Design and implementation of a BigQuery dataset and application programmer interface (API) for the U.S. National Water Model

Markert, Kel N.; da Silva, Gui; Ames, Daniel P.; Maghami, Iman; Williams, Gustavious P.; Nelson, E. James; Halgren, James; Patel, Arpita; Santos, Adler; Ames, Michael J.

doi:10.1016/j.envsoft.2024.106123

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Design and implementation of a BigQuery dataset and application programmer interface (API) for the U.S. National Water Model

2024
By Markert, Kel N. ; da Silva, Gui ; Ames, Daniel P. ; ...
Source: Environmental Modelling & Software, 179, 106123

[PDF-2.69 MB]

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Journal Title:

Environmental Modelling & Software
Personal Author:

Markert, Kel N. ; da Silva, Gui ; Ames, Daniel P. ; Maghami, Iman ; Williams, Gustavious P. ; ... More +

Markert, Kel N. ; da Silva, Gui ; Ames, Daniel P. ; Maghami, Iman ; Williams, Gustavious P. ; Nelson, E. James ; Halgren, James ; Patel, Arpita ; Santos, Adler ; Ames, Michael J. Less -
NOAA Program & Office:

NWS (National Weather Service)
Description:

We introduce an open-source web-based Application Programming Interface (API) developed within a representational state transfer (REST) architecture framework that provides access to the operational streamflow forecasts from the U.S. National Water Model (NWM). We built this API within the Google Cloud infrastructure, taking advantage of Google's API Gateway, BigQuery, and the Google Cloud Run architecture. We ran a data transformation from netCDF to tabular formation then ingested data into BigQuery using Apache Beam parallel processing technology. The API activates functions deployed to Cloud Run that executes SQL queries within the BigQuery data warehouse. The API gives users granular control to specify queries based on forecast type, reference datetime, stream segment specifics, and forecast ensemble members. This API greatly simplifies access and use of current and historic NWM forecasts, an otherwise arduous task due to the large volume of data and unwieldy storage methods. Retrieved forecast data can be used for many critical water management applications providing actionable intelligence for, e.g., flood management, safety, recreation, agriculture, and related uses.
Source:

Environmental Modelling & Software, 179, 106123
DOI:

https://doi.org/10.1016/j.envsoft.2024.106123
ISSN:

1364-8152
Format:

pdf
Publisher:

Elsevier BV
Document Type:

Journal Article
Funding:

Grant no. NA22NWS4320003
License:

https://creativecommons.org/licenses/by/4.0/
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CC BY
Compliance:

Submitted
Main Document Checksum:

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urn:sha-512:d88f7c23a7692930a0c10cb5a858cac4e512e9a31e00cde1f2835c37b07ab473e034997b3e605eabc85faad9bd49fbe7467ce0bec4295b120e78e06ae1f101ec
Download URL:

https://repository.library.noaa.gov/view/noaa/66525/noaa_66525_DS1.pdf
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Design and implementation of a BigQuery dataset and application programmer interface (API) for the U.S. National Water Model

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