University of Illinois at Urbana-Champaign
Enabling real-time water decision support services using model as a service
Abstract
dc:descriptionThrough application of computational methods and an integrated information system, real-time data and river modeling systems can help decision makers identify more effective actions for management practice. The purpose of this study is to develop real-time water decision support services for decision makers during droughts and floods. To enable ease of use and re-use, the workflows (i.e., analysis and model steps) of the real-time decision support model are published as Web services delivered through an internet browser, including model inputs, a published workflow service, and visualized outputs. The RAPID model, which is a river routing model developed at University of Texas Austin for parallel computation of river discharge, is applied to predict real-time river flow rates. A workflow to predict river flow using the RAPID model has been built and published as a Web application that allows non-technical users to remotely execute the model and visualize results as a service through a simple Web interface. The model service is prototyped in the San Antonio and Guadalupe River Basin in Texas. In the future, optimization model workflows will be developed to link with the RAPID model workflow to provide real-time water allocation decision support services.
Degree
thesis:*- Name thesis:degree_name
- M.S.
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Environ Engr in Civil Engr
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2014
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Zhao, Tingting
- Contributors dc:contributor
-
- Minsker, Barbara S.
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- Copyright 2014 Tingting Zhao
- Language dc:language
- en
Identifiers
dc:identifier.*- Handle dc:identifier
- http://hdl.handle.net/2142/49382
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/49382