• Journal of Korea Water Resources Association
• /
• v.47 no.3
• /
• pp.223-235
• /
• 2014

In recent, the various methods to predict the hydrological impacts due to climate change have been developed and applied. Especially the trend analysis using observed and future hydrological data has been performed than ever. Parametric or non-parametric tests can be applied for a trend analysis. However, the non-parametric tests have been commonly used in the case of trend analysis using hydrological data. Therefore, the two types of non-parametric tests, Mann-Kendall (MK) test and Spearman Rho (SR) test, were used to detect the trend in the observed and future rainfall data that were collected from the Nakdong River basin. Also, the Pre-Whitening (PW) and the Trend Free Pre-Whitening (TFPW) as the pre-process of the trend analysis were performed. Also, the result of trend analysis suggest that those pre-processes have a statistically significant effect. Additionally, the Sequential Mann-Kendall (SMK) was used to reveal the beginning point of a trend in the observed and future rainfall data in the Nakdong River basin. The rainfall patterns in most rainfall gauges using the observed rainfall show the increasing trend and the abrupt changes in the specific months (from April to May and September to October). Also, the beginning point of the trend is brought forward by several months when climate change is accelerated. Finally, the results of this study can provide the useful background for the research related to climate change and water resources planning in the Nakdong River basin.

• Journal of Korea Multimedia Society
• /
• v.22 no.12
• /
• pp.1430-1437
• /
• 2019

In this paper, we proposed a methodology for estimating rainfall intensity using a W-band FMCW automotive radar signal which is the core technology of autonomous driving car. By comparing and analyzing the results of rainfall and non-rainfall observation, we found that the reflection intensity of the automotive radar is changed with rainfall intensity. We could confirm the possibility of deriving the quantitative precipitation estimation using the methodology derived from this result. In addition it can be possible to develop a new paradigm of precipitation observation technique by observing various events together with the weather radar and the ground rainfall observation equipment.

• Journal of the Korea Organic Resources Recycling Association
• /
• v.30 no.1
• /
• pp.41-47
• /
• 2022

In this study, rainfall water outlet water quality monitoring was performed on the C industrial complex to evaluate the characteristics of non-point pollutant runoff from the industrial complex during rainfall and to use it as basic data for calculating the load and unit of non-point pollutant. As a result of calculating EMC according to the outflow amount by rainfall event, the 1st rainfall showed EMCs ranges of BOD, COD_Mn, SS, T-N, and T-P of 1.32~48.76, 3.32~43.75, 2.89~199.43, 2.76~8.93, 0.08~068, and the 2nd rainfall was 0.5~2.9, 2.71~7.13, 2.82~174.94, 1.33~4.03, 0.01~1.28 mg/L, respectively. As a result of calculating the ratio of cumulative outflow and cumulative pollution load, most of the pollution load was less than the rainfall outflow, but over time, the initial washing phenomenon occurred as the ratio of cumulative rainfall outflow and cumulative pollution load increased to more than 1.

• Journal of Environmental Science International
• /
• v.18 no.9
• /
• pp.983-992
• /
• 2009

The purpose of the present study is to analyze pollutant runoff characteristics from non-point sources in Joman River basin. The present study contains analyzed results of rainfall and SS, BOD, COD, TN, TP runoff from Joman River basin. This study contains a sensitivity analysis of parameters that affect the simulation results of rainfall and pollutants runoff. Result of the sensitivity analysis shows that proportion of watershed and impervious areas is the most sensitive to peak discharge and total flowrate for rainfall runoff and that WASHPO is the most sensitive parameter for pollutants runoff. For parameter estimation and verification, flowrate and water quality is measured at the Kangdong Bridge in Haeban stream. A single rainfall event is use to perform parameter estimation and verification. Results of the present study show that total pollutant loads of Joman River basin is 11,600 ton of SS, 452 ton of BOD, 1,084 ton of COD, 515 ton of TN, and 49 ton of TP, respectively. In addition, it is found that contribution ratio of non point source and total source is 89% of SS, 63% of BOD, 61% of COD, 21% of TN, and 32% of TP, respectively.

• Journal of Korean Society on Water Environment
• /
• v.26 no.2
• /
• pp.252-260
• /
• 2010

The point rainfall measurements need to be converted to the areal rainfall by means of mean areal precipitation (MAP) estimation methods. And it is not appropriate to evaluate the areal rainfall with constant drift because of the geomorphological influences to rainfall field. Non-stationarity should be applied to the estimation of the areal rainfall, therefore, to consider these effects. Kriging methods with special functional would be a suitable tool in this case. Generalized covariance Kriging method is the most developed one among different Kriging methods. From this point of view this study performs the analysis of its applicability to distributed runoff model. For these purpose, distributed rainfall was created by Thiessen and Kriging method. And distributed rainfall of each method was applied into HyGIS-GRM. The result of applying, Runoff was different in the rainfall data form. Therefore, To apply Kriging method with physical meaning is that it is the useful method as distributed rainfall-runoff model.

