. This paper presents a modelling framework to allow the downscaling of national- and regional-scale population and employment projections to local scale land-use changes, providing scenarios of future socio-economic change. A coupled spatial interaction population model and cellular automata land development model produces future urbanisation maps based on planning policy scenarios. The framework is demonstrated on Greater London, UK, with a set of future population and land-use scenarios being tested against flood risk under climate change. The framework is developed in Python using open-source databases and is designed to be transferable to other cities worldwide.     

Modeling of urban growth dynamics and its impact on surface runoff characteristics

Modeling urban growth and generating scenarios are essential for studying the impact and sustainability of an urban hydrologic system. Urban systems are regarded as complex self-organizing systems, where the dynamic transitions from one form of landuse to another occur over a period of time. Therefore, a modeling framework that captures and simulates this complex behavior is essential for generating urban growth scenarios. Cellular Automata (CA)-based models have the potential to model such discrete dynamic systems. In this study, a constraint-based binary CA model was used to predict the future urban growth scenario of the city of Roorkee (India). A hydrologic model was applied on the simulated urban catchment to study its hydrologic response. The Natural Resources Conservation Service Curve Number (NRCS-CN) method, which is suitable for ungauged urban watersheds, was adopted to determine the impact of urban growth on the quantity of storm water runoff over a period of time. The results indicate that urban growth has a linear relationship with peak discharge and time to peak for the catchment under investigation.     

Including the influence of groundwater exchanges in a lumped rainfall-runoff model

The growing realisation that groundwater and surface water systems are components of connected hydrologic system has in recent years sparked the development of integrated surface–ground water models. In this paper, a version of the IHACRES rainfall-runoff model is presented, in which the CMD module for calculating effective rainfall is coupled to a streamflow-groundwater module, and applied to the Coxs Creek catchment, a variably gaining-losing stream system in Australia. The aim is to determine the capacity for the coupled model to capture the switching off–on behaviour evident in the observed flow record. Model performance can be improved in terms of event prediction, volume of baseflow and the percentile of flow cessation, through manipulation of CMD parameters, however, improvements in some performance criteria come at the expense of performance in others. An analysis of the input rainfall time-series, generated using a standard weighted Thiessen polygon approach, reveals mismatches between observed streamflow events and the occurrence of rainfall, which impose major limits on model performance. The challenge is to develop a simple lumped rainfall-runoff model that has the potential to improve system understanding and allow for meaningful exploration of alternate climate, groundwater extraction and land use change scenarios, given a situation of data poor catchments in many parts of Australia.     

A software library for quantifying regional-scale nitrogen transport within river basin systems

A software library for quantifying nitrogen fate and transport at the regional-scale is presented as a tool for managing river basin systems. The tool is based on the United States Geological Survey (USGS) SPAtially Referenced Regression on Watershed attributes (SPARROW) model and implements the prediction portion of SPARROW to quantify overland and in-stream losses of nitrogen within a river basin system. The intention of the software library is to serve as an Application Programmers Interface (API) that can be used to construct analysis and visualization tools that address a variety of management scenarios. By leveraging the API along with other existing open source and freely available software libraries for visualization, numerical methods, and network algorithms, it is possible to produce decision support tools that relate pollution sources to downstream loadings. These tools can be used by water resource managers to understand how hypothetical regional-scale changes to the landscape (e.g. land use change) might impact water quality conditions. The use of the model API is demonstrated with a case study that addresses three potential management questions regarding nitrogen fate and transport in the Upper Neuse River Basin of North Carolina.     

A generic approach for developing process-level hydrologic modeling components

Component software architectures offer an alternative approach for building large, complex hydrologic modeling systems. In contrast to more traditional software paradigms (i.e. procedural or object-oriented approaches), using component-based approaches allows individuals to construct autonomous modeling units that can be linked together through shared boundary conditions during a simulation run. One of the challenges in component-based modeling is designing a simple yet robust means for authoring model components. We address this challenge by presenting an approach for efficiently creating standards-based, process-level hydrologic modeling components. Using this approach, a hydrologic process is implemented as a modeling component by (1) authoring a configuration file that defines the properties of the component and (2) creating a class with three methods that define the pre-run, runtime, and post-run behavior of the modeling component. We present the design and implementation of this approach, which we call the Simple Model Wrapper (SMW), and demonstrate how it can be applied to create an Open Modeling Interface (OpenMI)-compliant modeling component for a basic hydrologic process.     

