Chungju Dam Watershed Research Articles

A Study on Dam Break Simulation considering Continuous Rainfall Events

In recent years, flood damage resulting from continuous rainfall events has been on the rise. However, existing Emergency Action Plans (EAPs) addressing reservoir or dam failure only consider Probable Maximum Precipitation (PMP), which represents a single rainfall event. This study aims to address this limitation by simulating a dam break scenario caused by continuous rainfall events. The Chungju dam watershed was selected as the study area and a mega rainfall event scenario, involving continuous 500-year frequency rainfall intensity events, was defined. Next, the flood discharge resulting from the mega rainfall event scenario was estimated using the Consecutive Storm Event Based (ConSEB) model. The Simplified Dam Break (SMPDBK) model was employed to simulate the dam break. The flood discharge estimated for this scenario amounted to 31,080.34 cms, which is about 1.2 times larger than the Probable Maximum Flood (PMF). The dam break water level simulated by the SMPDBK model was 150 m and the flood damage area was estimated to be 307.45 km2. Based on the results of the study, we highlighted the need to consider continuous rainfall events within EAPs.

Reconstruction of July 2006 Heavy Rainfall Event Series in the Chungju Dam Watershed using a Regional Climate Model

The approach that uses a regional climate model (RCM) is emphasized to prevent and reduce extreme rainfall events that are becoming more powerful due to climate change. This paper presented a preliminary study to produce Probable Maximum Precipitation (PMP) or mega-disaster scenarios using RCMs in Korea. The heavy rainfall event in July 2006, during which the highest average precipitation during the Changma season was recorded, was reconstructed using the Weather Research and Forecasting (WRF) model for the Chungju Dam watershed. Even when considering errors in the rainfall observation data, the WRF model could successfully reconstruct the July 2006 heavy rainfall event. It is expected that more reliable results will be obtained if the flow observation data is used in combination with a runoff model. Keywords: Extreme Rainfall Event, Regional Climate Model, Changma, WRF

SWAT Modeling of Nitrogen Dynamics Considering Atmospheric Deposition and Nitrogen Fixation in a Watershed Scale

The Soil and Water Assessment Tool (SWAT) nitrogen (N) water quality model considers the artificial inputs associated with human activities, including point and nonpoint source pollution loads. Although SWAT has the ability to simulate atmospheric N deposition and fixation, they were not considered in the modeling research. N deposition from the air is an important and considerable pathway for the input of N species into watersheds and water bodies, causing soil and water body acidification and the leaching of N into surface and groundwater, resulting in eutrophication and degraded water quality. The goal of this study is to assess the effects of atmospheric and agricultural N loads on stream water quality at the watershed scale. For a 6642 km2 Chungju dam watershed, SWAT was calibrated for 4 years (2003-2006) and validated for another 4 years (2007-2010) using daily anthropogenic N data (sewage discharge pollutants and fertilizer) and monthly measured atmospheric deposition data for NO3ˉ, NH4+, and dissolved organic N (DON). At the watershed outlet, the Nash-Sutcliffe (1970) efficiency (NSE) of daily streamflow during the validation period was 0.74. The coefficient of determination (R2) of total N was 0.69 considering atmospheric deposition, whereas it was 0.33 when removing the deposition effect. The results of this study demonstrate the potential for using the N dynamics between the atmosphere and land for SWAT assessments of nonpoint source pollution and for modeling stream water quality.

