A team of scientists developed a new mathematical formulation that enables models to predict water runoff in complex landscapes.
Understanding how surface and subsurface waters can be affected by drought, fire, warming, and increased human demand requires computer models that can represent complex environments. Predictions are especially difficult for what scientists call patterned land cover, which include a pattern of raised polygons of organic-rich soil and vegetation with surface water between the polygons.
The research team’s new method may to be able to accurately predict runoff in these polygon landscapes.
The team claims that their new mathematical formulation appropriately captures the complexity of polygonal landscapes and their underlying soil structure. If it’s indeed effective, the formulation could also advance researchers’ ability to predict how surface and subsurface water flow will change over time in any watershed. Researchers and local stakeholders could use these predictions to help make decisions about the use of water from a given watershed.
The multi-institutional team implemented its method in the Department of Energy’s (DOE) Advanced Terrestrial Simulator (ATS) code. This new feature of ATS allows scientists to accurately predict how water flows both below and on the surface of landscapes, including how it partitions between groundwater and surface runoff to streams.
Researchers derived and tested this formulation against a series of benchmark problems and found it to be significantly more accurate in representing polygonal landscapes with convoluted soil structures than models previously used to represent these complex landscapes.
This, and other advances in ATS, now allow scientists to more accurately simulate surface and subsurface water flow in complex landscapes, including cases of post-fire storms on patchy burn scars and variable depth of bedrock in a given spatial area. This new modeling capability provides a significant advance toward better predictions of water availability and quality in a watershed.
