In this study, stage, streamflow, and precipitation data was collected from small watersheds in the Swanton Pacific Ranch for the first two hydrologic years following the 2020 CZU Lightning Complex. The Little Creek watershed was setup for high-resolution data collection with four separate stage gauge sites (Main Stem, North Fork, South Fork, and Upper North Fork) and four rain gauge sites (Al Smith House, Ridgeline, Upper North Fork, and Landing 23). Stage gauge sites were also established at Queseria, Archibald, and Mill creeks. Preliminary post-fire rating curves were developed for the four sites of Little Creek. The Main Stem (MS) and North Fork (NF) post-fire curves showed some flattening of the slope indicating channel filling, while the South Fork (SF) curve displayed a steepening indicating channel scouring. The Upper North Fork (UNF) rating curve did not indicate any shifts. However, at the time of this study the rating curves were incomplete due to limitations in streamflow measurements. Linear regression models were fit to pre-fire data (hydrologic years 2000-2008) to predict peak flows and storm flow volumes. Antecedent precipitation index (API) and total storm precipitation depth were found to be significant predictors while peak 1-hour rainfall intensity was not. Comparison of post-fire observations to pre-fire model predictions indicated that there were increases in both peak flow and storm flow volumes in Little Creek. However, these findings are not statistically significant due to the limited post-fire observations (n

This post-fire study was conducted to characterize and observe fire induced changes in physical habitat parameters, water-quality conditions and macroinvertebrate assemblages in the Little Creek watershed, a tributary to Scotts Creek located in Cal Poly’s Swanton Pacific Ranch in Davenport, California. Pre-fire data was collected by a Cal Poly student, John Hardy, for his 2017 thesis. Post-burn bioassessment surveys for this study were repeated at four of the same study sites used by Hardy to provide comparisons to the California Stream Condition Index via a modified version of the State of California’s Surface Water Ambient Monitoring Program protocol. Macroinvertebrates were taxonomically identified to the family level. Commonly used bioassessment indices were utilized in conjunction with Stepwise regression and Analysis of Variance on both pre- and post-fire datasets to illustrate how physical habitat and water quality parameters changed after the fire and to determine the significance of collected environmental variables (stream shading, cross sectional area, and median particle size) as predictors of macroinvertebrate community structure. Despite most of Little Creek having moderate and high burn severities, it was found that physical habitat, water quality and benthic macroinvertebrate populations were not greatly disturbed by the 2020 CZU lighting complex fire. Proportions of highly disturbance/pollution sensitive taxa and increased following the wildfire and there was a dramatic shift from collector-gatherer to predator organisms. Comparison of pre- and post-fire data in this study showed fire having a minimal effect on the studied watershed. Difference in study goals and associated protocols used in the pre- and post-fire studies and the low water year following the wildfire, complicates statistical comparisons and poses threat to the validity of results. However, there is opportunity for further investigation about the ability of an ecosystem to successfully recover from natural disasters and disturbances, specifically when there is little human impact (or influence) on the ecosystem.

Climate change and a growing wildland-urban interface are associated with an increase in the number and severity of wildfires. While severe wildfires do cause a costly and dangerous impact on the environment and the public, their after-effects comprise important subjects of study. In post-fire hydrologic studies, the reduced infiltration and plant cover that results from wildfires can commonly be associated with increased peakflows and erosion. Phenomena such as the flooding and debris flows in Montecito after the Thomas Fire in late 2017 can have important implications on infrastructure and human lives. Quantifying post-fire peak flows and flooding volumes has therefore become a special study of interest. However, the few studies that exist on post-fire hydrology across the United States have inconclusive and flawed results. Post-fire hydrological studies on coastal-redwood forests are also lacking in both number and quality. These research gaps were addressed through a three-year, post-fire hydrological study on the Litte Creek watershed of Swanton Pacific Ranch in Davenport, CA. The study took place from the 2021 to 2024 hydrological years (HY). Hydrographs and rating curves were developed to yield results for post-fire conditions. A frequency analysis utilizing Log Pearson Type III and Weibull calculations yielded post-fire results according to 0.5-, 1-, 2-, and 5-year return intervals. A statistical model based on precipitation, antecedent precipitation index, and streamflow data modelled pre-fire values. Subsequently, the pre- and post-fire peak flows and storm volumes were compared. The post-fire results from the analysis were also compared to those estimated from the USGS Linear Regression method and the RF-5 method from Wilder et al, 2020. It was found that a slight increase in post-fire peak flows and storm volumes occurred upon comparison to pre-fire values, primarily for the South Fork of the watershed. This observation was found to be present for flows and volumes below a 0.5-year return interval, with higher uncertainty beyond that threshold. The USGS and Wilder methods were found to v inaccurately predict the post-fire peak flows. However, calculation of USGS-Regression parameters for two areas (Main Stem and South Fork) yielded percent increases in post-fire peak flows (between 19-31%) and percent-runoff increases (between 36-59%) for peak flows between return intervals of 0.5 to 5 years. Results were found to be mostly statistically significant for all three sites (α < 0.05), except for the North-Fork site in several cases and some model intercepts across all three sites. Incision and erosion of streambeds and the recovery of vegetation since the 2020 fire may have played an underlying role in the study. Despite some errors in stage data, the small increases in post-fire parameters, and variations in burn-area conditions, the study represented a motivated attempt to use linear regression on post-fire hydrologic data and to improve upon the site’s previous study through a more comprehensive dataset. This attempt serves as one of many in studying post-fire hydrology, which serves to inform better decisions for wildfire, flood-management, and land-management agencies.