• Atmosphere
• /
• v.25 no.2
• /
• pp.283-294
• /
• 2015

For urban flash flood simulation, we need the higher resolution radar rainfall than radar rainfall of KMA, which has 10 min time and 1km spatial resolution, because the area of subbasins is almost below $1km^2$. Moreover, we have to secure the high quantitative accuracy for considering the urban hydrological model that is sensitive to rainfall input. In this study, we developed the quantitative precipitation estimation (QPE), which has 250 m spatial resolution and high accuracy using KMA AWS and SK Planet stations with Mt. Gwangdeok radar data in Seoul area. As the results, the rainfall field using KMA AWS (QPE1) is showed high smoothing effect and the rainfall field using Mt. Gwangdeok radar is lower estimated than other rainfall fields. The rainfall field using KMA AWS and SK Planet (QPE2) and conditional merged rainfall field (QPE4) has high quantitative accuracy. In addition, they have small smoothed area and well displayed the spatial variation of rainfall distribution. In particular, the quantitative accuracy of QPE4 is slightly less than QPE2, but it has been simulated well the non-homogeneity of the spatial distribution of rainfall.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.7 no.5
• /
• pp.89-97
• /
• 2007

This study proposed new simple methodologies for testing the stationarity of rainfall quantiles, and applied to the rainfall data at Seoul. The methodologies in this study are based on the analysis of frequency change of rainfall quantiles, different from previous studies like Ahn et al. (2001) who analyzed the change of rainfall quantiles themselves. The different types of methodologies are proposed in this study; one is to evaluate the occurrence frequency of rainfall with its return period more than the data length, and the other is to evaluate the effect of new observation on the highest rainfall data recorded. The application of these methodologies shows that the rainfall quantiles at Seoul have no significant proof leading their non-stationarity.

• Journal of Wetlands Research
• /
• v.18 no.1
• /
• pp.94-99
• /
• 2016

Non-point source control has been issued and intensively studied for the control of water quality in streams and rivers. In this study, non-point source pollutants monitoring was conducted at the end of five small streams which were connected to a main stream in three stages including Phase I (one hr before the rainfall), Phase II (one hr after the rainfall), and Phase III (six hrs after the rainfall). For all five small streams, the concentrations and loading rates of non-point source pollutants significantly increased due to the rainfall. As a result of this, priority control streams and priority pollutants were suggested to prepare for future plans of the non-point source control.

• Journal of Wetlands Research
• /
• v.14 no.4
• /
• pp.581-589
• /
• 2012

Non-point source pollutant is exerting a serious influence on the water quality, since the characteristics of stormwater runoff is varied by the land usage pattern of an area and a basin, and all sorts of pollutants on the earth in rainfall flow into the urban stream. This study estimated EMC of each pollutant to investigate the characteristics of stormwater runoff by separating the urban area as the housing area and industrial area. As a result of the analysis, the first flush effect occurred in the non-point source pollutant of housing area and industrial area, as the runoff concentration gradually reduces after it rapidly increases in the initial rainfall, and in case of the non-point source pollutant the control of first stage rain-water. It is considered to require the continuous follow-up study such as the scale of long-term rainfall event and water quality data, land usage pattern by GIS method, database of topography and geological features, and so forth.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.18 no.4
• /
• pp.4232-4241
• /
• 1976

This study was carried out to clarify the stochastic characteristics of monthly rainfalls and to select a proper model for generating the sequential monthly rainfall amounts. The results abtained are as follows: 1. Log-Normal distribution function is the best fit theoretical distribution function to the empirical distribution of monthly rainfall amounts. 2. Seasonal and random components are found to exist in the time series of monthly rainfall amounts and non-stationarity is shown from the correlograms. 3. The Monte Carlo model shows a tendency to underestimate the mean values and standard deviations of monthly rainfall amounts. 4. The 1st order Markov model reproduces means, standard deviations, and coefficient of skewness with an error of ten percent or less. 5. A correlogram derived from the data generated by 1st order Markov model shows the charaterstics of historical data exactly. 6. It is concluded that the 1st order Markov model is superior to the Monte Carlo model in their reproducing ability of stochastic properties of monthly rainfall amounts.