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

Hydrological Response to Hurricane Helene: Quantification via the Green-Ampt Method HydroLearn View Course Problem Statement The module is designed for the runoff generation during extreme events by analyzing the interaction between rainfall, infiltration, and runoff. It emphasizes the pivotal role of soil characteristics—such as type, saturation conditions, and infiltration capacity—in influencing hydrological responses. By quantifying total rainfall, infiltration, and runoff, and evaluating the effects of varying soil properties, this module provides valuable insights into watershed behavior. These findings aim to enhance runoff predictions, improve flood forecasting accuracy, and inform effective watershed management strategies.". Module Overview The Module will contain learner's knowledge enhancement self-pace engaging activies Topics Covered Description about Asheville, NC, Runoff Generation, Rainfall, Infiltration, Green-Ampt Method Prerequisites The user is required to have the basic understanding related to the hydrological processes. Learning Objectives The learner will be able to quantify total rainfall, infiltration, and runoff and differentiate between soil types for the watershed "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 If applicable, take this opportunity to address your suggested implementation mode to an instructor that is interested in adopting your module. Have you any adivce to offer? Particular methods that have worked for you? Or perhaps you designed your module to be used in a certain way? Course Authors 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 & Conservation. She has a background in Civil Engineering and has been working in field of environmental engineering and technology. Her expertise lies inusing 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 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 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.