Abstract
SWIM (Surface Water Integrated Modeling) is a Julia software package for static modeling and prediction of surface water and urban flooding based on analysis of terrain topography, terrain properties, and infrastructure.
SWIM consists of a collection of algorithms for analyzing terrain, identifying watershed boundaries, and providing a better understanding of how water accumulates and moves across the landscape. Such analyses are valuable for various purposes, including water resource management, flood modeling and mitigation, and environmental planning.
The algorithms are based on the assumption of infinitesimal flow and the identification of spill points. Spill-point analyses are highly computationally efficient compared to tools based on numerical simulation, making it easy to work interactively and test out various scenarios and measures. SWIM offers unique functionality, such as simplified infiltration models for both permeable and impermeable surfaces, as well as the calculation of time series that model how
water accumulates or drains over time without resorting to computationally intensive numerical time-stepping approaches.
SWIM consists of a collection of algorithms for analyzing terrain, identifying watershed boundaries, and providing a better understanding of how water accumulates and moves across the landscape. Such analyses are valuable for various purposes, including water resource management, flood modeling and mitigation, and environmental planning.
The algorithms are based on the assumption of infinitesimal flow and the identification of spill points. Spill-point analyses are highly computationally efficient compared to tools based on numerical simulation, making it easy to work interactively and test out various scenarios and measures. SWIM offers unique functionality, such as simplified infiltration models for both permeable and impermeable surfaces, as well as the calculation of time series that model how
water accumulates or drains over time without resorting to computationally intensive numerical time-stepping approaches.