모의조건에 따른 홍수 유출자료의 공간적 확장 영향분석

일괄형 수문모형(Lumped Model)을 활용한 홍수 유출자료의 공간확장에 영향을 미치는 강우-유출모형의 초기조건과 입력자료의 영향에 대해 연구하였다. 강우-유출모형의 초기조건으로는 기저유량 정보의 모형모의에 대한 영향과 저류함수법의 포화우량(<TEX>$R_{sa}$</TEX>)의 공간분포에 대한 분석을 실시하였으며, 강우-유출모형의 입력자료로서 강우정보의 영향을 자료의 유무에 관련한 과거자료의 조건을 중심으로 그 영향을 분석하였다. 이를 위해 충주댐유역을 선정하였으며, 충주댐 유역을 대규모유역으로 정하고 이를 기준으로 3개 중규모유역과 22개의 소유역으로 구분하였다. 영월1, 충주댐, 영월2의 수위관측소를 70년대 수문자료 유무에 따라 중심 수위관측소로 선정하였으며 이들을 개별적 중심축으로 삼고 1993년부터 2009년까지 30개의 홍수사상을 이용해 홍수유출자료 확장의 특성을 분석하였다. 관측유출을 직접유출과 기저유출로 분류하고 산정된 기저유출을 강우-유출모의에 적용하였다. 기저유출의 적용 유무 조건하에서 세 곳의 수위관측소를 중심으로 각각의 자료 확장성을 파악하였다. 기저유출을 고려한 모델 모의시 Nash-Sutcliffe Efficiency (NSE) 값은 모델 모의 만족범위를 넘어서는 사상이 10% 이상 증가되었다. 강우에 대한 초기유출의 양을 결정하는 포화우량(<TEX>$R_{sa}$</TEX>)의 분포는 세 곳 수위관측소의 유량값을 중심으로 중권역의 포화우량(<TEX>$R_{sa}$</TEX>)을 최적화하는 경우, 중권역의 최적화된 포화우량(<TEX>$R_{sa}$</TEX>) 값은 큰 차이를 보이지 않으며 포화우량(<TEX>$R_{sa}$</TEX>) 분포가 강우사상과 유출량의 크기분포에 큰 영향을 받지 않았다. 홍수 유출자료의 강수자료 영향은 30개의 홍수사상 자료에서 자료의 이상치를 제외한 17개 홍수사상을 이용해 검증하였으며 강우자료가 많아질수록 오차 범위가 줄어듦을 보였다. 하지만, 전체 홍수사상의 규모에 비해 그 영향이 크지 않는 것으로 파악되었다. The effects of initial conditions and input values of the rainfall-runoff model were studied in the applications of a lumped concept model for flood event data extension. For the initial conditions of the rainfall-runoff model, baseflow effects and spatial distributions of saturation points (<TEX>$R_{sa}$</TEX>) for the storage function methods (SFM) were analyzed. In addition, researches on the effects of rainfall data conditions as input values for the rainfall-runoff model were performed. The Chungju Dam watershed was selected and divided into 3 catchments including smaller size of 22 sub-catchments. The observed discharge and inflow amounts at Yeongwol 1, Chungju Dam, and Yeongwol 2 water level stations were individually operated as criteria for flood data extension in 30 flood events from 1993 to 2009. Direct and base flow were distinguished from a stream flow. In order to test capability of flood data extension, obtained base flow was applied to the rainfall-runoff model for three water level stations. When base flow was adopted in the model, the Nash-Sutcliffe Efficiency(NSE) was increased. The numbers of over satisfaction for model performance (>0.5) were increased over 10%. Saturation points (<TEX>$R_{sa}$</TEX>) which strongly influence the runoff amount when rainfall starts were optimized based on the runoff amount at three water level stations. The sizes of saturation points for three locations were similar which means saturation point size is not depending on the runoff amount. The effects of rainfall information for flood runoff were tested at 2002ev1 and 2008ev1. When increased the amount of rainfall information, the runoff simulations were closer to the simulations with full of rainfall information. However, the size of improvement was not substantial on rainfall-runoff simulations in terms of the size of total amount of rainfall.

Hydrologic impact of climate change with adaptation of vegetation community in a forest-dominant watershed

This study evaluated the impact on watershed hydrology by predicting future forest community change under a climate change scenario. The Soil and Water Assessment Tool (SWAT) was selected and applied to Chungju dam watershed (6,642 km2) of South Korea. The SWAT was calibrated and validated for 6 years (1998–2003) using the daily streamflow data from three locations. For the future evaluation of forest community and hydrology, the MIROC3.2 HiRes monthly climate data were adopted. The future data were corrected using 30 years (1977–2006, baseline period) of measured weather data, and they were daily downscaled by the Long Ashton Research Station-Weather Generator statistical method. To predict the future forest vegetation cover, the baseline forest community was modeled by a multinomial LOGIT model using variables of baseline precipitation, temperature, elevation, degree of base saturation, and soil organic matter, and the future forest community was predicted using the future precipitation and temperature scenario. The future temperature increase of 4.8 °C by 2080s (2070–2099) led to prediction of 30.8 % decrease of mixed forest and 75.8 % increase of coniferous forest compared to the baseline forest community. For the baseline evapotranspiration (ET) of 491.5 mm/year, the 2080s ET under the forest community change was 591.1 mm/year, whereas it was 551.8 mm/year with the remaining forest community stationary. The different ET results considering the future forest community clearly affected the groundwater recharge and streamflow in sequence.

