ABSTRACT:

NHDPlusV2 Data Cache in .rds

ABSTRACT:

Utilizing multiple sources of information for continuous topobathymetry.
WHAT

Problem Statement: How can we use multiple sources of observed elevation and bathymetry to create a continuous best estimate of channel geometry and coastal bathymetry?

WHY
Goal: When building modeling frameworks that span uplands, flood-plains, major rivers, and coastal areas, multiple sources of topography and bathymetry must be utilized together. They may have different accuracy, datum, or abstraction (points/lines vs grids).

HOW
Approach: Review existing practices from oceanographic, hydrologic, hydrographic, hydrometric, and hydrodynamic domains for measurement and modeling topo-bathymetric data. Propose model-data fusion methods to incorporate multiple sources of information to estimate representative channel shape, elevation, and slope.
Student Learning Goals: Students learn best practices for geospatial data collection and integration using reproducible workflows and team-based software development techniques.
Links to other projects: The problems addressed here is critical to a smooth transition from inland to coastal topo-bathymetry for routing and flood inundation. There is a potential, if pursued, to use the outcomes of this project as a demonstration of methods developed in other coastal theme projects.
Training opportunities: This project will be part of the coastal theme: students who participate in this theme will have 3 days of intensive training at the SI learning the specific needs of coupled inland-coastal modeling. Additional training and support will be available from the informatics and computational methods theme leads.
Supplementary Materials:
Explore research on continental channel geometry data needs: https://doi.org/10.1002/2016WR019285 and others.
Explore research on data fusion for bathymetric data: https://doi.org/10.1117/12.604259 and others.

DATA - What (or what types of) input data will be required?
Model Data: Existing Delaware River Basin model spatial framework.
Observed Data: Data collected by NWS Coastal Team for Delaware River model. Cross section data from USGS and other sources. Other data sources TBD.

ABSTRACT:

Reproducible model development and evaluation environment.
WHAT

Problem Statement:What is a suitable model development and evaluation for both existing NWM-subset(s) and new/novel model formulation investigation(s)?

WHY
Goal: Work with NWM-subset(s) and model formulation investigation(s) to design and demonstrate a base-line development and testing environment for reproducible model development and evaluation.

HOW
Approach: Review literature and community practices for reproducible model development and evaluation. Start with existing NWM containerization scheme. Determine appropriate abstraction to encapsulate a variety of hydrologic models and formulations. Implement example in cooperation with other themes.
Student Learning Goals: Students learn and demonstrate modern best practices for reproducible model formulation and software development.
Links to other projects: If completed successfully, outcomes of projects working with both subsets of them NWM and newly developed formulations should work with the approach implemented here. A final demonstration could compare new formulations to existing NWM using this same environment and evaluation architecture.
Training opportunities: This project will be part of the Scaling theme: students who participate in this theme will have 3 days of intensive training at the SI, including creating NWM subsets for CZO watersheds, running the NWM using jupyter notebooks/docker containers, using hydrologic data to evaluate hydrologic processes, using and analyzing CZO data.
Supplementary Materials:
Explore research toward community model development. https://doi.org/10.1002/2015WR017910 https://doi.org/10.1002/2016WR019285
Install and work through basic tutorials with Docker. https://docs.docker.com/get-started/ https://docker-curriculum.com/

DATA - What (or what types of) input data will be required?
Model Data: CUAHSI tool for NWM cutouts and forcings.
Observed Data: Readily available NWIS data.

ABSTRACT:

This resource contains a geopackage and a Jupyter notebook to be used in a demonstration based training using R to access NWM and NWIS streamflow data.

To work with this notebook,
1) click "Open With" > "Jupyter Hub" in the upper right.
2) Open the "Welcome" notebook and run steps 1 and 2 to download the contents of the resource.
3) In the "Welcome" notebook, you should see a link to the nwm_data_example.ipynb notebook. Click it.
5) Start reading and clicking "Run" at the top of the page to run the notebook chunks.

Note that the first block will take some time to run -- while it's running would be a good time to scan the rest of the notebook so you are ready to run the rest when the downloads are finished.

ABSTRACT:

Application of an international standard for hydrologic features toward more open hydrologic science data.

The idea of open science includes transparency and openness of scientific data, methods, and discourse. As hydrologic science becomes increasingly data intensive, computational, and increasingly at large landscape scales, the challenges for openness of scientific data increase in several ways. This talk will describe recent advances toward standard information models that aim to provide shared concepts and terminology for hydrologic information.

Hydrologic data are typically collected to describe some aspect of a waterbody or catchment. Hydrographic data, a type of hydrologic data, are the spatial description of these waterbody and catchment features. The new community standard, WaterML2 Part 3: Surface Hydrology Features (HY_Features), seeks to provide a conceptual model and common terminology for the hydrologic features that are the focus of hydrologic science.

The HY_Features standard can play a role in all aspects of open hydrologic science:
1) It can be used as a documentation language for data.
2) it can be used to describe the kinds of and relationships between hydrologic features associated with a scientific method or software.
3) it can provide a lingua franca for description of features that are the subject of hydrologic science.

HY_Features, published in early 2018, includes an informative description of the conceptual model, a set of normative statements (rules) that describe how to conform to the standard, and a data model described using Unified Modeling Language classes and diagrams. The standard does not include a specific data encoding. It is expected that encodings will be established as needed by organizations and/or the hydrologic science community.

Among the many potential applications of the HY_Features conceptual model, linking disparate information about and among hydrologic features on the internet has great potential for enhancing open science. This talk will present the findings of an international collaboration toward this goal called the Environmental Linked Features Interoperability Experiment (ELFIE). HY_Features concepts will be presented using applications implemented for the ELFIE as case studies to illustrate how HY_Features and the technology implemented in the ELFIE will enhance open and transparent hydrologic science.