A New Methodology for Calibrating Apex Model Using Combined PEST and Trial-Error Approach for Simulating Surface Runoff from Small Watersheds.

Surface runoff from agricultural and pasture watersheds are the major problem in Midwestern region of USA. Field scale hydrologic, Agricultural Policy Environmental eXtender (APEX), model can be used for simulating surface runoff from small watersheds. However, improved calibration of this model is needed to implement the best management practices. The common approach is “trial and error” for calibrating the APEX model. However, this approach is time consuming, and it is difficult to explicitly assess if a “trial and error” manual calibration has reached a best-fit. This is majorly because it is conducted by running APEX manually repetitively based on researcher’s experience and discretion. In this study, the automatic calibration software Parameter Estimation (PEST) was combined with the conventional trial-and-error method, the proposed Combined PEST and Trial-Error (CPTE) approach, to improve APEX calibration. A case study was developed to verify the CPTE approach. The results based on APEX runoff simulation indicate that the CPTE approach greatly improved the calibration of APEX model. Also it can overcome: (i) weaknesses of “Trial-Error” method in terms of tediousness and subjectivity involved in the decision to end a calibration, and (ii) drawback of PEST in that it may lead to biased simulation due to ignoring specific conditions of some parameters. Coupling inverse modeling and trial-error manual method can be an efficient and effective alternative in calibrating the APEX model.