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Dataset Submitted

Weather data for SWAT simulations

Authors: Lauren Padilla
Identified On: Jan 09 2025 15:24 UTC
DOI: https://doi.org/10.7266/tn236y6n
UDI: H4.x952.000:0004
Project Information

Funded By:
National Academies of Sciences Gulf Research Program

Funding Cycle:
Healthy Ecosystems 4

Research Group:
Development of Gulf Coast Resiliency Management Plan Using Sentinel Species and Natural Infrastructure

Point of Contact

Gioia Kennedy
Environmental Defense Fund
gkennedy@edf.org

Data Collection Period
2005-01-01
to
2099-12-31
Theme keywords

chemical transport, hydrology, hydrology modeling, hydrology model, watershed, climate, climate change

Abstract:

Weather input data to run SWAT simulations based on historic (2005 to 2020) conditions and modeled predictions of future climate conditions (baseline: 2000-2019 and future periods: 2040-2059 and 2080-2099) to evaluate effects of climate change.

Leaflet Powered by Esri | Austin Community College, Texas A&M University, City of Alvin, City of Austin, City of Bryan GIS, City of Cibolo, Texas, City of Houston, City of Missouri City, City of New Braunfels, City of Wimberley, County of Williamson, DETCOG, Montgomery County, TX GIS Office, Texas Parks & Wildlife, CONANP, Earthstar Geographics, Esri, TomTom, Garmin, SafeGraph, FAO, METI/NASA, USGS, EPA, NPS, USFWS
Suggested Citation:

Lauren Padilla. Weather data for SWAT simulations. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/tn236y6n

Purpose:

In our study, we were concerned about chemicals that are persistent – present in the environment long enough to expose humans and ecosystems; mobile – readily transported from their industrial petrochemical sources in flood waters and eroded soil and sediment that are caused by stormwater and storm surge; and toxic – harm the health of humans, plants and animals who come into contact with them. Specific chemical classes of concern that carry these traits include: polycyclic aromatic hydrocarbons (PAHs), per- and polyfluoroalkyl substances (PFAS), and metals. Soil and Water Assessment Tool (SWAT) provided estimates of chemical transport in stormwater, eroded soil, and rivers, accounting for drainage from the entire Galveston Bay watershed, as boundary conditions and inputs into the Delft3D coastal model used to estimate flooding. In conjunction with Delft3D, the modeling results show where and how stormwater and flooding may affect facilities and move contaminants into vulnerable communities and ecosystems. In addition, we used the coupled model to evaluate the benefit of community master plans that include nature-based solutions in two case studies: Galena Park, TX and Texas City, TX.

Data Parameters and Units:

Station (identifier), latitude (decimal degrees), longitude (decimal degrees), elevation (meters), timestamp (yyyyddd), precipitation (mm), temperature (Celsius)

Methods:

Historic (Jan 1980-Mar 2021) daily precipitation and temperature data developed and maintained by the USDA Agricultural Research Service was the starting point for developing weather inputs to SWAT. We retrieved gap-filled, continuous daily data at 33 real ground-based NOAA GHCN weather stations in the study area from this dataset. From this station network, we created virtual station data at the centroid of every subbasin in the model domain by spatial interpolation using inverse-distance-weighted averages of the time-series data at the original 33 stations. For daily evapotranspiration and solar radiation values, we ran the Weather Generator that accompanies SWAT. To estimate effects of climate change on toxic flooding potential, we ran simulations with future forecasts of precipitation and temperature derived from an ensemble of regionally-downscaled climate models. These data came from the Coordinated Regional Climate Downscaling Experiment (CORDEX). We chose data from the RCP8.5 scenario as a high end screening estimate from three different global climate models (GFDL-ESM, HadGEM2-ES, MPI-ESM-LR) paired with two different regional weather models (RegCM4, WRF). With these data, we ran SWAT simulations for a 20 year baseline period (2000-2019) and two future periods mid (2040-2059) and late (2080-2099) century.

Provenance and Historical References:

Mearns, L.O., et al., 2017: The NA-CORDEX dataset, version 1.0. NCAR Climate Data Gateway, Boulder CO, accessed 2023, https://doi.org/10.5065/D6SJ1JCH