The Everglades Depth Estimation Network (EDEN) Surface-Water Interpolation Model, Version 3

Scientific Investigations Report 2020-5083
USGS Greater Everglades Priority Ecosystems Science Program
Prepared in cooperation with the U.S. Army Corps of Engineers
By: , and 

Links

Abstract

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that estimate daily water-level data at ungaged locations, and applications that generate derived hydrologic data across the freshwater part of the Greater Everglades landscape. Version 3 (V3) of the EDEN interpolation surface-water model is the most recent update, replacing the version 2 (V2) model released in 2011.

The primary revision for the V3 model is the switch to the R programming language to create a more efficient and portable EDEN code relative to V2, without reliance on proprietary software. Using R, the interpolation script runs over 10 times faster and is more easily updated, for example, to accommodate changes in the gage network or to incorporate R software updates. Additional revisions made for the V3 model include updates to the interpolation model, the gage network, and groundwater-level estimations. The EDEN model domain in the Greater Everglades and Big Cypress National Preserve is divided into subdomains that are based on hydrologic boundaries. In the V3 model, the number of subdomains was increased from five to eight, which allows hydrologic boundaries, such as levees and canals, to be better represented in the interpolation scheme. Five pseudogages were added to constrain the water-level surface at subdomain boundaries. Changes made to the water-level gage network between the implementation of the V2 and V3 models are incorporated, and groundwater-level estimations are added, which are important information for hydrologic and ecological studies.

Summary model performance statistics indicate similar accuracy in water-level surfaces generated by the V3 and V2 models, with a root mean square error of 4.78 centimeters for both interpolation models against independent water-level measurements. Providing stability and continuity for the EDEN user community, the V3 model closely replicates the V2 model, with a root mean square difference of 3.87 centimeters for interpolated surfaces from April 1, 2014, to March 31, 2018. The additional groundwater levels provide a realistic estimate of the saturated groundwater surface continuous with the surface-water surface for Water Conservation Areas 2A and 2B from 2000 to 2011. This continuous surface is a more accurate estimation of the spatial distribution of water in the hydrologic system than before, providing needed information for ecological studies in areas where depth to water table affects habitats. Development of the EDEN V3 model advances the tools available to scientists and resource managers for guiding large-scale field operations, describing hydrologic changes, and supporting biological and ecological assessments.

Suggested Citation

Haider, S., Swain, E., Beerens, J., Petkewich, M., McCloskey, B., and Henkel, H., 2020, The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3: U.S. Geological Survey Scientific Investigations Report 2020–5083, 31 p., https://doi.org/10.3133/sir20205083.

ISSN: 2328-0328 (online)

Study Area

Table of Contents

  • Acknowledgments
  • Abstract
  • Introduction
  • Approach
  • Results
  • Summary and Conclusions
  • References Cited
  • Appendix 1
Publication type Report
Publication Subtype USGS Numbered Series
Title The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3
Series title Scientific Investigations Report
Series number 2020-5083
DOI 10.3133/sir20205083
Year Published 2020
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Caribbean-Florida Water Science Center
Description vii, 31 p.
Country United States
State Florida
Other Geospatial Greater Everglades landscape
Online Only (Y/N) Y
Google Analytic Metrics Metrics page
Additional publication details