충주댐 유역 홍수추적을 위한 소백산 레이더 강우자료의 적용성 검토

본 연구는 충주댐 유역(<TEX>$6,625.8km^2$</TEX>)을 대상으로 지점강우와 소백산 이중편파 레이더강우자료를 격자기반 분포형 강우-유출 모형인 KIMSTORM(KIneMatic wave STOrm Runoff Model)에 적용하여 홍수추적을 수행하여 레이더의 적용성을 검토하였다. 2012년 4개의 강우 이벤트(집중호우, 카눈, 볼라벤, 산바)에 대하여 한강홍수통제소로부터 보정된 소백산 레이더 강우자료를 제공받아 사용하였다. 레이더 강우와 지점 강우를 비교분석한 결과, 41개 지점의 지상강우보다 레이더의 면적평균강우량을 비교한 결과, 강우의 시공간적 패턴은 상당히 일치하였고 지상강우에 대한 레이더 강우의 비율은 0.97로 분석되었다. 이후 분포형 홍수추적을 위해 KIMSTORM을 이용하였으며, 격자크기 <TEX>$500{\times}500m$</TEX> 해상도의 198행<TEX>${\times}$</TEX>231열의 총 45,738개의 셀로 모형을 구축하였다. KIMSTORM 모형의 보정 결과, 평균 <TEX>$R^2$</TEX>(coefficient of determination), ME(model efficiency), VCI(volume conservation index)는 지상강우의 경우, 각각 0.83, 0.68, 1.10로 분석되었고, 레이더강우의 경우는 각각 0.80, 0.62, 1.08의 결과를 보였다. The purpose of this study is to evaluate the availability of dual-polarization radar rain for flood routing in Chungju Dam watershed(<TEX>$6,625.8km^2$</TEX>) using KIMSTORM (Grid-based KIneMatic wave STOrm Runoff Model). The Sobaek dual-polarization radar data for 1 heavy rain and 3 typhoon(Khanun, Bolaven, and Sanba) events in 2012 were obtained from Han River Flood Control Office. The spatio-temporal patterns between the two data were similar showing the ratio of radar rain to ground rain with 0.97. The KIMSTORM was set to <TEX>$500{\times}500m$</TEX> resolution and a total of 45,738 cells(198 rows<TEX>${\times}$</TEX>231 columns) for the watershed. For radar rain and 41 ground rains, the model was independently calibrated using discharge data at 3 streamflow gauging stations(YW1, YC, and CJD) with coefficient of determination(<TEX>$R^2$</TEX>), Nash and Sutcliffe Model Efficiency(ME), and Volume Conservation Index(VCI). The <TEX>$R^2$</TEX>, ME, and VCI 0.80, 0.62 and 1.08 for radar rain and 0.83, 0.68 and 1.10 for ground rain respectively.

SWAT modeling of best management practices for Chungju dam watershed in South Korea under future climate change scenarios

Suitable and practicable best management practices (BMPs) need to be developed due to steadily increasing agricultural land development, intensified fertilization practices, and increased soil erosion and pollutant loads from cultivated areas. The soil and water assessment tool model was used to evaluate the present and future proper BMP scenarios for Chungju dam watershed (6,642 km2) of South Korea, which includes rice paddy and upland crop areas. The present (1981–2010) and future (2040s and 2080s) BMPs of streambank stabilization, building recharge structures, conservation tillage, and terrace and contour farming were examined individually in terms of reducing nonpoint source pollution loads by applying MIROC3.2 HiRes A1B and B1 scenarios. Streambank stabilization achieved the highest reductions in sediment and T-N, and slope terracing was a highly effective BMP for sediment and T-P removal in both present and future climate conditions.

