A document by Hannah K Friedrich. Click on the document to view its contents.

Satellite imagery to rapidly develop maps of historical flood hazard and current inundated areas over large spatial coverage is indispensable in supporting situational awareness for improved debris estimation, transportation impacts and damage assessments. However, how best to utilize these maps as actionable information during flood disasters and for flood disaster response assistance is less clear. Furthermore, the integration of any satellite data from an “untrusted” (non-mandated) source into the operations chain and response protocols of a mandated agencies such as FEMA, PDC (PDC is already pulling some DFO-DSS layers) or the UN WFP would be a non-trivial procedure. These agencies desire to prioritize support and resource requirements for community lifelines. (Safety & Security; Food, Water & Shelter; Health & Medical; Energy (Power & Fuel); Communications; Transportation; and Hazardous Materials). The majority of these lifelines can be impacted by floods. The Global Flood Observatory’s (DFO, University of Colorado Boulder) web map server and its associated mobile app (DFO-Floods) is a resource for global extents of floods now delivered as map products via web services. This flood decision support system (DSS) serves flood maps along with other trusted geospatial data to the global disaster response community. However, acceptance of the DFO product line as a trusted information source requires additional tests to assess its performance in combination with the respective response process of agencies around the world. This would allow moving the product from a high Application Readiness Level into an Operational Readiness Level (ORL) for agency trusted data implementation. This paper reviews success examples of the DFO flood layers, illustrates the newly released mobile app and discusses the need for trusted flood map products and services to support the global disaster response community.

The Community Surface Dynamics Modeling System (CSDMS), an international organization of over 1700 members, has a mission to enable model use and development for research in earth surface processes. CSDMS strives to expand the use of quantitative modeling techniques, promotes best practices in coding, and advocates for the use of open-source software. As a service for its members, the CSDMS Integration Facility (IF) maintains a code repository for numerical models. The CSDMS Model Repository, initialized in 2009, currently holds over 300 open source models and tools. To submit code to the Repository, a community member completes an online form, providing metadata for their code and selecting an open source license. In return for the code contribution, CSDMS provides a home for the model on its publicly accessible site. The model page is initially populated with the metadata provided by the author, but it can be edited and expanded to include documentation, examples, references, and graphics. If the code is available on a public repository, such as GitHub, a link to it is provided from the Repository; otherwise, the code is added to the Repository’s GitHub repository. The version of the code submitted to the Repository is assigned a DOI, making it citable. A QR code, suitable for display on a conference poster, is also created. Finally, the CSDMS IF has devised a model h-index, which gives a measure of a model’s visibility through journal citations. By submitting code to the CSDMS Model Repository, a model developer gets visibility, findability, accessibility, storage, and preservation for their model code. CSDMS gets a library of open source models that can be used for research. This can help accelerate science, since it’s often easier to use or modify an existing model than it is to start from scratch. The Repository also helps prevent model codes from going “dark” and being forgotten. Above all, the Repository serves the ethos of community modeling promoted by CSDMS.