• Journal of Korea Water Resources Association
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• v.37 no.7
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• pp.553-567
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• 2004

This study proposes a modified standardized precipitation index (MSPI) which was developed to make up for the weakness of the SPI. Both MSPI and SPI are applied to the monthly rainfall at the Seoul station for the drought analysis. The MSPI proposed is nothing but the SPI for the normalized monthly rainfall, that is, an extra step for normalizing the monthly rainfall is included before driving the SPI. Thus, the MSPI has a structure to transfer the relative amount of rainfall to the next months, but the SPI the absolute amount of rainfall. The monthly rainfall data at the Seoul station used in this study are those collected from 1777 to 1996. The rainfall data collected before and after the long dry period around 1900 were also analyzed separately for the comparison. The results derived are as follows. (1) The MSPI was found to be more practical compared to the SPI. This was assured by comparing the analysis results of the data including and excluding the long dry period around 1900. (2) The MSPI is found to be less sensitive than the SPI to the extreme rainfall events. For the MSPI, the occurrence probabilities of moderate drought before and after the long dry period are similar, but those for the extreme drought becomes slightly decreased after the long dry period (from about 18 years of return period before the long dry period to the 16 years after the long dry period). However, the duration becomes longer after the long dry period (the duration for the extreme drought has been increased from 2 to 2.5 months after the long dry period). This results can also be compared with a rather unreasonable result derived by applying the SPI (for the extreme drought the return period has been decreased to be from 25 to 10 years after the long dry period, on the other hand the duration has been increased from 1.5 months to 3.5 months). So, we man conclude that the MSPI is more practical for the drought analysis that the SPI.

• Magazine of the Korean Society of Agricultural Engineers
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• v.17 no.3
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• pp.3848-3859
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• 1975

The author attempted to find most suitable formulas for probable rainfall intensities with analysis and consideration for characteristics of rainfall intensities according to the short and long period return periods at Cheong-Joo district. Above mentioned formulas induced by this study can be contributed to the credibility of runoff estimation for urban sewerage system, drainage works in small catchment area and embankment works in the rivers. The results of this study are summarized as follows: 1 Calculation values by Gumbel-Chow method were selected as a mean values for the calculation of probable rainfall intensities according to return periods in the short period. 2. Calculations for probable rainfall intensities for long period are based upon to the result by Iwai's method. Talbot type, {{{{I= {a} over {t+b} }}}} is confirmed as a most suitable formula for probable rainfall intensities among calculation methods in the short periods at Cheong-Joo district. 4. Specific coefficient method, I24=RN24${\beta}$N was selected as a means of calculation for suitable formulas of probable rainfall intensities according to return periods in case of long period. 5. Runoff estimation with high credibility by rational formula can be anticipated by establishment for the most suitable probable rainfall intensities at Cheong-Joo district.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.373-373
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• 2021

Rainfall forecasting is an important issue that is applied in many areas, such as agriculture, flood warning, and water resources management. In this context, this study proposed a statistical and machine learning-based forecasting model for monthly rainfall. The Bayesian Gaussian process was chosen to optimize the hyperparameters of the Stacked Long Short-term memory (SLSTM) model. The proposed SLSTM model was applied for predicting monthly precipitation of Seoul station, South Korea. Data were retrieved from the Korea Meteorological Administration (KMA) in the period between 1960 and 2019. Four schemes were examined in this study: (i) prediction with only rainfall; (ii) with deseasonalized rainfall; (iii) with rainfall and minimum temperature; (iv) with deseasonalized rainfall and minimum temperature. The error of predicted rainfall based on the root mean squared error (RMSE), 16-17 mm, is relatively small compared with the average monthly rainfall at Seoul station is 117mm. The results showed scheme (iv) gives the best prediction result. Therefore, this approach is more straightforward than the hydrological and hydraulic models, which request much more input data. The result indicated that a deep learning network could be applied successfully in the hydrology field. Overall, the proposed method is promising, given a good solution for rainfall prediction.

