Simple Method for Using Precomputed Hydrologic Models in Flood Forecasting with Uniform Rainfall and Soil Moisture Pattern

J American Water Resour Assoc

Dolder

et al. 2016

Self Cite

Global and continental scale flood forecast provide coarse resolution flood forecast, but from the perspective of emergency management, flood warnings should be detailed and specific to local conditions. The desired refinement can be provided by the use of downscaling global scale models and through the use of distributed hydrologic models to produce a high-resolution flood forecast. Three major challenges associated with transforming global flood forecasting to a local scale are addressed in this work. The first is using open-source software tools to provide access to multiple data sources and lowering the barriers for users in management agencies at local level. This can be done through the Tethys Platform that enables web water resources modeling applications. The second is finding a practical solution for the computational requirements associated with running complex models and performing multiple simulations. This is done using Tethys Cluster that manages distributed and cloud computing resources as a companion to the Tethys Platform for web app development. The third challenge is discovering ways to downscale the forecasts from the global extent to the local context. Three modeling strategies have been tested to address this, including downscaling of coarse resolution global runoff models to high-resolution stream networks and routing with Routing Application for Parallel computatIon of Discharge (RAPID), the use of hierarchical Gridded Surface and Subsurface Hydrologic Analysis (GSSHA) distributed models, and pre-computed distributed GSSHA models.(KEY TERMS: flood forecast; flood warning; web apps; emergency response; Tethys Platform.)

Section: Resultsmentioning

confidence: 99%

From Global to Local: Providing Actionable Flood Forecast Information in a Cloud‐Based Computing Environment

Pérez

J American Water Resour Assoc

Dolder

et al. 2016

Self Cite

“…The Canned GSSHA web app was developed to demonstrate the Canned Modeling method of flood forecasting (Dolder, Jones, & Nelson, 2015). The premise of the Canned Modeling method is that when a flood event is imminent, there is limited time to execute hydrologic model runs in an attempt to predict the outcome of the flood event.…”

Section: Canned Gsshamentioning

confidence: 99%

A new open source platform for lowering the barrier for environmental web app development

Environmental Modelling & Software

Christensen

Snow

et al. 2016

Self Cite

The interactive nature of web applications or "web apps" makes them a well-suited medium for conveying complex scientific concepts to lay audiences and creating decision support tools that harness cutting edge modeling techniques and promote the work of environmental scientists and engineers. Despite this potential, the technical expertise required to develop web apps represents a formidable barrier-even for scientists and engineers who are skilled programmers. This paper describes four hurdles that contribute to this barrier and introduces an approach to overcoming these hurdles. We present an open source implementation of this approach, a development and hosting environment for environmental web apps called Tethys Platform. Several case studies are provided that demonstrates how the approach, as implemented within Tethys Platform, successfully lowers the barrier to web app development in the environmental domain.

“…The second use case leverages the HTC toolkit to perform automated hydrologic ensemble forecasting. While the modeling and application of these examples are described in detail in other papers (Dolder et al, 2015;Perez et al, 2016;Snow et al, 2016), the presentation here focuses on the computing required to support the modeling.…”

Section: Use Casesmentioning

confidence: 99%

“…This requires that many (often tens of thousands) model scenarios (or parameterizations) be computed to adequately cover the parameter space. This method is discussed in greater detail in Dolder et al (2015).…”

Section: Canned Gsshamentioning

confidence: 99%

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

Christensen

J American Water Resour Assoc

Jones

et al. 2016

Self Cite

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.