The Effects of Climate and Human Drivers on Changes in Surface Water in the Southeastern United States

Abstract

Water stress is a global concern as a changing climate leads to variations in weather patterns and agricultural and urban areas continue to use water-intensive practices. Understanding spatial and temporal factors of surface water dynamics is key to better managing our resources and limiting the effects of water stress. However, many of the models we currently have for projecting changes in surface water do not account for human drivers such as land cover change or land use intensity. In this study, we assessed how different climate and anthropogenic drivers affect the variability of surface water in the Southeastern United States, an area that has experienced more land cover change than any other region in the country. We used the newly developed Dynamic Surface Water Extent (DSWE) Landsat Science Product from the U.S. Geological Survey to quantify surface water in the region for a time period of over 30 years. We used two linear mixed effect models with climate and anthropogenic variables (precipitation and temperature standardized anomalies, and percent of land cover types and population density respectively) as the fixed effects and the 8-digit Hydrologic Unit Code boundaries as the random effects. One model used only climate variables to estimate surface water and the other used both climate and anthropogenic variables. Our preliminary results show that the fixed effects in the second model described over 50% more of the variance in surface water than the fixed effects in the first model. These results indicate that human drivers such as land cover change and population density have more direct influence on estimating surface water than climate drivers alone. Because human drivers can be more easily managed by decision makers than climate drivers, we can infer from our results that water management practices and land use policies can be highly effective tools in adapting to and mitigating the effects of water stress.

Mollie D. Gaines

PhD Candidate

I am a PhD student with the Center for Geospatial Analytics at North Carolina State University.

Mirela G. Tulbure

Professor

I am an Associate Professor with the Center for Geospatial Analytics at North Carolina State University (NCSU).

Vini Perin

PhD Student

My research interests include surface water, agriculture, irrigation, remote sensing and hydrological modeling.