projects > hydrology monitoring network: data mining and modeling to separate human and natural hydrologic dynamics > project summary
Project Summary SheetFiscal Year 2005 Study Summary Report Project Title: Hydrology Monitoring Network: Data Mining and Modeling to Separate Human and Natural Hydrologic Dynamics Associated / Linked Projects: Freshwater Flows into Northeastern Florida Bay, Estimation of Critical Parameters in Conjunction with Monitoring of the Florida Snail Kite Population, Southern Inland and Coastal Systems (SICS) Model Development Overview & Objective(s): The emerging field of Data Mining addresses the issue of extracting information from large databases. It is comprised of several technologies that include signal processing, advanced statistics, multi-dimensional visualization, machine learning (including artificial neural networks (ANN)), and Chaos Theory. Data Mining can solve complex problems that may be unsolvable by any other means. The data from the CERP monitoring is a tremendous resource for addressing the critical questions for restoring the South Florida ecosystem. Estuarine systems are difficult systems to analyze due to the complexity of environmental factors occurring simultaneously. To enhance the evaluation of the CERP data base, there is an immediate need to apply new methodologies to systematically analyze the data set to answer critical questions such as relative impacts of controlled freshwater releases, tidal dynamics, and meteorological forcing on streamflow, water level, and salinity. This project will directly address the data analysis issues outlined above. The first year of the Data Mining Analysis Project will address these issues by demonstrating how data mining techniques can be applied to the Everglades data bases and ecological studies. Three studies have been selected for the demonstration work - Freshwater Inflows to Northeastern Florida Bay (Mark Zucker, Clinton Hittle), Estimation of Critical Parameters in Conjunction with Monitoring the Florida Snail Kite Population (Wiley Kitchens), and Southern Inland and Coastal Systems (Eric Swain). In addition, time will be spent during the first year identifying other issues of concern where data mining techniques can be applied during Years 2 and 3 of the project. Status: We have built preliminary ANN models of salinity response for Trout Creek using the 1996-2000 USGS data for the five gaging stations of creeks entering Florida Bay. The database used to build the preliminary model has been updated to include the recently available data for the period 2001 to 2004. We have been working with developers of the SICS model on how results from the ANN models can be used to assist in the calibration and confirmation of the SICS model. Short-term water level data (12 months) at sites instrumented for the Snail Kite study in WCA-3 have been hindcasted to create a 14 year water-level record for analysis. We are developing potential methodologies for estimating water levels and water depths at ungaged areas using ANN models. The approach utilizes static variables of location and percent vegetation and dynamic variables of water levels at known locations. On a side effort, we have also worked with the Loxahatchee National Wildlife Refuge staff and identified two problems in the Refuge that could be addressed using data mining techniques. These problems are related to the operations schedule and control of high conductivity water intrusion into the Refuge. Recent & Planned Products: Major products include (1) data bases of the measured and derived hydrologic data that will be used for integration with the Everglades snail kite study and analysis of freshwater inflows; (2) artificial neural network (ANN) models used to hindcast long-term water level response at 17 sites in WCA 3A; (3) ANN models used to analyze freshwater inflows for natural and anthropogenic components; and (4) a summary document describing the assessment of data networks for further integration and analysis using data mining techniques. Specific Relevance to Information Needs Identified in DOI's Science Plan in Support of Ecosystem Restoration, Preservation, and Protection in South Florida (DOI's Everglades Science Plan) [Page numbers listed below are from the DOI Everglades Science Plan. The Science Plan is posted on SOFIA's Web site: http://sofia.usgs.gov/publications/reports/doi-science-plan/]:
Key Findings:
|
U.S. Department of the Interior, U.S. Geological Survey
This page is: http://sofia.usgs.gov/projects/summary_sheets05/hydromonitor.html
Comments and suggestions? Contact: Heather Henkel - Webmaster
Last updated: 24 February, 2006 @ 04:20 PM(KP)