• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1285-1294
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• 2021

In recent years, as rainfall is concentrated and rainfall intensity increases worldwide due to climate change, the scale of flood damage is increasing. Rainfall of a previously unobserved magnitude falls, and the rainy season lasts for a long time on record. In particular, these damages are concentrated in ASEAN countries, and at least 20 million people among ASEAN countries are affected by frequent flooding due to recent sea level rise, typhoons and torrential rain. Korea supports the domestic flood warning system to ASEAN countries through various ODA projects, but the communication network is unstable, so there is a limit to the central control method alone. Therefore, in this study, an artificial intelligence-based flood prediction model was developed to develop an observation station that can observe water level and rainfall, and even predict and warn floods at once at one observation station. Training, validation and testing were carried out for 0.5, 1, 2, 3, and 6 hours of lead time using the rainfall and water level observation data in 10-minute units from 2009 to 2020 at Junjukbi-bridge station of Seolma stream. LSTM was applied to artificial intelligence algorithm. As a result of the study, it showed excellent results in model fit and error for all lead time. In the case of a short arrival time due to a small watershed and a large watershed slope such as Seolma stream, a lead time of 1 hour will show very good prediction results. In addition, it is expected that a longer lead time is possible depending on the size and slope of the watershed.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.775-784
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• 2022

In this study, to determine the optimal order of the full-logged I-D-F polynomial equation, which is mainly used to calculate the probable rainfall over a temporal rainfall duration, the probable rainfall was calculated and the regression coefficients of the full-logged I-D-F polynomial equation was estimated. The optimal variable of the polynomial equation for each station was selected using a stepwise selection method, and statistical significance tests were performed through ANOVA. Using these results, the statistically appropriately calculated rainfall intensity equation for each station was presented. As a result of analyzing the variable selection outputs of the full-logged I-D-F polynomial equation at 9 stations in Gyeongbuk, the 1^st to 3^rd order equations at 6 stations and the incomplete 3^rd order at 1 station were determined as the optimal equations. Since the 1^st order equation is similar to the Sherman type equation and the 2^nd order one is similar to the general type equation, it was presented as a unified form of rainfall intensity equation for convenience of use by increasing the number of independent variables. Therefore, it is judged that there is no statistical problem in considering only the 3^rd order polynomial regression equation for the full-logged I-D-F.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.4
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• pp.223-237
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• 2011

The intermittent freshwater discharge has an critical influence upon the biophysical environments and the ecosystems of the Yeongsan Estuary where the estuary dam altered the continuous mixing of saltwater and freshwater. Though freshwater discharge is controlled by human, the extreme events are mainly driven by the heavy rainfall in the river basin, and provide various impacts, depending on its magnitude and frequency. This research aims to evaluate the magnitude and frequency of extreme freshwater discharges, and to establish the magnitude-frequency relationships between basin-wide rainfall and freshwater inflow. Daily discharge and daily basin-averaged rainfall from Jan 1, 1997 to Aug 31, 2010 were used to determine the relations between discharge and rainfall. Consecutive daily discharges were grouped into independent events using well-defined event-separation algorithm. Partial duration series were extracted to obtain the proper probability distribution function for extreme discharges and corresponding rainfall events. Extreme discharge events over the threshold 133,656,000 $m^3$ count up to 46 for 13.7y years, following the Weibull distribution with k=1.4. The 3-day accumulated rain-falls which occurred one day before peak discharges (1day-before-3day -sum rainfall), are determined as a control variable for discharge, because their magnitude is best correlated with that of the extreme discharge events. The minimum value of the corresponding 1day-before-3day-sum rainfall, 50.98mm is initially set to a threshold for the selection of discharge-inducing rainfall cases. The number of 1day-before-3day-sum rainfall groups after selection, however, exceeds that of the extreme discharge events. The canonical discriminant analysis indicates that water level over target level (-1.35 m EL.) can be useful to divide the 1day-before-3day-sum rainfall groups into discharge-induced and non-discharge ones. It also shows that the newly-set threshold, 104mm, can just separate these two cases without errors. The magnitude-frequency relationships between rainfall and discharge are established with the newly-selected lday-before-3day-sum rainfalls: $D=1.111{\times}10^8+1.677{\times}10^6{\overline{r_{3day}}$, (${\overline{r_{3day}}{\geqq}104$, $R^2=0.459$), $T_d=1.326T^{0.683}_{r3}$, $T_d=0.117{\exp}[0.0155{\overline{r_{3day}}]$, where D is the quantity of discharge, ${\overline{r_{3day}}$ the 1day-before-3day-sum rainfall, $T_{r3}$ and $T_d$, are respectively return periods of 1day-before-3day-sum rainfall and freshwater discharge. These relations provide the framework to evaluate the effect of freshwater discharge on estuarine flow structure, water quality, responses of ecosystems from the perspective of magnitude and frequency.

