• Journal of The Korean Society of Agricultural Engineers
• /
• v.49 no.3
• /
• pp.21-31
• /
• 2007

This study is aimed at the development of a runoff forecasting model by using the Fuzzy inference system and Neural Network model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting. The Neuro-Fuzzy (NF) model were used in this study. The NF model, recently received a great deal of attention, improve the existing Neural Networks by the aid of the Fuzzy theory applied to each node. The study area is the downstreams of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model respectively. The schematic diagram method and the statistical analysis are conducted to evaluate the feasibility of rainfall-runoff modeling. The model accuracy was rapidly decreased as the forecasting time became longer. The NF model can give accurate runoff forecasts up to 4 hours ahead in standard above the Determination coefficient $(R^2)$ 0.7. In the comparison of the runoff forecasting using the NF and TANK models, characteristics of peak runoff in the TANK model was higher than ones in the NF models, but peak values of hydrograph in the NF models were similar.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.24 no.4
• /
• pp.99-108
• /
• 1982

This thesis aims to estimate the rainfall runoff from paddy field in a small watershed during irrigation period. When the data observed at the proposed site are not available, the Monthly Runoff Equation of Korean Rivers which was derived from data observed under the following assumptions is used to study the water balance. a. Monthly base flow was assumed as 10. 2mm even if these is no mouthly rainmfall. b. Monthly comsumption of rainfall was ranged from 100 to 2OOmm without relation to the rainfall depth. However, the small watershed which consists mainly of paddy fields encounters severe droughts and accordingly the baseflow is negligible. Under the circumstances the author has developed the following equation called "Flood Irrigation Method for Rainfall Runoff "taking account of the evapotranspiration, precipitation, seepage, less of transportation, etc. R= __ A 7000(1 +F) -5n(n+1)+ (n+1)(Pr-S-Et)] where: R: runoff (ha-m) A: catchment area (ha) F: coefficient of loss (o.o-0. 20) Pr: rainfall (mm) S: seepage Er: evapotranspiration (mm) To verify the above equation, the annual runoff ratio for 28 years was estimated using the Monthly Runoff Equation of Korean Rivers the Flood Irrigation Method and the Complex Hydrograph Method based on meteorological data observed in the Dae Eyeog project area, and comparison was made with data observed in the Han River basin. Consequently, the auther has concluded that the Flood Irrigation Method is more consi- stent with the Complex Hydrograph Method and data observed than the Monthly Runoff Equation of Korean Rivers.

• Journal of Environmental Science International
• /
• v.15 no.2
• /
• pp.141-155
• /
• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• Journal of Korean Society of Water and Wastewater
• /
• v.23 no.5
• /
• pp.599-608
• /
• 2009

This manuscript covers the results of field investigation and lab-scale experiments to design a double-layered biofilter system to control urban storm runoff. The biofilter system consisted of a coarse soil layer (CSL) for filtration and fine soil layer (FSL) for adsorption and biological degradation. The variations of flow rate and water quality of runoff from a local expressway were monitored for seven storm events. Laboratory column experiments were performed using seven kinds of soil and mulch to maximize pollutants removal. The site mean concentration (SMC) of storm runoff from the drainage area (runoff coefficient: 0.92) was measured to be 203 mg/L for SS, 307 mg/L for $TCOD_{Cr}$, 12.3 mg/L for TN, 7.3 mg/L for ${NH_4}^+-N$, and 0.79 mg/L for TP, respectively. This study employed a new design concept, to cover the maximum rainfall intensity with one month recurrence interval. Effective storms for last ten years (1998-2007) in seoul suggested the design rainfull intensity to be 8.8 mm/hr Single layer soil column showed the maximum removal rate of pollutants load when the uniformity coefficient of CSL was 1.58 and the silt/clay contents of FSL was virtually 7%. The removal efficiency during operation of double layer soil column was 98% for SS and turbidity, 75% for TCODCr, 56% for ${NH_4}^+-N$, 87% for TP, and 73-91% for heavy metals. The hydraulic conductivity of the soil column, 0.023 cm/sec, suggested that the surface area of the biofilter system should be about 1% of the drainage area to treat the rainfall intensity of one month recurrence interval.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.1B
• /
• pp.21-27
• /
• 2011

When execute runoff forecasting, can not remove perfectly uncertainty of forecasting results. But, reduce uncertainty by various techniques analysis. This study applied various forecasting techniques for runoff prediction's accuracy elevation in Gongju basin. statics techniques is ESP, Period Average & Moving average, Exponential Smoothing, Winters, Auto regressive moving average process. Authoritativeness estimation with results of runoff forecasting by each techniques used MAE (Mean Absolute Error), RMSE (Root Mean Squared Error), RRMSE (Relative Root Mean Squared Error), Mean Absolute Percentage Error (MAPE), TIC (Theil Inequality Coefficient). Result that use MAE, RMSE, RRMSE, MAPE, TIC and confirm improvement effect of runoff forecasting, ESP techniques than the others displayed the best result.

• Journal of Environmental Impact Assessment
• /
• v.20 no.4
• /
• pp.509-521
• /
• 2011

The purpose of this study is to estimate overall reliability and applicability of the watershed modeling for systematic management of point and non-point sources via water quality analysis and prediction of runoff discharge within watershed. Recently, runoff characteristics and pollutant characteristics have been changing in watershed by anomaly climate and urbanization. In this study, the effects of watershed scale were analyzed in runoff and water quality modeling using HSPF. In case of correlation coefficient, its range was from 0.936 to 0.984 in case A(divided - 2 small watersheds). On the other hand, its range was form 0.840 to 0.899 in case B(united - 1 watershed). In case of Nash-Sutcliffe coefficient, its range was from 0.718 to 0.966 in case A. On the other hand, its range was from 0.441 to 0.683 in case B. As a result, it was judged that case A was more accurate than case B. Therefore, runoff and water quality modeling in minimum watershed scale that was provided data for calibration and verification was judged to be favorable in accuracy. If optimal watershed dividing and parameter optimization using PEST in HSPF with more reliable measured data are carried out, more accurate runoff and water quality modeling will be performed.

