인공강우에 의한 Crust 형성이 산림토양의 침식과정에 미치는 영향

김명희,민일식 中部大學校 農業開發硏究所 1997 農業開發硏究論文集 Vol.5 No.-

인공강우 장치를 이용하여 발생된 강우에 의한 토양 표면에서의 crust 형성 진행에 따른 침투와 splash erosion및 runoff erosion에 의한 유출량의 변화를 분석하였다. 강우량에 따른 crust 형성 진행 단계에서 표면경사가 10%인 경우 Stage Ⅰ은 강우가 지표면에 도달되는 시점으로부터 runoff 발생 직전까지이며, 강우시작을 기점으로 누적강우가 24.0㎜에 도달했을 때 runoff erosion이 표토에서 발생하기 시작하였다. Stage Ⅱ는 표면유거의 시작부터 runoff 및 splash erosion의 발생이 빠르게 증가하다가 침식량의 변화가 일정하게 지속되기 전까지의 시기로서, 누적강우 130.0㎜까지 계속 침식량이 증가하여 최대유출 이후 Stage Ⅲ에 이르면서 유출량이 점차 감소하였다. 이 단계에서는 infitration의 양은 토양이 완전 포화 상태에 이르렀고 침투량은 전체 인공강우량의 36.23%이었다. Stage Ⅲ은 runoff와 splash erosion 발생비율이 일정하게 유지되는 시기로 더 이상의 infiltration은 진행되지 않았다. splash erosion은 누적강우 130.0㎜일 때보다 감소하였으나, runoff erosion은 Stage Ⅱ 이후에 침식량이 2배 이상 증가하였다. 표면경사가 30%인 경우 StageⅠ에서 runoff 발생 시기(누적강우 18.0㎜) 및 Stage Ⅱ 시기도 86.0㎜로 침식이 빠르게 진행되었다. 또한 infiltration도 전체 강우중 25.99%가 발생하여 경사도의 차이에 따라 유의적으로 변화하였다. 물에 의한 침식과정을 토양의 입경에 따른 변화로 볼 때 표토의 경사 10%의 경우 sand는 splash erosion에서, silt 및 cray는 runoff에서 토양침식량에 대해 차지하는 비율이 각각 높게 나타났다. 침식 이후 잔적토양에서는 경사 위쪽이 silt와 clay 함량이 더 많았으며, sand는 경사 아래쪽에 더 많이 분포하였다. 30%의 표면 경사일 때 splash erosion의 경우 sand의 함량이 많았으며, runoff erosion의 경우 sand는 누적강우가 증가할수록 많아졌으나 silt와 clay는 감소하였다. Soil crusts were formed on the surface after artificial rainfall and reduced the water infiltration rate and induced the erosion processes by increasing runoff and splash. The erosion amounts were investigated by changes of soil crust formation. At the case of 10% surface gradient, the model was divided three stages by crust formation. Stage I was from the arrival of raindrop to soil-surface through the artificial rainfall simulator to the initiation of runoff erosion, until 24.0㎜-cummulative rainfall input. Stage Ⅱ was from starting surface runoff, which the development of runoff and splash erosion rapidly increased, to steady state of erosion changes, until 130.0㎜-cummulative rainfall. Splash erosion were gradually decreased in Stage Ⅲ, in contrary to runoff being continuously increased. In this Stage soil was absolutely saturated, so that infiltration rate was 36.23% of total rainfall input. Splash erosion was decreased than 130.0㎜-cummulative rainfall, but runoff erosion was increased twice than erosion amount at Stage Ⅱ. In case of 30% gradient of soil surface, starting runoff erosion, in Stage Ⅰ, relatively early occurred at 18.0㎜-cummulative rainfall , and in Stage Ⅱ runoff and splash erosion rapidly proceeded. Infiltration rate also was 25.99% of total precipitaion and significantly changed by gradient degree. Mechanical analysis had a difference by water erosion. In case of 10% gradient, sands were accompanied the most with splash erosion, however, silts and clays occupied larger with runoff erosion. The results of mechanical analysis of the residual soil after erosion were indicated that sands largely distributed to the lower slope. When investigating 30% gradient, splash erosion had more sand amount, and in runoff erosion sands were increased with increasing rainfall input, while silt and clay were decreased.

