• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.5
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• pp.1137-1143
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• 1994

Through the numerical analysis of the capillary pressure-based Richards equation with and without the effect of the capillary hysteresis under the boundary condition having an antecedent rainfall. the moving tendency of the wetting front, the redistribution of the moisture content, infiltration rate, cumulative infiltration etc, were computed. The effect of the capillary hysteresis cannot be neglected in analyzing an unsaturated flow, and the more accurate results may be obtained by the consideration of the hysteresis effect. If the effect of the hysteresis cannot be considered, the analysis by the use of the main wetting curve may give more reliable result than that of the main drying curve.

• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.474-481
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• 2007

With population growth, industrialization, and urbanization within the watershed, the hydrologic response changed dramatically, resulting in increases in peak flow with lesser time to peak and total runoff with shortened time of concentration. Infiltration is directly affected by initial soil moisture condition, which is a key element to determine runoff. Influence of the initial soil moisture condition on hydrograph analysis should be evaluated to assess land use change impacts on runoff and non-point source pollution characteristics. The Long-Term Hydrologic Impact Assessment (L-THIA) model has been widely used for the estimation of the direct runoff worldwide. The L-THIA model was applied to the Little Eagle Creek (LEC) watershed and Its estimated direct runoff values were compared with the BFLOW filtered direct runoff values by other researchers. The $R^2$ value Was 0.68 and the Nash-Sutcliffe coefficient value was 0.64. Also, the L-THIA estimates were compared with those separated using optimized $BFI_{max}$ value for the Eckhardt filter. The $R^2$ value and the Nash-Sutcliffe coefficient value were 0.66 and 0.63, respectively. Although these higher statistics could indicate that the L-THIA model is good in estimating the direct runoff reasonably well, the Antecedent Moisture Condition (AMC) was not adjusted in that study, which might be responsible for mismatches in peak flow between the L-THIA estimated and the measured peak values. In this study, the L-THIA model was run with AMC adjustment for direct runoff estimation. The $R^2$ value was 0.80 and the Nash-Sutcliffe coefficient value was 0.78 for the comparison of L-THIA simulated direct runoff with the filtered direct runoff. However there was 42.44% differences in the L-THIA estimated direct runoff and filtered direct runoff. This can be explained in that about 80% of the simulation period is classified as 'AMC I' condition, which caused lower CN values and lower direct runoff estimation. Thus, the coefficients of the equation to adjust CN II to CN I and CN III depending on AMC condition were modified to minimize adjustments impacts on runoff estimation. The $R^2$ and the Nash-Sutcliffe coefficient values increase, 0.80 and 0.80 respectively. The difference in the estimated and filtered direct runoff decreased from 42.44% to 7.99%. The results obtained in this study indicate the AMC needs to be considered for accurate direct runoff estimation using the L-THIA model. Also, more researches are needed for realistic adjustment of the AMC in the L-THIA model.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.615-626
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• 2019

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.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.235-244
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• 2018

Potential maximum soil moisture retention (S) is a dominant parameter in the Soil Conservation Service (SCS; now called the USDA Natural Resources Conservation Service (NRCS)) runoff Curve Number (CN) method commonly used in hydrologic modeling for event-based flood forecasting (SCS, 1985). Physically, S represents the depth [L] soil could store water through infiltration. The depth of soil moisture retention will vary depending on infiltration from previous rainfall events; an adjustment is usually made using a factor for Antecedent Moisture Conditions (AMCs). Application of the method for continuous simulation of multiple storms has typically involved updating the AMC and S. However, these studies have focused on a time step where S is allowed to vary at daily or longer time scales. While useful for hydrologic events that span multiple days, this temporal resolution is too coarse for short-term applications such as flash flood events. In this study, an approach for deriving a time-variable potential maximum soil moisture retention curve (S-curve) at hourly time-scales is presented. The methodology is applied to the Napa River basin, California. Rainfall events from 2011 to 2012 are used for estimating the event-based S. As a result, we derive an S-curve which is classified into three sections depending on the recovery rate of S for soil moisture conditions ranging from 1) dry, 2) transitional from dry to wet, and 3) wet. The first section is described as gradually increasing recovering S (0.97 mm/hr or 23.28 mm/day), the second section is described as steeply recovering S (2.11 mm/hr or 50.64 mm/day) and the third section is described as gradually decreasing recovery (0.34 mm/hr or 8.16 mm/day). Using the S-curve, we can estimate the hourly change of soil moisture content according to the time duration after rainfall cessation, which is then used to estimate direct runoff for a continuous simulation for flood forecasting.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.525-530
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• 1999

A modified SCS TR-20 model that may be applied to a watershed having rice paddies as a land use type, was formulated and applied to a gauaged watershed. The model was applied to the Balan watershed of 26$\textrm{km}^2$ in size for estimation strorm hydrographs . And the simulation results from the model were also compared with thoses from the SCS model. The results showed that paddy fields play an important role to reduce peak runoff. When fractions of paddies are left to fallow conditions or when rice crop is replaced by other, the peak runoff was found to increase up to 10 to 20 percentg . The reduction rates in peak runoff appear to become greater for heavier storms or higher antecedent moisture conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1269-1276
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• 2015

