Functional Ontologies and Their Application to Hydrologic Modeling: Development of an Integrated Semantic and Procedural Knowledge Model and Reasoning Engine

This dissertation represents the research and development of new concepts and techniques for modeling the knowledge about the many concepts we as hydrologists must understand such that we can execute models that operate in terms of conceptual abstractions and have those abstractions translate to the data, tools, and models we use every day. This hydrologic knowledge includes conceptual (i.e. semantic) knowledge, such as the hydrologic cycle concepts and relationships, as well as functional (i.e. procedural) knowledge, such as how to compute the area of a watershed polygon, average basin slope or topographic wetness index. This dissertation is presented as three papers and a reference manual for the software created. Because hydrologic knowledge includes both semantic aspects as well as procedural aspects, we have developed, in the first paper, a new form of reasoning engine and knowledge base that extends the general-purpose analysis and problem-solving capability of reasoning engines by incorporating procedural knowledge, represented as computer source code, into the knowledge base. The reasoning engine is able to compile the code and then, if need be, execute the procedural code as part of a query. The potential advantage to this approach is that it simplifies the description of procedural knowledge in a form that can be readily utilized by the reasoning engine to answer a query. Further, since the form of representation of the procedural knowledge is source code, the procedural knowledge has the full capabilities of the underlying language. We use the term functional ontology to refer to the new semantic and procedural knowledge models. The first paper applies the new knowledge model to describing and analyzing polygons. The second and third papers address the application of the new functional ontology reasoning engine and knowledge model to hydrologic applications. The second paper models concepts and procedures, including running external software, related to watershed delineation. The third paper models a project scenario that includes integrating several models. A key advance demonstrated in this paper is the use of functional ontologies to apply metamodeling concepts in a manner that both abstracts and fully utilizes computational models and data sets as part of the project modeling process

Comparative Evaluation of Generalized River/Reservoir System Models

This report reviews user-oriented generalized reservoir/river system models. The terms reservoir/river system, reservoir system, reservoir operation, or river basin management "model" or "modeling system" are used synonymously to refer to computer modeling systems that simulate the storage, flow, and diversion of water in a system of reservoirs and river reaches. Generalized means that a computer modeling system is designed for application to a range of concerns dealing with river basin systems of various configurations and locations, rather than being site-specific customized to a particular system. User-oriented implies the modeling system is designed for use by professional practitioners (model-users) other than the original model developers and is thoroughly tested and well documented. User-oriented generalized modeling systems should be convenient to obtain, understand, and use and should work correctly, completely, and efficiently. Modeling applications often involve a system of several simulation models, utility software products, and databases used in combination. A reservoir/river system model is itself a modeling system, which often serves as a component of a larger modeling system that may include watershed hydrology and river hydraulics models, water quality models, databases and various software tools for managing time series, spatial, and other types of data. Reservoir/river system models are based on volume-balance accounting procedures for tracking the movement of water through a system of reservoirs and river reaches. The model computes reservoir storage contents, evaporation, water supply withdrawals, hydroelectric energy generation, and river flows for specified system operating rules and input sequences of stream inflows and net evaporation rates. The hydrologic period-of-analysis and computational time step may vary greatly depending on the application. Storage and flow hydrograph ordinates for a flood event occurring over a few days may be determined at intervals of an hour or less. Water supply capabilities may be modeled with a monthly time step and several decade long period-of-analysis capturing the full range of fluctuating wet and dry periods including extended drought. Stream inflows are usually generated outside of the reservoir/river system model and provided as input to the model. However, reservoir/river system models may also include capabilities for modeling watershed precipitation-runoff processes to generate inflows to the river/reservoir system. Some reservoir/river system models simulate water quality constituents along with water quantities. Some models include features for economic evaluation of system performance based on cost and benefit functions expressed as a function of flow and storage

Fostering collective action through participation in natural resource and environmental management: An integrative and interpretative narrative review using the IAD, NAS and SES frameworks

Solving humanity's social-environmental challenges calls for collective action by relevant actors. Hence, involving these actors in the policy process has been deemed both necessary and promising. But how and to what extent can participatory policy interventions (PIs) foster collective action for sustainable environmental and natural resource management? Lab and lab-in-the-field experiments on co-operation in the context of collective action challenges (i.e. social dilemmas) and case study research on participatory processes both offer insights into this question but have hitherto mainly remained unconnected. This article reviews insights from these two streams of literature in tandem, synthesising and analysing them using the institutional analysis and development (IAD) framework in combination with the network of action situations (NAS) framework and the social-ecological systems (SES) framework. We thus perform an integrative and interpretative narrative review to draw a richer and more nuanced picture of PIs: their potential impacts, their (institutional and behavioural) mechanisms and challenges, and caveats and recommendations for their design and implementation. Our review shows that PIs can indeed foster collective action by (a) helping the relevant actors craft suitable and legitimate institutional arrangements and (b) addressing and/or influencing actors' attributes of relevance to collective action, namely their individual and shared understandings, beliefs and preferences. To fulfil this potential, the organisers and sponsors of PIs must address and link to the broader context through soundly designed and implemented processes. Complementary follow-up, enforcement and conflict resolution mechanisms are necessary to nurture, reassure and sustain understandings, beliefs and preferences that undergird trust-building and collective action. The conceptual framework developed for the review can help researchers and practitioners further assess these insights, disentangle PIs' mechanisms and impacts, and integrate the research and practice of participatory governance and collective action

