• Journal of Environmental Science International
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• v.6 no.3
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• pp.205-211
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• 1997

For the prediction of multi-site rainfall with radar data and ground meteorological data, a rainfall prediction model was proposed, which uses the neural network theory, a kind of artifical Intelligence technique. The Input layer of the prediction model was constructed with current ground meteorological data, their variation, moving vectors of rain- fall field and digital terrain of the measuring site, and the output layer was constructed with the predicted rainfall up to 3 hours. In the application of the prediction model to the Pyungchang river basin, the learning results of neural network prediction model showed more Improved results than the parameter estimation results of an existing physically based model. And the proposed model comparisonally well predicted the time distribution of ralnfall.

• Journal of Korea Water Resources Association
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• v.33 no.6
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• pp.733-744
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• 2000

Due to the randomness of reservoir inflow and supply demand it is not easy to establish an optimal reservoir operation rule. However, the operation rule can be derived by the implicit stochastic optimization approach using synthetic inflow data with some demand satisfied. In this study the optimal reservoir operation which was reasonably formulated as Linear Tracking model for maximizing the hydro-energy of seven reservoirs system in the Han river was performed by use of the optimal control theory. Here the operation model made to satisfy the 2001st year demand in the capital area inputted the synthetic inflow data generated by multi-site Markov model. Based on the regressions and statistic analyses of the optimal operation results, monthly reservoir operation rules were developed with the seasonal probabilities of the reservoir stages. The comparatively larger dams which would have more controllability such as Hwacheon, Soyanggang, and Chungju had better regressions between the storages and outflows. The effectiveness of the rules was verified by the simulation during actually operating period.period.

• Journal of Korean Society on Water Environment
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• v.24 no.6
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• pp.725-740
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• 2008

In this study a multi-site daily precipitation generator which generates the precipitation with similar spatial correlation, and at the same time, with conserving statistical properties of the observed data is developed. The proposed generator is intended to be a tool for down-scaling the data obtained from GCMs or RCMs into local scales. The occurrences of precipitation are simultaneously modeled in multi-sites by 2-parameter first-order Markov chain using random variables of spatially correlated while temporally independent, and then, the amount of precipitation is simulated by 3-parameter mixed exponential probability density function that resolves the issue of maintaining intermittence of precipitation field. This approach is applied to the Nakdong river basin and the observed data are daily precipitation data of 19 locations. The results show that spatial correlations of precipitation series are relatively well simulated and statistical properties of observed precipitation series are simulated properly.

• Water for future
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• v.24 no.4
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• pp.67-72
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• 1991

Various modeling approaches to study along term behavior of streamflow or groundwater storagge have been conducted. In this study, a Multivariate AR (1) Model has been applied to generate monthly flows of the one key station which has historical flows using monthly flows of the three subordinate stations. The Model performance was examined using statistical comparisons between the historical and generated monthly series such as mean, various, skewness. Also, the correlation coefficients(lag-zero, and lag-one)between the two monthly flows were compared. The results showed that the modeled generated flows were statistically similar to the historical flows.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.929-940
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• 2011

In this study, the future expected discharges are analyzed for Daecheong and Yongdam Dam Watershed in Geum River watershed using A1B scenario based RCM with 27 km spatial resolutions from Korea Meteorological Agency and SWAT model. The direct use of GCM and RCM data for water resources impact assessment is practically hard because the spatial and temporal scales are different. In this study, the problems of spatial and temporal scales were settled by the spatial and temporal downscaling from watershed scale to weather station scale and from monthly to daily of RCM grid data. To generate the detailed hydrologic scenarios of the watershed scale, the multi-site non-stationary downscaling method was used to examine the fluctuations of rainfall events according to the future climate change with considerations of non-stationary. The similarity between simulation and observation results of inflows and discharges at the Yongdam Dam and Daecheong Dam was respectively 90.1% and 84.3% which shows a good agreement with observed data using SWAT model from 2001 to 2006. The analysis period of climate change was selected for 80 years from 2011 to 2090 and the discharges are increased 6% in periods of 2011~2030. The seasonal patterns of discharges will be different from the present precipitation patterns because the simulated discharge of summer was decreased and the discharge of fall was increased.

• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.59-71
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• 2013

The lack of sufficient flood data being kept across Korea has made it difficult to assess reliable estimates of the design flood while relatively sufficient rainfall data are available. In this regard, a rainfall simulation based derivation technique of flood frequency curve has been proposed in some of studies. The main issues in deriving the flood frequency curve is to develop the rainfall simulation model that is able to effectively reproduce extreme rainfall. Also the rainfall-runoff modeling that can convey uncertainties associated with model parameters needs to be developed. This study proposes a systematic approach to fully consider rainfallrunoff related uncertainties by coupling a piecewise Kernel-Pareto based multisite daily rainfall generation model and Bayesian HEC-1 model. The proposed model was applied to generate runoff ensemble at Daechung Dam watershed, and the flood frequency curve was successfully derived. It was confirmed that the proposed model is very promising in estimating design floods given a rigorous comparison with existing approaches.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.15-15
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• 2021