• Journal of Korean Society on Water Environment
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• v.30 no.1
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• pp.8-15
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• 2014

In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

• Journal of Korea Water Resources Association
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• v.38 no.12 s.161
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• pp.985-994
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• 2005

We examined problems of the principal component analysis(PCA), which is able to analyze at the low dimensionality as a methodologv to assess hydrologic time series, and introduced the theory and characteristics of independent component analysis(ICA) that can supplement problems of principal component analysis. We also applied the global sea surface temperature(SST) of the Nino region and assessed the correlation between El $\tilde{n}ino$-Southern Oscillation(ENSO) and SST. The results of examining separation-ability of principal components using mixed signals indicate that the independent component analysis is statistically superior compared to that of the principal component analysis. Finally, we assessed correlation between ENSO and global anomaly SST. The independent component analysis was applied to the $5^{\circ}{\times}5^{\circ}$(latitude and longitude) global anomaly SST in the Nino+3.4 region that is the El $\tilde{n}ino$ observation section. We assessed the correlation with the ENSO years. These results of the analysis show that only one independent component($86\%$) was able to represent the entire behavior and was consistent with the main ENSO years. Finally, we carried out independent component analysis for summer seasonal rainfalls at nine stations and could extract ICs to reflect geographical characteristics. The increasing trend has been shown at IC-1 and IC-2 since 1970s.

• Journal of Korea Water Resources Association
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• v.34 no.3
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• pp.275-285
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• 2001

Since the majority of streamflow during dry periods is provided by groundwater storage, the streamflow depends on a basin moisture state recharged from rainfall during wet periods. This hydrologic characteristics dives good condition to predict long-term streamflow if the basin state like groundwater recharge is known in advance. The objective of this study is to examine groundwater recharge effect to monthly streamflow, and to attempt monthly streamflow prediction using estimated groundwater recharge. The ground water recharge is used as an independent variable with streamflow and precipitation to construct multiple regression models for the prediction. Correlation analysis was performed to assess the effect of groundwater carry-over to streamflow and to establish the associations among independent variables. The predicted streamflow shows that the multiple regression model involved groundwater recharge gives improved results comparing to the model only using streamflow and precipitation as independent variables. In addition, this paper shows that the prediction model with the effect of groundwater carry-over taken into account can be developed using only precipitation.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.281-285
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• 2011

본 연구에서는 연최대치 독립 호우사상 계열과 연최대치 계열의 차이를 살펴보았다. 이를 위해 본 연구에서는 몇 가지 경우의 IETD 및 절단값을 적용하여 독립 호우사상을 결정하고, 그 특성을 살펴보았다. 이어 연최대치 계열과 연 최대치 독립 호우사상 계열을 비교하였다. 본 연구는 1961년부터 2010년까지 서울지점의 시강우 자료를 분석대상으로 사용하였다. 그 결과, IETD의 증가에 따라서 독립 호우사상의 발생빈도 및 평균 강우강도는 감소하고, 평균 지속기간은 증가하였다. 절단값의 증가에 따라 독립 호우사상의 발생빈도 및 평균 지속기간은 감소하고, 평균 강우강도는 증가하였다. 호우사상의 평균 강우강도는 강우 지속기간에 관계없이 거의 일정한 것으로 나타났다. 이러한 결과를 통해 지속기간이 짧은 호우사상의 최대 강우강도는 지속기간이 긴 호우사상의 최대 강우강도보다 매우 작을 것으로 파악되었다. 지속 기간이 짧은 경우, 연 최대치 계열과 연 최대치 독립 호우사상 계열의 차이는 매우 크며, 강우 지속기간이 길게 적용한 경우에는, 두 계열의 차이는 매우 줄어드는 것으로 나타났다.

