• Journal of Korea Water Resources Association
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• v.34 no.5
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• pp.473-486
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• 2001

The WGR model was developed to represent meso-scale precipitation. As a conceptual model, this model shows a good link between atmospheric dynamics and statistical description of meso-scale precipitation(Waymire et al., 1984). However, as it has maximum 18 parameters along with its non-linear structure, its parameter estimation has been remained a difficult problem. There have been several cases of its parameter estimation for different fields using non-linear programming techniques(NLP), which were also difficult tasks to hamper its wide applications. In this study, we estimated the WGR model parameters of the Han river basin using the genetic algorithm(GA) and compared them to the NLP results(Yoo and Kwon, 2000). As a result of the study, we can find that the sum of square error from the GA provide more consistent parameters to the seasonal variation of rainfall. Also, we can find that the higher rainfall amount during summer season is closely related with the arrival rate of rain bands, not the rain cell intensity.

• Journal of Korea Water Resources Association
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• v.38 no.5 s.154
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• pp.415-425
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• 2005

This study estimated the optimal rain gauge density and sub-basin size for the application of a daily rainfall-runoff analysis model called SWAT (Soil and Water Assessment Tool). Simulated rainfall data using a WGR multi-dimensional precipitation model (Waymire et al., 1984) were applied to SWAT for runoff estimation, and then the runoff error was analyzed with respect to various rain gauge density and sub-basin size. As results of the study, we could find that the optimal sub-basin size and the representative area of one rain gauge are similar to be about $80km^2$ for the Yong-Dam dam basin.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.683-696
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• 2013

Recent inundation damage has frequently occurred due to heavy rainfall in urban area, because rainfall has locally occurred exceeding the capability of a flood control plan by the exiting design rainfall from the data of Seoul weather station. Accordingly the objective of this study is to predict new design rainfall in order to make a future flood control plan considering climate change. In this study, for considering spatial characteristics of rainfall in urban area, data of AWS was used and for retaining insufficient rainfall data, WGR model was estimated the application of target area. The results were compared with the observation data and consequently show reasonable results. In addition, to prepare for climate change, design rainfall was calculated by applying for various climate scenarios and the result would be used in order to establish future flood control plan.

• Journal of Korea Water Resources Association
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• v.35 no.3
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• pp.307-319
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• 2002

This study used the WGR model to generate the rainfall input and the modified Clark method to estimate the runoff with the aim of investigating how the errors from the areal average rainfall propagates to runoff estimates. This was done for several cases of raingauge density and also by considering several storm directions. Summarizing the study results are as follows. (1) Rainfall and runoff errors decrease exponentially as the raingauge density increases. However, the error stagnates after a threshold density of raingauges. (2) Rainfall errors more affect to runoff estimates when the density of raingauges is relatively low. Generally, the ratio between estimation errors of rainfall and runoff volumes was found much less than one, which indicates that there is a smoothing effect of the basin. However, the ratio between estimation errors of rainfall to peak flow becomes greater than one to indicate the amplification of rainfall effect to peak flow. (3) For the study basin in this studs no significant effect of storm direction could be found. However, the runoff error becomes higher when the storm and drainage directions are identical. Also, the error was found higher for the peak flow than for the overall runoff hydrograph.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.743-754
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• 2007

This study theoretically compared three possible methods for the ground-truth, that is three ground-truth designs of radar rainfall using the rain gauge rainfall. Theoretical results derived are first applied to the rainfall field generated by the Waymire-Gupta-Rodriguez Iturbe(WGR) model, and then to the Mt. Gwanak radar data using the rain gauge data from MOCT within the radar range of observation. Overall application results were found to be similar to those from theoretical studies, also those from the application to the WGR rainfall field. In conclusion, the ground-truth design using only positive(+) rainfalls from both radar and rain gauges causes serious design bias to be inappropriate as a ground-truth design.

