Filters: partyWithName: U.S. Geological Survey (X) > partyWithName: Mark R. Nardi (X)
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A soil-water balance model (SWB) was developed to estimate potential recharge and irrigation water demand from the groundwater flow system in Florida and parts of Georgia, Alabama, and South Carolina for the period 1895 through 2010. This SWB model executable code detailed in the report SWB—A Modified Thornthwaite-Mather Soil-Water-Balance Code for Estimating Groundwater Recharge; Chapter 31 of Section A, Groundwater, of Book 6, Modeling Techniques By S.M. Westenbroek, V.A. Kelson,W.R. Dripps,R.J. Hunt, and K.R. Bradbury (https://pubs.usgs.gov/tm/tm6-a31/) The SWB model was not calibrated; however, various water budget components from the model output compared reasonably well with other estimates including irrigation...
A soil-water balance model (SWB) was developed to estimate potential recharge to the groundwater system in Brunswick, New Hanover, and Pender counties North Carolina 1980 through 2016 to support a regional groundwater flow model being produced for the surficial, Castle Hayne, and Peedee Aquifer System. The SWB model was not calibrated; however, various water budget components from the model output compared reasonably well with other estimates including evapotranspiration rates reported by NASA's MODIS (Moderate Resolution Imaging Spectroradiometer) satellite platform. This USGS data release contains all the input and output files for the simulations described in this data release.
A three-dimensional, groundwater flow model was developed with the numerical code MODFLOW-NWT to represent changes in groundwater pumping and aquifer recharge in the Northern Atlantic Coastal Plain aquifer system from Long Island, New York to North Carolina. The model was constructed using existing hydrogeologic and geospatial information to represent the aquifer system geometry, boundaries, and hydraulic properties of the 19 separate regional aquifers and confining units within the aquifer system. The model was calibrated using an inverse modeling parameter-estimation (PEST) technique to conditions from 1986 to 2008, the period for which data are most complete and reliable. The simulation period for this analysis...
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