Comparing the Effects of Inputs for NTT and ArcAPEX Interfaces on Model Outputs and Simulation Performance

摘要

The Agricultural Policy/Environmental eXtender (APEX) model has five different interfaces used to process and build simulation projects. These interfaces utilize different input databases that lead to different model default values. These values can result in different hydrologic, crop growth, and nutrient flow model outputs. This study compared structural and input value differences of the ArcAPEX and Nutrient Tracking Tool (NTT) interfaces. Long-term, water quality data from the Rock Creek watershed, located in Ohio were used to determine the impact of the differences on computation time, parameter sensitivity, and streamflow, total nitrogen (TN), and total phosphorus (TP) simulation performance. The input structures were the same for both interfaces for all files except soils, where NTT assigns three soil files per field, rather than a single one in ArcAPEX. As a result, computation times were three times as long for NTT as for ArcAPEX. There were twelve sensitive parameters in both cases, but the order of sensitivity was different. Both interfaces simulated streamflow well, but ARCAPEX simulated evapotranspiration, TN, and TP better than NTT, while NTT simulated crop yields better than ArcAPEX. However, none of the models met all of the performance criteria for either interface. Therefore, more work is needed to ensure models are properly calibrated before being used for scenario analysis. While it is acceptable for the values to be different from the SSURGO database, there is no documentation explaining the rationale for the modifications from the original source. This is one of the examples that highlights lack of detailed documentation that would be useful to model users. Overall, the results indicate that different interfaces lead to different model simulation results and, therefore, the authors recommend users specify the interface used and any modifications made to the associated databases when reporting model results.