• Water Engineering Research
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• v.1 no.2
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• pp.147-158
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• 2000

In this study, we characterized the seasonal variation of rainrate fields in the Han river basin using the WGR multi-dimensional precipitation model (Waymire, Gupta, and Rodriguez-Iturbe, 1984) by estimating and comparing the parameters derived for each month and for the plain area, the mountain area and overall basin, respectively. The first-and second-order statistics derived from observed point gauge data were used to estimate the model parameters based on the Davidon-Fletcher-Powell algorithm of optimization. As a result of the study, we can find that the higher rainfall amount during summer is mainly due to the arrival rate of rain bands, mean number of cells per cluster potential center, and raincell intensity. However, other parameters controlling the mean number of rain cells per cluster, the cellular birth rate, and the mean cell age are found invariant to the rainfall amounts. In the application to the downstream plain area and upstream mountain area of the Han river basin, we found that the number of storms in the mountain area was estimated a little higher than that in the plain area, but the cell intensity in the mountain area a little lower than that in the plain area. Thus, in the mountain area more frequent but less intense storms can be expected due to the orographic effect, but the total amount of rainfall in a given period seems to remain the same.

• Water Engineering Research
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• v.2 no.1
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• pp.63-72
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• 2001

The variation of sampling errors was characterized using the Waymire-Gupta-Rodriguez-Iturbe multi-dimensional rainfall model(WGR model). The parameters used for this study are those derived by Jung et al. (2000) for the Han River Basin using a genetic algorithm technique. The sampling error problems considered are those for using raingauge network, satellite observation and also for both combined. The characterization of sampling errors was done for each month and also for the downstream plain area and the upstream mountain area, separately. As results of the study we conclude: (1) The pattern of sampling errors estimated are obviously different from the seasonal pattern of monthly rainfall amounts. This result may be understood from the fact that the sampling error is estimated not simply by considering the rainfall amounts, but by considering all the mechanisms controlling the rainfall propagation along with its generation and decay. As the major mechanism of moisture source to the Korean Peninsula is obviously different each month, it seems rather normal to provide different pattern of sampling errors from that of monthly rainfall amounts. (2) The sampling errors estimated for the upstream mountain area is about twice higher than those for the down stream plain area. It is believed to be because of the higher variability of rainfall in the upstream mountain arean than in the down stream plain area.

• Water Engineering Research
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• v.3 no.1
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• pp.31-44
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• 2002

The effect of diurnal cycle, intermittent visit of observation satellite, sensor installation, partial coverage of remote sensing, heterogeneity of soil properties and precipitation to the soil moisture estimation error were analyzed to present the global sampling strategy of soil moisture. Three models, the theoretical soil moisture model, WGR model proposed Waymire of at. (1984) to generate rainfall, and Turning Band Method to generate two dimensional soil porosity, active soil depth and loss coefficient field were used to construct sufficient two-dimensional soil moisture data based on different scenarios. The sampling error is dominated by sampling interval and design scheme. The effect of heterogeneity of soil properties and rainfall to sampling error is smaller than that of temporal gap and spatial gap. Selecting a small sampling interval can dramatically reduce the sampling error generated by other factors such as heterogeneity of rainfall, soil properties, topography, and climatic conditions. If the annual mean of coverage portion is about 90%, the effect of partial coverage to sampling error can be disregarded. The water retention capacity of fields is very important in the sampling error. The smaller the water retention capacity of the field (small soil porosity and thin active soil depth), the greater the sampling error. These results indicate that the sampling error is very sensitive to water retention capacity. Block random installation gets more accurate data than random installation of soil moisture gages. The Walnut Gulch soil moisture data show that the diurnal variation of soil moisture causes sampling error between 1 and 4 % in daily estimation.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.7-14
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• 2001

In this study, we characterized the variation of sampling errors using the Waymire-Gupta-rodriguez-Iturbe multi-dimensional rainfall model (WGR model). The parameters used for this study are those derived by Jung et al. (2000) for the Han River Basin using a genetic algorithm technique. The sampling error problems considering in this study are those far using raingauge network, satellite observation and also for both combined. The characterization of sampling errors was done for each month and also for the downstream plain area and the upstream mountain area, separately. As results of the study we conclude: (1) The pattern of sampling errors estimated are obviously different from the seasonal pattern of mentally rainfall amounts. This result may be understood from the fact that the sampling error is estimated not simply by considering the rainfall amounts, but by considering all the mechanisms controlling the rainfall propagation along with its generation and decay. As the major mechanism of moisture source to the Korean Peninsula is obviously different each month, it seems rather norma1 to provide different pattern of sampling errors from that of monthly rainfall amounts. (2) The sampling errors estimated for the upstream mountain area is about twice higher than those for the down stream plain area. It is believed to be because of the higher variability of rainfall in the upstream mountain area than in the down stream plain area.