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 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.

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.

Data were collected from coastal wetlands (tidal swamps and marsh) along the Waccamaw and Savannah Rivers in South Carolina and Georgia (See Krauss et al. 2009 for additional details). Data collected include water level, porewater salinity (conductivity based), water temperature, and conductivity. First measurements began in 2004 and continued through 2016. Water level data: A network of water level recorders was established in 2004-2006 (forests) and in 2009 (marsh). Continuous hourly data were recorded using vented pressure transducers (model 138, Infinities USA, Port Orange, FL, USA) placed at the bottom of 7.6-cm diameter PVC pipes to an approximate depth of 1 m. All data were collected within the wetland and not in stream. In the data, 0 inches is approximate ground level. Porewater data: Salinity (conductivity based), temperature, and conductivity data were collected monthly from four wells per site. Wells were made of slotted 3.2-cm PVC and inserted into ground to a depth of 0.6 m. Salinity, conductivity, and water temperature were measured with a portable conductivity meter placed inside the well (Model 30, YSI Inc., Yellow Springs, OH, USA). Wells were capped and were pumped of residual water and allowed to refill prior to measurement. Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Literature: Krauss, K.W., J.A. Duberstein, T.W. Doyle, W.H. Conner, R.H. Day, L.W. Inabinette, and J.L. Whitbeck. 2009. Site condition, structure, and growth of baldcypress along tidal/non-tidal salinity gradients. Wetlands 29(2):505-519. https://doi.org/10.1672/08-77.1. Cormier, N., K.W. Krauss, W.H. Conner. 2013. Periodicity in stem growth and litterfall in tidal freshwater forested wetlands: Influence of salinity and drought on nitrogen recycling. Estuaries and Coasts 36(3):533-546. https://doi.org/10.1007/s12237-012-9505-z.

Data were collected from coastal wetlands (tidal swamps and marsh) along the Waccamaw and Savannah Rivers in South Carolina and Georgia (See Krauss et al. 2009 for additional details). Data collected include water level, porewater salinity (conductivity based), water temperature, and conductivity. First measurements began in 2004 and continued through 2016. Water level data: A network of water level recorders was established in 2004-2006 (forests) and in 2009 (marsh). Continuous hourly data were recorded using vented pressure transducers (model 138, Infinities USA, Port Orange, FL, USA) placed at the bottom of 7.6-cm diameter PVC pipes to an approximate depth of 1 m. All data were collected within the wetland and not in stream. In the data, 0 inches is approximate ground level. Porewater data: Salinity (conductivity based), temperature, and conductivity data were collected monthly from four wells per site. Wells were made of slotted 3.2-cm PVC and inserted into ground to a depth of 0.6 m. Salinity, conductivity, and water temperature were measured with a portable conductivity meter placed inside the well (Model 30, YSI Inc., Yellow Springs, OH, USA). Wells were capped and were pumped of residual water and allowed to refill prior to measurement. Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Literature: Krauss, K.W., J.A. Duberstein, T.W. Doyle, W.H. Conner, R.H. Day, L.W. Inabinette, and J.L. Whitbeck. 2009. Site condition, structure, and growth of baldcypress along tidal/non-tidal salinity gradients. Wetlands 29(2):505-519. https://doi.org/10.1672/08-77.1. Cormier, N., K.W. Krauss, W.H. Conner. 2013. Periodicity in stem growth and litterfall in tidal freshwater forested wetlands: Influence of salinity and drought on nitrogen recycling. Estuaries and Coasts 36(3):533-546. https://doi.org/10.1007/s12237-012-9505-z.

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.

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.

These data (vector and raster) were compiled for spatial modeling of salinity yield sources in the Upper Colorado River Basin (UCRB) and describe different scales of watersheds in the Upper Colorado River Basin (UCRB) for use in salinity yield modeling. Salinity yield refers to how much dissolved salts are picked up in surface waters that could be expected to be measured at the watershed outlet point annually. The vector polygons are small catchments developed originally for use in SPARROW modeling that break up the UCRB into 10,789 catchments linked together through a synthetic stream network. The catchments were used for a machine learning based salinity model and attributed with the new results in these vector GIS datasets. Although all of these feature classes include the same polygons, the attribute tables for each include differing outputs from new salinity models and a comparison with SPARROW model results from previous research. The new model presented in these datasets utilizes new predictive soil maps and a more flexible random forest function to improve on previous UCRB salinity spatial models. The raster data layers represent aspects of soils, topography, climate, and runoff characteristics that have hypothesized influences on salinity yields.

These data (vector and raster) were compiled for spatial modeling of salinity yield sources in the Upper Colorado River Basin (UCRB) and describe different scales of watersheds in the Upper Colorado River Basin (UCRB) for use in salinity yield modeling. Salinity yield refers to how much dissolved salts are picked up in surface waters that could be expected to be measured at the watershed outlet point annually. The vector polygons are small catchments developed originally for use in SPARROW modeling that break up the UCRB into 10,789 catchments linked together through a synthetic stream network. The catchments were used for a machine learning based salinity model and attributed with the new results in these vector GIS datasets. Although all of these feature classes include the same polygons, the attribute tables for each include differing outputs from new salinity models and a comparison with SPARROW model results from previous research. The new model presented in these datasets utilizes new predictive soil maps and a more flexible random forest function to improve on previous UCRB salinity spatial models. The raster data layers represent aspects of soils, topography, climate, and runoff characteristics that have hypothesized influences on salinity yields.

This model archive contains the datasets, procedures, and necessary program code used to describe the Salinas Valley Watershed Model (SVWM). The SVWM simulates the daily historical water balance and hydrologic conditions for the Salinas Valley study area including the many un-gaged tributary subdrainages in the rugged and mountainous upland areas surrounding flat-lying valley lowlands coinciding with developed areas including croplands irrigated with groundwater. The SVWM simulates the natural hydrologic system for the entire Salinas Valley watershed and adjacent coastal basins, excluding anthropogenic components such as pumping, diversions, irrigation, and reservoir operations, for the 70 years beginning October 1, 1948, and ending September 30, 2022. The SVWM uses two modeling applications; the Hydrologic Simulation Program – Fortran (HSPF, version 12.4; U.S. Environmental Protection Agency, 2000) to simulate the natural hydrologic system (Bicknell and others., 2005) and the Basin Characterization Model (BCM; Flint and others, 2021) to develop spatially distributed, historical climate inputs for HSPF. The HSPF application simulates the daily surface water and shallow subsurface water storage and flow processes, including interception storage and evaporation on vegetation, surface retention storage and evaporation, pervious land soil water storage and evapotranspiration, runoff from impervious and pervious land areas, streamflow, recharge from pervious land areas, and recharge from streamflow seepage. Climate inputs developed using the BCM are daily precipitation, daily maximum and minimum air temperature, and daily potential evapotranspiration (PET) (Hevesi and others, 2022). SVWM parameters were estimated using geospatial data and then adjusted by trial-and-error fitting of simulated daily streamflow to long-term records of observed streamflow at 29 U.S. Geological Survey stream gages (U.S. Geological Survey, 2016) and to estimated daily surface water inflows to Nacimiento and San Antonio Reservoirs (Henson and others, 2022a). The trial-and-error calibration provided a good match between simulated and observed daily, monthly, mean-monthly, and annual streamflow. The simulated output components from the SVWM include evapotranspiration, land area runoff (overland flow, interflow, baseflow), recharge, and groundwater recharge for the 690 HRUs, as well as streamflow and stream seepage losses for the 690 stream reaches connecting the HRUs.