The objectives of this study are to estimate the return period of flash flood and evaluate its appropriateness based on the actual observation events for small mountainous watersheds in the Han River basin. For these goals, Flash Flood Guidance (FFG) was estimated from 1-hr duration Threshold Runoff (TR) and Saturation Deficit (SD) of soil moisture which was derived from Sejong University Rainfall Runoff (SURR) model. Then, the return period of flash flood was calculated by comparing the rainfall quantile to the 1-hr duration rainfall that exceeded the FFG during the past period (2002-2010). Moreover, the appropriateness of the estimated return period of flash flood was evaluated by using the observation events from 2011 to 2016. The results of the return period of flash flood ranged from 1.1 to 19.9 years with a mean and a standard deviation of 1.6 and 1.1 years, respectively. Also, the result of the appropriateness indicated that 83% of the return periods derived from observation events were within the return period of flash flood range. Therefore, the estimated return period of flash flood could be considered as highly appropriate.
The purpose of this study is to evaluate the applicability of the GRM (Grid based rainfall-Runoff Model) to the continuous simulation by simulating the dam inflow. The GRM was previously developed for the simulation of rainfall-runoff events but has recently been improved to enable continuous simulation. The target watersheds are Chungju dam, Andong dam, Yongdam dam, and Sumjingang dam basins, and runoff models were constructed with the spatial resolution of 500 m × 500 m. The simulation period is 21 years (2001 to 2021). The simulation results were evaluated over the 17 year period (2005 to 2021), and were divided into three data periods: total duration, wet season (June to September), and dry season (October to May), and compared with the observed daily inflow of each dam. Nash-Sutcliffe efficiency (NSE), Kling-Gupta efficiency (KGE), correlation coefficient (CC), and total volume error (VE) were used to evaluate the fitness of the simulation results. As a result of evaluating the simulated dam inflow, the observed data could be well reproduced in the total duration and wet season, and the dry season also showed good simulation results considering the uncertainty of low-flow data. As a result of the study, it was found that the continuous simulation technique of the GRM model was properly implemented and the model was sufficiently applicable to the simulation of dam inflow in this study.
Rainfall falling in the impervious area of the cities flows over the surface and into the stormwater pipe networks to be discharged from the catchment. Therefore, it is very important to determine the size of stormwater pipes based on the peak discharge to mitigate urban flood. Climate change causes the severe rainfall in the small area, then the peak rainfall can not be discharged due to the capacity of the stormwater pipes and causes the urban flood for the short time periods. To mitigate these type of flood, the large stormwater pipes have to be constructed. However, the economic factor is also very important to design the stormwater pipe networks. In this study, 4 urban catchments were selected from the frequently flooded cities. Rainfall data from Seoul and Busan weather stations were applied to calculate runoff from the catchments using SWMM model. The characteristics of the peak runoff were analyzed using linear regression model and the 95% confidence interval and the coefficient of variation was calculated. The drainage density was calculated and the runoff characteristics were analyzed. As a result, the drainage density were depended on the structure of stormwater pipe network whether the structures are dendritic or looped. As the drainage density become higher, the runoff could be predicted more accurately. it is because the possibility of flooding caused by the capacity of stormwater pipes is decreased when the drainage density is high. It would be very efficient if the structure of stormwater pipe network is considered when the network is designed.
The rational method is formed area, rainfall intensity and runoff coefficient that is representation of land use or surface type. A runoff coefficient is a range for a each surface conditions. Drainage Sewer Design Guideline revised at 2011 proposes return periods 10~30 year instead of 5~10 year for increasing design flood. Ponce and ASCE refer higher values of runoff coefficient require for higher values of rainfall intensity and return period, therefore runoff coefficient had to be corrected but not. In case of park, land use and surface type are different from Korea and U.S, so impervious area ratio is different. The runoff coefficient for park is estimated considering with impervious area ratio and return period. 1,004's parks in 20 cities are randomly selected for impervious area ratio and runoff coefficient is estimated. And a proportion of 30 year return period runoff coefficient to 10 year return period with rainfall duration is calculated for 69 weather stations. The estimated runoff coefficient is 0.43~0.54 for return period 10~30 year and the difference of region and rainfall duration is not significant.
Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.
Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.
The dam reservoir inflow prediction is utilized to ensure for water supply and prevent future droughts. In this study, we predicted the dam reservoir inflow and analyzed how seasonal weather forecasting affected the accuracy of the inflow for even multi-purpose dams. The hindcast and forecast of GloSea5 from KMA were used as input for rainfall-runoff models. TANK, ABCD, K-DRUM and PRMS models which have individual characteristics were applied to simulate inflow prediction. The dam reservoir inflow prediction was assessed for the periods of 1996~2009 and 2015~2016 for the hindcast and forecast respectively. The results of assessment showed that the inflow prediction was underestimated by comparing with the observed inflow. If rainfall-runoff models were calibrated appropriately, the characteristics of the models were not vital for accuracy of the inflow prediction. However the accuracy of seasonal weather forecasting, especially precipitation data is highly connected to the accuracy of the dam inflow prediction. It is recommended to consider underestimation of the inflow prediction when it is used for operations. Futhermore, for accuracy enhancement of the predicted dam inflow, it is more effective to focus on improving a seasonal weather forecasting rather than a rainfall-runoff model.
