Hydrology Monitoring Network: Data Mining and Modeling to Separate Human and Natural Hydrologic Dynamics

Project Investigator: Paul Conrads Project Personnel: Mark Lowery, Ed Roehl, Ruby Daamen, Matt Petkewich Project Start Date: 2005 End Date: 2008 Recent Funding: (FY08) USGS GE PES, (FY07) USGS GE PES, (FY06) USGS GE PES, (FY05) USGS GE PES Work Plans Project Summaries Metadata Related Links

Summary

The goal of this project is to enhance the evaluation of the CERP database and address hydrologic issues important to DOI's efforts in South Florida.

New technologies in environmental monitoring have made it cost effective to acquire tremendous amounts of hydrologic and water-quality data. Although these data are a valuable resource for understanding environmental systems, often there is seldom a thorough analysis of the data. The monitoring network(s) supported by the Comprehensive Everglades Restoration Plan (CERP) records tremendous amounts of data each day and the data base incorporates millions of data points describing the environmental response of the system to changing conditions. 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. There also is a need to integrate longer-term hydrologic data with shorter-term hydrologic data collected for biological resource studies. This study will be undertaken as a series of pilot studies to demonstrate the efficacy of data mining techniques to evaluate CERP data and address hydrologic issues important to DOI's efforts in South Florida. In addition, preliminary assessment of the complete set of hydrologic data networks for further integration and analysis using data mining techniques will be conducted.

The objectives of the study include: (1) integration of hydrologic analysis and synthesis with biological studies; (2) separation of water level, stream flow, and salinity time series into the natural (tidal, climate) and anthropogenic components; and, (3) identification of additional areas where application of data mining techniques can address the DOI science needs in South Florida.

Work Plans

• 2005
• 2006
• 2007
• 2008

Project Summaries

• 2005
• 2006

Metadata

• Hydrologic Monitoring Network: Data Mining and Modeling to Separate Human and Natural Hydrologic Dynamics (project metadata)

Related Links

• Freshwater Flows to Northeastern Florida Bay
• Across Trophic Level System Simulation (ATLSS) - Snail Kite
• South Florida Surface Water Monitoring Network for the Support of MAP Projects (known as EDEN, Everglades Depth Estimation Network)