• 농업과학연구
• /
• 제38권1호
• /
• pp.129-143
• /
• 2011

In this study, to select the incoming solar radiation equation which is most suitable for the estimation of Penman evaporation, 12 incoming solar radiation equations were selected. The Penman evaporation rates were estimated using 12 selected incoming solar radiation equations, and the estimated Penman evaporation rates were compared with measured pan evaporation rates. The monthly average daily meteorological data measured from 17 meteorological stations (춘천, 강능, 서울, 인천, 수원, 서산, 청주, 대전, 추풍령, 포항, 대구, 전주, 광주, 부산, 목포, 제주, 진주) were used for this study. To evaluate the reliability of estimated evaporation rates, mean absolute bias error(MABE), root mean square error(RMSE), mean percentage error(MPE) and Nash-Sutcliffe equation were applied. The study results indicate that to estimate pan evaporation using Penman evaporation equation, incoming solar radiation equation using meteorological data such as precipitation, minimum air temperature, sunshine duration, possible duration of sunshine, and extraterrestrial radiation are most suitable for 11 study stations out of 17 study stations.

• 대한토목학회논문집
• /
• 제29권1B호
• /
• pp.47-62
• /
• 2009

지구가 온난화됨에 따라서 발생되는 기후변화는 증발과 같은 수문순환과정에 직접적인 영향을 주는 것으로 보고된 바 있다(IPCC, 2001). 또한 지역특성에 따른 기후변화가 증발에 미치는 영향을 파악하는 것은 필요하다. 본 연구에서는 지리지형적 특성을 고려하면서, 연별 pan 증발량을 모의하기 위한 6개 증발식들의 적용성을 비교 검토하였다. 이를 위하여, 전국 56개 연구지역을 지리지형적 특성(도시화율, 해안근접성, 지역 평균경사, 수역면적)에 따라서 분류하고, 기존에 제안된 증발식(Penman, Kohler-Nordenson-Fox(KNF), DeBruin-Keijman, Priestley-Taylor, Hargreaves, Rohwer)을 적용하여 pan 증발량과 비교 검토하였다. 또한 Penman 증발식의 풍속함수를 보정하고 보정된 식의 적용성을 검증하였다. 연구결과에서 KNF식은 가장 pan 증발량과 유사한 결과를 보여서 8.72%의 상대오차를 보였고, 그 다음으로 Penman 식은 8.75%의 상대오차를 보였으며, 반면에 질량이동에 근거한 Rohwer 식이 기장 큰 상대오차(33.47%)를 보였다. 그리고 풍속함수와 풍속과의 상관관계가 높게 나타나는 경우 Penman 식의 풍속함수 보정을 통하여 증발량 산정의 정확도를 높일 수 있었다.

• 한국농공학회지
• /
• 제43권2호
• /
• pp.78-84
• /
• 2001

The daily streamflow in the Yaluhe watershed located in the north-eastern part of China was simulated by DAWAST model and the water balance parameters of the model were calibrated by simplex method. Model verification tests were carried out. The range of root mean square error was 0.34∼1.50mm, that of percent error in volume was -16.9∼-62.0% and that of correlation coefficient was 0.727∼0.920. DAWAST model was revised to consider the phreatic evaporation from the ground water in the frozen soil by adjusting soil moisture content in the unsaturated layer at the end of the melting season. The results of estimation of the daily streamflow by the revised model were statistically improved, that is, the range of root mean square error was 0.31∼1.49mm, that of percent error in volume was -11.7∼-12.1%, and that of correlation coefficient was 0.810∼0.932. The accuracy of DAWAST model was improved and the applicability of DAWAST model was expanded to the frozen region.

• 환경영향평가
• /
• 제19권4호
• /
• pp.421-429
• /
• 2010

The reliability of the measurement of ambient trace species is an important issue, especially, in background area such as Gosan in Jeju Island. In a previous episodic study, it was suggested that the PM10 measurement result by the gravimetric method(GMM) was not in agreement with the result by the ${\beta}$-ray absorption method(BAM). In this study, a systematic comparison was carried out for the data between 2001 and 2008 at Gosan(GMM and BAM) and Jeju city (BAM) which is near to Gosan. It was found that at Gosan the PM10 concentration by BAM was higher than GMM and the correlation between them was low. The BAM results at Gosan and Jeju city showed similar trend implying the discrepancy at Gosan was not caused by instrumental problem of the BAM at Gosan. Based on the previous studies two probable reasons for the discrepancy are identified; (1) negative measurement error by the evaporation of volatile ambient species at the filter in GMM such as nitrate and ammonium and (2) positive error by the absorption of water vapor during measurement in BAM. There was no heater at the inlet of BAM at Gosan during the sampling period. Based on the size-segregated measurement data, it was identified that the evaporation error was minor, if any. The relationship between the two methods did not vary with the ambient relative humidity. Thus, at present, it is not clear why the discrepancy had been occurring and when using the PM10 data at Gosan, one should be aware the possible errors.

