State Water Resources Research Institute Program


Project ID: 2007FL202B
Title: Comparing NEXRAD Rainfall and Rain Gauge Data in South Florida Water Management District
Project Type: Research
Start Date: 3/01/2007
End Date: 2/29/2008
Congressional District: 19
Focus Categories: Hydrology, Methods, Models
Keywords: NEXRAD, Rain gauge data, South Florida Water Management District, artificial neural networks
Principal Investigator: Teegavarapu, Ramesh
Federal Funds: $ 5,000
Non-Federal Matching Funds: $ 12,500
Abstract: The use of NEXRAD rainfall data for providing information about the extreme rainfall amounts resulting from storms, hurricanes and tropical depressions is common today. Often corrections are applied to this rainfall data-based on what was actually measured on the ground by rain gages (generally referred to as "ground truth"). Understanding and modeling the relationships between NEXRAD and rain gage data are essential tasks to confirm the accuracy and reliability of the former surrogate method of rainfall measurement. Traditional non-linear regression models in many situations are found to be incapable of capturing these highly variant non-linear spatial and temporal relationships. This study proposes to investigate the use of emerging computational data modeling techniques and assess these functional approximation methods for this purpose. The project aims to understand and model the relationships between NEXRAD based rainfall data and the data measured by conventional rain gauges. Main goals of the project are: 1) Analyze raw and transformed NEXRAD rainfall data and rain gage data and understand associations; 2) Compare the NEXRAD and rain gauge data at different spatial and temporal scales and 3) Develop and test inductive (data-driven) models using artificial neural network concepts to understand and model the relationship between RADAR and rain gage data. The study areas selected from Upper and Lower Kissimmee basins of south Florida form the test-bed for the proposed approaches and ensure the testing of the validity and operational applicability of these approaches. The proposed research is highly relevant and critical to a number of water resources management agencies (e.g., South Florida Water Management District) that currently use NEXRAD based rainfall data for modeling and management of day-to-day operations of water resources systems. The products derived from the proposed study are expected to be tested for real-time use of NEXRAD-based rainfall data at South Florida Water Management District.

Progress/Completion Report, 2007, PDF
Progress/Completion Report, 2008, PDF
Progress/Completion Report, 2009, PDF
Progress/Completion Report, 2010, PDF

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