Changes in climate and land-use/land-cover will impact surface water dynamics throughout the 21st century and influence global surface water availability. However, most projections of surface water dynamics focus on climate drivers using local-scale …
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.
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
Seasonally continuous long-term information on surface water and flooding extent over subcontinental scales is critical for quantifying spatiotemporal changes in surface water dynamics. We used seasonally continuous Landsat TM/ETM + data and generic random forest-based models to synoptically map the extent and dynamics of surface water and flooding (1986–2011) over the Murray–Darling Basin (MDB).
Detailed information on the spatiotemporal dynamic in surface water bodies is important for quantifying the effects of a drying climate, increased water abstraction and rapid urbanization on wetlands.