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The model developed in this paper, the bacteria loading estimator spreadsheet tool (BLEST), was designed as an easy to use indicator bacteria model that can overcome the shortcomings of many of the simpler total maximum daily load (TMDL) modeling approaches by integrating spatial variation into load estimates. BLEST was applied to the Buffalo Bayou watershed in Houston, Texas and incorporated loading from point and nonpoint sources, such as wastewater treatment plants, sanitary sewer overflows, septic systems, storm sewer leaks, runoff, bed sediment resuspension, and direct deposition. The dry weather Escherichia coli load in Buffalo Bayou was estimated using BLEST to be 244 billion MPN/day and would require an overall 48% reduction to meet the contact recreation standard, while wet weather loads would need to be reduced by 99.7%. Dry weather loads were primarily caused by animal direct deposition, septic systems and discharges from storm sewers under dry weather conditions, while wet weather loads were mostly attributable to runoff and resuspension from sediment. Unlike most simple TMDL load allocation strategies, BLEST can be used to evaluate spatially variable load reduction strategies. For example, septic system load reductions implemented in less than 10% of the subwatersheds resulted in a decrease in bayou loading of more than 20%. [ABSTRACT FROM AUTHOR]