• Atmosphere
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• v.32 no.1
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• pp.1-15
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• 2022

Recently, Japan's Meteorological Research Institute presented the d4PDF database (Database for Policy Decision-Making for Future Climate Change, d4PDF) through large-scale climate ensemble simulations to overcome uncertainty arising from variability when the general circulation model represents extreme-scale precipitation. In this study, the change of precipitation characteristics between the historical and future climate conditions in the Yongdam-dam basin was analyzed using the d4PDF data. The result shows that annual mean precipitation and seasonal mean precipitation increased by more than 10% in future climate conditions. This study also performed an analysis on the change of the return period rainfall. The annual maximum daily rainfall was extracted for each climatic condition, and the rainfall with each return period was estimated. In this process, we represent the extreme-scale rainfall corresponding to a very long return period without any statistical model and method as the d4PDF provides rainfall data during 3,000 years for historical climate conditions and during 5,400 years for future climate conditions. The rainfall with a 50-year return period under future climate conditions exceeded the rainfall with a 100-year return period under historical climate conditions. Consequently, in future climate conditions, the magnitude of rainfall increased at the same return period and, the return period decreased at the same magnitude of rainfall. In this study, by using the d4PDF data, it was possible to analyze the change in extreme magnitude of rainfall.

• Journal of Korea Water Resources Association
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• v.49 no.12
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• pp.1007-1014
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• 2016

The FORGEX (Focused Rainfall Growth Extension) method was developed to estimate rainfall quantiles in the United Kingdom. This method does not need any regional grouping and can estimate rainfall quantiles with relatively long return period. The spatial dependence formula (ln $N_e$) was derived to consider the distance from growth curve of proper population to the distributed network maximum (netmax) data using the UK rainfall data. For this reason, there is an inaccurate problem in rainfall quantiles when this formula is applied in Korea. In this study, the new formula was derived in order to improve such shortcomings using rainfall data of 64 sites from the Korea Meteorological Administration (KMA). A 42-year period (1973~2014) was taken as the reference period from rainfall data, then the formula was derived using three parameters such as rainfall duration, number of site, area of network. Then the new formula was applied to the FORGEX method for regional rainfall frequency analysis. In addition, rainfall quantiles were compared with those from the UK formula. As a result, the new formula shows more accurate results than the UK formula, in which the FORGEX method by the UK formula underestimates rainfall quantiles. Finally, the new improved formula may estimate accurate rainfall quantiles for long return period.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.241-248
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• 2001

Normally at a flood season the operation of the dam depends on a short range weather forecast that makes many difficulties of the management at a dry season. It is needed to study the pattern of the long period rainfall. The concept of PMP(Probable Maximum Precipitation) was used for designing dam. From the concept, this study is applied the concept of monthly probable maximum precipitation for operating dam. It can be possible to let us know the appropriateness of a limiting water level at a rainy season. For the operation of dam at a dry season this study can predict roughly the flood season's pattern of precipitation by month or period, therfore the prediction of precipitation can rise efficient operation of a dam.

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.4
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• pp.52-65
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• 1984

In general precise estimation of hourly of daily distribution of the long-term run-off should be very important in a design of source of irrigation. However, there have not been a satisfying method for forecasting of stationar'y long-term run-off in Korea. Solving this problem, this study introduces unit-hydrograph method frequently used in short-term run-off analysis into the long-term run-off analysis, of which model basin was selected to be Sumgin-river catchment area. In the estimation of effective rainfall, conventional method neglects the Soil moisture condition of catchment area, but in this study, the initial discharge (qb) occurred just before rising phase of the hydrograph was selected as the index of a basin soil moisture condition and then introduced as 3rd variable in the analysis of the reationship between cumulative rainfall and cumulative loss of rainfall, which built a new type of separation method of effective rainfall. In next step, in order to normalize significant potential error included in hydrological data, especially in vast catchment area, Snyder's correlation method was applied. A key to solution in this study is multiple correlation method or multiple regressional analysis, which is primarily based on the method of least squres and which is solved by the form of systems of linear equations. And for verification of the change of characteristics of unit hydrograph according to the variation of a various kind of hydrological charateristics (for example, precipitation, tree cover, soil condition, etc),seasonal unit hydrograph models of dry season(autumn, winter), semi-dry season (spring), rainy season (summer) were made respectively. The results obtained in this study were summarized as follows; 1.During the test period of 1966-1971, effective rainfall was estimated for the total 114 run-off hydrograph. From this estimation results, relative error of estimation to the ovservation value was 6%, -which is mush smaller than 12% of the error of conventional method. 2.During the test period, daily distribution of long-term run-off discharge was estimated by the unit hydrograph model. From this estimation results, relative error of estimation by the application of standard unit hydrograph model was 12%. When estimating by each seasonal unit bydrograph model, the relative error was 14% during dry season 10% during semi-dry season and 7% during rainy season, which is much smaller than 37% of conventional method. Summing up the analysis results obtained above, it is convinced that qb-index method of this study for the estimation of effective rainfall be preciser than any other method developed before. Because even recently no method has been developed for the estimation of daily distribution of long-term run-off dicharge, therefore estimation value by unit hydrograph model was only compared with that due to kaziyama method which estimates monthly run-off discharge. However this method due to this study turns out to have high accuracy. If specially mentioned from the results of this study, there is no need to use each seasonal unit hydrograph model separately except the case of semi-dry season. The author hopes to analyze the latter case in future sudies.

