Discussions about calibrating APEX-Paddy model using monitoring data from the experiment field in Iksan, South Korea = Discussions about calibrating APEX-Paddy model using monitoring data from the experiment field in Iksan, South Korea

다국어 초록 (Multilingual Abstract)

The Agricultural Policy/Environmental eXtender (APEX) models have been developed to assess a wide variety of agricultural water resource, water quality, and other environmental problems at the field scale as well as more complex multi-subarea landscapes, whole farms, and watersheds. A key component of APEX application has been modified by National Academy of Agricultural Sciences, Wanju, Korea, named APEX-Paddy for simulating water quality with considering pertinent paddy management practices, such as puddling and flood irrigation management. Calibration and validation are an inevitable step prior to any model application, there is a need for a simple procedure to assess whether or not a parameter should be adjusted for calibration. However, a limited study has been done to evaluate the ability of APEX-paddy to simulate the impact of multiple management scenarios on nutrients loss. The objective of this study is to provide a rationale for a hierarchical selection of parameters to adjust during calibration those are most uncertain to that are least uncertain. The observation data of six experimental fields at Iksan in South Kora was used in calibration and evaluation process during 2013-2015. The APEX autocalibration tool (APEX-CUTE) was used for model calibration, sensitivity and uncertainty analysis. Four quantitative statistics, the coefficient of determination (R2), Nash-Sutcliffe (NSE), percent bias (PBIAS) and root mean square error (RMSE) were used in model evaluation. In this study, the hydrological process of the modified model, APEX-Paddy, is being calibrated and tested in predicting runoff discharge rate and nutrient yield. Field-scale calibration and validation procedures are described with an emphasis on important calibration parameters and guidance regarding logical sequences of calibration steps. Three quantitative statistics, Nash-Sutcliffe(NSE), percent bias(PBIAS) and root mean square error(RMSE) be used in model evaluation. This study helps to understand the calibration and validation direction is further provided for applications of APEX-Paddy at the field scales.