Evaluate hydrologic models for flash flood simulation in Pennsylvania using NGIAB

[sc328]

1. Requester Information:
This should include the name and contact information of the person making the request.

• PI's Full Name: Seann Reed
• PI's Affiliated Institute: NWS MARFC
• PI's Affiliated Email Address: seann.reed@noaa.gov
• Lapenta Intern's Full Name: Hudson Finley Davis
• Lapenta Intern's Affiliated Institute: University of Texas at Austin
• Lapenta Intern's Affiliated Email Address: hfdavis@utexas.edu

2. Project Information:
Provide a brief description of the project and its goals. This can help the infrastructure team understand the context and purpose of the requested resources. Please highlight how this project will be benefit from and/or provide benefit to other resources on the shared infrastructure.

Forecasting extreme flash flooding is an important and difficult challenge in the Middle-Atlantic Region of the United States. Ingredients that contribute to extreme and devastating flash floods include heavy rainfall, wet antecedent conditions, impervious land use, poorly drained soils, and steep topography, as well as susceptible infrastructure. While MARFC hydrologic models account for many of these factors and produce accurate forecasts for river floods, the prediction accuracy decreases and the uncertainty increases for smaller streams. In
an ongoing effort to improve the accuracy, spatial precision, and lead-times in NWS hydrologic models, this project will evaluate flood predictability using state-of-the-art hydrologic modeling tools in small watersheds (<1000 km2). Specifically, the principal investigator will use the NextGen water modeling framework. NextGen offers the ability to model watersheds at different scales and select from multiple process models for evaluation. Models evaluated in the NextGen framework will be readily transferable to National Water Model operations in the future.
We plan to study flooding caused by the remnants of Hurricane Debby in PA (August, 2024). This event caused catastrophic flooding in some locations such as Westfield, PA, on the Cowanesque River, while impacts were much lower in other PA watersheds that received comparable amounts of rain. A modeling deep dive into Debby will help us better understand factors that made some locations more susceptible to damaging flood impacts. We will also need to run long-term simulations for the study basins to validate model accuracy over a range of conditions and put the Debby results in context.

3. Project Description:
If your project involves developing software or scripts, briefly describe the software you plan to develop.

We anticipate using mostly existing NGIAB capabilities. We might need to develop Python scripts to reformat forcing data for use with NGIAB models or summarize results.

4. Resource Requirements:
Specify the compute, storage, and network resources needed for the project. Be as specific as possible about the number of resources required, and any specific configurations or capabilities needed. This information will help the infrastructure team determine the appropriate resources to allocate.

The top level estimate of resource requirement is 1000 core-hours of compute.

Our work plan involves executing models on smaller (< 1000 sq. km) domains, for up to 10-15 year periods. Based on experience communicated to me from OWP, these simulations will require perhaps 32 to 64 core-hours. Including several trials on three basins, our request will use less than an estimated 1000 core-hours of compute.

Options:
I'm not familiar enough with these options to express any preferences at this time. We would need to be able to upload our own forcing data and download our simulation results from whatever cloud service we are using.

1. Cloud Provider: AWS/Azure/GCP

2. Required Services in the Cloud:

   List of AWS Services

• EC2

• S3 – public, private, requester pay, bucket name suggestion?

• EBS (Amazon Elastic Block Store)

• EFS

• RDS

• VPC (Virtual Private Cloud)

• DynamoDB

• ECS

• EKS (Kubernetes Cluster)

• Lambda

• Others: please list

  List of Azure Services

• Virtual Machines

• Azure App Service

• Azure Kubernetes Service (AKS)

• Azure Functions

• Azure Batch

• Azure Blob Storage

• Azure File Storage

• Azure Machine Learning

• Azure Key Vault

• Other: please list

  List of GCP Services

• Google Compute Engine

• Google Kubernetes Engine (GKE)

• Google Cloud Storage

• Google VPC

• Google IAM

• Google BigQuery

• Google Cloud Functions

• Dataflow

• Other: please list

5. Working Group Detail

Working Group 1/2/3/4 (select one):

6. Timeline:
Indicate the expected timeline for the project and when the resources will be needed. This information can help the infrastructure team plan and allocate resources accordingly.

The Lapenta Internship for Finley Davis runs from June 2 - Aug 8th. This is when most of the simulations would be run. The PI, Seann Reed, would like access to the system starting April 28th to gain familiarity (e.g. understand data requirements and make a test run), and be in a position to help Finley get off to a fast start at the beginning of June.

7. Security and Compliance Requirements:
If there are any specific security or compliance requirements for the project, these should be clearly stated in the request. This will help ensure that the necessary security measures are in place for the project.

8. Estimation:
Include any cost estimation or requirements for the project. This will help the infrastructure team select the most cost-effective solutions for the project.

AWS Cost Calculator: https://calculator.aws/#/

Google Cloud # Calculator: https://cloud.google.com/products/calculator

9. Approval:
Indicate the necessary approval processes or sign-offs required for the request.

See e-mail correspondence with Matt Womble and Fred Ogden on Feb 21, 2025.

[arpita0911patel]

Thank you Seann (@sc328) for your request, we will get back to you soon on this.