최근 기후변화에 따른 서울의 강수 특성이 변화하고 있으며, 장마철 국지성 집중호우에 의한 하천 내 고립사고 발생 등 그 피해가 가속화될 전망이다. 하천의 안전사고 예방을 위해서는 상류에서 빠르게 유입되는 유량의 계측을 통한 홍수 예·경보가 무엇보다 중요하며, 실시간 계측된 유속과 유량 정보는 하류 지역의 홍수 도달시간 확보로 한 발 빠른 대응을 가능하게 한다. 본 연구에서는 우이천 시범유역을 대상으로 총 6개 지점에 대하여 CCTV기반 자동유량계측 기술을 시범적용하였으며, 사용된 자동유량계측 지점은 기존 환경부의 월계2교, 중랑교 지점과 더불어 추가로 중랑천 월계1교지점, 우이천 본류(창번2교)와 소하천구간(인수천: 지성교, 백운천: 청담교) 지점이다. 우이천과 중랑천 합류 후에는 하도구간에 대하여 중랑교 지점에 설치된 환경부의 계측 정보를 활용하여 홍수파의 도달시간을 검증하였다. 분석결과, 유량계측 오차는 0.9~8.9%로 분석되었으며, 유속계측 오차 또한 현장 계측 결과와 10%이내의 오차범위를 보임으로서 안정된 수리량 계측이 가능함을 검증하였다. 또한, SWMM 모델링 결과와 결합하여 Flow Nomograpgh 작성을 실시하였으며, 상하류 연계 홍수 예·경보 가능성을 진단하였다. 이는 실시간 계측된 자료와 모형을 통한 시뮬레이션 정보를 활용한 유역 단위의 신뢰성 있는 유출응답(강우-유량-수위 관계) 규명을 가능하게 하였다. 향후 지방하천과 소하천의 경우, 국가하천 수준에 부합하는 표준화된 수리량 계측 체계를 마련할 필요성이 있으며, 소유역 규모의 수량-수질 수자원 기초조사자료 생산은 지방하천설계 및 관련 이·치수계획 수립에도 도움이 될 것으로 사료된다.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.921-931
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• 2009

For the assessment of climate change impacts for the Byeongseong stream, CGCM 3.1 T63 is selected as future climate information. The projections come from CGCM used to simulate the GHG emission scenario known as A2. Air temperature and precipitation information from the GCM simulations are converted to regional scale data using the statistical downscaling method known as MSPG. Downscaled climate data from GCM are then used as the input data for the SWAT model to generate regional runoff and water quality estimates in the Byeongseong stream. As a result of simple sensitivity analysis, the increase of CO2 concentration leads to increase water yield through reduction of evapotranspiration and increase of soil water. Hydrologic responses to climate change are in phase with precipitation change. Climate change is expected to reduce water yields in the period of 2021-2030. In the period of 2051-2060, stream flow is expected to be reduced in spring season and increased in summer season. While soil losses are also in phase with water yields, nutrient discharges (i.e., total nitrogen) are not always in phase with precipitation change. However, it should be noted that there are a lot of uncertainties in such multiple-step analysis used to convert climate information from GCM-based future climate projections into hydrologic information.

• Journal of Korea Water Resources Association
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• v.46 no.9
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• pp.921-932
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• 2013

Runoff data availability is a substantial factor for precise flood control such as flood frequency or flood forecasting. However, runoff depths and/or peak discharges for small watersheds are rarely measured which are necessary components for hydrological analysis. To compensate for this discrepancy, a lumped concept such as a Storage Function Method (SFM) was applied for the partitioned Choongju Dam Watershed in Korea. This area was divided into 22 small watersheds for measuring the capability of spatial extension of runoff data. The chosen total number of flood events for searching parameters of SFM was 21 from 1991 to 2009. The parameters for 22 small watersheds consist of physical property based (storage coefficient: k, storage exponent: p, lag time: $T_l$) and flood event based parameters (primary runoff ratio: $f_1$, saturated rainfall: $R_{sa}$). Saturated rainfall and base flow from event based parameters were explored with respect to inflow at Choongju Dam while other parameters for each small watershed were fixed. When inflow of Choongju Dam was optimized, Youngchoon and Panwoon stations obtained average of Nash-Sutcliffe Efficiency (NSE) were 0.67 and 0.52, respectively, which are in the satisfaction condition (NSE > 0.5) for model evaluation. This result is showing the possibility of spatial data extension using a lumped concept model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.199-205
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• 2001

This study was conducted to figure out temperature profiles of a partially developed paddy rice canopy, which are necessary to run plant disease forecasting models. Air temperature over and within the developing rice canopy was monitored from one month after transplanting (June 29) to just before heading (August 24) in 1999 and 2001. During the study period, the temporal march of the within-canopy profile was analyzed and an empirical formula was developed for simulating the profile. A partially developed rice canopy temperature seemed to be controlled mainly by the ambient temperature above the canopy and the water temperature beneath the canopy, and to some extent by the solar altitude, resulting in alternating isothermal and inversion structures. On sunny days, air temperature at the height of maximum leafages was increased at the same rate as the ambient temperature above the canopy after sunrise. Below the height, the temperature increase was delayed until the solar noon. Air temperature near the water surface varied much less than those of the outer- and the upper-canopy, which kept increasing by the time of daily maximum temperature observed at the nearby synoptic station. After sunset, cooling rate is much less at the lower canopy, resulting in an isothermal profile at around the midnight. A fairly consistent drop in temperature at rice paddies compared with the nearby synoptic weather stations across geographic areas and time of day was found. According to this result, a cooling by 0.6 to 1.2$^{\circ}C$ is expected over paddy rice fields compared with the officially reported temperature during the summer months. An empirical equation for simulating the temperature profile was formulated from the field observations. Given the temperature estimates at 150 cm above the canopy and the maximum deviation at the lowest layer, air temperature at any height within the canopy can be predicted by this equation. As an application, temperature surfaces at several heights within rice fields were produced over the southwestern plains in Korea at a 1 km by 1km grid spacing, where rice paddies were identified by a satellite image analysis. The outer canopy temperature was prepared by a lapse rate corrected spatial interpolation of the synoptic temperature observations combined with the hourly cooling rate over the rice paddies.