The methodology of utilizing Intensity-Duration-flood Quantity (IDQ) curve for flood alert and warning was introduced and its performance was evaluated. For this purpose the lumped parameter model was calibrated and validated for gauged basin data set and the index precipitation equivalent to alert and warning flood was estimated. The index precipitation and IDQ curves associated by three different Antecedant Moisture Conditions (AMCs) are made provision for various possible flood scenarios. The test basin is Wonju-cheon basin ($94.4km^2$) located in Gangwon province, Korea. The IDQ curves corresponding to alert (50% of design flood level) and warning (70% of design flood level) level was estimated using the Clark unit hydrograph based lumped parameter model. The performance evaluation showed 0.704 of POD (Probability of Detection), 0.136 of FAR (False Alarm Ratio), and 0.633 of CSI (Critical Success Index), which is improved from the result of IDQ with single fixed AMC.

• Journal of Korean Society of Forest Science
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• v.96 no.5
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• pp.561-566
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• 2007

This study was conducted to clarify runoff production processes in forested catchment through hydrograph separation using three-component mixing model based on the End Member Mixing Analysis (EMMA) model. The study area is located in the coniferous-forested experimental catchment, Gwangneung Gyeonggido near Seoul, Korea (N 37 45', E 127 09'). This catchment is covered by Pinus Korainensis and Abies holophylla planted at stocking rate of 3,000 trees $ha^{-1}$ in 1976. Thinning and pruning were carried out two times in the spring of 1996 and 2004 respectively. We monitored 8 successive events during the periods from June 15 to September 15, 2005. Throughfall, soil water and groundwater were sampled by the bulk sampler. Stream water was sampled every 2-hour through ISCO automatic sampler for 48 hours. The geochemical tracers were determined in the result of principal components analysis. The concentrations of $SO_4{^{2-}$ and $Na^+$ for stream water almost were distributed within the bivariate plot of the end members; throughfall, soil water and groundwater. Average contributions of throughfall, soil water and groundwater on producing stream flow for 8 events were 17%, 25% and 58% respectively. The amount of antecedent precipitation (AAP) plays an important role in determining which end members prevail during the event. It was found that ground water contributed more to produce storm runoff in the event of a small AAP compared with the event of a large AAP. On the other hand, rain water showed opposite tendency to ground water. Rain water in storm runoff may be produced by saturation overland flow occurring in the areas where soil moisture content is near saturation. AAP controls the producing mechanism for storm runoff whether surface or subsurface flow prevails.

• Journal of Soil and Groundwater Environment
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• v.21 no.6
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• pp.36-45
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• 2016

Variability in precipitation due to climate change causes difficulties in securing stable surface water resource, which requires understanding of relation between precipitation and stream discharge. This study simulated stream discharge in a small mountainous forested catchment using antecedent precipitation index (API) models which represent variability of saturation conditions of soil layers depending on rainfall events. During 13 months from May 2015 to May 2016, stream discharge and rainfall were measured at the outlet and in the central part of the watershed, respectively. Several API models with average recession coefficients were applied to predict stream discharge using measured rainfall, which resulted in the best reflection time for API model was 1 day in terms of predictability of stream discharge. This indicates that soil water in riparian zones has fast response to rainfall events and its storage is relatively small. The model can be improved by employing seasonal recession coefficients which can consider seasonal fluctuation of hydrological parameters. These results showed API models can be useful to evaluate variability of streamflow in ungauged small forested watersheds in that stream discharge can be simulated using only rainfall data.

• Journal of the Korean Geotechnical Society
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• v.28 no.7
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• pp.41-53
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• 2012

During rainfall period, to identify the characteristics of the infiltration of moisture, electrical resistivity monitering survey was carried out to weathered zone. Four regions of geophysical exploration areas with different rock types, four regions were selected. An area consists of mafic granite and three areas are composed of sedimentary rocks (Sandstone, Shale, Unconsolidated Mudstone). Survey was conducted from June (rainy season) to November (dry season), and during the period the change in resistivity was observed. According to the result of monitoring exploration on Geumjeong and Jinju areas, for the estimation of the standard rainfall, it is necessary to estimate the effects of the antecedent rainfall during the rainy season based on the overall rainfall from June till October and also necessary to consider this for the estimation of the half period. Also, the vertical distribution of the low resistivity anomaly zone does not show that the infiltration of moisture does not occur uniformly from the surface of the ground to the lower ground but shows that it occurs along the relaxed gap of the crack or soil stratum of the weathering zone. In Pohang area, the type of moisture infiltration is different from that of the granite or sedimentary rock. Since, after the rainfall, the rate of infiltration to the lower ground is high and the period of cultivation to the lower bedrock aquifer is short, it has similar effect to that of the antecedent rainfall applied for the estimation of the standard rainfall being presently used. In Danyang, due to the degree of water content of the ground, the duration period of the low resistivity anomaly zone observed in the lower ground of the place where clastic sedimentary rock is distributed is similar to that in Pohang area. The degree of lateral water diffusion at the time of localized heavy rain is the same as that of the sedimentary rock in Jinju. According to the above analysis results, in Danyang area, the period when the antecedent rainfall has its influence is estimated as three weeks or so.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.