Shot Noise Process 기반 강우-유출 모형을 이용한 유출 앙상블 멤버 생성

강민석,조은샘,유철상 한국수자원학회 2019 한국수자원학회논문집 Vol.52 No.9

This study proposes a method to generate runoff ensemble members using a rainfall-runoff model based on the shot noise process (hereafter the rainfall-runoff model). The proposed method was applied to generate runoff ensemble members for three drainage basins of Daerim 2, Guro 1 and the Jungdong, whose results were then compared with the observed. The parameters of the rainfall-runoff model were estimated using the empirical formulas like the Kerby, Kraven II and Russel, also the concept of modified rational formula. Gamma and exponential distributions were used to generate random numbers of the parameters of the rainfall-runoff model. Especially, the gamma distribution is found to be useful to generate various random numbers depending on the pre-assigned relationship between mean and standard deviation. Comparison between the generated runoff ensemble members and the observed shows that those runoff ensemble members generated using the gamma distribution with its standard deviation twice of the mean properly cover the observed runoff. 본 연구에서는 shot noise process 기반 강우-유출 모형(이하 강우-유출 모형)을 이용하여 유출 앙상블 멤버를 생성하는 방법을 제안하였다. 아울러 제안된 방법을 적용하여 대림 2, 구로 1, 중동 빗물펌프장 등 3개 배수유역에 대한 유출 앙상블 멤버를 생성하고, 이를 관측 유출량과 비교해 보았다. 강우-유출 모형의 매개변수는 Kerby 공식, Kraven II 공식, Russel 공식 및 수정합리식의 개념을 이용하여 추정하였다. 강우-유출 모형 매개변수의 난수 발생을 위해서는 감마분포와 지수분포를 이용하였다. 특히, 감마분포의 경우에는 평균과 표준편차의 관계를 어떻게 설정하느냐에 따라 다양한 난수 발생이 가능함을 확인하였다. 생성된 유출 앙상블과 관측 유출량과의 비교 결과, 표준편차가 평균의 두 배인 감마 분포를 이용하여 만든 유출 앙상블이 관측 유출량을 가장 적절히 포괄함을 확인하였다.

A Simple Model for Runoff Predictability

Roman Olson,Axel Timmermann,June-Yi Lee,Soon-Il An 한국기상학회 2021 한국기상학회 학술대회 논문집 Vol.2021 No.10

Recent work has identified potential multi-year predictability in soil moisture (Chikamoto et al., 2015). Whether this long-term predictability translates into an extended predictability of runoff still remains an open question. To address this question we develop a physically-based zero-dimensional stochastic runoff model. The model extends previous work of Dolgonosov and Korchagin (2007) by including a runoff-generating soil moisture threshold. We consider several assumptions on the input rainfall noise. We analyze the applicability of analytical solutions for the stationary probability density function (pdf) and for the waiting time for runoff under different assumptions. Out results suggest that knowing soil moisture provides important information on the waiting time for runoff. In addition, we fit the simple model to the daily NCEP1 reanalysis output on a near-global scale, and analyze the fitted model performance. Over many tropical regions, the model reproduces the simulated runoff in NCEP1 reasonably well. More detailed analysis over a single gridpoint illustrates that the model, despite its simplicity, is able to capture some key features of the runoff time series and pdfs of a more complex model. Our model exhibits runoff predictability of up to two months in advance. Our results suggest that there is an optimal predictability “window” in the transition zone between runoff-generating and dry conditions. Our model can serve as a “null hypothesis” model reference against more complex models for runoff predictability.

