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Lumped Arid/Semi-arid Model (LASAM) for infiltration and surface runoff

The LASAM simulates infiltration and runoff based on Layered Green & Ampt with redistribution (LGAR) model. LGAR is a model which partitions precipitation into infiltration and runoff, and is designed for use in arid or semi-arid climates. LGAR closely mimics precipitation partitioning results simulated by the famous Richards/Richardson equation (RRE), without the inherent reliability and stability challenges the RRE poses. Therefore, this model is useful when accurate, stable precipitation partitioning simulations are desired in arid or semi-arid areas. LGAR in Python (no longer supported) is available here.

LASAM is designed for use in environments where cumulative potential evapotranspiration is greater than cumulative precipitation. Because the lower boundary condition of LASAM is effectively no-flow, the model assumes that water only leaves the vadose zone via AET. This is a reasonable assumption in arid and semi arid areas. If applied in humid areas, the model domain of LASAM will likely become completely saturated.

Published papers: For details about the model please see our manuscript on LGAR (weblink).

Build and Run Instructions

Detailed instructions on how to build and run LASAM can be found here INSTALL.

• Test examples highlights
  • simulations with synthetic forcing data and unittest (see build/run).
  • simulations with real forcing data (see build/run)
  • LASAM coupling to Soil Freeze Thaw (SFT) model (see instructions)

Model Configuration File

A detailed description of the parameters for model configuration is provided here.

Calibratable parameters

A detailed description of calibratable parameters is provided here.

Nextgen Realization Files

Realization files for running LASAM (coupled/uncoupled modes) in the nextgen framework are provided here.

Getting help

For questions, please contact Ahmad (ahmad.jan(at)noaa.gov) and/or Peter (peter.lafollette(at)noaa.gov), the two main developers/maintainers of the repository.

Known issues or raise an issue

LASAM is a newly developed model and we are constantly looking to improve the model and/or fix bugs as they arise. Please see the Git Issues for known issues or if you want to suggest adding a capability or to report a bug, please open an issue.

Getting involved

See general instructions to contribute to the model development (instructions) or simply fork the repository and submit a pull request.