• Smart Structures and Systems
• /
• 제30권4호
• /
• pp.421-432
• /
• 2022

Regarding the high significance of correct pan evaporation modeling, this study introduces two novel neuro-metaheuristic approaches to improve the accuracy of prediction for this parameter. Vortex search algorithms (VSA), sunflower optimization (SFO), and stochastic fractal search (SFS) are integrated with a multilayer perceptron neural network to create the VSA-MLPNN, SFO-MLPNN, and SFS-MLPNN hybrids. The climate data of Arcata-Eureka station (operated by the US environmental protection agency) belonging to the years 1986-1989 and the year 1990 are used for training and testing the models, respectively. Trying different configurations revealed that the best performance of the VSA, SFO, and SFS is obtained for the population size of 400, 300, and 100, respectively. The results were compared with a conventionally trained MLPNN to examine the effect of the metaheuristic algorithms. Overall, all four models presented a very reliable simulation. However, the SFS-MLPNN (mean absolute error, MAE = 0.0997 and Pearson correlation coefficient, R_P = 0.9957) was the most accurate model, followed by the VSA-MLPNN (MAE = 0.1058 and R_P = 0.9945), conventional MLPNN (MAE = 0.1062 and R_P = 0.9944), and SFO-MLPNN (MAE = 0.1305 and R_P = 0.9914). The findings indicated that employing the VSA and SFS results in improving the accuracy of the neural network in the prediction of pan evaporation. Hence, the suggested models are recommended for future practical applications.

• 농업과학연구
• /
• 제8권2호
• /
• pp.195-202
• /
• 1981

회개, 수자원획(水資源劃) 등(等) 이수(利水)를 목적(目的)으로 하는 장기유출해석(長期流出解析)에 있어 가장 중요(重要)한 인자(因子) 중(中)의 하나인 유역증발산량(流域蒸發散量)을 Water budget방법(方法)에 의(依)하여 산정(算定)하여, Pan, Potential, Regional evaporation과 Temperature와의 관계(關係)를 구명(究明)하여 유출기록(流出記錄)이 없는 무계기(無計器) 지역(地域)의 유역증발산량(流域蒸發散量)과 장기유출량(長期流出最)을 추정(推定)하기 위하여 금강수계(錦江水系) 용담지점(龍潭地點)의 5 개년(個年) 자료(資料)를 분석(分析)한 결과(結果)는 다음과 같다. 1. Pan evaporation과 River basin evaporation과의 비(比)($E_w/E_{pan}$)가 계절별(季節別) 성향(性向)을 가장 질서(秩序)있게 나타났으며, Pan evaporation으로부터 River basin evaporation을 Fig. 9 또는 Table-7로부터 추정(推定)할 수 있다. 2. Penman의 Potential evaporation을 적용하기 위하여 cloudness effect와 Wind function의 지역상수(地域常數)를 결정한 결과, 용담지역(龍潭地域)의 지역상수(地域常數)는 다음과 같다. $R_A=R_C(0.13+0.52{\frac{n}{D}})$ $E_a=0.35(e_s-e)(1.8+1.0U)$ 3. Regional evaporation [$E_R=(1-a)R_C-E_P$]는 유도과정의 가정에 따른 functional error가 큰 것으로 보여지나, 유역(流域)전반의 물리(物理), 화학(化學), 생물학적(生物學的)인 증발(蒸發)기구를 포괄적(包括的)으로 포용(包容)하고 있는 이와같은 이론적(理論的)인 함수개발(函數開發)이 요망된다. 4. 기상자료(氣象資料)가 미비(未備)한 지역(地域)에서는 기온(氣溫)만으로 Fig-11과 같이 개락적(槪略的)인 월(月) 평균(平均) 증발산(蒸發散)을 구(求)할 수 있다.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2017년도 학술발표회
• /
• pp.392-395
• /
• 2017

