• Journal of Korea Water Resources Association
• /
• v.47 no.4
• /
• pp.357-370
• /
• 2014

This study aims to develop a rainfall field tracking method for depth-area-duration (DAD) analysis and assess whether the proposed tracking methods are able to properly estimate the maximum average areal rainfall (MAAR) within the study area during a rainfall period. We proposed three different rainfall field tracking algorithms (Box-tracking, Point-tracking, Advanced point-tracking) and then applied them to the virtual rainfall field with 1hr duration and also compared DAD curves of each method. In addition, we applied the three tracking methods and a traditional GIS-based tool to the typhoon 'Nari' rainfall event of the Yongdam-Dam watershed and then assess applicability of the proposed methods for DAD analysis. The results showed that Box-tracking was much faster than the other two tracking methods in terms of searching for the MAAR but it was impossible to describe rainfall spatial pattern during its tracking processes. On the other hand, both Point-tracking and Advanced point-tracking provided the MAAR by considering the spatial distribution of rainfall fields. In particular, Advanced point-tracking estimated the MAAR more accurately than Point-tracking in the virtual rainfall field, which has two rainfall centers with similar depths. The proposed automatic rainfall field tracking methods can be used as effective tools to analyze DAD relationship and also calculate areal reduction factor.

• Journal of Korea Water Resources Association
• /
• v.36 no.5
• /
• pp.879-892
• /
• 2003

This study has performed the regionalization of point rainfall which has the hydrological homogeneity for regional frequency analysis of the rainfall. For the study, the recorded rainfall data were collected from 60 rainfall gauge stations distributed all over country of the Korea Meteorological Administration, and 32 rainfall characteristic elements were analyzed from the collected data. Using the principal component analysis to be data reduction technique of the multivariate analysis and the cluster analysis to be grouping technique about many of rainfall characteristic elements of each station, the regionalization of point rainfall was accomplished rationally and efficiently. As the result, hydrological homogeneous regions of point rainfall were divided by 5 regions and 3 other regions, and rainfall characteristics of divided each region were analyzed and compared relatively using regional mean values of each rainfall element data.

• 한국방재학회:학술대회논문집
• /
• 2007.02a
• /
• pp.575-578
• /
• 2007

The objective of this study is to analyze the regionalization of point rainfall by statistical methods for regional frequency analysis of the rainfall. The rainfall data used in this study are annual maximum rainfall at 57 stations during the period of more than 30 years for 12 durations(10min, 1, 2, 3, 4, 5, 6, 8, 10, 12, 18, 24hr) in Korea. The Mann-Whitney U test, Kruskal-Wallis one-way analysis of variance of nonparametric test the principal component and the cluster analysis have been performed to analyze the regionalization of rainfall. The results of this study are as follows; (1) The region which hydrological homogeneous is accepted does not exist for whole duration in Korea. (2) The result of nonpametric test shows that hydrological homogeneous regions of point rainfall are divided by 5 regions. (3) In case of cluster analysis hydrological homogeneous regions of point rainfall are divided by 6 regions and 4 other areas.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2004.05b
• /
• pp.1290-1294
• /
• 2004

In this study, new stochastic point rainfall models which can consider the correlation structure between rainfall intensity and duration are developed. In order to consider the negative and positive correlation simultaneously, the Gumbels type-II bivariate distribution is applied, and for the cluster structure of rainfall events, the Neyman-Scott cluster point process is selected. In the theoretical point of view, it is shown that the models considering the dependent structure between rainfall intensity and duration have slightly heavier tail autocorrelation functions than the corresponding independent mode]s. Results from generating long time rainfall events show that the dependent models better reproduce historical rainfall time series than the corresponding independent models in the sense of autocorrelation structures, zero rainfall probabilities and extreme rainfall events.

• Journal of Korea Water Resources Association
• /
• v.35 no.2
• /
• pp.173-186
• /
• 2002

Rainfall-runoff model is usually used in estimating the design flood, and the most important elements in this model are probable rainfall and unit hydrograph. So, it is the most important step to estimate probable rainfall reasonably and exactly. If a basin area exceeds a certain scale, probable areal rainfall should be used as probable rainfall, but, Probable point- mean rainfall be usually used in Korea. Consequently, probable rainfall is used too high and unit hydrograph is used relatively too low. Thus the improvement is unavoidable. So, in this study, the parameters are proposed that transform the 1day, 2day rainfall to 24hr, 48hr rainfall, and areal rainfall data series are composed by using the same time rainfall data. Also, the areal reduction factor(ARF) is developed as the increase of area by the calculated probable point mean rainfall and probable areal rainfall by frequency analysis in Han-River basin. It can be the measure to easily transform probable point- mean rainfall to probable areal rainfall.

