For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1-888-ASK-USGS.For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprodTo order this and other USGS information products, visit http://store.usgs.gov Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner. AbstractPotential changes in climate could alter interactions between environmental and societal systems and adversely affect the availability of water resources in many coastal communities. Changes in streamflow patterns in conjunction with sea-level rise may change the salinity-intrusion dynamics of coastal rivers. Several municipal water-supply intakes are located along the Georgia and South Carolina coast that are proximal to the present day saltwater-freshwater interface of tidal rivers. Increases in the extent of salinity intrusion resulting from climate change could threaten the availability of freshwater supplies in the vicinity of these intakes. To effectively manage these supplies, water-resource managers need estimates of potential changes in the frequency, duration, and magnitude of salinity intrusion near their water-supply intakes that may occur as a result of climate change. This study examines potential effects of climate change, including altered streamflow and sea-level rise, on the dynamics of saltwater intrusion near municipal water-supply intakes in two coastal areas. One area consists of the Atlantic Intracoastal Waterway (AIW) and the Waccamaw River near Myrtle Beach along the Grand Strand of the South Carolina Coast, and the second area is on or near the lower Savannah River near Savannah, Georgia. The study evaluated how future sea-level rise and a reduction in streamflows can potentially affect salinity intrusion and threaten municipal water supplies and the biodiversity of freshwater tidal marshes in these two areas.Salinity intrusion occurs as a result of the interaction between three principal forces-streamflow, mean coastal water levels, and tidal range. To analyze and simulate salinity dynamics at critical coastal gaging stations near four municipal water-supply intakes, various data-mining techniques, including artificial neural network (ANN) models, were used to evaluate hourly streamflow, salinity, and coastal water-level data collected over a period exceeding 10 years. The ANN models were trained (calibrated) to learn the specific interactions that cause salinity intrusions, and resulting models were able to accurately simulate historical salinity dynamics in both study areas.1 U.S. Geological Survey.2 Advanced Data Mining, LLC, G...
Many coastal utilities will find it challenging to adapt to future climate conditions in which sea‐level rise and extreme weather cycles could increase the frequency and duration of seawater intrusion into estuaries. This article describes a method of assessing risk to utility water supplies and details its use in two coastal systems supplying freshwater to municipalities in Georgia and South Carolina. The method uses long‐term weather and hydrologic data to develop empirical models that represent the seawater intrusion process in the vicinity of an intake. Data available from past droughts and storms provided sufficient variability to model the range of anticipated future weather and hydrologic conditions. The model can be varied using permutations of historical conditions and climate change forecasts to estimate future impacts at the intake. The models and data are deployed in a spreadsheet program that features a graphical user interface and supporting graphics, making it readily usable by utility personnel.
The Savannah Harbor is one of the busiest ports on the East Coast of the United States and is located downstream from the Savannah National Wildlife Refuge, which is one of the Nation's largest freshwater tidal marshes. The Georgia Ports Authority and the U.S. Army Corps of Engineers funded hydrodynamic and ecological studies to evaluate the potential effects of a proposed deepening of Savannah Harbor as part of the Environmental Impact Statement. These studies included a three-dimensional (3D) model of the Savannah River estuary system, which was developed to simulate changes in water levels and salinity in the system in response to geometry changes as a result of the deepening of Savannah Harbor, and a marsh-succession model that predicts plant distribution in the tidal marshes in response to changes in the water-level and salinity conditions in the marsh. Beginning in May 2001, the U.S. Geological Survey entered into cooperative agreements with the Georgia Ports Authority to develop empirical models to simulate the water level and salinity of the rivers and tidal marshes in the vicinity of the Savannah National Wildlife Refuge and to link the 3D hydrodynamic river-estuary model and the marsh-succession model. For the development of these models, many different databases were created that describe the complexity and behaviors of the estuary. The U.S. Geological Survey has maintained a network of continuous streamflow, water-level, and specific-conductance (field measurement to compute salinity) river gages in the study area since the 1980s and a network of water-level and salinity marsh gages in the study area since 1999. The Georgia Ports Authority collected water-level and salinity data during summer 1997 and 1999 and collected continuous water-level and salinity data in the marsh and connecting tidal creeks from 1999 to 2002. Most of the databases comprise time series that differ by variable type, periods of record, measurement frequency, location, and reliability. Understanding freshwater inflows, tidal water levels, and specific conductance in the rivers and marshes is critical to enhancing the predictive capabilities of a successful marsh succession model. Data-mining techniques, including artificial neural network (ANN) models, were applied to address various needs of the ecology study and to integrate the riverine predictions from the 3D model to the marsh-succession model. ANN models were developed to simulate riverine water levels and specific conductance in the vicinity of the tidal marshes for the full range of historical conditions using data from the river gaging networks. ANN models were also developed to simulate the marsh water levels and pore-water salinities using data from the marsh gaging networks. Using the marsh ANN models, the continuous marsh network was hindcasted to be concurrent with the long-term riverine network. The hindcasted data allow ecologists to compute hydrologic parameters-such as hydroperiods and exposure frequency-to help analyze historical vegetation data. To integrate ...
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