Assessment of Snowmelt Impact on Chungju Dam Watershed Inflow Using Terra MODIS Data and SWAT Model

본 연구에서는 충주댐 유역(<TEX>$6,642.0km^2$</TEX>)을 대상으로 Terra MODIS (Moderate-Resolution Imaging Spectroradiometer) 위성영상과 SWAT (Soil and Water Assessment Tool) 모형을 이용하여 융설이 댐유입량에 미치는 영향을 분석하였다. SWAT 모형의 융설 매개변수인 적설면적 감소곡선(Snow Cover Depletion Curve; SCDC)을 결정하기 위해 10 sets (2000-2010)의 Terra MODIS 위성영상으로부터 추출한 적설분포도와 지상 강설자료를 이용하여 구축한 적설심분포도(snow depth distribution; SDD)를 도출한 결과, 50% 적설면적일 때의 적설면적감소계수(sno50cov)는 0.4~0.7의 범위를 가지는 것으로 분석되었다. 매년의 융설 매개변수를 적용하여 융설기간 (11~4월)동안의 유출을 보정한 결과 평균 <TEX>$R^2$</TEX>는 0.54이었다. 10년 동안 융설기간의 유출량은 평균 104.3 mm로 연 유출량의 12.0%를 차지하는 것으로 분석되었다. This study is to evaluate the snowmelt impact on dam inflow for the Chungju Dam watershed <TEX>$6,642.0km^2$</TEX> using Terra MODIS (Moderate-Resolution Imaging Spectroradiometer) and Soil and Water Assessment Tool (SWAT). To determine the SWAT snowmelt parameter; snow cover depletion curve (SCDC) the snow depth distribution (SDD) using Terra MODIS was used, the snow depth was spatially interpolated using snowfall data of ground meteorological stations. For 10 sets (2000-2010) data during snowmelt period (November-April), the sno50cov parameter, that is, the 50% coverage at a fraction of SCDC which determines the shape of snow depletion process, showed the values of 0.4 to 0.7. The SWAT model was calibrated with average <TEX>$R^2$</TEX> of 0.54 using the sno50cov of each year. The 10 years average streamflow during snowmelt period was 104.3 mm which covers 12.0% of the annual streamflow.

고해상도 다중위성 강수자료와 분포형 수문모형의 유출모의 적용

본 연구에서는 다중위성 강수자료의 수문학적 적용성을 평가하기 위하여 Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Global Satellite Mapping of Precipitation (GSMaP), Climate Prediction Center (CPC) Morphing technique(CMORPH) 등 전 지구 규모의 고해상도 다중위성 강수자료와 분포형 수문모형을 이용하여 유출모의를 수행하였다. 충주댐 유역에 대하여 2002년 1월 1일부터 2009년 12월 31일까지의 기간에 대하여 Coupled Routing and Excess Storage (CREST) 모형을 적용하였다. 분석기간은 준비기간(2002-2003년, 2006-2007년), 보정기간(2004-2005년), 그리고 검증기간(2008-2009년)으로 구분하여 모의를 수행하였다. 각 다중위성 강수자료를 지상관측자료와 비교결과, 강수의 계절적 변동특성은 잘 반영하고 있으나 연강수량합계 및 월평균강수량에서 TMPA는 과대추정을, GSMaP과 CMORPH는 과소추정하는 경향을 보여주었다. 또한 유출분석결과, TMPA를 제외한 GSMaP과 CMORPH의 충주댐 유역에 대한 수문학적 적용성이 매우 낮은 것을 알 수 있었으며, 향후 다중위성 강수자료의 활용에 앞서 통계적 보정이나 강수알고리즘에 대한 개선이 필요한 것으로 판단된다. In this study we evaluated the hydrological applicability of multi-satellite precipitation estimates. Three high-resolution global multi-satellite precipitation products, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), the Global Satellite Mapping of Precipitation (GSMaP), and the Climate Precipitation Center (CPC) Morphing technique (CMORPH), were applied to the Coupled Routing and Excess Storage (CREST) model for the evaluation of their hydrological utility. The CREST model was calibrated from 2002 to 2005 and validated from 2006 to 2009 in the Chungju Dam watershed, including two years of warm-up periods (2002-2003 and 2006-2007). Areal-averaged precipitation time series of the multi-satellite data were compared with those of the ground records. The results indicate that the multi-satellite precipitation can reflect the seasonal variation of precipitation in the Chungju Dam watershed. However, TMPA overestimates the amount of annual and monthly precipitation while GSMaP and CMORPH underestimate the precipitation during the period from 2002 to 2009. These biases of multi-satellite precipitation products induce poor performances in hydrological simulation, although TMPA is better than both of GSMaP and CMORPH. Our results indicate that advanced rainfall algorithms may be required to improve its hydrological applicability in South Korea.

