Geology topics

Dulcinea Marie Avouris

Publications and source records attributed to Dulcinea Marie Avouris.

7 recordsLinked to original sources

USGS2026

Cyanobacteria Assessment Network: Pilot study with Sentinel-2 derived chlorophyll data

Harmful algal blooms (HABs) affect global water quality, limiting uses like recreation and consumption because of excessive algal biomass and toxin production. These blooms cause surface scums, taste and odor issues, hypoxia, and negative health and socioeconomic impacts. The US Army Corps of Engineers (USACE) manages over 400 lakes and reservoirs and seeks to improve monitoring of HABs through Sentinel-2 (S2) satellite imagery. The purpose of this project is to develop workflows for a national chlorophyll-a product with 20 m spatial resolution, enabling HAB monitoring for over 270,000 lakes and reservoirs. The 1-year pilot study established a federal partnership to conduct preliminary S2 processing steps, using datasets from Florida, Ohio, and Oregon. Key steps included in situ data aggregation, data assimilation, S2 algorithm evaluation, spatial and temporal compositing, satellite sensor cross-validation, and web hosting of an example prototype product. The study covers 29 USACE reservoirs, with cross-validation using Sentinel-3 (S3) data from 212 lakes. The multiagency initiative aligns with federal agency missions to protect health and the environment, supports acts like the 2017 Harmful Algal Bloom and Hypoxia Research and Control Act, and has annual potential avoided costs of $42 million.

contiguous United States↗

USGS2026

Aquatic reflectance derived from Sentinel-2 Multispectral Imager data for inland waters in the conterminous United States

Satellite-based earth observation is a robust tool for tracking change in ecosystems. While terrestrially focused applications of remote sensing have empowered wide adoption for research and management, remote sensing of inland aquatic ecosystems remains comparably nascent. This divergence, in part, stems from the lack of standardized, accessible, and near real-time remotely sensed surface reflectance, atmospherically corrected for aquatic environments. To date, surface reflectance products at national scales and with minimal latency are typically designed exclusively for terrestrial environments. Rectifying this situation can be accomplished by applying aquatic-focused atmospheric correction algorithms independent of those used for terrestrial ecosystems. As a first step to filling this data gap, we present the first national scale, dynamically updated, analysis-ready, aquatic reflectance dataset for inland water derived from Sentinel-2 for the conterminous United States.

conterminous United States↗

USGS2025

Post-wildfire sediment fluxes and turbidity plumes in a coastal-draining watershed

Coastal watersheds impacted by wildfires experience higher erosion resulting in increased sediment delivery to the ocean that alters limiting factors (i.e., light) for marine organisms. With increasing wildfire magnitude and severity, it is critical to explore changes in riverine discharges to the ocean to assess cascading hazards associated with wildfires. In situ data, remotely sensed turbidity data, and hydrological model (Soil and Water Assessment Tool “SWAT”) simulations have been adapted to capture and investigate fire-related land use change impacts on Malibu Creek, California, USA. Modifying SWAT land cover inputs using burn severity data had minimal impact on simulations, requiring additional parameterization for acceptable model performance. Remotely sensed turbidity, in situ discharge, rating curve sediment loads, and SWAT simulated discharge and sediment loads increased following the Woolsey Fire. When compared to in situ and rating curve data in similar non-fire water years, the 2019 Woolsey Fire water year in situ discharge was 1.8 times higher, SWAT simulated discharges were 1.4–1.7 times higher, and rating curve sediment load was 1.3 times higher. However, the SWAT simulated sediment loads were slightly lower (0.8–0.9 times) than rating curve sediment loads in similar non-fire water years. Mean coastal turbidity increased to 18.2 Formazin Nephelometric Unit (FNU) during the first storm post-fire (mean background value of 4.3 FNU). Synergies between methods demonstrated rapid coastal sediment exports (remote sensing) and ongoing erosion post-fire (SWAT). These data are essential to understanding fire-related marine ecological changes and implementing effective management and conservation initiatives.

