All Issue

2022 Vol.15, Issue 1
31 March 2022. pp. 1-12
Abstract
References
1
ASCE. (1993). Criteria for Evaluation of Watershed Models. Journal of Irrigation and Drainage Engineering. 119(3): 429-442. 10.1061/(ASCE)0733-9437(1993)119:3(429)
2
Beven, K. and Binley, A. (1992). The Future of Distributed Models: Model Calibration and Uncertainty Prediction. Hydrological Processes. 6(3): 279-298. 10.1002/hyp.3360060305
3
Chung, G. H., Park, H. S., Sung, J. Y., and Kim, H. J. (2012). Determination and Evaluation of Optimal Parameters in Storage Function Method using SCE-UA. Journal of Korea Water Resources Association. 45(11): 1169-1186. 10.3741/JKWRA.2012.45.11.1169
4
Chung, G. H. and Park, H. S. (2013). Modification of the Fixed Coefficient Method for the Parameter Estimation of Storage Function Method. Journal of Korea Water Resources Association. 46(1): 73-85. 10.3741/JKWRA.2013.46.1.73
5
Criss, R. E. and Winston, W. E. (2008). Do Nash Values Have Value? Discussion and Alternate Proposals. Hydrological Processes: An International Journal. 22(14): 2723-2725. 10.1002/hyp.7072
6
Duan, Q., Sorooshian, S., and Gupta, V. K. (1992). Effective and Efficient Global Optimization for Conceptual Rainfall-runoff Models. Water Resources Research. 28(4): 1015-1031. 10.1029/91WR02985
7
Duan, Q. Y., Gupta, V. K., and Sorooshian, S. (1993). Shuffled Complex Evolution Approach for Effective and Efficient Global Minimization. Journal of Optimization Theory and Applications. 76(3): 501-521. 10.1007/BF00939380
8
Gupta, H. V., Sorooshian, S., and Yapo, P. O. (1998). Toward Improved Calibration of Hydrologic Models: Multiple and Noncommensurable Measures of Information. Water Resources Research. 34(4): 751-763. 10.1029/97WR03495
9
Gupta, H., Thiemann, M., Trosset, M., and Sorooshian, S. (2003). Reply to Comment by K. Beven and P. Young on ‘Bayesian Recursive Parameter Estimation for Hydrologic Models’. Water Resources Research. 39(5): 1117. 10.1029/2002WR001405
10
Hwang, S. H., Ham, D. H., and Kim, J. H. (2012). A New Measure for Assessing the Efficiency of Hydrological Data-driven Forecasting Models. Hydrological Sciences Journal. 57(7): 1257-1274. 10.1080/02626667.2012.710335
11
Jain, S. K. and Sudheer, K. P. (2008). Fitting of Hydrologic Models: A Close Look at the Nash-Sutcliffe index. Journal of Hydrologic Engineering. 13(10): 981-986. 10.1061/(ASCE)1084-0699(2008)13:10(981)
12
Krause, P., Boyle, D. P., and Bäse, F. (2005). Comparison of Different Efficiency Criteria for Hydrological Model Assessment. Advances in Geosciences. 5: 89-97. 10.5194/adgeo-5-89-2005
13
Lee, D. E., Kim, Y. S., Yu, W. S., and Lee, G. H. (2017). Evaluation on Applicability of On/Off-line Parameter Calibration Techniques in Rainfall-runoff Modeling. Journal of Korea Water Resources Association. 50(4): 241-252. 10.3741/JKWRA.2017.50.4.241
14
Legates, D. R. and McCabe Jr, G. J. (1999). Evaluating the Use of “Goodness‐of‐fit” Measures in Hydrologic and Hydroclimatic Model Validation. Water resources research. 35(1): 233-241. 10.1029/1998WR900018
15
McCuen, R. H., Knight, Z., and Cutter, A. G. (2006). Evaluation of the Nash-Sutcliffe efficiency index. Journal of hydrologic engineering. 11(6): 597-602. 10.1061/(ASCE)1084-0699(2006)11:6(597)
16
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., and Veith, T. L. (2007). Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Transactions of the ASABE. 50(3): 885-900. 10.13031/2013.23153
17
Schaefli, B. and Gupta, H. V. (2007). Do Nash Values Have Value?. Hydrological Processes. 21: 2075-2080. 10.1002/hyp.6825
18
Shin, C. K., Cho, H. S., Jung, K. S., and Kim, J. H. (2004). Grid based Rainfall-runoff Modelling using Storage Funcion Method. Journal of Korea Water Resources Association. 37(11): 969-978. 10.3741/JKWRA.2004.37.11.969
19
Singh, J., Knapp, H. V., and Demissie, M. (2004). Hydrologic Modeling of the Iroquois River Watershed using HSPF and SWAT. ISWS CR 2004-08. Champaign, Ill.: Illinois State Water Survey.
20
Vrugt, J. A., Gupta, H. V., Bastidas, L. A., Bouten, W., and Sorooshian, S. (2003). Effective and Efficient Algorithm for Multiobjective Optimization of Hydrologic Models. Water Resources Research. 39(8): 1214. 10.1029/2002WR001746
21
Wang, Q. J. (1991). The Genetic Algorithm and Its Application to Calibrating Conceptual Rainfall-runoff Models. Water Resources Research. 27(9): 2467-2471. 10.1029/91WR01305
22
Yapo, P. O., Gupta, H. V., and Sorooshian, S. (1998). Multi-objective Global Optimization for Hydrologic Models. Journal of hydrology. 204(1-4): 83-97. 10.1016/S0022-1694(97)00107-8

Korean References Translated from the English

23
신철균, 조효섭, 정관수, 김재한 (2004). 저류함수기법을 이용한 격자기반의 강우-유출모형 개발. 한국수자원학회논문집. 37(11): 969-978. 10.3741/JKWRA.2004.37.11.969
24
이대업, 김연수, 유완식, 이기하 (2017). 온·오프라인 매개변수 보정기법에 따른 강우-유출해석 적용성 평가. 한국수자원학회논문집. 50(4): 241-252.
25
정건희, 박희성 (2013). 자류함수법의 매개변수 추정을 위한 상수고정법의 개선. 한국수자원학회논문집. 46(1): 73-85. 10.3741/JKWRA.2013.46.1.73
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정건희, 박희성, 성지연, 김현준 (2012). SCE-UA를 이용한 저류함수모형 최적 매개변수 선정 및 평가. 한국수자원학회논문집. 45(11): 1169-1186. 10.3741/JKWRA.2012.45.11.1169
Information
  • Publisher :Korean Society of Disaster and Security
  • Publisher(Ko) :한국방재안전학회
  • Journal Title :Journal of Korean Society of Disaster and Security
  • Journal Title(Ko) :한국방재안전학회 논문집
  • Volume : 15
  • No :1
  • Pages :1-12
  • Received Date :2022. 03. 14
  • Revised Date :2022. 03. 21
  • Accepted Date : 2022. 03. 25