충주댐 유역의 유출량에 대한 SWAT 모형의 예측 불확실성 분석 기법 비교

SWAT(Soil and Water Assessment Tool) 모형의 적용성 검증을 위해서는 매개변수 민감도 분석 및 검 보정, 예측 불확실성 분석을 필요로 한다. 최근 SWAT 모형의 불확실성을 분석하기 위한 다양한 기법들이 개발되었는데, 본 연구는 충주댐 유역(6,581.1 <TEX>$km^2$</TEX>)을대상으로유역출구점의 실측 일 유출량자료(1998~2003)를 바탕으로 SWAT 모형의 유출관련 매개변수에 대한 불확실성 분석을 실시하였다. 이때 사용된 분석 기법으로는 SUFI2 (Sequential Uncertainty FItting algorithm ver.2), GLUE(Generalized Likelihood Uncertainty Estimation), ParaSol (Parameter Solution) 등을 적용하였다. 이러한 기법은 모두 SWAT-CUP (SWAT-Calibration Uncertainty Program; Abbaspour et al., 2007) 모형에 탑재되어있으며, 모형의 결과로써 검 보정, 매개변수의 민감도 분석, 각종 목적 함수 및 불확실성의 범위 등이 자동으로 산출되므로 모형의 사용자가 불확실성 평가 기법의 분석 및 비교를 손쉽게 할 수 있다. 그 결과 대표적인 목적 함수인 결정 계수(<TEX>$R^2$</TEX>; Legates and McCabe, 1999)와 NS (Nash and Sutcliffe, 1970) 모형효율은 모두 0.67에서 0.92 사이의 값을 나타내어 대체적으로 모의가 잘 이루어졌음을 알 수 있었다. 그러나 불확실성의 범위를 나타내는 지표인 p-factor 및 r-factor에서는 평가 기법 별로 그 차이가 확연하게 드러났다. 여기서 p-factor는 불확실성 범위에 실측치가 포함되는 비율이며, r-factor는 불확실성의 상대적인 범위로 각각 1과 0에 가까울수록 모의기법의 성능이 우수함을 의미한다. 세가지 알고리듬 중에서 SUFI2의 p-factor가 약 0.79로 가장 높게 나타났으며, ParaSol의 r-factor가 0.03으로 가장 작게 나타났다. 본 연구의 결과는 SWAT 모형을 이용한 수문 모의에서 수문분석에 따른 예측결과의 불확실성을 정량적으로 평가함으로서, 모형의 적용성 평가 및 모의결과의 신뢰성 확보에 근거자료로 활용이 가능할 것으로 판단된다. To fulfill applicability of Soil and Water Assessment Tool (SWAT) model, it is important that this model passes through a careful calibration and uncertainty analysis. In recent years, many researchers have come up with various uncertainty analysis techniques for SWAT model. To determine the differences and similarities of typical techniques, we applied three uncertainty analysis procedures to Chungju Dam watershed (6,581.1 <TEX>$km^2$</TEX>) of South Korea included in SWAT-Calibration Uncertainty Program (SWAT-CUP): Sequential Uncertainty FItting algorithm ver.2 (SUFI2), Generalized Likelihood Uncertainty Estimation (GLUE), Parameter Solution (ParaSol). As a result, there was no significant difference in the objective function values between SUFI2 and GLUE algorithms. However, ParaSol algorithm shows the worst objective functions, and considerable divergence was also showed in 95PPU bands with each other. The p-factor and r-factor appeared from 0.02 to 0.79 and 0.03 to 0.52 differences in streamflow respectively. In general, the ParaSol algorithm showed the lowest p-factor and r-factor, SUFI2 algorithm was the highest in the p-factor and r-factor. Therefore, in the SWAT model calibration and uncertainty analysis of the automatic methods, we suggest the calibration methods considering p-factor and r-factor. The p-factor means the percentage of observations covered by 95PPU (95 Percent Prediction Uncertainty) band, and r-factor is the average thickness of the 95PPU band.

