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- Title
Effects of Climate and Anthropogenic Drivers on Surface Water Area in the Southeastern United States.
- Authors
Gaines, Mollie D.; Tulbure, Mirela G.; Perin, Vinicius
- 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. Plain Language Summary: People and the environment rely on water to exist and thrive, especially water on the Earth's surface because that is the easiest place to get it. The amount of surface water and where it is located is changing with the climate and changes in people's water use, and our need for it is increasing. To plan ahead for future water needs, we need to better understand how the climate and people are changing surface water patterns both separately and together. To help improve our understanding of these changes, we modeled the amount of surface water in three different ways. First, we modeled based on climate data (like temperature and precipitation); second, based on human data (like land use and population); and third, based on both climate and human data together. We found that we could best model the amount of surface water if we used both climate and human data together, and that human data can explain a lot of the changes in the amount of surface water. These results mean that we can work to control changes in the amount of surface water by controlling human actions through planning and policies. Key Points: We developed top‐down data‐driven models to estimate percent surface water area based on Landsat imagery and climate and human driversCompared to estimates based on climate and human drivers independently, combining them reduces percent surface water area estimation errorForest‐dominated land cover was the most influential explanatory variable to estimate percent surface water area across all our variables
- Subjects
UNITED States; SURFACE area; SURFACE of the earth; RANDOM effects model; LAND cover; RANDOM forest algorithms; EMISSION inventories; PLAINS
- Publication
Water Resources Research, 2022, Vol 58, Issue 3, p1
- ISSN
0043-1397
- Publication type
Article
- DOI
10.1029/2021WR031484