[논문]국내 논필지 모니터링 자료를 이용한 APEX-Paddy 모델 적용성 평가

모하마드 캄루자먼; 조재필; 최순군; 송정헌; 송인홍; 황세운

doi:10.5389/ksae.2020.62.1.001

국내 논필지 모니터링 자료를 이용한 APEX-Paddy 모델 적용성 평가
Evaluating the Performance of APEX-Paddy Model using the Monitoring Data of Paddy Fields in Iksan, South Korea 원문보기

한국농공학회논문집 = Journal of the Korean Society of Agricultural Engineers, v.62 no.1, 2020년, pp.1 - 16

모하마드 캄루자먼 (Department of Agricultural Engineering, Gyeongsang National University) , 조재필 (Convergence Center for Watershed Management, Integrated Watershed Management Institute (IWMI)) , 최순군 (Climate Change and Agro-Ecology Division, Department of Agricultural Environment, National Academy of Agricultural Science, RDA) , 송정헌 (Department of Agricultural and Biological Engineering & Tropical Research and Education Center, University of Florida) , 송인홍 (Department of Rural Systems Engineering, Research Institute of Agriculture and Life Sciences, Seoul National University) , 황세운 (Department of Agricultural Engineering, Institute of Agriculture and Life Science, Gyeongsang National University)

초록
AI-Helper

APEX 모형은 다양한 영농 활동의 토양과 물환경에 대한 영향을 필지 및 유역 규모로 평가하기 위해 개발된 모형이다. 최근 APEX의 주요 기작을 바탕으로 논에서의 수도작 운영에 따른 물수지, 양분 유출에 대한 모의가 가능하도록 한 APEX-Paddy가 고안된 바 있다. 본 연구에서는 익산 지역의 논 시험포 모니터링 자료를 이용하여 APEX-Paddy 모형의 적용성을 평가하고자 하였다. 2013년과 2014년의 논 유출량과 부하량 자료를 수집하고 자동보정 툴 APEX-CUTE 4.1과 추가적 수동보정을 통해 모형의 모의성능을 검토하고 한계점을 고찰하였다. 연구결과, 논의 물수지와 질소 배출부하량은 대체로 합리적인 수준의 모의성능을 보이는 한편 유사량과 인 배출부하량 모의에 있어 논의 담수상태 유사배출 기작에 대한 고려가 미흡하여 모의성능에 한계가 있는 것으로 분석되었으며 원인에 대해 고찰하였다. 더불어 자동보정 툴의 적용에 있어 매개변수 민감도를 바탕으로 한 수동보정 결과보다 정확도가 다소 떨어지는 경향을 보여 그 활용에 유의가 필요한 것으로 판단되었다.

Abstract ▼ AI-Helper

The APEX model has been developed for assessing agricultural management efforts and their effects on soil and water at the field scale as well as more complex multi-subarea landscapes, whole farms, and watersheds. Recently, a key component of APEX application, named APEX-Paddy, has been modified for simulating water quality by considering paddy rice management practices. In this study, the performance of the APEX-Paddy model was evaluated using field data at Iksan experimental paddy sites in Korea. The discharge and pollutant load data during 2013 and 2014 were used to both manually and automatically calibrate the model. The APEX auto-calibration tool (APEX-CUTE 4.1) was used for model calibration and sensitivity analysis. Results indicate that APEX-Paddy reasonably performs in predicting runoff discharge rate and nitrogen yield. However, sediment and phosphorus yield is not correctly predicted due to the limitation of model schemes. With APEX-Paddy, the performance in reproducing the discharge and nitrogen yield is found to be a satisfactory level after manual calibration. The manually calibrated model performed better than the automatically calibrated model in nearly all comparisons. For runoff, manual calibration reduced PBIAS while R2 and NSE values of the automatically calibrated model were the same as the manual calibration. For T-N, NSE and PBIAS were reduced when using manual calibration, whereas R2 value was the same as manual calibration. The limitation of the APEX-Paddy model for predicting sediment, as well as the phosphorous yield, was discussed in this study.

주제어

표/그림 (15)

그림 Fig. 1 Location of experimental field and weather station
그림 Fig. 2 Weir height in different management practices
표 Table 1 Typical paddy management schedule of the Iksan field
그림 Fig. 3 Schematic diagram of the Agricultural Policy/Environmental eXtender (APEX) ‐Paddy algorithm (Modified from Choi et al. 2017)
그림 Fig. 4 Apex-Paddy model simulated (a) water loss, and (b) nutrients loss
표 Table 2 Recommended statistics for the watershed model (Moriasi et al. 2007)
그림 Fig. 5 The sensitivity of discharge influential parameters
표 Table 3 Sensitive parameters considered for calibration of the model
그림 Fig. 6 The sensitivity of nitrogen yield influential parameters
그림 Fig. 7 The sensitivity of phosphorus yield influential parameters
그림 Fig. 8 Observed and simulated daily (a) discharge, (b) nitrogen yield, (c) sediment yield, and (d) phosphorus over the manual calibration period of the paddy the growing season in 2013, and 2014
표 Table 4 Performance statistics for the manually calibrated APEX-Paddy model, including the coefficient of determination (R²), Nash Sutcliffemodel efficiency equation (NSE), and Percent Bias (PBIAS) (Individual year and entire calibration period)
표 Table 5 Performance statistics for the Auto-calibrated APEX-Paddy model, including the coefficient of determination (R²), Nash Sutcliffe model efficiency equation (NSE), and Percent Bias (PBIAS) (Individual year and entire calibration period)
그림 Fig. 9 Observed and simulated daily (a) discharge, (b) nitrogen yield, (c) sediment yield, and (d) phosphorus over the automatic calibration period of the paddy the growing season in 2013, and 2014
그림 Fig. 10 (a) Rainfall pattern, (b) Sediment inside the paddy field and sediment yield

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