Application of the Precipitation-Runoff Modeling System (PRMS) in the Apalachicola-Chattahoochee-Flint River Basin in the southeastern United States

Abstract

For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1-888-ASK-USGS.For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprodTo order this and other USGS information products, visit http://store.usgs.gov Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner. AbstractA hydrologic model of the Apalachicola-ChattahoocheeFlint River Basin (ACFB) has been developed as part of a U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center effort to provide integrated science that helps resource managers understand the effect of climate change on a range of ecosystem responses. The hydrologic model was developed as part of the Southeast Regional Assessment Project using the Precipitation Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, and land use on basin hydrology. The ACFB PRMS model simulates streamflow throughout the approximately 50,700 square-kilometer basin on a daily time step for the period 1950-99 using gridded climate forcings of air temperature and precipitation, and parameters derived from spatial data layers of altitude, land cover, soils, surficial geology, depression storage (small water bodies), and data from 56 USGS streamgages. Measured streamflow data from 35 of the 56 USGS streamgages were used to calibrate and evaluate simulated basin streamflow; the remaining gage locations were used for model delineation only. The model matched measured daily streamflow at 31 of the 35 calibration gages with Nash-Sutcliffe Model Efficiency Index (NS) greater than 0.6. Streamflow data for some calibration gages were augmented for regulation and water use effects to represent more natural flow volumes. Time-static parameters describing land cover limited the ability of the simulation to match historical runoff in the more developed subbasins.Overall, the PRMS simulation of the ACFB provides a good representation of basin hydrology on annual and monthly time steps. Calibration subbasins were analyzed by separating the 35 subbasins into five classes based on physiography, land use, and stream type (tributary or mainstem). The lowest NS values were rarely below 0.6, whereas the median NS for all five classes was within 0.74 to 0.96 for annual mean streamflow, 0.89 to 0.98 for mean monthly streamflow, and 0.82 to 0.98 for monthly mean streamflow. The median bias for all five classes was within -4.3 to 0.8 percent for annual mean streamflow, -6.3 to 0.5 percent for mean monthly streamflow, and -9.3 to 1....

Efficient Wetland Surface Water Detection and Monitoring via Landsat: Comparison with in situ Data from the Everglades Depth Estimation Network

“…Many comparisons of water detection indices across a range of environments [21,[24][25][26][27]29,57] have demonstrated the utility of MNDWI as a relatively strong performing metric. Previous research aimed at detecting open water and vegetated wetland environments in central Georgia (GA), USA, also found MNDWI to be an effective index for various hydrologic modeling purposes [58][59][60]. In the GA studies, surface extent was estimated either by using MNDWI as an input to CART or through the subjective selection of thresholds on MNDWI based on ancillary data and personal knowledge of the study areas.…”

Towards simplification of hydrologic modeling: identification of dominant processes

“…Figure 5c shows the most dominant process by HRU for the ApalachicolaChattahoochee-Flint River watershed in the southeastern US. This watershed has been the subject of previous PRMS modeling studies (LaFontaine et al, 2013). When using this information at a finer resolution, it shows that evapotranspiration is the most dominant process watershed wide, but with pockets of HRUs in the northern part of the watershed where runoff is the most dominant and a pocket in the southern part of the watershed where infiltration is most dominant.…”

“…Assign appropriate ranges for the 35 calibration parameters (Markstrom et al, 2015;as in LaFontaine et al, 2013). These are shown in Table 1. 2.…”

Evaluation of Statistically Downscaled GCM Output as Input for Hydrological and Stream Temperature Simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)

“…Therefore, evaluating streamflow on a daily basis may not be appropriate. This known limitation in the predictive capability of models using the gridded forcings to reproduce measured streamflow magnitudes and timing must be considered when using these results (Mannshardt-Shamseldin et al 2010;LaFontaine et al 2013). Although other climate forcings could have been used to better simulate basin hydrology (i.e., nongridded station data or finer-resolution gridded inputs), the GSD dataset was selected as it provided coverage of the conterminous United States and a consistent framework for all components of the SERAP.…”

“…The USGS PRMS was used to simulate and evaluate the effects of various combinations of precipitation, climate, and land use on watershed response in the ACFB and is documented in LaFontaine et al (LaFontaine et al 2013). PRMS is a modular, deterministic, distributed-parameter, physical-process watershed model used to simulate the generation of streamflow by process algorithms that are based on physical laws or empirical relations with measured or estimated characteristics ( Figure 3).…”