• Applied Biological Chemistry
• /
• v.40 no.4
• /
• pp.334-341
• /
• 1997

In the laboratory experiment, concentration and rate of runoff of 7 pesticides were measured under the simulated rainfall. Total runoff rate of metolachlor, alachlor, chlorothalonil, chlorpyrifos, EPN, phorate and captafol were 57.0, 14.2, 13.2, 7.9, 7.2, 7.1 and 2.8%, respectively, and the average runoff concentrations were 940, 399, 55, 7.0, 9.3, 151 and 7.0 ppb, respectively. Significant relationship was observed between the runoff rate and water solubility in the laboratory experiment(r=0.923). Even though not very high, relatively significant results were obtained in other experimental conditions. Based on the results, runoff rate prediction$[Y=0.2812{\times}10exp(0.261logWS-0.366)+0.3594{\times}10exp(-0.545logKoc+1.747)+0.3594{\times}10exp(-0.362log\;Kow+1.105]$ and conversion equations were calculated to investigate the possibility of estimating runoff rate in the field by natural rain. Calculated runoff rate by conversion equation was similar to experimental result with captafol in the field while 6 times higher result was obtained by the prediction equation. Therefore, those prediction and conversion equations derived from the laboratory experiment data and physicochemical properties of the pesticides could be used for the prediction of field runoff rate of pesticides by natural rainfall.

• Journal of Korea Water Resources Association
• /
• v.35 no.3
• /
• pp.331-344
• /
• 2002

This study is aimed at the development of a deterministic runoff model which can be used for flood runoff. The model is formulated by the watershed runoff model. Based on the assumptions that runoff system is nonlinear, the proposed watershed runoff model is the conceptual model. In the model structure, the conceptual model divides the runoff system into a surface structure and a subsurface structure corresponding to the surface flow, and inter flow and ground water flow respectively. The lag time effect of surface can be represented by the sub-tank of surface structure in the conceptual model. The parameter calibration of inter flow and ground water flow in the subsurface structure of the conceptual model is performed by separating the components with numeric filter The runoff coefficient($\alpha$$_2$) is expressed as the function of antecedent precipitation index(API). The parameters with the surface flow can be calibrated with the runoff coefficient($\alpha$$_1$ and $\alpha$/$_{11}$) in the conceptual model. In the conceptual model, an algorithm is developed to calibrate the parameters automatically based on efficiency criteria. The comparative study shows that simulated value from the conceptual model well agreed to observed value.

• Journal of Korean Society on Water Environment
• /
• v.27 no.6
• /
• pp.848-854
• /
• 2011

The objective of this research was to experimentally test the effect of rice straw mats on the reduction of runoff, sediment and discharge under a laboratory scale with different rainfall intensity and slopes. We used the small runoff plots of $1m{\times}1m{\times}0.65m$ ($L{\times}W{\times}H$) in size were filled with loamy sand. Experimental treatments were bare (control), rice straw mats + PAM(SP), rice straw mats + PAM + sawdust(SPS) and rice straw mats + PAM + rice husks(SPR); slope of 10% or 20%; and rainfall intensity of 30 or 60 mm/hr. Runoff volume and coefficient from covered plots were significantly lower than those from control plots. Under the 30 mm/hr and 10% simulations, average runoff coefficient of covered plots decreased more than 92%. Under 60 mm/hr and 20% simulations, the ratios were between 39.8~58.1%. Under the condition of 30 mm/hr rainfall and 10% slope, sediment discharge from covered plots was practically zero. And at 20% plots, sediment reduction ratio was more than 95%. Under the condition of 60 mm/hr rainfall, sediment reduction ratio of 10 and 20% plots ranged between 86.3~95.3% and between 79.8~86.5%, respectively. The differences in initial runoff time, runoff and sediment discharge among different cover materials were not significant. Rainfall intensity showed higher impact on initial runoff time, runoff, and sediment discharge than slope. It was also shown that even if runoff reduction by surface cover were low, sediment discharge reduction could be very significant and contribute to improve the water quality of streams in sloping agricultural regions. It was concluded that the use of straw mat and PAM on sloping agricultural fields could reduce soil erosion and muddy runoff significantly and help improve the water quality and aquatic ecosystem in receiving waters.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.60 no.1
• /
• pp.111-120
• /
• 2018

The purpose of this study was to develop a ridge regression (RR) model to estimate BOD and TP load using runoff weighted value. The concept of runoff weighted value, based on distributed curve-number (CN), was introduced to reflect the impact of land covers on runoff. The estimated runoff depths by distributed CN were closer to the observed values than those by area weighted mean CN. The RR is a technique used when the data suffers from multicollinearity. The RR model was developed for five flow duration intervals with the independent variables of daily runoff discharge of seven land covers and dependent variables of daily pollutant load. The RR model was applied to Heuk river watershed, a subwatershed of the Han river watershed. The variance inflation factors of the RR model decreased to the value less than 10. The RR model showed a good performance with Nash-Sutcliffe efficiency (NSE) of 0.73 and 0.87, and Pearson correlation coefficient of 0.88 and 0.93 for BOD and TP, respectively. The results suggest that the methods used in the study can be applied to estimate pollutant load of different land cover watersheds using limited data.