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Advancing the Accessibility, Reusability, and Interoperability of Environmental Modeling Workflows Through Web Services

Global flood forecasting can benefit developing countries and ungauged regions that lack observational data, computational infrastructure, and human capacity for streamflow modeling. Many technical challenges exist to provide flood predictions on a global scale. First, existing land surface forecasts use coarse resolution grid cells, which provide limited information when used for flood forecasting at local scales. There is, so far, no modeling system that can provide rapid and accurate global flood predictions with low cost. Second, accurate flood predictions often require integrating interdisciplinary models, data sources, and analysis routines into a workflow. Limited accessibility, reusability, and interoperability of models restrict integrated modeling from producing more reliable results. Web services have been demonstrated as an effective way for data and model sharing because of the capability of enabling communication among heterogeneous applications over the internet. However, publishing models or analysis routines as web services is still challenging and, hence, is not commonly done. To address the above challenges, I present a computational system for global streamflow prediction, using existing, well-established open source software tools, that quickly downscales the runoff generated from such coarse grid-based land surface models (LSMs) onto high-resolution vector-based stream networks then routes the results using a vector-based river routing model. A set of experiments are conducted to demonstrate the feasibility and credibility of this approach. I also present a tool to publish complex environmental models as web services by adopting the OpenGMS Wrapper System (OGMS-WS) and Docker. The streamflow prediction system is deployed as a web service using this tool, and the service is used to analyze the historical streamflow tendency in Bangladesh. Next, I present a ready-to-use tool called Tethys WPS Server, which provides a simplified and formalized way to expose web app functionality as standardized Open Geospatial Consortium (OGC) Web Processing Services (WPS) alongside a web app's graphical user interface. Three Tethys web apps are developed to demonstrate how web app functionality(s) can be exposed as WPS using Tethys WPS Server, and to show how these WPS can be coupled to build a complex modeling web app. In sum, this dissertation explores new computational approaches and software tools to advance global streamflow prediction and integrated environmental modeling.

Identiferoai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-9898
Date27 March 2020
CreatorsQiao, Xiaohui
PublisherBYU ScholarsArchive
Source SetsBrigham Young University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations
Rightshttps://lib.byu.edu/about/copyright/

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