Large-scale analytical water quality model coupled with GIS for simulation of point sourced pollutant discharges

Mathematical modeling is an important tool for water quality studies, and the integration of water quality models with geographic information systems (GIS) is very useful for information extraction and for results interpretation. In this context, this work presents the development of a water quality model coupled with GIS (MapWindow GIS) for representing impacts of point-sourced pollutants released with distinct durations under different flow scenarios, allowing a systemic view of the entire basin, and capable of being used with low data availability. The model is called SIAQUA-IPH and uses a pollutograph convolution scheme to represent multiple discharges and confluences in the basin, based on analytical solutions of the longitudinal advection-dispersion equation. Operational tests presented a full operational performance from all technical solutions adopted, and a representation of plumes considered satisfactory in comparison to observations. Additionally, a simple sensitivity analysis is presented, that gives useful insights about the model application.     

An integrated assessment approach to conduct analyses of climate change impacts on whole-farm systems

This paper argues that an integrated assessment (IA) approach, combining simulation modelling with deliberative processes involving decision makers and other stakeholders, has the potential to generate credible and relevant assessments of climate change impacts on farming systems. The justification for the approach proposed is that while simulation modelling provides an effective way of exploring the range of possible impacts of climate change and a means of testing the consequences of possible management or policy interventions, the interpretation of the outputs is highly dependent on the point of view of the stakeholder. Inevitably, whatever the responses to climate change, there will be trade-offs between the benefits and costs to a range of stakeholders. The use of a deliberative process that includes stakeholders, both in defining the topics addressed and in debating the interpretations of the outcomes, addresses many of the limitations that have been previously identified in the use of computer-based tools for agricultural decision support. The paper further argues that the concepts of resilience and adaptive capacity are useful for the assessment of climate change impacts as they provide an underpinning theory for processes of change in land use systems. The integrated modelling framework (IMF) developed for the simulation of whole-farm systems is detailed, including components for crop and soil processes, livestock systems and a tool for scheduling of resource use within management plans. The use of the IMF for assessing climate change impacts is then outlined to demonstrate the range of analyses possible. The paper concludes with a critique of the IA approach and notes that issues of quantification and communication of uncertainty are central to the success of the methodology.     

A UML package for specifying real-time objects

The Unified Modeling Language (UML) provides a robust set of tools for modeling software systems. However, these tools do not directly address the requirements of real-time systems. Many real-time systems require the specification of data that has strict timing constraints. This paper presents a UML package for specifying real-time objects called RT-Object. The constructs in the package are based on the objects of the Real-Time Semantic Objects Relationships And Constraints (RTSORAC) model. The RT-Object package has been used to design real-time objects in a Real-Time Multi-User Virtual Environment (RTMUVE), in which widely distributed users collaborate in time-critical planning and decision making.     

Exploring uncertainty and model predictive performance concepts via a modular snowmelt-runoff modeling framework

Model selection is an extremely important aspect of many hydrologic modeling studies because of the complexity, variability, and uncertainty that surrounds the current understanding of watershed-scale systems. However, development and implementation of a complete precipitation-runoff modeling framework, from model selection to calibration and uncertainty analysis, are rarely confronted. This paper introduces a modular precipitation-runoff modeling framework that has been developed and applied to a research site in Central Montana, USA. The case study focuses on an approach to hydrologic modeling that considers model development, selection, calibration, uncertainty analysis, and overall assessment. The results of this case study suggest that a modular framework is useful in identifying the interactions between and among different process representations and their resultant predictions of stream discharge. Such an approach can strengthen model building and address an oft ignored aspect of predictive uncertainty; namely, model structural uncertainty.     

An optimization-model-based interactive decision support system for regional energy management systems planning under uncertainty

In this study, an interactive decision support system (UREM-IDSS) has been developed based on an inexact optimization model (UREM, University of Regina Energy Model) to aid decision makers in planning energy management systems. Optimization modeling, scenario development, user interaction, policy analysis and visual display are seamlessly integrated into the UREM-IDSS. Uncertainties in energy-related parameters are effectively addressed through the interval linear programming (ILP) approach, improving the robustness of the UREM-IDSS for real-world applications. Thus, it can be used as an efficient tool for analyzing and visualizing impacts of energy and environmental policies, regional/community sustainable development strategies, emission reduction measures and climate change in an interactive, flexible and dynamic context. The Region of Waterloo has been selected to demonstrate the applicability and capability of the UREM-IDSS. A variety of scenarios (including a reference case) have been identified based on different energy management policies and sustainable development strategies for in-depth analysis of interactions existing among energy, socio-economy, and environment in the Region. Useful solutions for the planning of energy management systems have been generated, reflecting complex tradeoffs among energy-related, environmental and economic considerations. Results indicate that the UREM-IDSS can be successfully used for evaluating and analyzing not only the effects of an individual policy scenario, but also the variations between different scenarios compared with a reference case. Also, the UREM-IDSS can help tackle dynamic and interactive characteristics of the energy management system in the Region of Waterloo, and can address issues concerning cost-effective allocation of energy resources and services. Thus, it can be used by decision makers as an effective technique in examining and visualizing impacts of energy and environmental policies, regional/community development strategies, emission reduction measures, and climate change within an integrated and dynamic framework.     