Assessment of MIROC3.2 HiRes Climate and CLUE-s Land Use Change Impacts on Watershed Hydrology Using SWAT

The aim of this study was to evaluate hydrologic impacts of potential climate and land use changes in a mountainous watershed in South Korea. The climatic data predicted by MIROC3.2 HiRes GCM A1B for three time periods (2010-2039, 2040-2069, and 2070-2099) were prepared using a change factor statistical downscaling method. The future land uses were predicted using the Conservation of Land Use and its Effects at Small regional extent (CLUE-s) model by establishing logistic regression model for five land use types with 11 driving forces represented by spatial information. By applying the climate and land use predictions to the Soil and Water Assessment Tool (SWAT), the watershed hydrologic components (including evapotranspiration, surface runoff, groundwater recharge, and streamflow) were evaluated. For the predicted 2070-2099 temperature and precipitation changes (+4.8C and +34.4%), and 6.2% decrease in forest areas and 1.7% increase in urban areas, the combined land use with climate change scenario resulted in more streamflow change (+55.4%) than the single climate and single land use change scenario (+39.8% and +10.8%), respectively. The predicted large increase in future precipitation and the corresponding decrease in forest land are predicted to have substantial impacts on watershed hydrology, especially on surface runoff and streamflow. Therefore, to mitigate negative hydrologic impacts and utilize positive impacts, both land use and climate changes should be considered in water resource planning for the Chungju dam watershed.

Projection of future climate change impacts on nonpoint source pollution loads for a forest dominant dam watershed by reflecting future vegetation canopy in a Soil and Water Assessment Tool model

This study is to assess the future impact of climate change on hydrological behavior considering future vegetation canopy prediction and its propagation to nonpoint source pollution (NPS) loads. The SWAT (Soil and Water Assessment Tool) model was used for the assessment. For a forest dominant ChungjuDam watershed of South Korea, the MIROC3.2hires climate data of SRES A1B and B1 scenarios were adopted and downscaled for the watershed. The future vegetation canopy information was projected by the monthly relationship between Terra MODIS (MODerate resolution Imaging Spectroradiometer) LAI (Leaf Area Index) and temperature. The future predicted LAI increased up to 1.9 in 2080s April and October because of the temperature increase 3.6 degrees C and 5.3 degrees C respectively. By reflecting the future LAI changes, the future estimated percent changes of maximum annual dam inflow, SS, T-N, and T-P were + 42.5% in 2080s A1B,-35.6% in 2020s A1B,+73.7% in 2080s A1B and-21.0% in 2080s B1 scenario respectively. The increase of T-N load was from the increase of subsurface lateral flows and the groundwater recharges by the future rainfall increase. The decrease of T-P load was by decrease of sediment load during wet days because the effect of LAI increase is greater than the increase of rainfall.

SWAT application to estimate design runoff curve number for South Korean conditions

AbstractRunoff estimations based on the standard USDA–NRCS curve number (CN) table without calibration have a tendency to give inaccurate results when the CN values are applied in South Korea which has many high slope watersheds and that has a continental monsoon climate. Particularly for the design flood estimation, accurately calibrated CN values are required because the estimated peak flow is very sensitive to the selection of CN. However, the lack of flood data makes it difficult to calibrate and assign runoff CNs to Korean watersheds. Even if sufficient data are available to estimate CN values, it is also difficult to obtain the direct flows by separating base flows from total runoff hydrographs due to the temporal irregularity of rainfall events and the resulting complex pattern of runoff. Therefore, an alternative method for estimating CNs needs to be developed to overcome these issues.The purpose of this study is to present a method for estimating runoff CNs using the soil and water assessment tool (SWAT) model which can take into account watershed heterogeneities such as climate conditions, land use and soil types. The proposed CN estimation method uses the simulated flow data by SWAT instead of using measured flow data. This method has advantages in estimating CN values spatially for each subbasin division considering watershed characteristics. The use of daily data can reduce the sensitivity to the abnormality that is commonly involved in flow data with a small time scale. The SWAT‐based CN estimation method, combined with the asymptotic CN method, was applied to the Chungju dam watershed in South Korea. A regression equation was then developed from this approach, which was used to estimate CN values that decrease exponentially as rainfall amounts increase and that converge to 60·6 and 79·4 without and with considering subsurface lateral flow, respectively. Furthermore, the CN values for the antecedent moisture conditions were determined using the probabilistic approach. The CN associated with the 50% probability for the Chungju dam watershed is 87·8 which can be taken to be representative of antecedent moisture condition (AMC) II. The CNI and CNIII associated with 90% and 10% probabilities are 78·9 and 94·1, respectively. The estimated CNII = 87·8 differs markedly from the geographic information system (GIS)‐based CN 65·0, which implies that the standard USDA–NRCS CN method should be calibrated to the studied area of interest. Copyright © 2010 John Wiley &amp; Sons, Ltd.

