Molly S Wood
Molly Wood is the National Sediment Specialist for the USGS Water Resources Mission Area’s Observing Systems Division. Most of her work focuses on developing policies and methods for measuring fluvial sediment transport and for computing streamflow using complex rating techniques. She also teaches national and international training courses on surface-water and sediment data collection.
Biography
Molly Wood has a B.S. and M.S. in Civil and Environmental Engineering from the University of Tennessee and is a registered Professional Engineer. She started working with the USGS in 2002; initially as a Hydrologist in the Florida Water Science Center working on the Comprehensive Everglades Restoration Plan, then as Surface-Water Specialist for the Idaho Water Science Center, and now as the National Sediment Specialist for USGS Headquarters. She provides technical guidance for and leads initiatives to support national sediment and streamflow monitoring programs and related research. Her scientific work includes the estimation of fluvial sediment transport using surrogate technologies, estimation of reservoir capacity and sustainability, and applications of statistical hydrology. She has provided technical assistance in hydrologic data collection and research to government agencies across the world, including in Iraq, Laos, Chile, and Brazil.
Science and Products
Sediment Acoustics
The U.S. Geological Survey recognizes the need to provide sediment acoustic training and to develop standardized techniques and practices.
Fluvial Sediment and Geomorphology: Resources for Monitoring and Analysis
The USGS collects fluvial sediment and geomorphic data and conducts related research at numerous sites across the Nation. This information is essential to informed solutions to sediment-related and overall water resource management issues.
Field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor
Sequoia Scientific’s LISST-ABS is a submersible acoustic instrument that measures the acoustic backscatter sensor (ABS) concentration at a point within a river, stream, or creek. Compared to traditional physical methods for measuring suspended-sediment concentration (SSC), sediment surrogates like the LISST-ABS offer continuous data that can be...
Manaster, Adam E.; Straub, Timothy D.; Wood, Molly S.; Bell, Joseph M.; Dombroski, Daniel E.; Curran, Christopher A.
Envisioning a multi-agency and multi-academic institution geomorphology data exchange portal
Access to bathymetry and geomorphology data for rivers and reservoirs is a critical need in multiple agencies and academia. These data are needed to make water-resource-management decisions regarding river restoration, resource protection, infrastructure design and sustainability, and flood-risk reduction, and during natural disasters. Sharing of...
Wood, Molly S.; Boyd, Paul M
Acoustic Sediment Estimation Toolbox (ASET): A software package for calibrating and processing TRDI ADCP data to compute suspended-sediment transport in sandy rivers
Quantifying suspended-sediment transport is critical for a variety of disciplines related to the management of water resources. However, the number of gauging stations and monitoring networks in most rivers around the world is insufficient to improve understanding of river dynamics and support water resource management decisions. This is mainly...
Dominguez Ruben, Lucas Gerardo; Szupiany, Ricardo; Latosinski, Francisco; Lopez Weibel, Cecilia; Wood, Molly S.; Boldt, Justin A. Measuring suspended sediment in sand-bedded rivers using down-looking acoustic doppler current profilers
The use of side-looking acoustic Doppler velocity meters (ADVMs) to estimate fluvial suspended-sediment concentrations (SSC) has become more operational by the U.S. Geological Survey in recent years; however, direct transfer of these techniques to down-looking acoustic Doppler current profilers (ADCPs) currently is not widely feasible. Key...
Wood, Molly S.; Szupiany, Ricardo N.; Boldt, Justin A.; Straub, Timothy; Domanski, Marian M. Strategic directions of the USGS water mission area’s fluvial sediment science program
The USGS Water Mission Area’s Sediment Science Program provides leadership, training, and methods development in fluvial sediment science for the USGS and its external partners. Overarching objectives of the USGS Sediment Science Program (which includes the Federal Interagency Sedimentation Project) include: 1) developing and...
Wood, Molly S.; Straub, Timothy Time-series sediment acoustics and LISST-ABS testing
Acoustics and other surrogates can be used to accurately and cost-effectively provide time-series estimates of suspended-sediment concentration and load, which is essential for creating informed solutions to many sediment-related environmental, engineering, and agricultural concerns. Interagency efforts in recent years have advanced...
Straub, Timothy; Wood, Molly S.; Domanski, Marian M.; Manaster, Adam (Contractor) Estimating sand concentrations using ADCP‐based acoustic inversion in a large fluvial system characterized by bi‐modal suspended‐sediment distributions
Quantifying sediment flux within rivers is a challenge for many disciplines due, mainly, to difficulties inherent to traditional sediment sampling methods. These methods are operationally complex, high cost, and high risk. Additionally, the resulting data provide a low spatial and temporal resolution estimate of the total sediment flux, which has...
Szupiany, Ricardo N.; Lopez Weibel, Cecilia; Guerrero, Massimo; Latosinski, Francisco; Wood, Molly S.; Dominguez Ruben, Lucas; Oberg, Kevin
Sediment acoustic index method for computing continuous suspended-sediment concentrations
Suspended-sediment characteristics can be computed using acoustic indices derived from acoustic Doppler velocity meter (ADVM) backscatter data. The sediment acoustic index method applied in these types of studies can be used to more accurately and cost-effectively provide time-series estimates of suspended-sediment concentration and load, which is...
Landers, Mark N.; Straub, Timothy D.; Wood, Molly S.; Domanski, Marian M.
Estimating peak-flow frequency statistics for selected gaged and ungaged sites in naturally flowing streams and rivers in Idaho
The U.S. Geological Survey, in cooperation with the Idaho Transportation Department, updated regional regression equations to estimate peak-flow statistics at ungaged sites on Idaho streams using recent streamflow (flow) data and new statistical techniques. Peak-flow statistics with 80-, 67-, 50-, 43-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent...
Wood, Molly S.; Fosness, Ryan L.; Skinner, Kenneth D.; Veilleux, Andrea G. Evaluation of multiple-frequency, active and passive acoustics as surrogates for bedload transport
The use of multiple-frequency, active acoustics through deployment of acoustic Doppler current profilers (ADCPs) shows potential for estimating bedload in selected grain size categories. The U.S. Geological Survey (USGS), in cooperation with the University of Montana (UM), evaluated the use of multiple-frequency, active and passive acoustics as...
Wood, Molly S.; Fosness, Ryan L.; Pachman, Gregory; Lorang, Mark; Tonolla, Diego
Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14
The Kootenai River white sturgeon (Acipenser transmontanus) and other native fish species are culturally important to the Kootenai Tribe of Idaho, but their habitat and recruitment have been affected by anthropogenic changes to the river. Although the interconnections among anthropogenic changes and their impacts on fish are complex, the Kootenai...
Wood, Molly S.; Fosness, Ryan L.; Etheridge, Alexandra B. Surrogate analysis and index developer (SAID) tool and real-time data dissemination utilities
The use of acoustic and other parameters as surrogates for suspended-sediment concentrations (SSC) in rivers has been successful in multiple applications across the Nation. Critical to advancing the operational use of surrogates are tools to process and evaluate the data along with the subsequent development of regression models from which real-...
Domanski, Marian M.; Straub, Timothy D.; Wood, Molly S.; Landers, Mark N.; Wall, Gary R.; Brady, Steven J.