This set of data includes four potential annual recharge grids for the State of Maine that were simulated using the Maine Soil-Water-Balance model for 1991 through 2015. The files include a grid representing the uncertainty in the potential recharge and a grid showing the annual average precipitation from the climate dataset that the simulation is based on. A 25-year simulation of potential recharge to groundwater from the Maine Soil-Water-Balance model for the years 1991 to 2015 produced annual results from which the four potential recharge grids were derived. The four are: 25-year mean, median, maximum, and minimum simulated annual potential. A data exclusion zone (see Scientific Investigations Report 2019–5125) has been applied to the recharge datasets, resulting in a dataset that covers most, but not all, of the State of Maine. The potential recharge grids are given in units of inches per year, with a raster grid cell size of 250 meters. The uncertainty in the simulated grid values is the standard deviation grid, which represents the standard deviation of the simulated median recharge grid. The precipitation data used in the 25-year simulation are from DayMet version 3 daily data. The average annual precipitation grid is the calculated annual average from those data. Further details about the generation and application of the data can be found in Scientific Investigations Report 2019–5125.

A water table fluctuation model simulated potential recharge rates from 2016 to 2018 for two agricultural sites in southeastern Minnesota. The model calculated potential recharge rates through the analysis of groundwater rises. A total of 42 piezometers were analyzed for this study using the water table fluctuation model. This methodology of calculating potential recharge rates was used as an independent method from two other methods: a soil-water-balance model (https://doi.org/10.5066/P90N4AWG), and DRAINMOD (https://doi.org/10.5066/P987N30U).

A previous soil-water balance (SWB) model [Smith and Westenbroek, 2015; http://dx.doi.org/10.3133/sir20155038) for Minnesota was updated to simulate potential recharge rates from 2014 to 2018. The previous model was developed to estimate mean annual potential recharge from 1995 to 2010. The updated model was also run with a newer version of the SWB model, also known as SWB version 2.0 {Westenbroek and others, 2018; https://doi.org/10.3133/tm6A59). The updated model was used to extract potential recharge rates for comparison to recharge rates calculated for two agricultural field sites in southeastern Minnesota, as part of the associated report, U.S. Geological Survey Scientific Investigations Report 2020-5006 (http://dx.doi.org/10.3133/sir20205006). The potential recharge rates were also used to simulate potential recharge rates for all of southeastern Minnesota from 2014-2018. For this model, the land-use grid was updated to the 2011 National Land Cover Database (NLCD); otherwise, the other input datasets and the lookup table were left unaltered from the original model. Daymet (version 3) daily surface weather data necessary for running this SWB model, including "prcp", "tmax", and "tmin", can be downloaded from this SWB model archive. Alternatively, the Daymet v3 are available upon request through the following link: https://doi.org/10.3334/ORNLDAAC/1328.

A previous soil-water balance (SWB) model [Smith and Westenbroek, 2015; http://dx.doi.org/10.3133/sir20155038) for Minnesota was updated to simulate potential recharge rates from 2014 to 2018. The previous model was developed to estimate mean annual potential recharge from 1995 to 2010. The updated model was also run with a newer version of the SWB model, also known as SWB version 2.0 {Westenbroek and others, 2018; https://doi.org/10.3133/tm6A59). The updated model was used to extract potential recharge rates for comparison to recharge rates calculated for two agricultural field sites in southeastern Minnesota, as part of the associated report, U.S. Geological Survey Scientific Investigations Report 2020-5006 (http://dx.doi.org/10.3133/sir20205006). The potential recharge rates were also used to simulate potential recharge rates for all of southeastern Minnesota from 2014-2018. For this model, the land-use grid was updated to the 2011 National Land Cover Database (NLCD); otherwise, the other input datasets and the lookup table were left unaltered from the original model. Daymet (version 3) daily surface weather data necessary for running this SWB model, including "prcp", "tmax", and "tmin", can be downloaded from this SWB model archive. Alternatively, the Daymet v3 are available upon request through the following link: https://doi.org/10.3334/ORNLDAAC/1328.

The files and folders in this data release contain the input and output files and MATLAB algorithms used for simulations described in the associated journal article (https://doi.org/10.1007/s10040-024-02868-x). The algorithms implement a data-driven, mechanistic model of vertical infiltration through the unsaturated zone and recharge to the water table that is developed from water-balance concepts. The model of infiltration and recharge is defined in terms of observed states (such as, the water-table altitude) and unobserved states (such as, fluxes through the unsaturated zone and recharge to the water table) and includes both diffuse and preferential flow through the unsaturated zone to the water table. Estimates of the daily contributions to recharge at the water table from diffuse and preferential flow are performed by interpreting daily time-series records of observations of water-table altitude and meteorological inputs (such as, the liquid precipitation rate, snowmelt rate, and the Potential Evapotranspiration (PET) rate). The modeling approach used here is an extension of concepts of modeling infiltration and rapid recharge originally presented in Shapiro and Day-Lewis (2021) https://doi.org/10.1029/2020WR029110 and Shapiro and others (2022) (https://doi.org/10.1111/gwat.13206). The model of infiltration and recharge to the water table is applied to daily records available at 32 U.S. Geological Survey (USGS) Climate Response Network (CRN) wells located in the Delaware River Basin (DRB) in the eastern United States from January 1, 2005, through December 31, 2021. The daily water-table altitude and the meteorological records described in the associated journal article (https://doi.org/10.1007/s10040-024-02868-x) are included as input files to the MATLAB algorithms described in this data release.

The data is derived from a Soil-Water Balance model for New Hanover, Brunswick, and Pender counties for the years 1979-2016 which is located on the USGS Model Node.

The data is derived from a Soil-Water Balance model for New Hanover, Brunswick, and Pender counties for the years 1979-2016 which is located on the USGS Model Node.

Groundwater recharge is an important part of water budget estimation and is a critical data component used in creating and calibrating groundwater flow models such as MODFLOW. Soil Water Balance Models (SWB) can be used to estimate potential groundwater recharge across spatial domains and through time. This metadata record describes an SWB archive for parts of the Coastal Plain of North Carolina, South Carolina, and Georgia, eastern United States. The model was run for various land cover build out scenarios and several downscaled climate models (SWB) The model’s pixel resolution is 609.9-meters (m) and it was run for the for the period 1979 - 2060. The SWB model executable code is 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. Due to size limitations climate data used in the production of this model are not included in this archive, URLs to locate the climate data are included.

Groundwater recharge is an important part of water budget estimation and is a critical data component used in creating and calibrating groundwater flow models such as MODFLOW. Soil Water Balance Models (SWB) can be used to estimate potential groundwater recharge across spatial domains and through time. This metadata record describes an SWB archive for parts of the Coastal Plain of North Carolina, South Carolina, and Georgia, eastern United States. The model was run for various land cover build out scenarios and several downscaled climate models (SWB) The model’s pixel resolution is 609.9-meters (m) and it was run for the for the period 1979 - 2060. The SWB model executable code is 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. Due to size limitations climate data used in the production of this model are not included in this archive, URLs to locate the climate data are included.