본 연구에서는 일 증발접시 증발량 산정을 위한 딥러닝 (deep learning) 모형의 적용성을 평가하였다. 본 연구에서 적용된 딥러닝 모형은 deep belief network (DBN) 기반 deep neural network (DNN) (DBN-DNN) 모형이다. 모형 적용성 평가를 위하여 부산 관측소에서 측정된 기상자료를 활용하였으며, 증발량과의 상관성이 높은 기상변수들 (일사량, 일조시간, 평균지상온도, 최대기온)의 조합을 고려하여 입력변수집합 (Set 1, Set 2, Set 3)별 모형을 구축하였다. DBN-DNN 모형의 성능은 통계학적 모형성능 평가지표 (coefficient of efficiency, CE; coefficient of determination, $r^2$; root mean square error, RMSE; mean absolute error, MAE)를 이용하여 평가되었으며, 기존의 두가지 형태의 ANN (artificial neural network), 즉 모형학습 시 SGD (stochastic gradient descent) 및 GD (gradient descent)를 각각 적용한 ANN-SGD 및 ANN-GD 모형과 비교하였다. 효과적인 모형학습을 위하여 각 모형의 초매개변수들은 GA (genetic algorithm)를 이용하여 최적화하였다. 그 결과, Set 1에 대하여 ANN-GD1 모형, Set 2에 대하여 DBN-DNN2 모형, Set 3에 대하여 DBN-DNN3 모형이 가장 우수한 모형 성능을 나타내는 것으로 분석되었다. 비록 비교 모형들 사이의 모형성능이 큰 차이를 보이지는 않았으나, 모든 입력집합에 대하여 DBN-DNN3, DBN-DNN2, ANN-SGD3 순으로 모형 효율성이 우수한 것으로 나타났다.

• 설비공학논문집
• /
• 제15권2호
• /
• pp.152-158
• /
• 2003

Titration method is one of the widely used methods for the concentration measurement of absorbent ammonia/water. However, this method is inconvenient because the solution should be extracted for the measurement. Moreover, significant error can be introduced by the evaporation of ammonia during the sampling and measuring procedure. In this study a reliable in-line concentration measurement method was proposed. To prove the validity of the concept, a measuring apparatus was designed, built, and tested with water. It is found that the location of flow inlet and exit is important in the measurement accuracy. The flow inlet and exit located in the middle of the test cell showed the best result. By the error analysis, it is expected that the ammonia concentration can be measured within the error of $\pm$0.18% assuming the error of 0.1 K in temperature measurement and 0.1 g in weight measurement.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2008년도 학술발표회 논문집
• /
• pp.75-81
• /
• 2008

The water shortage in mega cities in Asia, which face a rapid growth in urban population, is an outstanding problem. It is important, therefore, to accurately estimate the water balance in each city in order to use the limited water resources effectively. In this study, we estimated the potential water resources in し sixteen mega cities in Asia. The target cities were Delhi and Calcutta, India; Colombo, Sri Lanka; Dhaka, Bangladesh; Yangon, Myanmar; Bangkok, Thailand; Kuala Lumpur, Malaysia; Singapore; Jakarta, Indonesia; Hanoi, Vietnam; Beijing and Hong Kong, the People's Republic of China; Seoul, the People's Republic of Korea; Manila, the Philippines, and Sapporo and Tokyo, Japan. The potential water resources were estimated by subtracting the actual evaporation from the amount of rainfall. The actual evaporation was estimated using the potential evaporation obtained by Hamon's equation which requires the air temperature and the possible hours of sunshine. When the results of Hamon's and Penman's evaporation equations were compared, a considerable error appeared in the low latitude region. The estimation using Hamon's equation was corrected with the linear regression line of Hamon's and Penman's equations. A classification of the land cover was carried out based on satellite photographs of the target cities, and the volume of surface runoff for each city was obtained using the runoff ratios which depended on the land cover. As a result, the potential water resources in the above mega cities in Asia were found to be greater than the world average. However, the actual water resources which are available for one person to use are probably very limited.

• 한국수자원학회논문집
• /
• 제52권1호
• /
• pp.11-19
• /
• 2019

본 연구에서는 인공위성 및 재분석 자료인 Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MOD16의 실제증발산량 산출물을 활용하여 한국수자원조사기술원(Korea Institute of Hydrological Survey, KIHS)에서 관리하고 있는 청미천(cheongmicheon farmland site, CFK)과 설마천(seolmacheon site, SMK) flux tower에서 검증하였고, Triple collocation (TC) 방법을 활용하여 자료간의 불확실성 및 상관성분석을 수행하였다. 플럭스타워와의 검증 결과에서는 전반적으로 GLEAM>GLDAS>MOD16순으로 좋은 결과를 나타내었으며, 세가지 산출물의 조합(S1: flux tower vs. GLDAS vs. MOD16, S2: flux tower vs. GLDAS vs. GLEAM, S3: flux tower vs. GLEAM vs. MOD16)을 통한 TC 결과에서는 청미천(설마천)에서 GLEAM>GLDAS>MOD16>flux tower (GLDAS>GLEAM>MOD16>flux tower)순으로 좋은 결과를 나타내었다. TC 분석 결과에서 Flux tower의 error variance와 correlation coefficient가 상대적으로 좋은 결과를 나타내지 못하였으므로, 한반도 지역에서 인공위성과 재분석 자료(GLDAS vs. GLEAM vs. MOD16)만을 활용하여 TC를 적용하였다. 그 결과, GLDAS와 GLEAM이 한반도 영역에서 낮은 error variance 와 높은 correlation coefficient를 나타낸 반면, MOD16의 경우, 농지에서 낮은 correlation coefficient과 높은 error variance를 나타내었다.