Skip to main content
Open Access Publications from the University of California

This series is automatically populated with publications deposited by UCLA Henry Samueli School of Engineering and Applied Science Department of Civil and Environmental Engineering researchers in accordance with the University of California’s open access policies. For more information see Open Access Policy Deposits and the UC Publication Management System.

Turbidity and fecal indicator bacteria in recreational marine waters increase following the 2018 Woolsey Fire.


Wildfires increase runoff and sediment yields that impact downstream ecosystems. While the effects of wildfire on stream water quality are well documented, oceanic responses to wildfire remain poorly understood. Therefore, this study investigated oceanic responses to the 2018 Woolsey Fire using satellite remote sensing and in situ data analyses. We examined 2016-2020 turbidity plume (n = 192) and 2008-2020 fecal indicator bacteria (FIB, n = 15,015) measurements at variable proximity to the Woolsey Fire. Shifts in coastal water quality were more pronounced in the "inside" region, which drained the burn area. The inside region experienced 2018-2019 plume surface area monthly means that were 10 and 9 times greater than 2016-2017 and 2017-2018 monthly means, respectively. Further, linear regressions showed that 2018-2019 three-day precipitation totals produced plumes of greater surface area. We also noted statistically significant increases in the inside region in 2018-2019 total coliform and Enterococcus monthly means that were 9 and 53 times greater than 2008-2018 monthly means, respectively. These results indicate that sediment and microbial inputs to coastal ecosystems can increase substantially post-wildfire at levels relevant to public and environmental health, and underscore the benefit of considering remote sensing and in situ measurements for water quality monitoring.

Bridge Digital Twinning Using an Output-Only Bayesian Model Updating Method and Recorded Seismic Measurements.


Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation using the measured ground motions at nearby stations; however, the damage assessment outcomes would suffer from uncertainties in structural and soil material properties, input excitations, etc. For instrumented bridges, these uncertainties can be reduced by integrating sensory data with prior models through a model updating approach. This study presents a sequential Bayesian model updating technique, through which a linear/nonlinear FE model, including soil-structure interaction effects, and the foundation input motions are jointly identified from measured acceleration responses. The efficacy of the presented model updating technique is first examined through a numerical verification study. Then, seismic data recorded from the San Rogue Canyon Bridge in California are used for a real-world case study. Comparison between the free-field and the foundation input motions reveals valuable information regarding the soil-structure interaction effects at the bridge site. Moreover, the reasonable agreement between the recorded and estimated bridge responses shows the potentials of the presented model updating technique for real-world applications. The described process is a practice of digital twinning and the updated FE model is considered as the digital twin of the bridge and can be used to analyze the bridge and monitor the structural response at element, section, and fiber levels to diagnose the location and severity of any potential damage mechanism.

Cover page of Influence of kinematic SSI on foundation input motions for pile-supported bridges

Influence of kinematic SSI on foundation input motions for pile-supported bridges


The seismic analysis of bridge structures is often performed using the substructure method in which the foundation is replaced by an equivalent "spring" representing foundation impedance. Ground motions from seismic hazard analyses correspond to a free-field condition, and therefore should be modified to account for kinematic soil-structure interaction effects before being used as input to the springs. This paper presents closed-form analytical solutions for the response of an elastic pile subjected to harmonic seismic excitation in uniform elastic soil. We use these solutions to compute transfer functions relating foundation input motion to free-field ground motion and use the results to verify predictions from a beam-on-Winkler-foundation numerical model. The two approaches show good agreement, indicating that the numerical modeling method is appropriate for investigating more complex effects such as soil and pile nonlinearity. Ground motion deamplification due to kinematic SSI is demonstrated to be significant for stiff foundations in soft ground conditions. Numerical simulations using recorded ground motions demonstrates that transfer functions can be computed only from frequency bands for which the motions contain adequate energy.

Cover page of An early warning system for wave-driven coastal flooding at Imperial Beach, CA

An early warning system for wave-driven coastal flooding at Imperial Beach, CA


AbstractWaves overtop berms and seawalls along the shoreline of Imperial Beach (IB), CA when energetic winter swell and high tide coincide. These intermittent, few-hour long events flood low-lying areas and pose a growing inundation risk as sea levels rise. To support city flood response and management, an IB flood warning system was developed. Total water level (TWL) forecasts combine predictions of tides and sea-level anomalies with wave runup estimates based on incident wave forecasts and the nonlinear wave model SWASH. In contrast to widely used empirical runup formulas that rely on significant wave height and peak period, and use only a foreshore slope for bathymetry, the SWASH model incorporates spectral incident wave forcing and uses the cross-shore depth profile. TWL forecasts using a SWASH emulator demonstrate skill several days in advance. Observations set TWL thresholds for minor and moderate flooding. The specific wave and water level conditions that lead to flooding, and key contributors to TWL uncertainty, are identified. TWL forecast skill is reduced by errors in the incident wave forecast and the one-dimensional runup model, and lack of information of variable beach morphology (e.g., protective sand berms can erode during storms). Model errors are largest for the most extreme events. Without mitigation, projected sea-level rise will substantially increase the duration and severity of street flooding. Application of the warning system approach to other locations requires incident wave hindcasts and forecasts, numerical simulation of the runup associated with local storms and beach morphology, and model calibration with flood observations.

Cover page of Commercially available garden products as important sources of antibiotic resistance genes-a survey.

Commercially available garden products as important sources of antibiotic resistance genes-a survey.


The dissemination of antibiotic resistance genes (ARGs) in the environment contributes to the global rise in antibiotic resistant infections. Therefore, it is of importance to further research the exposure pathways of these emerging contaminants to humans. This study explores commercially available garden products containing animal manure as a source of ARGs in a survey of 34 garden products, 3 recently landscaped soils, and 5 native soils. DNA was extracted from these soils and quantified for 5 ARGs, intI1, and 16S rRNA. This study found that both absolute and relative gene abundances in garden products ranged from approximately two to greater than four orders of magnitude higher than those observed in native soils. Garden products with Organic Materials Review Institute (OMRI) certification did not have significantly different ARG abundances. Results here indicate that garden products are important sources of ARGs to gardens, lawns, and parks.