• The Journal of Engineering Geology
• /
• v.24 no.4
• /
• pp.463-471
• /
• 2014

This paper considers the effect of rainfall on non-point source (NPS) pollutant loads. The impact of runoff on the occurrence of NPS pollutants was found to be influenced by rainfall amount, rainfall intensity, and the number of antecedent dry days (ADD), both independently and in combination. The close correlation ($R^2$ = 0.9920) between rainfall and runoff amounts was demonstrated at the study site (a flower farm) over the period between January 2011 and December 2013. The relationships among pollutant levels, runoff, and rainfall was not satisfactory results except for the Biochemical Oxygen Demand ($BOD_5$). The correlation coefficients between $BOD_5$, and both runoff and rainfall, were greater than 0.92. However, the relationships of other pollutants, such as Suspended Solid (SS), Chemical Oxygen Demand ($COD_{Mn}$), Total Nitrogen (TN), and Total Phosphorus (TP), with runoff and rainfall had correlation coefficients of less than 0.70. The roles of rainfall was different from rainfall categories on the occurrence of runoff. Instantaneous rainfall intensity was a principle factor on the occurrence of runoff following light rainfall events (total ${\leq}30mm$). For rainfall of intermediate intensity (total precipitation 31-50 mm), the combined effect of both average rainfall intensity and ADD was found to influence runoff generation. We conclude that the control of NPS pollutants with the reflection of the climate change that makes the remarkable effect of amounts and forms on the rainfall and runoff.

• Journal of Korean Society of Environmental Engineers
• /
• v.36 no.1
• /
• pp.13-19
• /
• 2014

The management of non point sources was marked by the need for clean water environments. It was proposed the fundamentals to promote the reasonable land management in this study. We monitored rainfall events at two non point sources with different crop cultivations such as a sweet potato and a cherry tree for three years. Because the most important factor was rainfall, the rainfall runoff and pollutant loads were generated 100% in the case of rainfall ranges with 50 < rainfall (mm). However the frequency of rainfall runoff was interacted with the crop cultivation and soil characteristics in the case of rainfall ranges such as 30 < rainfall (mm) ${\leq}50^a$ and 10 < rainfall (mm) ${\leq}30^b$. The frequency of rainfall runoff was a : 60% and b : 5% in the cherry tree cultivation with growing significantly and pollutant loads were lower than that of the sweet potato cultivation. Meanwhile the frequency of rainfall runoff was a : 60% and b : 5% in the sweet potato cultivation.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.4
• /
• pp.13-22
• /
• 2020

The Doam Lake watershed has a significant impact on the downstream water system due to nutrients and sediment outflow during rainfall caused by steep slopes, soil losses, and fertilization. These non-point sources are unclear in the discharge area and are affected by land use patterns, soil characteristics, and topographical features of the watershed. Therefore, this study conducted rainfall monitoring from July to October 2019 in Songcheon upstream of the Doam Lake watershed, one of the non-point pollution source management areas. Then, after analyzing rainfall runoff, Event Mean Concentration (EMC) and Mass First Flush ratio (MFFn) were calculated to compare and analyze the characteristics of rainfall and the non-point pollutant discharge. As a result of the analysis, it showed various non-point pollutant emission characteristics for each rainfall event. In addition, the concentration of EMC and the MFFn were affected by the average rainfall intensity and the maximum rainfall intensity, and were not significantly affected by the number of antecedent drying days. In the future, it is expected that effective non-point source reduction measures and management measures according to rainfall intensity through continuous monitoring and analysis will be needed.

• Journal of Korea Water Resources Association
• /
• v.41 no.7
• /
• pp.747-759
• /
• 2008

This study, a point rainfall process model, which could represent appropriately observed rainfall data, was to select. The point process models-rectangular pulses Poisson process model(RPPM), Neyman-Scott rectangular pulses Poisson process model(NS-RPPM), and modified Neyman-Scott rectangular pulses Poisson process model(modified NS-RPPM)-all based on Poisson process were considered as possible rainfall models, whose statistical analyses were performed with their simulation rainfall data. As results, simulated rainfall data using the NS-RPPM and the modified NS-RPPM represent appropriately statistics of observed data for several aggregation levels. Also, simulated rainfall data using the modified NS-RPPM shows similar characteristics of rainfall occurrence to the observed rainfall data. Especially, the modified NS-RPPM reproduces high-intensity rainfall events that contribute largely to occurrence of natural harzard such as flood and landslides most similarly. Also, the modified NS-RPPM shows the best results with respect to the total rainfall amount, duration, and inter-event time. In conclusions, the modified NS-RPPM was found to be the most appropriate model for the long-term simulation of rainfall.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.2
• /
• pp.63-74
• /
• 2019

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs). Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for construction of ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall), Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessen network, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that used all station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models that used point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The model performance for the ANNs model 2 in Chungju dam resulted in the $R^2$ value of 0.94, NSE of 0.94 $NSE_{ln}$ of 0.88 and PBIAS of -0.04 respectively. The model-2 predictions of Soyangriver Dam with the $R^2$ and NSE values greater than 0.94 were reasonably well agreed with the observations. The results of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.