• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.105-119
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• 2021

An increase in the frequency and intensity of both floods and droughts has been recently observed due to an increase in climate variability. Especially, land-use change associated with industrial structure and urbanization has led to an imbalance between water supply and demand, acting as a constraint in water resource management. Accurate rainfall-runoff analysis plays a critical role in evaluating water availability in the water budget analysis. This study aimed to explore various continuous rainfall-runoff models over the Soyanggang dam watershed. Moreover, the ensemble modeling framework combining multiple models was introduced to present scenarios on streamflow considering uncertainties. In the ensemble modeling framework, rainfall-runoff models with fewer parameters are generally preferred for effective regionalization. In this study, more than 40 continuous rainfall-runoff models were applied to the Soyanggang dam watershed, and nine rainfall-runoff models were primarily selected using different goodness-of-fit measures. This study confirmed that the ensemble model showed better performance than the individual model over different flow regimes.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.28-36
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• 2000

A TIN, Triagulated Irregular Network, based topographic modeling method and a distributed rainfall-runoff model using the topographic representation is presented. In the TIN based topographic representation, a watershed basin is modeled as a set of contiguous non-overlapping triagular facets : the watershed basin is subdivided according to streamlines to deal with water movement one-dimensionally ; and each partitioned catchment is approximated to a slope element having a quasi-three-dimensional shape by using cubic spline functions. On an approximated slope element, water movement is represented by combined surface-subsurface kinematic wave equations considering a change of slope gradient and slope width. By using the distributed rainfall-runoff model, the effects of spatial variability of soil properties on runoff response are examined.

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.28-36
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• 2000

A TIN, Triangulated Irregular Network, based topographic modeling method and a distributed rainfall-runoff model using the topographic representation is presented. In the TIN based topographic representation, a watershed basin is modeled as a set of contiguous non-overlapping triangular facets: the watershed basin is subdivided according to streamlines to deal with water movement one-dimensionally; and each partitioned catchment is approximated to a slope element having a quasi-three-dimensional shape by using cubic spline functions. On an approximated slope element, water movement is represented by combined surface-subsurface kinematic wave equations considering a change of slope gradient and slope width. By using the distributed rainfall-runoff model, the effects of spatial variability of soil properties on runoff response are examined.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.87-96
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• 2019

The objective of this study was to develop a general inundation modeling technique considering the effect of drainage delay in the paddy field districts. In most studies, farmland inundation simulations have been conducted using previously developed watershed models. However, the water cycle in the paddy fields has a different structure from that of the general watershed, and the effect of the drainage delay should be considered. In this study, the drainage delay algorithm was developed using water balance equation, and the inundation modeling was performed for inundation-prone paddy fields located near Doowol stream. As a result, the depth of inundation was 43.1 cm and 45.2 cm, respectively, due to the 100-year and 200-year frequency rainfall. With the operation of drainage pump ($0.1m^3/s$), inundation depths decreased by 5.8 cm and 6.0 cm, respectively, and inundation time reduced by 20 hours and 21 hours, respectively for the 100-year and 200-year frequency rainfall. The result showed that the general inundation modeling technique developed in this study could reflect the effect of drainage delay due to the rise of external water level and the flooding reduction effect by operation of drainage pump. The results of this study are expected to be useful to establish measures for damage caused by farmland inundation.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.275-275
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• 2021

A fixed Z-R relationship approach, such as the Marshall-Palmer relationship, for an entire year and for different seasons can be problematic in cases where the relationship varies spatially and temporally throughout a region. From this perspective, this study explores the use of long-term radar reflectivity for South Korea to obtain a nationwide calibrated Z-R relationship and the associated uncertainties within a Bayesian regression framework. This study also investigates seasonal differences in the Z-R relationship and their roles in reducing systematic error. Distinct differences in the Z-R parameters in space are identified, and more importantly, an inverse relationship between the parameters is clearly identified with distinct regimes based on the seasons. A spatially structured pattern in the parameters exists, particularly parameter α for the wet season and parameter β for the dry season. A pronounced region of high values during the wet and dry seasons may be partially associated with storm movements in that season. Finally, the radar rainfall estimates through the calibrated Z-R relationship are compared with the existing Z-R relationships for estimating stratiform rainfall and convective rainfall. Overall, the radar rainfall fields based on the proposed modeling procedure are similar to the observed rainfall fields, whereas the radar rainfall fields obtained from the existing Marshall-Palmer Z-R relationship show a systematic underestimation. The obtained Z-R relationships are validated by testing the predictions on unseen radar-gauge pairs in the year 2018, in the context of cross-validation. The cross-validation results are largely similar to those in the calibration process, suggesting that the derived Z-R relationships fit the radar-gauge pairs reasonably well.

• Journal of Korea Water Resources Association
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• v.53 no.7
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• pp.493-505
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• 2020

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.

• Journal of Korean Society of Disaster and Security
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• v.8 no.1
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• pp.15-19
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• 2015

In rainfall-runoff models employed in hydrological applications, runoff amount is estimated through temporal delay of effective precipitation based on a linear system. Its amount is resulted from the linearized ratio by analyzing the convolution multiplier. Furthermore, in case of kernel density estimate (KDE) used in probabilistic analysis, the definition of the kernel comes from the convolution multiplier. Individual data values are smoothed through the kernel to derive KDE. In the current study, the roles of the convolution multiplier for KDE and rainfall-runoff models were revisited and their similarity and dissimilarity were investigated to discover the mathematical applicability of the convolution multiplier.

• Geomechanics and Engineering
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• v.1 no.3
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• pp.193-204
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• 2009

A 10.4-m high highway embankment retained behind mechanically stabilized earth (MSE) walls is under construction in the northeastern part of the Indian state of Bihar. The structure is constructed with compacted, micaceous, grey, silty sand, reinforced with polyester (PET) geogrids, and faced with reinforced cement concrete fascia panels. The connections between the fascia panels and the geogrids failed on several occasions during the monsoon seasons of 2007 and 2008 following episodes of heavy rainfall, when the embankment was still under construction. However, during these incidents the MSE embankment itself remained by and large stable and the collateral damages were minimal. The observational data during these incidents presented an opportunity to develop and calibrate a simple procedure for estimating rainfall induced pore water pressure development within MSE embankments constructed with backfill materials that do not allow unimpeded seepage. A simple analytical finite element model was developed for the purpose. The modeling results were found to agree with the observational and meteorological records from the site. These results also indicated that the threshold rainwater infiltration flux needed for the development of pore water pressure within an MSE embankment is a monotonically increasing function of the hydraulic conductivity of backfill. Specifically for the MSE embankment upon which this study is based, the analytical results indicated that the instabilities could have been avoided by having in place a chimney drain immediately behind the fascia panels.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.