Data and code for "Watershed-Scale Green Infrastructure Reduces Storm-Driven Escherichia coli Extremes"

Data and code repository supporting the manuscript "Watershed-Scale Green Infrastructure Reduces Storm-Driven Escherichia coli Extremes: Tail-Aware Modeling and Dependence-Robust Inference for Bacteria TMDL Implementation" (Cleaner Water, Elsevier). Contents: Gould_etal_Ecoli_GI_Repository.zip: Python analysis scripts, calibrated SWAT scenario outputs (daily simulated E. coli concentrations for Baseline and GI scenarios, 2011–2019), observed data (TCEQ Station 10786, n = 166), and hydroclimate driver data. Includes all scripts to reproduce Tables 1–6, S1–S9, Figures 1–5, and Figures S1–S4. Gould_etal_Ecoli_VC_SWAT_Model.zip: Village Creek–Lake Arlington watershed SWAT model files. Subfolder Baseline_TxtInOut-flow+bact-calibration contains the calibrated baseline model (SWAT v2012 rev. 670, calibrated for daily streamflow and E. coli at USGS Station 08048970 and TCEQ Station 10786, 2011–2019). Subfolder GI_Simulations contains TxtInOut files for all six green infrastructure scenarios (S1–S6). Contact: Dr. Gehendra Kharel, STREAM Lab, (Sustainable Tools for Risk Evaluation and Climate-Water Modeling), Texas Christian University ([e-mail])