Dissertations and Theses
Date of Award
2023
Document Type
Thesis
Department
Earth and Atmospheric Sciences
First Advisor
Steven Kidder
Second Advisor
Reza Khanbilvardi
Third Advisor
Robert Walter
Keywords
Groundwater Exploration, Hydrograph Identification, Springshed Modeling, Watershed Protection, Remote Sensing
Abstract
The analysis and protection of watersheds, along with spring water resources, depend on the accurate identification of catchments. Building on previous research that correlated spring hydrographs with high-resolution, satellite-based Global Precipitation Measurement – Integrated Multi-satellitE Retrievals for GPM (GPM-IMERG) data, I improve the speed and accuracy of catchment identification and hydrodynamic characterization via an enhanced Empirically Constrained Hydrologic Operation (ECHO) algorithm. This research (1) establishes optimal parameter inputs for the algorithm to enable reliable identification of source point-locations, (2) removes human in-the-loop processing, and thus reduce potential operator bias, and (3) explores the potential for using a limited dataset of precipitation proxies for delineation and geolocation. The algorithm is validated within a semi-controlled environment using IMERG and United States Geologic Survey (USGS) precipitation gauge data that has a known location. It is benchmarked against statistical approaches: Cross-Correlation, Pearson Correlation, Spearman Correlation, Total Accumulation, and Binary Frequency. The results demonstrate success of the ECHO algorithm in controlled geolocation when the gauge location is withheld while establishing higher accuracy over the alternative statistical approaches. This enhanced ECHO method holds implications for water resource protection, groundwater exploration, and introduces novel applications for rapidly delineating traditional watersheds, springsheds, and transboundary aquifers. This is particularly useful in scenarios where standard, time-consuming dye tracing tests might be impractical, difficult, or impossible to mount.
Recommended Citation
Longenecker, Jake M., "Advancing the Accuracy of Watershed Analysis Across Diverse Hydrometeorological and Geologic Regimes via Classification and Analysis of GPM-IMERG Products" (2023). CUNY Academic Works.
https://academicworks.cuny.edu/cc_etds_theses/1118
Comments
This research aims to better identify and protect the areas where water flows underground. The study builds on earlier work that used a novel computer algorithm called “ECHO”, using satellite data to understand groundwater movement utilizing rainfall patters. The goals are to fine-tune the method for finding where groundwater comes from and how it moves, and to see if limited rainfall data or other sources of information can be used for this purpose of identification. This research refined and tested the ECHO algorithm using known rainfall data from US government gauges and a satellite network, and by comparing ECHO to standard statistical correlation tests. The results show that our novel ECHO algorithm works substantially better standard statistical tests and can identify the location of a rain gauge even when the exact location is unknown to the operator, but which is known a priori, which is called a “blind” test. The knowledge gained from blind tests can then be used for more complex scenarios. This improved ECHO method can be used to protect water resources, explore how underground water moves, and quickly identify important groundwater flow paths, including those that cross borders, ultimately improving our understanding of groundwater systems that are becoming increasingly critical for survival.