강우자료 형태에 따른 인공신경망의 일유입량 예측 정확도 평가 = Influence of Rainfall observation Network on Daily Dam Inflow using Artificial Neural Networks

다국어 초록 (Multilingual Abstract)

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs).
Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for constructionof ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall),Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessennetwork, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that usedall station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models thatused point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The modelperformance for the ANNs model 2 in Chungju dam resulted in the R2 value of 0.94, NSE of 0.94 NSEln of 0.88 and PBIAS of –0.04 respectively.
The model-2 predictions of Soyangriver Dam with the R2 and NSE values greater than 0.94 were reasonably well agreed with the observations. Theresults of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.

참고문헌 (Reference)

1 박지창, "저수지 수위 정밀 측정에 의한 댐 유입량 자료 개선" 한국환경과학회 18 (18): 309-314, 2009

2 최승용, "입력 강우 형태에 따른 수위예측 회귀모형의 성능 비교분석" 한국방재학회 11 (11): 313-325, 2011

3 박혜경, "인공신경망을 이용한 팔당호의 조류발생 모델 연구" 한국물환경학회 29 (29): 19-28, 2013

4 최진용, "인공신경망모형을 이용한 기온기반 기준증발산량 산정" 한국농공학회 61 (61): 95-105, 2019

5 강문성, "인공신경망 이론을 이용한 단기 홍수량 예측" 한국농공학회 45 (45): 45-57, 2003

6 류용준, "웨이블렛 변환을 적용한 인공신경망에 의한 충주댐 일유입량 예측" 한국수자원학회 45 (45): 1321-1330, 2012

7 김미은, "수질 및 수문인자의 상관성을 고려한 중단기 수질예측모형 구축에 관한 연구" 한국방재학회 15 (15): 459-470, 2015

8 마샤 모라디, "수문학적 예측을 위한 딥러닝기반 인공신경망의 최적화 알고리즘 비교: 남강댐 일유출량을 사례를 중심으로" 한국방재학회 18 (18): 377-384, 2018

9 김선호, "베이지안 기법 기반의 댐 예측유입량 산정기법 개발 및 평가" 한국수자원학회 50 (50): 489-502, 2017

10 박명기, "다목적댐 유입량 예측을 위한 Recurrent Neural Network 모형의 적용 및 평가" 한국수자원학회 51 (51): 1217-1227, 2018

11 이종형, "공간 분포된 강우를 이용한 유출 해석" 한국농공학회 47 (47): 3-14, 2005

12 장대원, "강우의 공간분포를 고려한 SWAT 모형의 적용" 한국습지학회 20 (20): 94-103, 2018

13 Lee, G. S., "The prediction of runoff using artificial neural network in the Young-san River" 33 (33): 251-256, 2000

14 Hoshin Vijai Gupta, "Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration" American Society of Civil Engineers (ASCE) 4 (4): 135-143, 1999

15 LI LI, "Satellite-derived flow 시그널 및 인공신경망 모형을 활용한 임진강 유역 유출량 산정" 한국수자원학회 49 (49): 589-597, 2016

16 J.E. Nash, "River flow forecasting through conceptual models part I — A discussion of principles" Elsevier BV 10 (10): 282-290, 1970

17 Yoon, Y. N., "Hydrology-basic and application" cheongmoongak 2007

18 Kang, M. S., "Forecasting long_term steamflow from a small waterhed using artificial neural network" 43 (43): 69-77, 2001

19 François Anctil, "Evaluation of Neural Network Streamflow Forecasting on 47 Watersheds" American Society of Civil Engineers (ASCE) 10 (10): 85-88, 2005

20 A. W. MINNS, "Artificial neural networks as rainfall-runoff models" Informa UK Limited 41 (41): 399-417, 2009

21 Sung Eun Kim, "Artificial neural network ensemble modeling with exploratory factor analysis for streamflow forecasting" IWA Publishing 17 (17): 614-639, 2015

22 Kang, M. S., "Application of grey model and artificial neural networks to flood forecasting" 42 (42): 473-486, 2006

23 Kim, S. E., "A study on improvement of generalization accuracy of artificial neural network modeling using factor analysis and cluster analysis:application to flow and water quality prediction" 50 (50): 31-40, 2017

24 Raji Pushpalatha, "A review of efficiency criteria suitable for evaluating low-flow simulations" Elsevier BV 420-421 : 171-182, 2012

25 Hwang, J. S., "A classification analysis using bayesian neural network" 12 (12): 11-25, 2001