Modeling within a Digital Watershed Context

2008 S.C. Water Resources Conference - Addressing Water Challenges Facing the State and Regio

Design of a Metadata Framework for the Environmental Models with an Example Hydrologic Application in HydroShare

Environmental modelers rely on a variety of computational models to make predictions, test hypotheses, and address specific problems related to environmental science and natural resource management. Scientists and engineers must devote significant effort to preparing these computational models. While significant attention has been devoted to sharing and reusing environmental data, less attention has been devoted to sharing and reusing environmental models. A first step toward increasing environmental model sharing and reuse is to define a general metadata framework for models that is flexible and, therefore, applicable across the wide variety of models used by environmental modelers. This paper proposes a general approach for representing environmental model metadata that extends the Dublin Core metadata framework. The framework is implemented within the HydroShare system and applied for a hydrologic model sharing use case. This example application demonstrates how the metadata framework implemented within HydroShare can assist in model sharing, publication, reuse, and reproducibility

An Architectural Overview Of HydroShare, A Next-Generation Hydrologic Information System

HydroShare is an online, open-source, collaborative system being developed for sharing hydrologic data and models as part of the NSF’s Software Infrastructure for Sustained Innovation (SI2) program. The goal of HydroShare is to enable scientists to easily discover and access hydrologic data and models, retrieve them to their desktop, or perform analyses in a distributed computing environment that may include grid, cloud, or high performance computing. Scientists may also publish outcomes (data, results or models) into HydroShare, using the system as a collaboration platform for sharing data, models, and analyses. HydroShare involves a large distributed software development effort requiring collaboration between domain scientists, software engineers, and software developers across eight U.S. universities, RENCI, and CUAHSI. HydroShare expands the data sharing capabilities of the Hydrologic Information System of the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI): It broadens the classes of data accommodated, enables sharing of models and model components, and leverages social media functionality to enhance collaboration around hydrologic data and models. The HydroShare architecture is a stack of storage and computation, web services, and user applications. A content management system, Django+Mezzanine, provides user interface, search, social media functions, and services. A geospatial visualization and analysis component enables searching, visualizing, and analyzing geographic datasets. The integrated Rule-Oriented Data System (iRODS) is used to manage federated data content and perform rule-based background actions on data and model resources, including parsing to generate metadata catalog information and the distributed execution of models and workflows. A web browser is the main interface to HydroShare, however a web services applications programming interface (API) supports access through HydroDesktop and other hydrologic modeling systems, and the architecture separates the interface layer and services layer exposing all functionality through these web services. This presentation will describe key components of HydroShare and discuss how HydroShare is designedto enable better hydrologic science concomitant with sustainable open-source software practices

HydroShare: Sharing Diverse Environmental Data Types and Models as Social Objects with Application to the Hydrology Domain

The types of data and models used within the hydrologic science community are diverse. New repositories have succeeded in making data and models more accessible, but are, in most cases, limited to particular types or classes of data or models and also lack the type of collaborative and iterative functionality needed to enable shared data collection and modeling workflows. File sharing systems currently used within many scientific communities for private sharing of preliminary and intermediate data and modeling products do not support collaborative data capture, description, visualization, and annotation. In this article, we cast hydrologic datasets and models as “social objects” that can be published, collaborated around, annotated, discovered, and accessed. This article describes the generic data model and content packaging scheme for diverse hydrologic datasets and models used by a new hydrologic collaborative environment called HydroShare to enable storage, management, sharing, publication, and annotation of the diverse types of data and models used by hydrologic scientists. The flexibility of HydroShare\u27s data model and packaging scheme is demonstrated using multiple hydrologic data and model use cases that highlight its features

Toward Open and Reproducible Environmental Modeling by Integrating Online Data Repositories, Computational Environments, and Model Application Programming Interfaces

Cyberinfrastructure needs to be advanced to enable open and reproducible environmental modeling research. Recent efforts toward this goal have focused on advancing online repositories for data and model sharing, online computational environments along with containerization technology and notebooks for capturing reproducible computational studies, and Application Programming Interfaces (APIs) for simulation models to foster intuitive programmatic control. The objective of this research is to show how these efforts can be integrated to support reproducible environmental modeling. We present first the high-level concept and general approach for integrating these three components. We then present one possible implementation that integrates HydroShare (an online repository), CUAHSI JupyterHub and CyberGIS-Jupyter for Water (computational environments), and pySUMMA (a model API) to support open and reproducible hydrologic modeling. We apply the example implementation for a hydrologic modeling use case to demonstrate how the approach can advance reproducible environmental modeling through the seamless integration of cyberinfrastructure services

Hydrologic Model Development Using a Loosely Integrated Paradigm

Component software architectures offer an alternative approach for building large, complex hydrologic models. In contrast to more traditional software paradigms (i.e. procedural or object-oriented approaches), component-based approaches allow individuals to construct autonomous modeling units that can be linked together through shared boundary conditions. One of the challenges in component-based modeling is designing a simple yet robust means for authoring model components. This is addressed by presenting an approach for efficiently creating standards-based, process-level hydrologic model components. Using this approach, a process is developed into a model component by (1) authoring a configuration file that defines its properties and (2) creating a class with three methods to define the pre-run, run time, and post-run behavior. The design and implementation of this approach are discussed, then its usage is demonstrated by creating an OpenMI-compliant model component for a basic hydrologic process

Data and model integration for hydrologic applications

As research studies grow in size and in scope, the use of component integration frameworks becomes a more common modeling practice. These software systems provide mechanisms for sharing data among disparate computational modules during simulation runtime, to collectively solve a given problem. This functionality is particularly desirable when modeling cross-disciplinary systems such as climate science and watershed hydrology. Many hydrologic models rely on weather parameters, which may be observed in the field or estimated by other models, to drive simulation. While much of this data is readily available, the method by which it is integrated into coupled hydrologic simulations is not a trivial process, especially when dealing with large data stores. This work investigates modes of integration for large datasets within coupled hydrologic models. The approach is demonstrated by incorporating publicly available observation data as well as preprocessed datasets within a coupled modeling framework. We present this work and demonstrate how the methodology can be leveraged to simulate watershed-scale hydrologic systems