Surface water flow in landscape models: 1. Everglades case study

Many landscape models require extensive computational effort using a large array of grid cells that represent the landscape. The number of spatial cells may be in the thousands and millions, while the ecological component run in each of the cells to account for landscape dynamics is often process based and fairly complex. To compensate for the increased computational complexity of the model there is a tendency to simplify the hydrologic component that fluxes material horizontally across the landscape. Instead of full scale hydrologic models based on stable implicit schemes, computationally simpler explicit algorithms are incorporated and run with quite large time steps. As a result some fairly inadequate behavior may be observed, especially when the temporal and spatial steps are modified without due care. We illustrate these problems with a series of runs performed using the Everglades Landscape Model (Southern Florida, USA), that covers an area of more than 10 000 km2. Several algorithms for hydrologic fluxing are compared in terms of their computational complexity and stability. We argue that a compromise can be drawn by supplementing the explicit modeling scheme with a series of additional checks and conditions that provide for model stability, and with some empirical assumptions that allow the model to operate over a sufficiently large range of temporal and spatial scales.