The Quality of Stakeholder-Based Decisions: Lessons from the Case Study Record

The increased use of stakeholder processes in environmental decisionmaking has raised concerns that the inherently “political” nature of such processes may sacrifice substantive quality for political expediency. In particular, there is concern that good science will not be used adequately in stakeholder processes nor be reflected in their decision outcomes. This paper looks to the case study record to examine the quality of the outcomes of stakeholder efforts and the scientific and technical resources stakeholders use. The data for the analysis come from a “case survey,” in which researchers coded information on over 100 attributes of 239 published case studies of stakeholder involvement in environmental decisionmaking. These cases reflect a diversity of planning, management, and implementation activities carried out by environmental and natural resource agencies at many levels of government. Overall, the case study record suggests that there should be little concern that stakeholder processes are resulting in low quality decisions. The majority of cases contained evidence of stakeholders improving decisions over the status quo; adding new information, ideas, and analysis; and having adequate access to technical and scientific resources. Processes that stressed consensus scored higher on substantive quality measures than those that did not. Indeed, the data suggested interesting relationships between the more “political” aspects of stakeholder decisionmaking, such as consensus building, and the quality of decisions.

Integrating Expert System and Geographic Information System for Spatial Decision Making

Spatial decision making is a process of providing an effective solution for a problem that encompasses semi-structured spatial data. It is a challenging task which involves various factors to consider. For example, in order to build a new industry, an appropriate site must be selected for which several factors have to be taken into consideration. Some of the factors, which can affect the decision in this particular case, are air pollution, noise pollution, and distance from living areas, which makes the decision difficult. The geographic information systems (GIS) and the expert systems (ES) have many advantages in solving problems in their prospective areas. Integrating these two systems will benefit in solving spatial decision making problems. In the past, many researchers have proposed integrating systems which extracts the data from the GIS and saves it in the database for decision making. Most of the frameworks which have been developed were system dependent and are not properly structured. So it is difficult to search the data. This thesis proposes a framework which extracts the GIS data and processes it with the help of ES decision making capabilities to solve the spatial decision making problem. This framework is named GeoFilter. This research classifies various types of mechanisms that can be used to integrate these two systems

The CRANE Framework for Simulation Model Workflows

CRANE is presented as a flexible framework for linking simulation models and model support tools to form integrated modelling systems for engineering and scientific applications, evaluated using the scientific workflow approach. CRANE was written using an object-oriented programming language; the separation of its core processing component from its user interface; support for plugins that can be updated and enhanced independent of the framework; and with intuitive user-friendly features and human-readable configuration files. Its strength is its ability to connect to legacy simulation models, whose code cannot be modified, through structured and/or free-format text files. The framework contains an engine that interprets the requirements of simulation models and modelling support tools, and facilitates the flow of data between these components in a simulation workflow. In addition, a user interface provides a familiar graphic interface through which the engine can be configured and monitored during the evaluation of the simulation workflow. A case study was undertaken to demonstrate the ability of CRANE to wrap around, configure, and evaluate two versions of a hydrologic simulation model. Using the default parameter configuration, both versions of the model failed to capture the hydrologic regime of the basin; the modified version of the model only marginally improved the results by redistributing excess meltwater in a presumably more physically based way. The modified version of the model allowed excess meltwater to contribute to ponded storage and infiltrate into soil. By contrast, the original version of the model increased the evaporation rate to account for the excess meltwater. Given the poor overall performance of the model in this particular modelling scenario, the contribution of the modification could not be definitively commented upon. It was concluded that further assessment would be improved by better parameterization of the model. CRANE was used to configure the input files for the model, as well as to execute a simple simulation workflow. Unfortunately, the relative simplicity of the case study did not highlight the more advanced features of the framework. As this is a preliminary introduction of the framework, additional and different types of case studies are recommended, the results from which would identify areas where the framework can continue to be developed and enhanced

Syntactic and Semantic Interoperability Among Hydrologic Models

Development of integrated hydrologic models requires coupling of multidisciplinary, independent models and collaboration between different scientific communities. Component-based modeling provides an approach for the integration of models from different disciplines. A key advantage of component-based modeling is that it allows components to be created, tested, reused, extended, and maintained by a large group of model developers and end users. One significant challenge that must be addressed in creating an integrated hydrologic model using a component-based approach is enhancing the interoperability of components between different modeling communities and frameworks. The major goal of this work is to advance the integration of water related model components coming from different disciplines using the information underlying these models. This is achieved through addressing three specific research objectives. The first objective is to investigate the ability of component-based architecture to simulate feedback loops between hydrologic model components that share a boundary condition, and how data is transfered between temporally misaligned model components. The second objective is to promote the interoperability of components across water-related disciplinary boundaries and modeling frameworks by establishing an ontology for components\u27 metadata. The third study objective is to develop a domain-level ontology for defining hydrologic processes