A biogeochemistry model was developed to examine plant gross primary productivity (GPP), net primary productivity (NPP), plant respiration, soil respiration, soil organic carbon sequestration rate and storage under scenarios of drought and normal conditions at Tidal Freshwater Forested Wetlands (TFFW) sites along the Waccamaw River and Savannah River in the Southeastern United States.

Salinity and variability of salinity in shallow waters shape living resources and habitat within Gulf of Mexico estuaries. The salinity gradient is widely recognized as foundational in maintaining biological diversity and productivity of estuaries. A clear understanding of the factors controlling salinity and variability of salinity in estuarine surface waters is essential for proper stewardship and for sustaining ecological structure and function. Salinity data are collected by numerous Federal, State, and local agencies and universities as part of routine data collection programs. We used online databases to compile salinity data in Gulf of Mexico estuaries. The primary criteria for inclusion in the compilation were a lengthy record of continuous collection with data sondes of at least hourly intervals. Stations that represented full estuarine gradients, from fresh to saline, were prioritized. Data were compiled in separate spreadsheets for each State using comma-delimited formatting. For each State, a second spreadsheet provides information on each station. A few stations started collecting salinity as early as the mid-1980s. More stations came on line by the mid- to late 1990s. Starting in the late 2000s many more stations came on line.

Model generated soil pore water salinity (psu) values under scenarios of drought and normal conditions at Tidal Freshwater Forested Wetlands (TFFW) sites along the Waccamaw River and Savannah River in the Southeastern United States.

A critical aspects of the uniqueness of coastal drought is the effects on salinity dynamics of creeks and rivers. The location of the freshwater-saltwater interface along the coast is an important factor in the ecological and socio-economic dynamics of coastal communities. Salinity is a critical response variable that integrates hydrologic and coastal dynamics including streamflow, precipitation, sea level, tidal cycles, winds, and tropical storms. The position of the interface determines the composition of freshwater and saltwater aquatic communities as well as the freshwater availability for water intakes. Many definitions of drought have been proposed, with most describing a decline in precipitation which has a negative impacts on water supply. Indices have been developed incorporating data such as rainfall, streamflow, soil moisture, groundwater levels, and snow pack. These water availability drought indices were developed for upland areas and may not be ideal for characterizing coastal drought. The availability of real-time and historical salinity datasets provides an opportunity for the development of a salinity-based coastal drought index. The challenge for the salinity data analysis is to characterize the salinity dynamics in response to drought while excluding responses attributable to the occasional and (or) periodic saltwater intrusion events. An approach similar to the Standardized Precipitation Index was modified and applied to salinity data obtained from sites in South Carolina and Georgia. Evaluation of the coastal drought index indicates that the index can be used for different estuary types, for regional comparison, and as an index for wet (high freshwater inflow) and drought conditions. This data release will provide all the supporting data for the journal article including salinity datasets (with estimated missing values) and the computed indices.

The polygon datasets were created to assist in visualizing the results of salinity modeling in Gulf of Mexico estuaries and bays. Statistical algorithms (Asquith and others, 2023) were developed to predict daily salinities for 91 salinity monitoring sites (Rodgers and Swarzenski, 2019) operated by 7 agencies in near coastal United States waters of the Gulf of Mexico. These monitoring sites are assigned to 15 salinity groups roughly corresponding to distinct bays and estuaries. The statistical algorithms facilitate the study of trends and drivers of salinity in near coastal waters. The groups polygon dataset consists of 15 polygons representing the outer boundary or hull of each of the 15 salinity groups. The site polygons dataset consists of 91 polygons—one polygon each per salinity monitoring site. The polygons were created using the Watershed Boundary Dataset, the National Hydrography Dataset, and aerial imagery. A detailed description of the polygon creation method is in the metadata processing steps. Creation of the polygons was motivated by a need to construct visual cues (maps and map animations) for testing the veracity of the statistical algorithms.

This digital dataset contains the baseline and future climate data used as the basis for analysis of current and future water supplies and demands in the Salinas and Carmel Rivers Basin Study (SCRBS). SCRBS uses a suite of integrated hydrologic models to explore impacts of future climate and socioeconomic scenarios on water supplies and demands in the basins. SCRBS considers one baseline climate scenario that represents recent historical climate conditions and five future climate scenarios that encompass the range of uncertainty in projections of future climate conditions through the end of the 21st century. The baseline scenario was developed by removing trends from an observed historical climate dataset such that the long-term monthly mean and variance over the full period of record (1931-2015) are consistent with observed historical averages over the baseline period (1980-2009). Future climate scenarios were developed by adjusting the baseline scenario to reflect projected changes in the distributions of monthly precipitation and temperature. The five future climate scenarios reflect the range of projected changes across an ensemble of statistically downscaled climate projections: Hot-Wet (HW), Warm-Wet (WW), Hot-Dry (HD), Warm-Dry (WD), and Central Tendency (CT). Analysis of future climate conditions was based on the Localized Constructed Analogues (LOCA) dataset, which includes statistically downscaled climate projections from global climate models (Pierce and others, 2014). Baseline and future climate scenarios were spatially downscaled from a native 1/16° grid to a 270-meter grid. The data set includes daily 270-meter gridded spatially distributed daily precipitation (PPT), maximum and minimum air temperature (TMX and TMN, respectively), and potential evapotranspiration (PET) from 1/1/2016 to 12/31/2100. Pierce, D. W., Cayan, D. R., and Thrasher, B. L., 2014, Statistical downscaling using Localized Constructed Analogs (LOCA): Journal of Hydrometeorology, v. 15, no. 6, p. 2558-2585, https://doi.org/10.1175/JHM-D-14-0082.1.

This digital dataset contains the baseline climate scenario data used for the Salinas and Carmel Rivers Basin Study (SCRBS). The baseline climate scenario has the climate trends removed from it. The files included in this child item are the daily 270-meter gridded spatially distributed daily precipitation (PPT), maximum and minimum air temperature (TMX and TMN, respectively), and potential evapotranspiration (PET) from 1/1/2016 to 12/31/2100.

Imputed salinities from either salinity or specific conductance observations and covariate data in data structures deemed suitable for statistical modeling of salinity in near-coastal environments of the northern Gulf of Mexico are provided for 15 salinity groups. The data herein were created by the 'covardr2formodel.R' script of 'covESTUSAL software' (Asquith and others, 2023), which represents terminal decisions on variable setup and transformations. The design ideal is data downloaded from this data release would be used in some path of “input” within statistical modeling software. Copious documentation of the decision process for data assembly is provided by Asquith and others (2023).

This dataset includes water temperature and water salinity data from continuous hydrology loggers and spot checks from a handheld water quality meter at restoration and reference sites at Willapa National Wildlife Refuge, from March 2014 to August 2015.