SWAT 모형의 유출해석모듈 개선이 수질모의에 미치는 영향

For reliable water quality simulation by semi distributed model, accurate daily runoff simulation should have preceded. In this study, newly developed channel routing method which is nonlinear storage method is combination of Muskingum routing method and variable storage routing method and temporally weighted average curve number method were applied for effect analysis of water quality simulation. Developed modules, which are added in SWAT models and simulation, were conducted for the Chungju dam watershed. The simulation result by each module applied effect. As a result of analysis contribute water quality modeling, nonlinear storage method is more effective than temporally weighted average curve number method. Nutrient loading discharge was affected by development of runoff delaying from improvement of channel routing, because of characteristics of nonpoint source pollution.

봄철 SWAT 모형의 산림 토양수분과 Terra MODIS 위성영상 NDVI와의 상관성 분석

The purpose of this study is to identify how much the MODIS NDVI (Normalized Difference Vegetation Index) can explain the forest soil moisture simulated from SWAT (Soil and Water Assessment Tool) model. For ChungjuDam watershed () which covers 82.2% of forest, the SWAT model was calibrated for four years (2003-2006) at two locations of the watershed using daily streamflow data and was verified for three years (2000-2002) with average Nash and Sutcliffe model efficiencies of 0.69 and 0.75 respectively. For the period from March to June, the average spatial correlation between 16 days composite MODIS NDVI and the corresponding SWAT forest soil moisture was 0.90. The two variables averaged for each data set during that period showed an inverse relation with the average coefficient of determination of 0.55.

SWAT을 이용한 충주댐 유역의 유출곡선지수 산정 방안

본 연구에서는 기후조건, 토지이용 및 토양조건 등의 유역의 비균질성을 고려할 수 있는 SWAT 모형을 이용하여 홍수량 계산에 활용될 수 있는 유출곡선지수를 산정하는 방법을 제시하였다. 이 방법은 Hawkins 등(1993)이 제시한 점근 유출곡선지수 산정법을 기반으로 하되, 실측 홍수량 시간자료를 직접 이용하지 않고 SWAT에 의한 모의 지표 유출량 일자료를 이용하는 점이 특징이다. SWAT 모형이 지표유출성분량을 산정할 수 있고 소유역 분할에 따른 공간모의 및 유역의 비균질 특성을 반영할 수 있는 장점을 이용한 것이며, 또한 일자료를 이용함으로써 단기사상 자료의 오류에 따른 영향을 최소화할 수 있다. 이 방법에 의해 산정된 유출곡선지수는 모형에 의한 유출량 모의치와 관측치의 적합 과정을 거친 것으로 대상 유역의 유출 특징이 반영된 것이다. 본 제안 방법을 충주댐 상류유역에 대해 적용하여 전체유역 및 임의 소유역의 유출곡선지수를 산정하였고, 이를 강우량에 따라 지수함수형으로 감소하는 회귀식을 제시하였다. The objective of this study is to present a methodology for estimating runoff curve number(CN) using SWAT model which is capable of reflecting watershed heterogeneity such as climate condition, land use, soil type. The proposed CN estimation method is based on the asymptotic CN method and particularly, it uses surface flow data simulated by SWAT. This method has advantages to estimate spatial CN values according to subbasin division and to reflect watershed characteristics because the calibration process has been made by matching the measured and simulated streamflows. Furthermore, the method is not sensitive to rainfall-runoff data since CN estimation is on a daily basis. The SWAT based CN estimation method is applied to Chungju dam watershed. The regression equation of the estimated CN that exponentially decays with the increase of rainfall is presented.

NOAA위성영상 및 기상자료를 이용한 융설 관련 매개변수 추출

Establishment of snowmelt factors is necessary to simulate stream flow using snowmelt models during snowmelt periods. The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. The objective of this study was to extract snowmelt factors using RS, GIS technique and meteorological data. Snow cover maps were derived from NOAA/AVHRR images for the winter seasons from 1997 to 2003. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation station. Depletion curves of snowmelt area were described from the linear regression equations of each year between the average temperature and snow cover area in Soyanggang-dam and chungju-dam watershed.