Modeling of Phosphorus Loads From Florida Sugarcane Farms Using Ontology-Based Simulation.

Increasing phosphorus (P) loads to naturally oligotrophic ecosystems through surface runoff and/or artificial drainage from agricultural lands have been identified as one of sources to degrade surface water quality by accelerating eutrophication and have altered ecosystem structure by decreasing biodiversity since mid-20th century. Such deterioration of natural ecosystems has been observed in the Everglades Protection Area (EPA, ~8,250 km²) where P is accumulated partly due to P-enriched drainage from the Everglades Agricultural Area (EAA). Various approaches have been made to assess the effect of different best management practices on the P loads, including mathematical modeling that can reduce the costs for future monitoring programs.

Recently, we developed a new modeling environment where soil-plant-nutrient processes are represented as database objects in an ontology-based simulation (OntoSim) and have been successfully applied to simulate sub-irrigation and open ditch drainage commonly managed on sugarcane farms in the EAA (OntoSim-Sugarcane). Our aim was to pursue further model calibration and validation of P processes such as sugarcane P uptake and soil P mineralization/immobilization so that P loads from farms in the EAA can be simulated.

We calibrated (1999-2000) and validated (2001-2002) the OntoSim-Sugarcane model using a 4-year record (1999-2002) of discharge water volumes and P concentrations in the discharge waters at one farm basin (1,244 ha) in the EAAwhere sugarcane-vegetable rotations are prominent. Complimentary data on soil properties, canal levels, and rainfall were used. By assembling the information into the model, monthly P loads were simulated and the fits between simulated and observed ones were quantified using the Nash-Sutcliffe efficiency (NSE) coefficient. Based on >0.60 of NSE obtained from model calibration and validation, we can conclude that OntoSim-Sugarcane is able to simulate monthly P loads within the farm; thus it has potential to be used by Florida farmers as a decision support tool to reduce P loads from the EAA to EPA.