California↗

USGS2025

Advancements in satellite observations of inland and coastal waters: Building towards a global validation network

The use of satellite-based remote sensing imagery for water quality monitoring of inland and coastal waters has become widespread over the last few decades, with the expansion of, and investment in, operational Earth-observing missions. Satellite-based sensors are uniquely suited to provide synoptic, system-wide water quality parameter estimates that supplement traditional field-based sampling methods. The remote sensing of water quality parameter estimates is particularly valuable in systems with high temporal and spatial variability, as well as in areas that are difficult to access, or where agencies lack funding for routine monitoring. However, optically complex inland and coastal waters pose additional challenges for developing robust remote sensing retrieval models for optical properties and water quality parameters. One of the biggest challenges is collecting high quality field measurements that are used to calibrate and validate the retrieval algorithms. Here, we present the current status of satellite missions, field methods that include instruments used and commonly measured parameters, and repositories of historical field data that are relevant to inland and coastal water studies. We then present data requirements for model validation and highlight gaps in validation coverage. Finally, we provide suggestions for future field campaigns to improve coordination with remote sensing data collection and to ensure that field data is well suited for use in model or algorithm development.

Remote Sensing↗

USGS2025

Designs for cyanobacterial harmful algal bloom monitoring in the Sacramento–San Joaquin Delta, California

Cyanobacterial harmful algal blooms (CHABs) are a growing concern in freshwater environments. These blooms can lead to degraded water quality, ecosystem disruptions, and public health threats due to the production of potent cyanotoxins. The Sacramento–San Joaquin Delta (California, USA; the Delta) has experienced CHABs since 1999, including CHABs that produce cyanotoxins at concentrations exceeding recreational advisory threshold levels. In response to the CHAB monitoring needs in the Delta, in 2024 a CHAB monitoring strategy for the Sacramento–San Joaquin Delta was released. The CHAB monitoring strategy recommended implementing a comprehensive monitoring program aligned with regional priorities, and this report responds directly to that recommendation. Building on the CHAB monitoring strategy, it describes three example monitoring designs that draw from past studies to address present needs. To develop designs, the report outlines key components and considerations for implementing a CHAB monitoring program in the Delta. It provides: background on monitoring and modeling approaches, an overview of current monitoring programs in the region, guidance for selecting monitoring locations, indicators, and sampling frequencies, and example designs to guide program planning and budgeting. The overarching goal of the report is to help agencies and stakeholders move from high-level recommendations to practical, actionable designs that are tailored to the Delta’s physical, anthropogenic, and ecological landscape.

ESS Open Archive↗

USGS2025

An integrated sensor network and data driven approach to satellite remote sensing of dissolved organic matter

Traditional remote sensing retrieval models for water quality have historically relied on limited, localized data sets due to the prohibitive costs of extensive field campaigns and logistical challenges of collecting match-up data with satellite overpasses. As a result, these models often lack generalizability across seasons, tides, and sites. Furthermore, small field data sets limit the utility of modern machine learning techniques to advance remote sensing retrieval models. In situ optical sensors deployed in a sensor network to continuously monitor larger water bodies can drastically increase the number of measurements, providing the opportunity to develop new approaches for building robust remote sensing retrieval models by leveraging both remote sensing data and in situ networks as an integrated monitoring system. This study leverages a large “ground-to-space” sensor network that combines an in situ optical sensor network with satellite-based remote sensing to overcome these limitations. Utilizing a large-scale data set from the U.S. Geological Survey's Sacramento—San Joaquin River Delta monitoring network, of dissolved organic matter fluorescence measurements, and remote sensing data from the European Space Agency's Sentinel-2A and -2B satellites, this study implemented a data driven approach for dissolved organic matter models. The data set, consisting of 982 samples collected between 2018 and 2021 was used to train and validate a random forest model ( R 2 = 0.76, RMSE = 6.1 Quinine Sulfate Equivalents), with demonstrated applicability across diverse site conditions, tidal stages, and seasons. This work provides a scalable solution to address critical challenges in water quality monitoring and offers a replicable framework for global water quality management.

Calfornia↗

USGS2024

Impacts of wildfire runoff on giant kelp in Malibu, California

This study investigates the effects of post-wildfire sediment runoff on giant kelp (Macrocystis pyrifera) populations in Malibu, California, following the 2018 Woolsey Fire. The research utilizes satellite data and the Soil and Water Assessment Tool (SWAT) to assess changes in sediment delivery and its correlation with reduced kelp abundance. Findings indicate a significant decrease in kelp canopy recovery, post-fire, with ongoing limited regrowth up to 2023. This study underscores the critical impacts of wildfire-induced sediment runoff on marine ecosystems and emphasizes the need for tailored coastal management and restoration strategies to mitigate these effects and support the resilience of kelp forests, which are vital for biodiversity and coastal ecosystem services.

California↗