多层多视多体建模方法研究

仿真是一种基于模型的试验行为，从某种意义上，模型的正确和准确，决定了仿真的效率和质量。但一组好的模型的诞生，必须有一套正确的建模方法作支持。从这个角度讲，一种科学有效的建模方法比一组好的模型更重要。该文在归纳目前国内外仿真界较为流行的多种建模方法并进行对比分析的基础上，提出了多层多视多体建模的思想，并给出了该建模方法的具体应用过程。最后，采用该文方法，建立了一组仿真模型。     

面向对象建模集成环境AML-Tools的设计与实现

该文描述了一个新的面向对象建模集成环境AML-Tools。AML是一个基于Ada95的建模语言,它吸取了Ada95的基本原理和思想,利用支持面向对象建模的设施对其进行扩充和改造,使之适用于软件建模的各个阶段;引进了程序包、任务等程序单元的概念并使之成为AML的核心成份;吸取了多视点模型的思想,将描述同一实体不同侧面特征的信息分别封装在相应的程序单元声明、程序单元体和程序单元描述中;利用新的并发模型、同步设施和限制设施,有效地解决了系统并发性、不确定性等非功能特性的描述问题。     

The implications of complexity for integrated resources management

Integrated environmental resources management is a purposeful activity with the goal to maintain and improve the state of an environmental resource affected by human activities. In many cases different goals are in conflict and the notion “integrated” clearly indicates that resources management should be approached from a broad perspective taking all potential trade-offs and different scales in space and time into account. However, we are yet far from putting into practice integrated resources management fully taking into account the complexity of human-technology-environment systems. The tradition of resources management and of dealing with environmental problems is characterized by a command and control approach. The increasing awareness for the complexity of environmental problems and of human-technology-environment systems has triggered the development of new management approaches. The paper discusses the importance of focusing on the transition to new management paradigms based on the insight that the systems to be managed are complex adaptive systems. It provides arguments for the role of social learning processes and the need to develop methods combining approaches from hard and soft systems analysis. Soft systems analysis focuses on the importance of subjective perceptions and socially constructed reality. Soft systems methods and group model building techniques are quite common in management science where the prime target of management has always been the social system. Resources management is still quite slow to take up such innovations that should follow as a logical consequence of adopting an integrated management approach. Integrated water resources management is used as example to provide evidence for the need to implement participatory and adaptive management approaches that are able to cope with increasing uncertainties arising from fast changing socio-economic conditions and global and climate change. Promising developments and future research directions are discussed. The paper concludes with pointing out the need for changes in the scientific community to improve the conditions for interdisciplinary, system-oriented and trans-disciplinary research.     

A simulation model to study the impact of resource changes on motor vehicle division field offices

This paper presents a network-based simulation model for the microcomputer to solve the resource balancing problem. The specific application discussed is systems planning for Motor Vehicles operations; however, the approach is adaptable to many organizations. The developed software is an interactive concept program, and can be used by people with no experience in computer programming.     

Towards integrating GIS and catchment models

Modeling the impact of non-point source pollution in catchments is a complex problem, and one that has troubled natural resource managers for many years. The development of spatially distributed hydrologic models has led to improved model forecasting at the cost of requiring more detailed spatial information. In addition, the analysis is much more sensitive to errors in the data. Incorporation of catchment models into a Geographical Information System (GIS) has improved matters by streamlining data input and providing better interpretation of model outputs. This paper reviews different strategies for linking a catchment model with GIS. It examines data issues related to the performance of models and how well they match physical landscape conditions. Integration with GIS is shown to be necessary for the efficient and proper operation of models in resource management situations. The paper concludes that tighter integration between generic sub-models for physical landscape processes and GIS is still required.