Effects of Climate and Anthropogenic Drivers on Surface Water Area in the Southeastern United States

Abstract

Surface water is the most readily accessible water resource and provides an array of ecosystem services, but its availability and access are stressed by changes in climate, land cover, and population size. Understanding drivers of surface water dynamics in space and time is key to better managing our water resources. However, few studies estimating changes in surface water account for climate and anthropogenic drivers both independently and together. We used 19 years (2000–2018) of the newly developed Dynamic Surface Water Extent Landsat Science Product in concert with time series of precipitation, temperature, land cover, and population size to statistically model maximum seasonal percent surface water area as a function of climate and anthropogenic drivers in the southeastern United States. We fitted three statistical models (linear mixed effects, random forests, and mixed effects random forests) and three groups of explanatory variables (climate, anthropogenic, and their combination) to assess the accuracy of estimating percent surface water area at the watershed scale with different drivers. We found that anthropogenic drivers accounted for approximately 37% more of the variance in the percent surface water area than the climate variables. The combination of variables in the mixed effects random forest model produced the smallest mean percent errors (mean −0.17%) and the highest explained variance (R2 0.99). Our results indicate that anthropogenic drivers have greater influence when estimating percent surface water area than climate drivers, suggesting that water management practices and land‐use policies can be highly effective tools in controlling surface water variations in the Southeast.

Landscape Pollution Source Dynamics Highlight Priority Locations for Basin‐Scale Interventions to Protect Water Quality Under Hydroclimatic Variability

“…Weaker performance during the validation period is not surprising given that we set up the model with contemporary land use and management, and many changes have occurred in the watershed over 20 years. Within the U.S., the southeast has experienced the most rapid recent land use change, particularly forest loss to suburban sprawl (Gaines et al., 2022; Homer et al., 2020; Sanchez et al., 2020; Sleeter et al., 2018). NC, and particularly the CFRB, has some of the highest urban and suburban growth rates in the country (U.S. Census Bureau, 2020) and is undergoing agricultural intensification, notably via expansion of swine CAFOs from the 1980s through the early 1990s and ongoing growth of poultry CAFOs (Environmental Working Group & Waterkeeper Alliance, 2016; Miralha et al., 2021; Montefiore et al., 2022).…”

Landscape pollution source dynamics highlight priority locations for basin-scale interventions to protect water quality under extreme events

“…Weaker performance during the validation period is not surprising given that we set up the model with contemporary land use and management, and many changes have occurred in the watershed over 20 years. Within the U.S., the southeast has experienced the most rapid recent land use change, particularly forest loss to suburban sprawl (Gaines et al, 2022;Homer et al, 2020;Georgina M. Sanchez et al, 2020;Sleeter et al, 2018).…”

Salinization and sedimentation drive contrasting assembly mechanisms of planktonic and sediment‐bound bacterial communities in agricultural streams

“…Given the flat topography and highly altered hydrology of the MAP, delineating watersheds for specific sample sites poses significant challenges and is a current area of research for the region (Gaines et al, 2022; Yasarer et al, 2020). Thus, 12‐digit hydrologic unit code (HUC‐12) watersheds from the National Watershed Boundary (NWB) dataset were used for determining watershed characteristics for each sample location (US Geological Survey and US Department of Agriculture‐Natural Resource Conservation Service, 2013).…”

“…Given the flat topography and highly altered hydrology of the MAP, delineating watersheds for specific sample sites poses significant challenges and is a current area of research for the region (Gaines et al, 2022;Yasarer et al, 2020). Thus, 12-digit hydrologic unit code (HUC-12) watersheds from the National Watershed Boundary Although HUC-12 boundaries do not represent true watersheds for each site, we refer to HUCs as watersheds for simplicity.…”