설마천 연구지역에서의 토양수분량을 활용한 유출 발생 특성분석

김기영,이용준,정성원,이연길 한국수자원학회 2019 한국수자원학회논문집 Vol.52 No.9

Soil moisture and runoff have very close relationship. Especially the water retention capacity and drainage characteristics of the soil are determined by various factors of the soil. In this study, a total of 40 rainfall events were identified from the entire rainfall events of Sulma basin in 2016 and 2017. For each selected events, the constant-K method was used to separate direct runoff and baseflow from total flow and calculate the runoff coefficient which shows positive exponential curve with Antecedent Soil Moisture (ASM). In addition to that, the threshold of soil moisture was determined at the point where the runoff coefficient starts increasing dramatically. The threshold of soil moisture shows great correlation with runoff and depth to water table. It was founded that not only ASM but also various factors, such as Initial Soil Moisture (ISM), storage capacity of soil and precipitation, affect the results of runoff response. Furthermore, wet condition and dry condition are separated by ASM threshold and the start and peak response are analyzed. And the results show that the response under wet condition occurred more quickly than that of dry condition. In most events occurred in dry condition, factors reached peak in order of soil moisture, depth to water table and runoff. However, in wet condition, they reached peak in order of depth to water table, runoff and soil moisture. These results will help identify the interaction among factors which affect the runoff, and it will help establish the relationship between various soil conditions and runoff. 토양수분과 유출은 매우 밀접한 관계를 가지고 있으며, 특히 토양 내의 여러 요소들에 의해 토양의 수분보유능력과 배수의 특성이 결정된다. 본 연구에서는 2016년, 2017년 설마천 유역에서 총 40개의 사상을 분리하였다. 선정한 사상별로 constant-K 방법을 적용하여 직접유출과 기저유출을 분리하고 유출계수를 산정하였다. 산정된 유출계수는 선행토양함수와 지수함수 형태의 증가를 보였다. 또한 유출계수가 급증하기 시작하는 토양수분의 임계값을 선정하였으며, 이 값은 유출과 지하수면과의 큰 상관관계를 나타내었다. 선행토양함수뿐만 아니라 초기 토양수분, 토양 저류량, 강우량 등 여러 인자들도 유출 결과에 영향을 미치는 것으로 분석되었다. 또한 선행토양수분의 임계값에 따라 강우사상을 건조, 습윤 상태로 분리하여 시작 반응과 첨두 반응을 분석해 보았으며, 습윤 상태에서의 반응이 건조 상태에서 보다 빠르게 발생하였다. 건조 상태에 속하는 대부분의 사상에서는 토양수분이 정점에 도달한 후 지하수면과 유출량 순으로 정점에 도달하는 첨두 반응이 일어났으나 습윤 상태에서는 반대로 지하수면과 유출량이 토양수분보다 먼저 정점에 도달하였다. 본 연구의 결과는 유출에 기여하는 인자들 사이의 상호작용을 확인하고 토양의 다양한 조건과 유출 사이의 관계를 규명하는 데에 크게 기여할 것으로 판단된다.

Characterization of Road Runoff and Performance Assesment of Hydrodynamic Filter Separator

이준호,방기웅 한국도시환경학회 2010 한국도시환경학회지 Vol.10 No.2

Storm runoff from road contains significant loads of micro particles, heavy metals and organic constituents. The majority of storm runoff pollution is trapped in particles smaller than 100 μm in diameter. Storm water data collected from two road sites in the Chungbuk, Korea areas to characterize the road runoff. The quantity of road runoff and quality constituents, including COD, SS, TKN, PO4-P, TP, Fe, Cd, Cu, Cr and particle size distribution were analyzed. There were three major objectives of this study. The first objective was to characterize the road runoff and first flush. The second objective was to measure and evaluate particle size distribution of the road runoff. The final objective was the assessment of the hydrodynamic filter separator (HDFS) for treatment of micro particle in road runoff. Because many road runoff pollutants are associated with micro particles, new device called hydrodynamic filter separator has been developed for the treatment of road runoff.

Temporally weighted average curve number method for daily runoff simulation

Kim, Nam Won,Lee, Jeongwoo John Wiley Sons, Ltd. 2008 Hydrological processes Vol.22 No.25

<P>The modified Soil Conservation Service curve number (CN) method is widely used in long-term continuous models to predict daily surface runoff. However, it has been shown that this method gives poor results in reproducing peak flows in high rainfall periods. This is because there is an inaccuracy stemming from the model algorithm as it adjusts the daily runoff curve number as a function of soil moisture content at the end of the previous day. This paper proposes an alternative daily based curve number technique that can provide better prediction of daily runoff during the high flow season. The proposed method uses the temporally weighted average curve number (TWA-CN) to estimate daily surface runoff, while considering the effect of rainfall during a given day as well as the antecedent soil moisture condition. To test the applicability of the TWA-CN method, it was incorporated with the long-term, continuous simulation watershed models SWAT and SWAT-G. Simulations were conducted for the Miho River watershed located in the middle of South Korea. The graphical displays and statistics of the determination coefficient (R<SUP>2</SUP>) and the Nash–Sutcliffe model efficiency (NSE) of the observed and simulated daily runoff indicated that the modified SWAT with the TWA-CN method may provide better runoff prediction (R<SUP>2</SUP> = 0·837, NSE = 0·833) than the original SWAT (R<SUP>2</SUP> = 0·815, NSE = 0·824). Likewise, the determination coefficient (R<SUP>2</SUP> = 0·816) and the Nash–Sutcliffe efficiency (NSE = 0·834) for the modified SWAT-G are also higher than the original version (R<SUP>2</SUP> = 0·782, NSE = 0·825). It is expected that the improved capability in predicting surface runoff using the suggested CN estimate method will provide a sound contribution to the accurate simulations of water yield. Copyright © 2008 John Wiley & Sons, Ltd.</P>

