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Analysis of the Effect of Objective Functions on Hydrologic Model Calibration and Simulation (목적함수에 따른 매개변수 추정 및 수문모형 정확도 비교·분석)

  • Lee, Gi Ha;Yeon, Min Ho;Kim, Young Hun;Jung, Sung Ho
    • Journal of Korean Society of Disaster and Security
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    • v.15 no.1
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    • pp.1-12
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    • 2022
  • An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.

Diagnosis of Nitrogen Content in the Leaves of Apple Tree Using Spectral Imagery (분광 영상을 이용한 사과나무 잎의 질소 영양 상태 진단)

  • Jang, Si Hyeong;Cho, Jung Gun;Han, Jeom Hwa;Jeong, Jae Hoon;Lee, Seul Ki;Lee, Dong Yong;Lee, Kwang Sik
    • Journal of Bio-Environment Control
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    • v.31 no.4
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    • pp.384-392
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    • 2022
  • The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R2: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

Learning Curve of the Direct Anterior Approach for Hip Arthroplasty (직접전방 접근법을 통한 인공 고관절 치환술의 학습곡선)

  • Ham, Dong Hun;Chung, Woo Chull;Choi, Byeong Yeol;Choi, Jong Eun
    • Journal of the Korean Orthopaedic Association
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    • v.55 no.2
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    • pp.143-153
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    • 2020
  • Purpose: To evaluate the timing of the improvement in surgical skills of the direct anterior approach for hip arthroplasty through an analysis of the clinical features and learning curve in 58 cases. Materials and Methods: From November 2016 to November 2018, 58 patients, who were divided into an early half and late half, and underwent hip arthroplasty by the direct anterior approach, were enrolled in this retrospective study. The operation time and complications (fracture, lateral femoral cutaneous nerve injury, heterotopic ossification, infection, and dislocation) were assessed using a chi-square test, paired t-test, and cumulative sum (CUSUM) test. Results: The mean operation times in total hip arthroplasty (26 cases) and bipolar hemi-arthroplasty were 132.1 minutes and 79.7 minutes, respectively, demonstrating a significant difference between the two groups. CUSUM analysis based on the results revealed breakthrough points of the operation time, decreasing to less than the mean operation time because of the 16th case in total hip arthroplasty and 14th case in bipolar hemiarthroplasty. Complications were encountered in the early phase and late phase: five cases of fractures in the early phase, no case in the late phase; eight and two cases of lateral femoral cutaneous nerve injury, respectively; three and two cases of heterotopic ossification, respectively; and one case of dislocation, one case of infection and three cases of others in the early phase. The CUSUM chart for the fracture rate during operation in the early phase revealed the following: five cases fracture (17.2%) in the early phase and no case in the late phase (0%). This highlights the learning curve and the need for monitoring the inadequacy of operation based on the complications. Conclusion: Hip arthroplasty performed by the direct anterior approach based on an anatomical understanding makes it difficult to observe the surgical field and requires a learning curve of at least 30 cases.

Optimization and Development of Prediction Model on the Removal Condition of Livestock Wastewater using a Response Surface Method in the Photo-Fenton Oxidation Process (Photo-Fenton 산화공정에서 반응표면분석법을 이용한 축산폐수의 COD 처리조건 최적화 및 예측식 수립)

  • Cho, Il-Hyoung;Chang, Soon-Woong;Lee, Si-Jin
    • Journal of Korean Society of Environmental Engineers
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    • v.30 no.6
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    • pp.642-652
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    • 2008
  • The aim of our research was to apply experimental design methodology in the optimization condition of Photo-Fenton oxidation of the residual livestock wastewater after the coagulation process. The reactions of Photo-Fenton oxidation were mathematically described as a function of parameters amount of Fe(II)($x_1$), $H_2O_2(x_2)$ and pH($x_3$) being modeled by the use of the Box-Behnken method, which was used for fitting 2nd order response surface models and was alternative to central composite designs. The application of RSM using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal(%) of livestock wastewater and test variables in coded unit: Y = 79.3 + 15.61x$_1$ - 7.31x$_2$ - 4.26x$_3$ - 18x$_1{^2}$ - 10x$_2{^2}$ - 11.9x$_3{^2}$ + 2.49x$_1$x$_2$ - 4.4x$_2$x$_3$ - 1.65x$_1$x$_3$. The model predicted also agreed with the experimentally observed result(R$^2$ = 0.96) The results show that the response of treatment removal(%) in Photo-Fenton oxidation of livestock wastewater were significantly affected by the synergistic effect of linear terms(Fe(II)($x_1$), $H_2O_2(x_2)$, pH(x$_3$)), whereas Fe(II) $\times$ Fe(II)(x$_1{^2}$), $H_2O_2$ $\times$ $H_2O_2$(x$_2{^2}$) and pH $\times$ pH(x$_3{^2}$) on the quadratic terms were significantly affected by the antagonistic effect. $H_2O_2$ $\times$ pH(x$_2$x$_3$) had also a antagonistic effect in the cross-product term. The estimated ridge of the expected maximum response and optimal conditions for Y using canonical analysis were 84 $\pm$ 0.95% and (Fe(II)(X$_1$) = 0.0146 mM, $H_2O_2$(X$_2$) = 0.0867 mM and pH(X$_3$) = 4.704, respectively. The optimal ratio of Fe/H$_2O_2$ was also 0.17 at the pH 4.7.