• Korean Journal of Environmental Agriculture
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• v.31 no.4
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• pp.318-327
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• 2012

BACKGROUND: For Non-Point Source(NPS) loads reduction, pollutant loads need to be quantified for major farming methods. The objective of this study was to evaluate impacts of farming methods on NPS pollutant loads from a paddy rice field during the growing season. METHODS AND RESULTS: The height of drainage outlet, amount of fertilizer, irrigation water quality were considered as farming factors for scenarios development. The control was derived from conventional farming methods and four different scenarios were developed based combination of farming factors. A field scale model, CREAMS-PADDY(Chemicals, Runoff, and Erosion from Agricultural Management Systems for PADDY), was used to calculate pollutant nutrient loads. The data collected from an experimental plot located downstream of the Idong reservoir were used for model calibration and validation. The simulation results agreed well with observed values during the calibration and validation periods. The calibrated model was used to evaluate farming scenarios in terms of NPS loads. Pollutant loads for T-N, T-P were reduced by 5~62%, 8~37% with increasing the height of drainage outlet from 100 mm of 100 mm, respectively. When amount of fertilizer was changed from standard to conventional, T-N, T-P pollutant loads were reduced by 0~22%, 0~24%. Irrigation water quality below water criteria IV of reservoir increased T-N of 9~65%, T-P of 9~47% in comparison with conventional. CONCLUSION(S): The results indicated that applying increased the height of drainage after midsummer drainage, standard fertilization level during non-rainy seasons, irrigation water quality below water criteria IV of reservoir were effective farming methods to reduce NPS pollutant loads from paddy in Korea.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.779-789
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• 2016

The effective rainfall is calculated considering the soil moisture. It utilizes observed data directly in order to incorporate the soil moisture into the rainfall-runoff model, or it calculates indirectly within the model. The rainfall-runoff model, IHACRES, used in this study computes the catchment wetness index (CWI) first varying with temperature and utilize it for estimating precipitation loss. The nonlinear relationship between the CWI and the effective rainfall in the Hapcheondam watershed was derived and utilized for the long-term runoff calculation. The effects of variable and constant CWI during calibration and validation were suggested by flow regime. The results show the variable CWI is generally more effective than the constant CWI. The $R^2$ during high flow period shows relatively higher than the ones during normal or low flow period, but the difference between cases of the variable and constant CWI was insignificant. The results indicates that the high flow is relatively less sensitive to the evaporation and soil moisture associated with temperature. On the other hand, the variable CWI gives more desirable results during normal and low flow periods which means that it is crucial to incorporate evaporation and soil moisture depending on temperature into long-term continuous runoff simulation. The NSE tends to decrease during high flow period with high variability which could be natural because NSE index is largely influenced by outliers of underlying variable. Nevertheless overall NSE shows satisfactory range higher than 0.9. The utilization of variable CWI during normal and low flow period would improve the computation of long-term rainfall-runoff simulation.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1656-1660
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• 2006

도시 주변의 급격한 택지개발, 도시 인구의 집중, 대규모 계획단지의 개발은 유역의 유출특성에 큰 영향을 주게 되고, 도시화가 진행됨에 따라 불투수 표면이 증가되고 침투율이 감소됨으로써 유출계수의 증가요인이 되고 있다. 이에 따라 유역의 자연 저류지 기능이 저하되고, 우수가 하천으로 유입되는 시간이 단축됨으로써 첨두홍수량 뿐만 아니라 유출총량의 증대를 초래하여 도시 주변의 중소하천 유역에서는 막대한 재산 및 인명 피해가 발생하고 있다. 이러한 도시화로 인해 증가된 유출량을 저감시키는 구조적 방안으로 대부분 강우 유출수를 일시 저류하여 유출량을 조절하는 우수유출 억제시설이 권장되고 있으나, 이들 시설에 대한 수리학적 침수방어능력이 명확히 규명되지 못한 실정이다. 본 연구의 목적은 도시지역 침수방지 대책 수립에 필요한 On/Off-Line 저류지의 평가 및 설계에 기존 부정류 모형들의 모의가능성을 평가 비교하고, 가상하도와 실제하도에 적용하여 모형을 검보정 함으로서 저류지 해석의 실용화 모형을 확립함에 있다. 본 연구 결과는 도시지역에 적용할 수 있는 도시홍수방어시스템의 일환으로 구축함으로써, 도시지역에서 저류지 홍수저감효과를 평가하는 등 침수재해와 연계된 구조적 대책 수립에 필요한 기초자료로 활용하고자 한다. 본 연구에서 연구된 저류지 모형을 이용하여 On-Line 및 Off-Line 저류지에 적용한 결과 두 종류의 저류지 모두 홍수방어를 위해 이용될 수 있었다. On/Off-Line 저류지 모두 첨두유량이 발생할 경우 어느정도의 첨두값의 감쇠를 발생시킬 수 있는 것으로 판단된다. 그러나 저류지 상류단의 수위감소는 저류지로 유출로 인해 저류지 상류 하도부에서 유속의 증가를 발생시켰고 이로 인해 수위는 저류지가 존재하지 않는 경우보다 낮게 나타나고 있다. On-Line 저류지의 경우 Off-Line 의 경우에 비해 수위, 유량이 저류지의 상류단에서 크게 나타났다. On-Line 저류지의 경우 Off-Line 의 경우에 비해 같은 값의 첨두홍수량을 저류하기 위해서 상대적으로 넓은 저류면적이 필요한 것으로 나타난다. 대등한 수위감소값의 홍수저감효과를 발휘하기 위해서 본 연구에서는 On-Line 저류지 면적은 Off-Line 저류지에 비 두배 이상이 필요한 것으로 보여졌다.

