Date of Degree
MS (Master of Science)
Civil and Environmental Engineering
Krajewski, Witold F.
First Committee Member
Second Committee Member
Soil moisture estimates from space on a continuous spatial domain could afford researchers with insight about agricultural productivity, flood vulnerability, and biological processes. To evaluate satellite soil moisture estimates, the SMAPVEX-16 experiment was one of a suite of verification data collection campaigns for NASA’s Soil Moisture Active Passive satellite. Soil moisture and its role in rainfall partitioning are of great interest to researchers at the Iowa Flood Center [IFC], which was founded in Iowa City, Iowa after a devastating flood event in 2008. A network of two dual-pol capable X-band radar units owned by the IFC, as well as five tipping bucket rain gauges, complemented by 15 from the USDA’s Agricultural Research Service were deployed in Central Iowa from May to August 2016 to monitor precipitation on a fine spatiotemporal domain. The data from this particular experiment was analyzed.
Several radar-rainfall algorithms were assembled with a focus on assimilating multivariate radar data. Different variables allow researchers to overcome problems due to signal attenuation by X-band radars, and process radar observations into rainfall accumulations by several methods popular in the literature. Special techniques for accumulating instantaneous rainfall rates at discrete observation intervals were employed to account for the movement of storms. The rain totals between the observation points were estimated and the accumulations were compared to the rain gauge totals.
Methods of rain rate calculation that assimilate many sources of data, such as radar reflectivity, differential reflectivity, and specific differential phase shift yielded the best results.
Algorithms, Radar, Rainfall, Remote Sensing, X-band
xi, 90 pages
Includes bibliographical references (pages 57-58).
Copyright © 2019 John R. Brammeier
Brammeier, John R.. "On the performance of X-band dual-polarization radar-rainfall estimation algorithms during the SMAPVEX-16 field campaign." MS (Master of Science) thesis, University of Iowa, 2019.