September 30 – Having returned to the College of Agriculture and Human Sciences recently after spending a year as the Interim Vice President for Research, Innovation and Sponsored Programs for the university, Dr. Ali Fares’ latest research endeavor has been featured in the Journal of the American Water Resources Association. The article “Effects of Spatial and Temporal Data Aggregation on the Performance of the Multi-Radar Multi-Sensor System (MRMS)” is a culmination of research Fares produced alongside four other Texas area researchers where this system was used to predict precipitation across Texas’ lower Colorado River Basin. Results of this research show the MRMS’s ability to capture precipitation reasonably well over the study area, but it experiences some challenges when it came to larger precipitation events, all that are explained in depth throughout the article. Dr. Fares and his team at the Cooperative Agricultural Research Center, colleagues Drs. Ripendra Awal and Hamidah Habibi, are currently continuing this research by evaluating the performance of MRMS over Harris County during extreme events and also explore potential flood resiliency strategies across the Greater Houston Area.

ABSTRACT: The objectives of this study were to (1) evaluate the performance of the Multi-Radar Multi-Sensor(MRMS) system in capturing precipitation compared to gauge data, and (2) assess the effects of spatial (1–50 km) and temporal (15–120 min) data aggregation scales on the performance of the MRMS system. Point-to-grid comparisons were conducted between 215 rain gauges and the MRMS system. The MRMS system at 1 km spatial and 15 min temporal resolutions captured precipitation reasonably well with average R2, root mean square error (RMSE), and percent bias (PBIAS) values of 0.65, 0.5 mm, and 11.9 mm; whereas Threat Score, probability of detection, and false alarm ratio were 0.57, 0.92, and 0.40, respectively. Decreasing temporal resolution from 15 min to two hours resulted in an increase in R2 and a decrease in RMSE, whereas PBIAS was not affected. Reducing spatial resolution from 1 to 50 km resulted in increases inR2 and PBIAS, whereas RMSE was decreased. Increasing spatial aggregation scale from 1 to 50 km resulted in an R2 increase of only 0.08. Similarly, improvement inR2was only modest (0.17) compared to an eightfold reduction in temporal resolution(from 15 min to two hours). While aggregating data at coarser temporal resolutions resolved some of the under/overestimation issues of the MRMS system, it was apparent even at coarser spatial and temporal resolutions the MRMS system inherently overestimated smaller precipitation events while underestimated bigger events

To read the entire article on Dr. Fares and his colleagues research here.

This work was supported by the USDA National Institute of Food and Agriculture, 1890 Evans Allen Program projects under Section 1445.

Written by: Taelor Smith

Dr. Ali Fares

 

 

Ali Fares, Ph.D.
Professor of Water Security
alfares@pvamu.edu
(936) 261-5095