• Proceedings of the KAIS Fall Conference
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• 2007.11a
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• pp.109-112
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• 2007

본 연구에서는 댐 하류지역의 물관리를 위한 기초자료를 제공하기 위해 금강수계의 댐 하류지역인 논산지점을 대상으로 기 개발된 수위-유량 곡선식에 의해 추정된 유출량과 RRFS에 의해 추정된 유출량을 실제 분석하고자하는 시점에서 도보측정에 의해 측정된 유출량과 비교하였다. 이러한 유출분석을 위해 유출분석의 기초자료인 논산유역의 면적강우량을 산정하고자 8개의 강우관측지점을 선정하고 티센계수를 구하였다. 각 방법별 유출량의 비교를 위해 도보측정에 의한 유출량은 2005년부터 2006년까지 각각 39회와 40회에 걸쳐 추정되었고 기 개발된 수위-유량곡선식에 의한 유출량은 국가수자원관리 종합시스템에서 제공하는 수위-유량곡선식을 사용하여 추정되었으며 RRFS에 의한 유출량은 매개변수의 민감도분석과 보정에 의해 추정되었다. 이들 방법에 의한 유출량 중에서 도보측정에 의한 유출량을 참값으로 가정하고 수위-유량곡선식에 의한 유출량과 RRFS에 의한 유출량, 각각에 대한 상대평균제곱근오차와 상대절대오차를 구하였다. 이러한 오차분석 결과에서 2005년과 2006년 모두 RRFS에 의한 유출량이 기 개발된 수위-유량 곡선식에 의한 유출량보다 도보 측정에 의한 유출량에 더 근접하는 좋은 결과를 나타내었다. 따라서 향후 댐 하류 주요지점을 대상으로 유출분석을 실시할 경우 본 연구와 같은 분석 절차를 거쳐야 할 것이다.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of Environmental Impact Assessment
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• v.24 no.1
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• pp.16-34
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• 2015

Impervious covers(IC) are artificial structures, such as driveways, sidewalks, building's roofs, and parking lots, through which water cannot infiltrate into the soil. IC is an environmental concern because the pavement materials seal the soil surface, decreasing rainwater infiltration and natural groundwater recharge, and consequently disturb the hydrological cycle in a watershed. Increase of IC in a watershed can cause more frequent flooding, higher flood peaks, groundwater drawdown, dry river, and decline of water quality and ecosystem health. There has been an increased public interest in the institutional adoption of LID(Low Impact Development) and GI(Green Infrastructure) techniques to address the adverse impact of IC. The objectives of this study were to construct the modeling site for a samll urban watershed with the Storm Water Management Model(SWMM), and to evaluate the effect of various LID techniques on the control of rainfall runoff processes and non-point pollutant load. The model was calibrated and validated using the field data collected during two flood events on July 17 and August 11, 2009, respectively, and applied to a complex area, where is consist of apartments, school, roads, park, etc. The LID techniques applied to the impervious area were decentralized rainwater management measures such as pervious cover and green roof. The results showed that the increase of perviousness land cover through LID applications decreases the runoff volume and pollutants loading during flood events. In particular, applications of pervious pavement for parking lots and sidewalk, green roof, and their combinations reduced the total volume of runoff by 15~61 % and non-point pollutant loads by TSS 22~72 %, BOD 23~71 %, COD 22~71 %, TN 15~79 %, TP 9~64 % in the study site.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.29-29
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• 2011