• Journal of the Korean Society of Safety
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• v.37 no.6
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• pp.148-157
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• 2022

Every year, particularly during the monsoon rainy season, landslides at the Chuncheon province of South Korea cause tremendous damage to lives, properties, and infrastructures. More so, the high rainfall intensity and long rainfall days that occurred in 2020 have increased the water content in the soil, thereby increasing the chances of landslide occurrences. Besides this, the rainfall thresholds and characteristics responsible for the initiation of landslides in this region have not been properly identified. Therefore, this paper addresses the rainfall thresholds responsible for the initiation of landslides at Chuncheon from a regional perspective. Using data obtained from rainfall measurements taken from 2002 to 2011, we identify a threshold relationship between rainfall intensity and rainfall duration for the initiation of landslides. In addition, we identify the relationship between the rainfall intensity using a 3-day, 7-day, and 10-day antecedent rainfall observation. Specifically, we estimate the rainfall data at 8 sites where debris flow occurred in 2011 by kriging. Following this, the estimated data are used to construct the relationship between the intensity (I), duration (D), and frequency (F) of rainfall. The results of the intensity-duration-frequency (IDF) analysis show that landslides will occur under a rainfall frequency below a 2-year return period at two areas in Chuncheon. These results will be effectively used to design structures that can prevent the occurrence of landslides in the future.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.2
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• pp.39-52
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• 2020

A high quality, long-term, high-resolution precipitation dataset is an essential in climate analyses and global water cycles. Rainfall data from station observations are inadequate over many parts of the world, especially North Korea, due to non-existent observation networks, or limited reporting of gauge observations. As a result, satellite-based rainfall estimates have been used as an alternative as a supplement to station observations. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and global coverage. CHIRPS is a global precipitation product and is made available at daily to seasonal time scales with a spatial resolution of 0.05° and a 1981 to near real-time period of record. In this study, we analyze the applicability of CHIRPS data on the Korean Peninsula by supplementing the lack of precipitation data of North Korea. We compared the daily precipitation estimates from CHIRPS with 81 rain gauges across Korea using several statistical metrics in the long-term period of 1981-2017. To summarize the results, the CHIRPS product for the Korean Peninsula was shown an acceptable performance when it is used for hydrological applications based on monthly rainfall amounts. Overall, this study concludes that CHIRPS can be a valuable complement to gauge precipitation data for estimating precipitation and climate, hydrological application, for example, drought monitoring in this region.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.451-454
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• 2003

This study was mainly conducted to derive the design drought rainfall by the consecutive duration using probability weighted moments with rainfall in the regional drought frequency analysis. Selecting the drought rainfall series by the consecutive durations of drought observed for the long period all over the regions in Korea, optimal regionalization of the drought rainfall was classified by the climatologically and geographically homogeneous regions. Using the L-moment ratio and Kolmogorov- Smimov test, resonable frequency distribution for the drought rainfall was selected by the regions and consecutive periods of drought. Design drought rainfalls by the regions and consecutive durations were derived and compared by at-site and regional drought frequency analysis using the method of L-moments.