Automatic calibration of a hydrologic model for simulating groundwater table fluctuations on farms in the everglades agricultural area of south Florida
The Shuffled Complex Evolution—Universal Algorithm (SCE-UA) is an automatic calibration algorithm that has shown success in finding a globally optimum objective function with more efficiency than other methods. We incorporated the SCE-UA into our novel modeling environment, utilizing an ontology-based simulation (OntoSim-Sugarcane) framework adapted to analyze groundwater table (WT) fluctuations and drainage practices on four farm basins in the Everglades Agricultural Area of south Florida. Utilizing two water years (WY96–97) of farm WT fluctuations observed at a portion (<16 ha) of each farm basin, two parameters —lateral hydraulic conductivities of soil profile and vertical hydraulic conductivity of underlying limestone—were automatically calibrated. Regardless of farms, the best parameter sets that minimize the objective function of daily root mean square error could be found after 1500 simulation runs. The quality of matching simulated to observed values of farm WT were further assessed by the Nash–Sutcliffe efficiency coefficient (NSE). The NSE ranged from 0.38 to 0.75 (calibration period, WY96–97) and 0.10 to 0.76 (validation period, WY98–99) on all four farms. These results indicate that this coupling strengthens the capability of OntoSimSugarcane to model hydrology by objectively finding the best parameter sets.
| Main Authors: | , , , |
|---|---|
| Format: | Journal Article biblioteca |
| Language: | English |
| Published: |
Wiley
2014-10
|
| Subjects: | automatic calibration, hydrologic model, groundwater table management, everglades agricultural area, |
| Online Access: | https://hdl.handle.net/10568/68417 http://soils.ifas.ufl.edu/faculty/grunwald/home/PDFs/Kwon%20et%20al%202014%20Irrig%20and%20Drain.pdf https://doi.org/10.1002/ird.1822 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The Shuffled Complex Evolution—Universal Algorithm (SCE-UA) is an automatic calibration algorithm that has shown success
in finding a globally optimum objective function with more efficiency than other methods. We incorporated the SCE-UA into our
novel modeling environment, utilizing an ontology-based simulation (OntoSim-Sugarcane) framework adapted to analyze groundwater
table (WT) fluctuations and drainage practices on four farm basins in the Everglades Agricultural Area of south Florida.
Utilizing two water years (WY96–97) of farm WT fluctuations observed at a portion (<16 ha) of each farm basin, two parameters
—lateral hydraulic conductivities of soil profile and vertical hydraulic conductivity of underlying limestone—were automatically
calibrated. Regardless of farms, the best parameter sets that minimize the objective function of daily root mean square error could
be found after 1500 simulation runs. The quality of matching simulated to observed values of farm WT were further assessed by the
Nash–Sutcliffe efficiency coefficient (NSE). The NSE ranged from 0.38 to 0.75 (calibration period, WY96–97) and 0.10 to 0.76
(validation period, WY98–99) on all four farms. These results indicate that this coupling strengthens the capability of OntoSimSugarcane
to model hydrology by objectively finding the best parameter sets. |
|---|