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Hydrological Response to Hurricane Helene: Quantification via the Green-Ampt Method


CIROH_HydroLearn

Problem Statement

This module is focused on understanding Runoff generation during extreme weather events, using Hurricane Helene as a case study. It explores how intense rainfall interacts with different components of the landscape particularly the soil, to influence the movement of water across and beneath the surface. The primary goal is to examine the hydrological processes that control how precipitation is divided into infiltration, surface runoff, and subsurface flow during such high-impact events. The role of soil properties, which significantly shape the watershed’s response to heavy rainfall have been explained. Key factors such as soil texture, type, saturation levels, and infiltration capacity determine how much water is absorbed into the ground versus how much becomes overland flow. For example, well-drained sandy soils tend to absorb more water and delay runoff, while compacted or clayey soils often lead to quicker and more pronounced runoff due to limited infiltration. Through this module, hydrologist and practitioners will learn how to quantify and compare rainfall, infiltration, and runoff volume under different soil conditions. The outcomes of this module is to calculate the runoff, while also providing a scientific basis for sustainable watershed management.

Module Overview

This module aims to explore the hydrological dynamics of Hurricane Helene, with a focus on runoff generation, and watershed response following the storm event. It addresses the question: How does rainfall translate into streamflow during extreme events, and what factors control this response? To answer this, learners will examine key factors such as soil properties,and antecedent moisture conditions, which influence water movement through a watershed. As part of the technical component of the module, learner will implement the Green-Ampt infiltration model, a physically based method used to estimate runoff based on rainfall intensity, soil infiltration capacity, and hydraulic properties. By quantifying these parameters, the module provides a foundation for understanding how different landscapes respond to extreme precipitation, and how this knowledge can be applied to improve flood forecasting, watershed modeling, and the design of flood protection infrastructure Target Audience Operational Hydrologist Tools Needed Computer with access to Internet, Excel, Jupyter Notebook Suggested Implementation Mode The intent of this module is to bring together different concepts and techniques typically covered in hydrology courses using a real-world case study with an actual hydrologic problem on flood protection. The design of the module is such that hydrologist should be able to complete all activities on their own and each activity has its own worksheet for analyzing the progress and knowledge acquired from the module. Expected Completion Time One to two weeks is a reasonable timeframe to complete the entire module. Course Adaptation This course was adapted from HydroLearn411: "Quantifying Runoff Generation" This course is available for adaptation and customization by other instructors. You can request a link to download a copy of the course and import it back into your own new HydroLearn course.

Topics Covered

1. Knowledge about theAsheville, NC, 2. How to determine the Soil types and properties 3. How to determine the precipitation 2. How to determine the Runoff Generation using Green Ampt

Prerequisites

This module is designed for NOAA hydrologists and other professionals working in the field of water resources and environmental science. A background in a relevant scientific discipline such as hydrology, environmental engineering, or earth system science will be helpful and will serve as the prerequisites for successful engagement with the material. While prior experience with Python programming is beneficial, it is not mandatory. All necessary data processing scripts and computational tools will be provided, enabling learners to follow the examples and complete the module’s activities without the need for advanced coding skills. --- Let me know if you’d like a version adapted for a course website or catalog!

Learning Objectives

TAt the end of the module, you should be able to quantify the parameters associated with the watershed:- The learner will be able to calculate the total rainfall, infiltration, and runoff The learner will be able to differentiate between soil types for the watershed and measure its effect on runoff generation 3. The learner will be able to identify the effect of soil saturation condition and infiltration capacity on runoff generation

"This will be accomplished through activities within each section. Results from each activity will be recorded in specified results templates. The results templates for each activity can be found at the beginning of each activity. The results templates are organized such that results from one activity can easily be used in successive activities."

Suggested Implementation

Self-paced

Course Authors

Instructor_Image #1

Rimsha Hasan

Rimsha Hasan is a doctoral candidate at the University of Nebraska-Lincoln, USA, specializing in hydrology and groundwater modeling with a focus within the field of Natural Resources and Conservation. She has a background in Civil Engineering and has been working in field of environmental engineering and technology. Her expertise lies in using the geospatial tools and technologies, including ArcGIS, QGIS, and Google Earth Engine (GEE), which she extensively utilized in her research. Recently, she applied Google Earth Engine to analyze water quality and quantity in water resources, leading to a published study on the topic.

Email: rhasan4@unl.edu

Instructor_2 Image

Soelem Aafnan

Soelem Aafnan Bhuiyan is a doctoral candidate at the Department of Civil, Environmental and Infrastructure Engineering at George Mason University. His research focuses on satellite data assimilation in storm surge modeling. Soelem received his Bachelor's in Water Resources Engineering from Bangladesh University of Engineering and Technology before joining George Mason University as a graduate student. In addition to his research, Soelem was part of the NOAA NWS Summer Institute 2023 and NASA SMAPVEX 2022 field campaign. When not in front of the computer screen, Soelem can be found hiking or taking photos of distant stars.

Email:sbhuiya2@gmu.edu

     

Data Disclaimer

       

This experimental data represents the NWS’s best approximation of the maximum inundation extent that occurred on Sep. 26 (or Sep. 27), 2024, as of Jan 6, 2025, based upon modeled river discharge. These maps were not publicly available during the event (coinciding with Hurricane Helene). This information should be used for educational purposes only.        

   
     

Acknowledgement

       

This project received funding under award NA22NWS4320003 by National Oceanic and Atmospheric Administration (NOAA) Cooperative Institute Program to the Cooperative Institute for Research on Hydrology (CIROH) through the University of Alabama. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the opinions of NOAA.        

   
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  2. Course Number

    OP_030
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  4. Estimated Effort

    06:00
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