Lillian E. Gorman Sanisaca
Lillian E. Gorman Sanisaca has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Allen C. Gellis
Earth System Processes Division, Water Resources Mission Area, U.S. Geological Survey, 12201 Sunrise Valley Dr., Reston, VA 20192, USA
2 shared publications - David L. Lorenz
Hydrologist, U.S. Geological Survey WRD, Mounds View, Minnesota 55420
1 shared publication - Kenneth D. Skinner
U.S. Geological Survey Idaho Water Science Center Boise ID USA
1 shared publication - Matthew Joseph Cashman
U.S. Geological Survey, Water Mission Area, Reston, VA, United States of America
1 shared publication - Molly A. Maupin
Respectively, Supervisory Hydrologist, U.S. Geological Survey, 230 Collins Road, Boise, Idaho 83702
1 shared publication
Latest Publications
- Open Access
- 1 January 2019
- Published by US Geological Survey
Annual wastewater nutrient data preparation and load estimation using the Point Source Load Estimation Tool (PSLoadEsT)
The Point-Source Load Estimation Tool (PSLoadEsT) provides a user-friendly interface for generating reproducible load calculations for point source dischargers while managing common data challenges including duplicates, incompatible input tables, and incomplete or missing nutrient concentration or effluent flow data. Maintaining a consistent method across an entire study area is important when estimating loads to be used as calibration data for regional water-quality models. PSLoadEsT is written using the open-source programming language R and has an easy-to-use interface written in Visual Basic for Applications® within a Microsoft Access® database file that guides the user through the necessary steps to estimate point source loads. The purpose of this report is to provide a detailed user guide for PSLoadEsT.
- 1 January 2019
- Published by US Geological Survey
Open AccessAnnual wastewater nutrient data preparation and load estimation using the Point Source Load Estimation Tool (PSLoadEsT)
The Point-Source Load Estimation Tool (PSLoadEsT) provides a user-friendly interface for generating reproducible load calculations for point source dischargers while managing common data challenges including duplicates, incompatible input tables, and incomplete or missing nutrient concentration or effluent flow data. Maintaining a consistent method across an entire study area is important when estimating loads to be used as calibration data for regional water-quality models. PSLoadEsT is written using the open-source programming language R and has an easy-to-use interface written in Visual Basic for Applications® within a Microsoft Access® database file that guides the user through the necessary steps to estimate point source loads. The purpose of this report is to provide a detailed user guide for PSLoadEsT.
- Open Access
- 1 January 2018
- Published by US Geological Survey
Sediment Source Assessment Using Sediment Fingerprints
Sediment is one of the most common causes of loss of stream-biologic integrity, whether in suspension in the water column, or as deposition on a stream or lake bottom. Fine-grained silts and clays are of particular concern because they can degrade habitat and often carry phosphorus and (or) other contaminants harmful to humans and aquatic life. Sediment-impaired water bodies, usually identified by fair to poor macroinvertebrate index scores, are placed on the 303(d) list of impaired waters, where a sediment Total Maximum Daily Load (TMDL) is developed under the Clean Water Act (https://www.epa.gov/tmdl). In order to effectively manage sediment, it is necessary to identify the sediment sources and locations of “hot spots” of erosion and deposition.
- 1 January 2018
- Published by US Geological Survey
Open AccessSediment Source Assessment Using Sediment Fingerprints
Sediment is one of the most common causes of loss of stream-biologic integrity, whether in suspension in the water column, or as deposition on a stream or lake bottom. Fine-grained silts and clays are of particular concern because they can degrade habitat and often carry phosphorus and (or) other contaminants harmful to humans and aquatic life. Sediment-impaired water bodies, usually identified by fair to poor macroinvertebrate index scores, are placed on the 303(d) list of impaired waters, where a sediment Total Maximum Daily Load (TMDL) is developed under the Clean Water Act (https://www.epa.gov/tmdl). In order to effectively manage sediment, it is necessary to identify the sediment sources and locations of “hot spots” of erosion and deposition.
- Open Access
- 1 January 2017
- Published by US Geological Survey
Determining the sources of fine-grained sediment using the Sediment Source Assessment Tool (Sed_SAT)
A sound understanding of sources contributing to instream sediment flux in a watershed is important when developing total maximum daily load (TMDL) management strategies designed to reduce suspended sediment in streams. Sediment fingerprinting and sediment budget approaches are two techniques that, when used jointly, can qualify and quantify the major sources of sediment in a given watershed. The sediment fingerprinting approach uses trace element concentrations from samples in known potential source areas to determine a clear signature of each potential source. A mixing model is then used to determine the relative source contribution to the target suspended sediment samples.The computational steps required to apportion sediment for each target sample are quite involved and time intensive, a problem the Sediment Source Assessment Tool (Sed_SAT) addresses. Sed_SAT is a user-friendly statistical model that guides the user through the necessary steps in order to quantify the relative contributions of sediment sources in a given watershed. The model is written using the statistical software R (R Core Team, 2016b) and utilizes Microsoft Access® as a user interface but requires no prior knowledge of R or Microsoft Access® to successfully run the model successfully. Sed_SAT identifies outliers, corrects for differences in size and organic content in the source samples relative to the target samples, evaluates the conservative behavior of tracers used in fingerprinting by applying a “Bracket Test,” identifies tracers with the highest discriminatory power, and provides robust error analysis through a Monte Carlo simulation following the mixing model. Quantifying sediment source contributions using the sediment fingerprinting approach provides local, State, and Federal land management agencies with important information needed to implement effective strategies to reduce sediment. Sed_SAT is designed to assist these agencies in applying the sediment fingerprinting approach to quantify sediment sources in the sediment TMDL framework.
- 1 January 2017
- Published by US Geological Survey
Open AccessDetermining the sources of fine-grained sediment using the Sediment Source Assessment Tool (Sed_SAT)
A sound understanding of sources contributing to instream sediment flux in a watershed is important when developing total maximum daily load (TMDL) management strategies designed to reduce suspended sediment in streams. Sediment fingerprinting and sediment budget approaches are two techniques that, when used jointly, can qualify and quantify the major sources of sediment in a given watershed. The sediment fingerprinting approach uses trace element concentrations from samples in known potential source areas to determine a clear signature of each potential source. A mixing model is then used to determine the relative source contribution to the target suspended sediment samples.The computational steps required to apportion sediment for each target sample are quite involved and time intensive, a problem the Sediment Source Assessment Tool (Sed_SAT) addresses. Sed_SAT is a user-friendly statistical model that guides the user through the necessary steps in order to quantify the relative contributions of sediment sources in a given watershed. The model is written using the statistical software R (R Core Team, 2016b) and utilizes Microsoft Access® as a user interface but requires no prior knowledge of R or Microsoft Access® to successfully run the model successfully. Sed_SAT identifies outliers, corrects for differences in size and organic content in the source samples relative to the target samples, evaluates the conservative behavior of tracers used in fingerprinting by applying a “Bracket Test,” identifies tracers with the highest discriminatory power, and provides robust error analysis through a Monte Carlo simulation following the mixing model. Quantifying sediment source contributions using the sediment fingerprinting approach provides local, State, and Federal land management agencies with important information needed to implement effective strategies to reduce sediment. Sed_SAT is designed to assist these agencies in applying the sediment fingerprinting approach to quantify sediment sources in the sediment TMDL framework.