Debris flows and sediment-laden floods in the Transverse Ranges of southern California pose severe hazards to nearby communities and infrastructure. Frequent wildfires denude hillslopes and increase the likelihood of these hazardous events. Debris-retention basins protect communities and infrastructure from the impacts of debris flows and sediment-laden floods and also provide critical data for volumes of sediment deposited at watershed outlets. In this study, we supplement existing data for the volumes of sediment deposited at watershed outlets with newly acquired data to develop new empirical models for predicting volumes of sediment produced by watersheds located in the Transverse Ranges of southern California. The sediment volume data represent a broad sample of conditions found in Ventura, Los Angeles and San Bernardino Counties, California. The measured volumes of sediment, watershed morphology, distributions of burn severity within each watershed, the time since the most recent fire, triggering storm rainfall conditions, and engineering soil properties were analyzed using multiple linear regressions to develop two models. A “long-term model” was developed for predicting volumes of sediment deposited by both debris flows and floods at various times since the most recent fire from a database of volumes of sediment deposited by a combination of debris flows and sediment-laden floods with no time limit since the most recent fire (n = 344). A subset of this database was used to develop an “emergency assessment model” for predicting volumes of sediment deposited by debris flows within two years of a fire (n = 92). Prior to developing the models, 32 volumes of sediment, and related parameters for watershed morphology, burn severity and rainfall conditions were retained to independently validate the long-term model. Ten of these volumes of sediment were deposited by debris flows within two years of a fire and were used to validate the emergency assessment model. The models were validated by comparing predicted and measured volumes of sediment. These validations were also performed for previously developed models and identify that the models developed here best predict volumes of sediment for burned watersheds in comparison to previously developed models.