Comparisons of RDII Predictions Using the RTK-based and Regression Methods

RTK 방법 및 회귀분석 방법을 이용한 RDII 예측 결과 비교

  • Received : 2016.01.20
  • Accepted : 2016.03.21
  • Published : 2016.04.15


In this study, the RDII predictions were compared using two methodologies, i.e., the RTK-based and regression methods. Long-term (1/1/2011~12/31/2011) monitoring data, which consists of 10-min interval streamflow and the amount of precipitation, were collected at the domestic study area (1.36 km2 located in H county), and used for the construction of the RDII prediction models. The RTK method employs super position of tri-triangles, and each triangle (called, unit hydrograph) is defined by three parameters (i.e., R, T and K) determined/optimized using Genetic Algorithm (GA). In regression method, the MovingAverage (MA) filtering was used for data processing. Accuracies of RDII predictions from these two approaches were evaluated by comparing the root mean square error (RMSE) values from each model, in which the values were calculated to 320.613 (RTK method) and 420.653 (regression method), respectively. As a results, the RTK method was found to be more suitable for RDII prediction during extreme rainfall event, than the regression method.


Rainfall-Derived Inflow and Infiltration(RDII);Regression Method;RTK Method;Unit Hydrograph


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Grant : 차세대 에코이노베이션기술개발사업

Supported by : 환경부