• Korean Journal of Environmental Agriculture
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• v.25 no.4
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• pp.306-315
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• 2006

Two different experiments, adsorption/desorption and runoff by rainfall simulation of four pesticides, such as alachlor, ethalfluralin, ethoprophos and pendimethalin were undertaken their runoff and erosion losses from sloped land and to assess the influence of their properties and environmental factors on them. The mobility of four pesticides and which phase they were transported by were examined in adsorption study, and the influence of rainfall pattern and sloping degree on the pesticide losses were evaluated in simulated rainfall study. Freundlich adsorption parameters (K) by the adsorption and desorption methods were 1.2 and 2.2 for ethoprophos, 1.5 and 2.6 for alachlor, respectively. And adsorption distribution coefficients (Kd) by the adsorption and desorption methods were 56 and 94 for ethalfluralin, and 104 and 189 for pendimethalin, respectively. K or Kd values of pesticides by the desorption method which were desorbed from the soil after thoroughly mixing, were higher than these ones by the adsorption method which pesticides dissolved in water were adsorbed to the soil. Another parameter (1/n), representing the linearity of adsorption, in Freundlich equation for the pesticides tested ranged from 0.96 to 1.02 by the desorption method and from 0.87 to 1.02 by the adsorption method. Therefore, the desorption method was more independent from pesticide concentration in soil solution than the adsorption method. By Soil Survey and Land Research Center (SSLRC)'s classification for pesticide mobility, alachlor and ethoprophos were classified into moderately mobile $(75{\leq}Koc<500)$, and ethalfluralin and pendimethalin were included to non-mobile class (Koc > 4000). Runoff and erosion loss of pesticides by three rainfall scenarios were from 1.0 to 6.4% and from 0.3 to 1.2% for alachlor, from 1.0 to 2.5% and from 1.7 to 10.1% for ethalfluralin, from 1.3 to 2.9% and from 3.9 to 10.8% for pendimethalin, and from 0.6 to 2.7% and from 0.1 % 0.3% for ethoprophos, respectively. Distribution of pesticides in soil profile were investigated after the simulated rainfall study. Alachlor and ethoprophos were leached to from 10 to 15 cm of soil layer, but ethalfluralin and pendimethalin were mostly remained at the top 5 cm of soil profile. The losses of the pesticides at 30% of sloping degree were from 0.2 to 1.9 times higher than those at 10%. The difference of their runoff loss was related with their concentration in runoff water while the difference of their erosion loss must be closely related with the quantity of soil eroded.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.4
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• pp.306-317
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• 2017

Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And $NDVI_{UAV}$ in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to $NDVI_{UAV}$ and other meteorological factors were well reflected in the model.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.171-182
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• 2006

In this study, rainfall-runoff analysis was performed for Yongdam watershed($930km^2$) using KOWACO flood analysis model based on Storage Function Method as lumped hydrologic model and Vflo which was developed for real-time flood prediction by University of Oklahoma. The results shows that, the hydrographs of lumped and distributed model with uncalibrated parameters which estimated from physical or experimental relationship show significant biases from observed hydrographs. However, the hydrograph at Cheoncheon site from the distributed model follows the actual hydrograph to an extent that no more calibration is necessary. It encourages that distributed model can have advantages for application in real-time flood forecasting as physically based distributed hydrologic model which can construct event-independent basin parameter group.