GSA Annual Meeting in Seattle, Washington, USA - 2017

Paper No. 37-11
Presentation Time: 4:30 PM


WONG, Stephanie S.1, YELDERMAN Jr., Joe C.1 and BYARS, Bruce2, (1)Geosciences, Baylor University, One Bear Place #97354, Waco, TX 76798, (2)Center for Spatial Research, Baylor University, One Bear Place 97351, Waco, TX 76798,

Precipitation data are important in hydrogeologic studies, particularly for improving understanding of groundwater systems, protecting important recharge areas, and managing resources. While it is generally known that precipitation varies in amount and intensity both temporally and spatially, karst recharge studies have traditionally focused on significant recharge features and used average rainfall for a given time period. Alternatively, prepositioned rain gauges have been used to determine spatial variability. Neither method adequately accounts for spatially variable precipitation and diffuse recharge. Rainfall products produced from the National Weather Service’s Next Generation Weather Radar (NEXRAD) program is an alternative to precipitation estimates based solely on a sparse rain gauge network. Weather Surveillance Radar-1988 Doppler (WSR-88D) data are processed using Precipitation Processing System (PPS) algorithms to estimate rainfall in a 4 km grid at hourly intervals, which can then be aggregated to produce daily, monthly, or yearly totals.

Being able to capture and examine the temporal and spatial variability of precipitation events is especially relevant for understanding recharge to karst aquifers. In this study, WSR-88D data were gathered and processed for the outcrop portion of the Northern Segment of the Edwards Balcones Fault Zone (BFZ) aquifer in Central Texas to better understand response to recharge. Since groundwater and surface water interact in this unconfined portion of the aquifer, rain gauge data and WSR-88D data were compared and correlated to USGS stream gauge data as well as groundwater levels to gain greater insight to the timing and magnitude of responses to recharge events. Preliminary results indicate that: 1) WSR-88D data, which undergo National Weather Service bias-correction and quality control processes, are a rich source of precipitation data that can be efficiently collected and aggregated; and 2) the regular spatial- and high temporal-resolution of WSR-88D data facilitates greater correlation of recharge events with continuous monitoring surface water and groundwater data. By pairing WSR-88D data with traditional hydrologic data, a more detailed understanding of groundwater systems and recharge dynamics can be achieved.

  • GSA2017_Wong_FINAL.pdf (3.6 MB)