Paper No. 162-9
Presentation Time: 10:35 AM
PROJECTING RECHARGE AND SPRINGFLOW IN A KARSTIC AQUIFER SYSTEM UNDER A CHANGING CLIMATE: WILL CURRENT MANAGEMENT APPROACHES BE ADEQUATE?
BERTETTI, F. Paul1, BASAGAOGLU, Hakan1, YANG, Changbing1, SCHMIDT, Logan1, WOOTTEN, Adrienne M.2, SHARMA, Chetan3 and CHAKRABORTY, Debaditya3, (1)Edwards Aquifer Authority, 900 E. Quincy, San Antonio, TX 78215, (2)South Central Climate Adaptation Science Center, The University of Oklahoma, 201 Stephenson Parkway Suite 2100, Norman, OK 73019, (3)School of Civil and Environmental Engineering, and Construction Management, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249
The Edwards (Balcones Fault Zone) Aquifer in south-central Texas is a prolific limestone karst aquifer system. Not only is the aquifer the primary source of water for more than two million people in the region, but it also provides springflow to several federally protected species. The aquifer is managed using a regulatory framework that includes a cap on permitted withdrawals, reductions in permitted withdrawals during drought, pumping forbearance lease programs, and supplemental supplies from an aquifer storage and recovery system that are implemented during significant droughts. Combined, these measures provide protection of spring flows specified as part of the Edwards Aquifer Habitat Conservation Plan (EAHCP) and its associated Incidental Take Permit (ITP). The current EAHCP ITP will expire in 2028, and its renewal will require assessment of the potential impacts of future climate change on springflow.
We embarked on a comprehensive strategy to develop springflow projections through the proposed ITP renewal period of 30 years. Region-oriented downscaled global climate model projections were generated and used as input for estimating future recharge. Current estimates of aquifer recharge utilize stream gauging to measure stream losses across the recharge zone (Edwards Formation outcrops) and do not directly incorporate a climate or meteorological component. To address this, a new machine learning-assisted recharge model was developed by training a tree-based ensemble model to reproduce historical recharge values using input variables including precipitation and temperature. The resulting model performs well relative to a validation set of historical values and was used with climate model output to produce projected recharge sequences. These recharge sequences were then used in an existing numerical groundwater flow model to produce future projected spring flows and aquifer water levels under various climate scenarios. Results indicate generally lower recharge is expected, but no droughts more severe than the current drought of record were identified. The results also suggest the current aquifer management framework is suitable for use over the next three decades as part of a renewed EAHCP ITP.