SWAT (Soil and Water Assessment Tool) 모형은 물리적 기반의 준분포형 강우-유출 모형으로서, 대규모의 복잡한 유역에서 장기간에 걸친 다양한 종류의 토양과 토지이용 및 토지관리 상태에 따른 유출과 유사 및 오염물질의 거동에 대한 토지관리 방법의 영향을 예측이 가능하여, 수자원 관리 계획 및 유역관리를 위한 의사결정 지원 등 그 적용 범위가 매우 광범위하다. 이러한 모형의 적용성 검증을 위해서는 매개변수 민감도 분석 및 검 보정, 예측 불확실성 분석을 필요로 한다. 최근 수문 모델의 불확실성을 분석하기 위한 다양한 기법들이 개발 되었는데, 본 연구는 충주댐 유역(6,581.1 m)을 대상으로 유역출구점의 실측 일 유출량 자료(1998~2003)를 바탕으로 SWAT 모형의 유출관련 매개변수(총 18개)에 대한 불확실성 분석을 실시하였다. 이때 사용된 분석 기법으로는 SUFI2 (Sequential Uncertainty FItting algorithm 2), GLUE (Generalized Likelihood Uncertainty Estimation), ParaSol (Parameter Solution)등을 적용 하였다. 이러한 기법은 모두 SWAT-CUP (SWAT-Calibration Uncertainty Program, Abbaspour, 2007) 모형에 탑재되어있으며, 모형의 결과로써 검 보정, 매개변수의 민감도 분석, 각종 목적 함수 및 불확실성의 범위 등이 자동으로 산출 되므로 모형의 사용자가 불확실성 평가 기법의 분석 및 비교를 손쉽게 할 수 있다. 그 결과 대표적인 목적 함수인 결정 계수( $^2$)와 NSE (Nash-Sutcliffe Model Efficiency)는 모두 0.65에서 0.92사이의 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 모의 기법의 성능이 우수함을 의미한다. 세 가지 알고리듬 중에서 SUFI2의 p-factor가 약 0.51로 가장 높게 나타났으며, ParaSol의 r-factor가 0.00으로 가장 작게 나타났다. 여기서 p-factor는 불확실성 범위에 실측치가 포함되는 비율이며, r-factor는 불확실성의 상대적인 범위를 의미한다. 본 연구의 결과는 SWAT 모형을 이용한 수문모델링에서 수문분석에 따른 예측결과의 불확실성을 정량적으로 평가함으로서, 모형의 적용성 평가 및 모의결과의 신뢰성 확보에 근거자료로 활용이 가능할 것으로 판단된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.289-297
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• 2010

Common practice of Soil Water Assessment Tool (SWAT) model validation is to use a single variable (i.e., streamlfow) to calibrate SWAT model due to the paucity of actual hydrological measurement data in Korea. This approach, however, often causes errors in the simulated results because of numerous sources of uncertainty and complexity of SWAT model. We employed multi-variables (i.e., streamflow, evapotranspiration, and soil moisture), which were measured at mixed forest in Seolmacheon catchment ($8.54\;km^2$), in order to assess the performance and reduce the uncertainties of SWAT model output. Meteorological and surface topographical data of the catchment were obtained as basic input variables and SWAT model was calibrated using daily data of streamflow (Jan. - Dec.), evapotranspiration (Sep. - Dec.), and soil moisture (Jun. - Dec.) collected in 2007. The model performance was assessed by comparing its results with the observation (i.e., streamflow of 2003 to 2008 and evapotranspiration and soil moisture of 2008). When the multi-variable measurements were used to calibrate the SWAT model, the model results showed better agreement with the measurements compared to those using a single variable measurement by showing increases in coefficient of determination ($R^2$) from 0.72 to 0.76 for streamflow, from 0.49 to 0.59 for soil moisture, and from 0.52 to 0.59 for evapotranspiration. The findings highlight the importance of reliable and accurate collective observation data for improving performance of SWAT model and promote its facilitation for estimating more realistic hydrological cycles at catchment scale.

• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.985-997
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• 2020

SWAT (Soil and Water Assessment Tool)-MODFLOW (Modular Groundwater Flow) is a coupled model that linking semi-distributed watershed hydrology with fully-distributed groundwater behavior. In this study, the groundwater simulation results of SWAT and SWAT-MODFLOW were compared for Bokhacheon watershed in Namhan river basin. The models were calibrated and validated with 9 years (2009~2017) daily streamflow (Q) data of Heungcheon (HC) water level gauge station and the daily groundwater level observation data of Yulheon (YH). For SWAT, the groundwater parameters of GW_DELAY, GWQMN, and ALPHA_BF affecting baseflow and recession phase were treated. The SWAT results showed the coefficient of determination (R²) of 0.7 and Nash-Sutcliffe model efficiencies (NES_Q, NSE_inQ) for Q and 1/Q with 0.73 and -0.1 respectively. For SWAT-MODFLOW, the spatio-temporal aquifer hydraulic conductivity (K, m/day), specific storage (S_s, 1/m), and specific yield (S_y) were applied. The SWAT-MODFLOW showed R², NSE_Q, and NSE_inQ of 0.69, 0.74, and 0.51 respectively. The SWAT-MODFLOW considerably enhanced the low flow simulation with the help of aquifer physical information. The total streamflow of SWAT and SWAT-MODFLOW were 718.6 mm and 854.9 mm occupying baseflow of 342.9 mm and 423.5 mm respectively.