Climate change impact on urban drainage system are analyzed in Seoul by using high-resolution climate change scenario comparing 2000s (1971~2000) with 2020s (2011~2040), 2050s (2041~2070) and 2080s (2071~2100). The historical hourly observed rainfall data were collected from KMA and the climate change scenario-based hourly rainfall data were produced by RegCM3 and Sub-BATS scheme in this study. The spatial resolution obtained from dynamic downscaling was $5{\times}5km$. The comparison of probability rainfalls between 2000s and 2080s showed that the change rates are ranged on 28~54%. In particular, the increase rates of probability rainfall were significant on 3, 6 and 24-hour rain durations. XP-SWMM model was used for analyzing the climate change impacts on urban drainage system. As the result, due to the increase of rainfall intensities, the inundated areas as a function of number of flooded manhole and overflow amounts were increasing rapidly for the 3 future periods in the selected Gongneung 1, Seocho 2, Sinrim 4 drainage systems. It can be concluded that the current drainage systems on the selected study area are vulnerable to climate change and require some reasonable climate change adaptation strategies.
Journal of the Korean Society for Marine Environment & Energy
/
v.13
no.1
/
pp.1-11
/
2010
In order to understand the biological environmental characteristics with temporal variations of the physico-chemical factors in 2012 Yeosu Expo site of Korea, we investigated at one station, once per week, from April 2006 to December 2007. The surface water temperature ranged from 6.8 to $27.8^{\circ}C$ and the bottom water temperature ranged from 6.3 to 25.9 $25.9^{\circ}C$. The salinity varied from 12.8 to 33.0 psu in the surface water and from 25.2 to 33.6 psu in the bottom water. A strong halocline was observed between the surface and bottom layers in the summer when a rapid decrease of salinity coincided with heavy rainfall. The DIN concentration ranged from 1.36 to $82.7{\mu}M$ in the surface water and from 0.82 to $25.2{\mu}M$ in the bottom water. Phosphate concentration varied from 0.06 to $2.13{\mu}M$ in the surface water and from 0.07 to $1.38{\mu}M$ in the bottom water. Silicate was $1.68-52.0{\mu}M$ in the surface water and $1.37-30.7{\mu}M$ in the bottom water. The nutrient concentrations were generally high during heavy rainfalls and low water temperature periods, and considerably decreased in spring and autumn. The N/P ratio ranged from 4.43 to 325 in the surface water and from 3.8 to 321 in the bottom water. It increased rapidly during the heavy rainfall season and remained at a value of approximately 16 in other periods. The chlorophyll a concentration ranged from 0.46 to $65.0{\mu}g$$L^{-1}$ in the surface water and from 0.71 to $15.0{\mu}g$$L^{-1}$ in the bottom water. $Chl-{\alpha}$ concentration remained low in periods of low water temperature, however rapidly increased in periods of high water temperature. From the results of principal component analysis (PCA) and multiple regression analysis (MRA), we conclude that temporal variations of physico-chemical and biological factors were greatly affected by the influx of fresh water, and that nutrients were well controlled by their uptake and assimilation by phytoplankton. Also, during the low water temperature periods, environmental structure in this study site was affected by recycled nutrients through nutrient cycling and mineralization.
We analyzed a time series composed of the annual precipitations of Seoul based on the measurements of a Korean raingage and a modern raingage. The precipitations measured with a Korean raingage for the period of 1771 to 1907 are followed by the precipitations with a modern raingage for the period of 1908 to 1990. The latter part of the time series of annual precipitations were obtained from a book for annual precipitations of Korea by Korea Meteorological Administration and the former from Wada's table 1 for monthly precipitations reproduced from the daily rainfall measurements by a Korean raingage for the period of the Yi Dynasty. In our analysis three different precipitation regimes clearly stand out of the entire period. In order to define objectively the period of each precipitation regime we made a time series of 9 year moving averages from the above time series. By taking into account the shapes of the moving average time series and by using a threshold value of annual precipitation 1050 mm, we defined three precipitation regimes of wet period 1(WP1), dry period (DP), and wet period 2 (WP2). The WP1 and WP2 show very similar characteristics in out statistical analyses. On the other hand, DP is very different from the two periods in many statistical aspects. The strong similarities of the WP1 and WP2 regimes in the magnitudes of statistical parameters and in the shapes of their power spectrum distribution are supporting very positively the soundness of precipitation amounts measured with a Korean raingage in spite of numerous conceivable errors which might have been introduced into measurements of precipitation due to changes of observation site and environment, the scale of units employed, and urbanization of Seoul, etc. However, the annual precipitation amounts are not enough to examine throughly the characteristic of precipitation variations during the two regimes. It is definitely necessarly to recover the daily amounts of precipitation, based on two or three times measurements of rainfall with a Korean raingage, scattered in various ancient documents such as the official diary of 'Seungjeong-weon'
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