Search USGSSearch

Geology topics

Andrew Meredith

Publications and source records attributed to Andrew Meredith.

3 recordsLinked to original sources

Fault activity in the San Gabriel Mountains, southern California, USA: Insights from landscape morphometrics, erosion rates, and fault-slip rates

Many studies use landscape form to determine spatial patterns of tectonic deformation, and these are particularly effective when paired with independent measures of rock uplift and erosion. Here, we use morphometric analyses and 10 Be catchment-averaged erosion rates, together with reverse slip rates from the Sierra Madre−Cucamonga fault zone, to reveal patterns in uplift, erosion, and fault activity in the range front of the San Gabriel Mountains in southern California, USA. Our analysis tests two prevailing hypotheses: (1) the range front of the San Gabriel Mountains is at steady state, in which rock uplift balances erosion and topographic elevations are stable throughout time, and (2) that west-to-east increases in elevation, relief, erosion rate, and stream-channel steepness across the interior of the massif reflect a parallel reverse-slip rate gradient on the range-bounding Sierra Madre−Cucamonga fault zone. We show that although deviations from steady state occur, the range-front hillslopes and stream channels are typically both well-connected and adjusted to patterns in Quaternary uplift driven by motion on the range-front fault network. Accordingly, landscape morphometrics, 10 Be erosion rates, and model erosion rates effectively image spatial and temporal patterns in uplift. Interpreted jointly, these data reveal comparable peak slip rates on the Sierra Madre−Cucamonga fault zone and show that they do not monotonically increase from west to east. Thus, the eastward-increasing gradients developed within the interior of the massif are not solely related to reverse slip on the range-front faults. Evaluated on shorter length scales (<10 km), morphometric data corroborate earlier descriptions of the Sierra Madre−Cucamonga fault zone as multiple individual faults or fault sections, with slip rates tapering toward fault tips. We infer that these patterns imply the predominance of independent fault or fault section ruptures throughout the Quaternary, though data cannot rule out the possibility of large, connected Sierra Madre−Cucamonga fault zone ruptures. Deeper in the hanging wall of the Sierra Madre−Cucamonga fault zone, secondary faults accommodate range-front uplift. Motion on these faults may contribute to active uplift of the highest topography within the massif, in addition to partly reconciling differences between geologic and geodetic Sierra Madre−Cucamonga fault zone reverse-slip rates. This study provides a new, unified perspective on tectonics and landscape evolution in the San Gabriel Mountains.

California

Evaluation of a satellite-based cyanobacteria bloom detection algorithm using field-measured microcystin data

Widespread occurrence of cyanobacterial harmful algal blooms (CyanoHABs) and the associated health effects from potential cyanotoxin exposure has led to a need for systematic and frequent screening and monitoring of lakes that are used as recreational and drinking water sources. Remote sensing-based methods are often used for synoptic and frequent monitoring of CyanoHABs. In this study, one such algorithm – a sub-component of the Cyanobacteria Index called the CI cyano , was validated for effectiveness in identifying lakes with toxin-producing blooms in 11 states across the contiguous United States over 11 bloom seasons (2005–2011, 2016–2019). A matchup data set was created using satellite data from MEdium Resolution Imaging Spectrometer (MERIS) and Ocean Land Colour Imager (OLCI), and nearshore, field-measured Microcystins (MCs) data as a proxy of CyanoHAB presence. While the satellite sensors cannot detect toxins, MCs are used as the indicator of health risk, and as a confirmation of cyanoHAB presence. MCs are also the most common laboratory measurement made by managers during CyanoHABs. Algorithm performance was evaluated by its ability to detect CyanoHAB ‘Presence’ or ‘Absence’, where the bloom is confirmed by the presence of the MCs. With same-day matchups, the overall accuracy of CyanoHAB detection was found to be 84% with precision and recall of 87 and 90% for bloom detection. Overall accuracy was expected to be between 77% and 87% (95% confidence) based on a bootstrapping simulation. These findings demonstrate that CI cyano has utility for synoptic and routine monitoring of potentially toxic cyanoHABs in lakes across the United States.

Science for the Total Environment

Measurement of cyanobacteria bloom magnitude using satellite remote sensing

Cyanobacterial harmful algal blooms (cyanoHABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude, information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatio-temporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape-based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Ocean Land Color Imager (OLCI) on Sentinel-3 data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision-making for recreational and drinking water sources.

Florida, Ohio