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

Abstract

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 ArcA-PEX. 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.

Calibrating Agro-Hydrological Model under Grazing Activities and Its Challenges and Implications

“…A variety of interfaces, such as WinAPEX [64], ArcAPEX [65], APEXEditor [61], and NTT [66][67][68], exist to set up the APEX model. The NTT interface allows users to simulate complex management scenarios via the APEX model with the required databases embedded in this interface [69,70]. NTT is a web-based interface that uses APEX 0806, which is the basis of APEXgraze.…”

“…Then, the model was parameterized using an updated parameter file (Figure 2) that includes 100 process-specific parameters plus the default 70 S-curve [63]. Twenty key parameters (Table 2) related to hydrology and sediment were selected from prior works [50,69,71]. The upper and lower bounds of these parameters, published in the APEXgraze user manual [63], are listed in Table 2, as are the initial parameters obtained from WRE1 through NTT.…”

“…Parameter's Definition Lower Upper Initial PARAM [2] Root growth-soil strength 1 2 2 PARAM [4] Water storage N leaching 0 1 0.9 PARAM [7] N fixation 0 1 0.9 PARAM [8] Soluble phosphorus runoff coefficient 10 20 20 PARAM [14] Nitrate leaching ratio 0.1 1 0.6 PARAM [15] Runoff CN residue adjustment parameter 0 0.3 0.05 PARAM [17] Soil evaporation-plant cover factor 0 0.5 0.2 PARAM [20] Runoff curve number initial abstraction 0.05 0.4 0.2 PARAM [23] Hargreaves PET equation coefficient 0.0023 0.0032 0.0032 PARAM [34] Hargreaves PET equation exponent 0.5 0.6 0.48 PARAM [42] SCS curve number index coefficient 0.3 2.5 0.8 PARAM [50] Rainfall interception coefficient 0.05 0.3 0.1 PARAM [69] Coefficient adjusting microbial activity in the topsoil layer 0.1 1 1 PARAM [70] Microbial decay rate coefficient 0.5 1.5 1 PARAM [72] Volatilization/nitrification partitioning coefficient 0.05 0.5 0.5 PARAM [18] Sediment routing exponent 1 2 1.5 PARAM [19] Sediment routing coefficient 0.0001 0.05 0 PARAM [45] Sediment routing travel time coefficient 0.5 10 5 PARAM [65] RUSLE2 transport capacity parameter 0.001 0.1 0.001 PARAM [66] RUSLE2 threshold transport capacity coefficient 1 10 1…”

“…where θ i,m is the i th discretized parameter, m so that θ i,m ∈ (θ n, m , θ x,m ); δ m = θ x, m − θ n,m , θ n and θ x are lower and upper range of m parameters so that m ∈ M, and M is set indices of 20 selected parameters (Table 2), i.e., M = [2, 4,7,8,14,15,17,18,19,20,23,34,42,45,50,69,65,66,70,72] (2)…”