지형공간 특성자료를 이용한 하천유역의 강우-유출해석

안승섭,이증석,도준현 한국환경과학회 2003 한국환경과학회지 Vol.12 No.9

The subject basin of the research was the basin of Yeongcheon Dam located in the upper reaches of the Kumho River. The parameters of the model were derived from the results of abstracting topological properties out of rainfall-runoff observation data about heavy rains and Digital Elevation Modeling(DEM) materials. This research aimed at suggesting the applicability of the CELLMOD Model. a distribution-type model, in interpreting runoff based on the topological properties of a river basin, by carrying out runoff interpretation for heavy rains using the model. To examine the applicability of the model, the calculated peaking characteristics in the hydrograph was analyzed in comparison with observed values and interpretation results by the Clark Model. According to the result of analysis using the CELLMOD Model proposed in the present research for interpreting the rainfall-runoff process, the model reduced the physical uncertainty in the rainfall-runoff process, and consequently, generated improved results in forecasting river runoff. Therefore it was concluded that the algorithm is appropriate for interpreting rainfall-runoff in river basins. However, to enhance accuracy in interpreting rainfall-runoff. it is necessary to supplement heavy rain patterns in subject basins and to subdivide a basin into minor basins for analysis. In addition, it is necessary to apply the model to basins that have sufficient observation data, and to identify the correlation between model parameters and the basin characteristics(channel characteristics).

레이더 강수량과 PRMS 모형을 이용한 유출량 평가

김태정,김성훈,이성호,김창성,권현한 한국수자원학회 2020 한국수자원학회논문집 Vol.53 No.7

The rainfall-runoff model has been generally adopted to obtain a consistent runoff sequence with the use of the long-term ground-gauged based precipitation data. The Thiessen polygon is a commonly applied approach for estimating the mean areal rainfall from the ground-gauged precipitation by assigning weight based on the relative areas delineated by a polygon. However, spatial bias is likely to increase due to a sparse network of the rain gauge. This study aims to generate continuous runoff sequences with the mean areal rainfall obtained from radar rainfall estimates through a PRMS rainfall-runoff model. Here, the systematic error of radar rainfall is corrected by applying the G/R Ratio. The results showed that the estimated runoff using the corrected radar rainfall estimates are largely similar and comparable to that of the Thiessen. More importantly, one can expect that the mean areal rainfall obtained from the radar rainfall estimates are more desirable than that of the ground in terms of representing rainfall patterns in space, which in turn leads to significant improvement in the estimation of runoff. 현재 유역단위 수문해석을 목적으로 장기간 자료 확보가 용이하고 신뢰도가 확보된 지상관측소 강수량 자료를 강우-유출 모형을 활용하여 유출량을 평가하고 있다. 지상관측소 강수량 자료를 이용하여 면적평균 강수량을 산정하는데 있어 일반적으로 지상관측소의 위치 정보를 바탕으로 Thiessen 다각형법을 널리 이용하고 있으나 지상관측소의 공간적 편중으로 인해 면적평균 강수량 산정과정에서 제약이 있다. 본 연구에서는 시공간적으로 연속적인 강수량 관측이 가능한 기상레이더 자료를 이용하여 유역단위 면적평균 강수량을 산정하고 이를 PRMS 모형의 입력 자료로 활용하여 유출량을 평가하였다. 세부적으로 레이더 강수량의 편의 오차를 해결하기 위하여 G/R Ratio 기법을 적용하여 유역별로 레이더 강수량을 보정하였다. 레이더 강수량을 이용한 유출특성은 Thiessen 면적강수량을 이용한 유출의 통계적 특성을 현실적으로 재현하였다. 지상 관측소에 의존하여 생산하는 Thiessen 면적강수량에 비하여 레이더 강수량을 활용하는 것이 유역에 발생하는 강수의 공간적 특성을 효과적으로 반영하는 것으로 사료되며 향후 수문해석에서 정확도를 확보한 유출량을 제시할 것으로 판단된다.

