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Application of RUSLE and MUSLE for Prediction of Soil Loss in Small Mountainous Basin

산지소유역의 토사유실량 예측을 위한 RUSLE와 MUSLE 모형의 적용성 평가

  • Jung, Yu-Gyeong (Department of Forest Resources, Yeungnam University) ;
  • Lee, Sang-Won (Department of Forest Resources, Yeungnam University) ;
  • Lee, Ki-Hwan (Department of Forest Resources, Yeungnam University) ;
  • Park, Ki-Young (Department of Forest Resources, Yeungnam University) ;
  • Lee, Heon-Ho (Department of Forest Resources, Yeungnam University)
  • Received : 2013.10.30
  • Accepted : 2014.02.12
  • Published : 2014.03.31

Abstract

This study aims to predict the amount of soil loss from Mt. Palgong's small basin, by using influence factors derived from related models, including RUSLE and MUSLE models, and verify the validity of the model through a comparative analysis of the predicted values and measured values, and the results are as follows: The amount of soil loss were greatly affected by LS factor. In comparison with the measured value of the amount of total soil loss, the predicted values by the two models (RUSLE and MUSLE), appeared to be higher than those of the measured soil loss. Predicted values by RUSLE were closer to values of measured soil loss than those of MUSLE. However, coefficient of variation of MUSLE were lower, but two model's coefficient of variation in similar partial patterns in the prediction of soil loss. RUSLE and MUSLE, prediction soil loss models, proved to be appropriate for use in small mountainous basin. To improve accuracy of prediction of soil loss models, more effort should be directed to collect more data on rainfall-runoff interaction and continuous studies to find more detailed influence factors to be used in soil loss model such as RUSLE and MUSLE.

본 연구는 산지소유역에서 예측한 토사유실량 모형과 실측한 토사유실량을 비교함으로써 예측모형의 적용성 여부를 검토하였다. 또한, 정량적인 토사량 산정을 위하여 72개의 조사지점별로 각각의 영향인자를 산정하여 토사유실량 모형의 정확도를 높이고자 하였다. 토사유실량 산정에 영향을 주는 인자로는 LS 인자가 영향성이 가장 높은 것으로 나타났다. RUSLE, MUSLE 모형과 실측된 토사유실량의 총량을 비교한 결과, 두 모형은 실측치에 비하여 다소 높은 값을 보였으며, RUSLE 모형이 실측치와 근사한 값을 나타내었다. 조사 지점별 값의 비교에서는 MUSLE 값의 변동계수가 더 낮았으나, 값의 차이가 크지 않았다. 따라서 산지소유역에서의 RUSLE와 MUSLE 모형을 이용한 토사유실량의 예측은 적합한 것으로 보여진다. 또한, 산지소유역에서 토사유실량 예측 정도를 높이기 위해서는 강우사상에 대한 데이터 수집과 기존 토사유실 예측 모형에 사용되는 인자의 보완 및 개선에 대한 연구가 요구된다.

Keywords

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