주차장 지역의 강우에 의한 Pb와 Zn의 유출 특성

임종권 ( Jong Kwon Im ),손현석 ( Hyun Seok Son ),김성근 ( Sung Keun Kim ),조경덕 ( Kyung Duk Zoh ) 한국물환경학회 2010 한국물환경학회지 Vol.26 No.6

Runoff from a parking lot can be highly contaminated nonpoint source due to the impermeability of rainwater. This study presented runoff characteristics of heavy metals especially Zn and Pb from a parking lot during total 17 rain events. Monitoring results showed the first flush phenomenon within 30 min was observed in all rain events, but the event mean concentration (EMC) did not clearly show the characteristics of runoff. The ranges of Pb and Zn was 4~20l μg/L and l3l~672 μg/L, respectively, and the runoff mass of Zn and Pb was highly to related with the flow rate, and runoff coefficient of rain. The runoff mass of Zn was greater than that of Pb in all events. The runoff mass of Pb was highly correlated with the amount of TSS, and TSS and DOC were was related with the mass of Zn. This result implies that Pb and Zn are mainly existed in the particulate form. The results can be used to as meaningful data in the management of nonpoint source, and in the management in the runoff catchment in the parking lot.

Hybrid 모델을 이용한 하천 유출량 예측

문병석 ( Byoung-seok Moon ),이현기 ( Hyeon-ki Lee ),박근홍 ( Geun-hong Park ) 한국환경기술학회 2014 한국환경기술학회지 Vol.15 No.1

하천유역에서 유출량을 예측하기 위해서는 강우-유출과정을 잘 모형화해야 하지만 수문자료의 비선형성, 비정규성 및 시공간적 다양성 등 여러 가지 요인에 의해서 많은 오차를 내포하고 있다. 그러나 최근 들어 이러한 문제점을 해결하기 위해 인공 신경망 및 퍼지이론 등의 인공지능 모형이 강우-유출 모형에 많이 적용되고 있는 실정이다. 그러나 인공 신경망의 과도한 학습시간과 진동학습(지역최소점에 빠진경우)의 문제점을 극복하지 못한 것으로 나타났다. 따라서 본 연구에서는 인공 신경망 모형의 단점을 극복하기 위해 인공 신경망모형에 유전자 알고리즘(genetic algorithm)을 결합한 결합(hybrid)모형에 의한 하천 실시간 하천 유출량을 예측하였다. 본 연구의 목표지점은 섬진강 수계의 한 지류인 요천에 있는 남원 수위표지점과 섬진강 수계의 본류에 있는 구례 수위표지점을 선정하였다. 본 연구에 사용한 자료는 각 목표지점에 영향을 미치는 강우자료, 상류 지역 및 목표지점의 유출량 자료이다. 하천 유출량 예측을 위한 모형을 구성하기 위해 먼저 강우량 자료는 지점강우량을 면적평균강우량으로 환산하였다. 그리고 면적평균강우량 및 각 유출량의 자기상관함수 및 교차상관함수를 구해 모형을 구성하여 하천의 유출량을 예측하였다. 예측된 결과를 실측치와 통계적학적으로 비교한 결과 모델 1을 제외한 모델들이 통계적 특성을 잘 반영하고 있음을 알 수 있었다. The prediction of the runoff in a drainage basin requires modeling for the process of rainfall runoff. Modeling of the rainfall-runoff process generally results in many aberrations due to various factors such as nonlinear and irregular characteristics of hydrological data and variables in time and space. In order to resolve these problems, artificial intelligence models such as the artificial neural network (ANN) and fuzzy theory have recently been widely applied in this field. This study predicts real-time runoff based on the hybrid model of ANN and genetic algorithm (GA). The two areas observed in this study were a stage gate in Yo-river, a branch stream of the Sumjin-river the main stream of the Sumjin-river. The data used in this study included rainfall and runoff of the upper streams of the two areas. In order to establish the prediction model for runoff, the point rainfall figures were translated into those of mean area rainfall. Mean area rainfalls, auto correlation function of each runoff, and cross correlation function were then used for the model. The comparison between the estimates and the observational runoff showed that all the models reflect statistical characteristics correctly expect model 1.