• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.203-208
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• 2000

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.2 s.25
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• pp.13-24
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• 2007

This study is to derive the rainfall intensity formula based on the representative probability distribution using multivariate analysis in Korea. The annual maximum rainfall data at 57 stations having more than 30years long records were used for 12 durations(10min, 1, 2, 3, 4, 5, 6, 8, 10, 12, 18, 24hr). 50 rainfall characteristics elements are analyzed from the collected data. The widely used 14 probability distributions are applied to the basic data in hydrologic frequency analysis. The homogeneous tests(principal component and cluster analysis) are applied to find the rainfall homogeneity. The results of this study are as followings; (1) The homogeneous test shows that there is no appropriate representative distribution for the whole duration in Korea. But hydrological homogeneous regions of point rainfall could be divided by 5 regions. (2) The GEV distribution for zones I, III, IV, V and the Gumbel distribution for zone II are determined as the representative probability distribution. (3) Comparative analysis of the results shows that the probable rainfalls of representative zones are different from those of existing researches. (4) Rainfall intensity formulas are determined on the basis of the linearization technique for the probable rainfall.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.649-656
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• 2006

The purpose of study is to measure soil erosion quantity for elapsed four years from the fire on forest fired sites of Dong-gu, Daegu. This study was conducted to investigate the characteristics of soil erosion by fire occurrence influencing on the soil erosion were. Also analysis result follows that the relations between soil erosion quantity and rainfall intensity, the slope and elapsed year. The results analysed were as follows: 1. Soil erosion by year of occurrence of forest fire was increased 1.9 to 5.7 times as rainfall intensity was increased by 30 m/hr, and 1.4 to 14.2% as degree of slope was increased by $10^{\circ}$. 2. In the first year of forest fire occurrence, soil erosion was fairly heavy for 10 minutes of initial rainfall of which rainfall intensity was 80 m/hr and degree of slope was $30^{\circ}$. The amount of soil erosion was gradually reduced as elapsed time. From two years after fire, the amount of soil erosion by rainfall intensity and degree of slope was nearly constant. 3. The amount of soil erosion by rainfall intensity and slope in accordance with elapsed time after fire was reduced 28.9 to 94.1% in three years after occurrence of forest fire as compared to the first year of fire. Soil erosion was fairly heavy by rainfall intensity and slope in the first year of fire, but it was gradually reduced from two years after fire. 4. In the analysis on influences of each factors on the amount of soil erosion on forest fired sites, the amount of soil erosion was significant differences in major impacts of each rainfall intensity, degree of slope and elapsed year after fire and interaction of rainfall intensity${\times}$degree of slope and rainfall intensity${\times}$elapsed year after fire, but no differences were observed in interaction of degree of slope${\times}$elapsed year after fire and rainfall intensity${\times}$degree of slope${\times}$elapsed year after fire. Rainfall intensity was the most affecting factor on the amount of soil erosion and followed by degree of slope and elapsed year after fire. 5. For correlation between soil erosion and affecting three factors, soil erosion showed significant positive relation with rainfall intensity and degree of slope at I % level, and significant negative relation with elapsed year after fire at 1 % level. 6. As a result of regression of affecting three factors on soil erosion. rainfall intensity was most significant impact factor in explaining the amount of soil erosion on forest fired sites, followed by degree of slope and elapsed year after forest fire. 7. The formula for estimating soil erosion using rainfall intensity, degree of slope and elapsed year after forest fire occurrence was made. S.E = 0.092R.I + 0.211D.S - 0.942E.Y(S.E : Soil erosion, R.I : Rainfall intensity, D.S : Degree of slope, E.Y : Elapsed year after forest fire occurrence)

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.203-208
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• 2000

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.124-129
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• 2000

• Wind and Structures
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• v.29 no.4
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• pp.247-270
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• 2019

Wind-resistant design of existing cooling tower structures overlooks the impacts of rainfall. However, rainstorm will influence aerodynamic force on the tower surface directly. Under this circumstance, the structural response of the super-large cooling tower (SLCT) will become more complicated, and then the stability and safety of SLCT will receive significant impact. In this paper, surrounding wind fields of the world highest (210 m) cooling tower in Northwest China underthree typical wind velocities were simulated based on the wind-rain two-way coupling algorithm. Next, wind-rain coupling synchronous iteration calculations were conducted under 9 different wind speed-rainfall intensity combinations by adding the discrete phase model (DPM). On this basis, the influencing laws of different wind speed-rainfall intensity combinations on wind-driving rain, adhesive force of rain drops and rain pressure coefficients were discussed. The acting mechanisms of speed line, turbulence energy strength as well as running speed and trajectory of rain drops on structural surface in the wind-rain coupling field were disclosed. Moreover, the fitting formula of wind-rain coupling equivalent pressure coefficient of the cooling tower was proposed. A systematic contrast analysis on its 3D distribution pattern was carried out. Finally, coupling model of SLCT under different working conditions was constructed by combining the finite element method. Structural response, buckling stability and local stability of SLCT under different wind velocities and wind speed-rainfall intensity combinations were compared and analyzed. Major research conclusions can provide references to determine loads of similar SLCT accurately under extremely complicated working conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.150-150
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• 2021

Soil erosion due to climate change is one of the global environmental issues. Especially, Korea is vulnerable to soil erosion as the frequency of extreme rainfall events and rainfall intensity are increasing. Soil erosion causes various problems such as reduced farmlands, deterioration of water quality in rivers, etc. To these severe problems, understanding the process of soil erosion is the first process. Then, it is necessary to quantify and analyze soil ersoion using an erosion model. Soil erosion models are divided into empirical, conceptual, and physics-based models according to the structures and characteristics of models. This study used GSSHA (Gridded Surface Subsurface Hydrologic Analysis), the physics-based erosion model, running on WMS (Watershed Modeling System) to analyze soil erosion vulnerability of the CheonCheon watershed. In addition, we compared the six sediment transport capacity formulas provided in the model and evaluated the equations fir on this study site. Therefore, this result can be as a primary tool for soil conservation management.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.4
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• pp.67-74
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• 2007

Rational method has been widely used to calculate peak runoff drainage design or small watershed because of simplicity and convenience. Runoff coefficient(C) is the most important parameter in the rational method which varies according to rainfall intensity, return period, rainfall duration time and soil characteristics. In practice, constant which is value of C in rational formula has been used from the table, originally based on ASCE. These table value does not consider the upper conditions of the depending factors, hence peak runoff calculation could be in correct. Therefore to calculate C in this paper we have devised an improved formula, considering relationship with rainfall duration, return period and CN of NRCS method. This formula is considered to be more reliable and helpful to the hydrologists and engineers to predict correct peak runoff.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.77-86
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• 1986

The purpose of this study is to estimate an optimum formula of rainfall intensity on basis of the characteristics for short period of rainfall duration in Kyungpook province for the design of urban sewerage and small basin drain system. Results studied are as follows; 1. The optimum method for Taegu and Pohang, Iwai's and Gumbel-Chow's method are recommended respectively. 2. The opotimum type of rainfall intensity for these area, $I=\frac{a}{\sqrt{t}+b}$ (Japanese type), is confirmed with 2.52~4.17 and 1.86~4.54 as a standard deviation for Taegu and Pohang respectively. The optimum formula of rainfall intensity are as follows. Taegu : T : 200 year - $I=\frac{824}{\sqrt{t}+1.5414}$ T : 100 year - $I=\frac{751}{\sqrt{t}+1.4902}$ T : 50 year - $I=\frac{678}{\sqrt{t}+1.4437}$ T : 30 year - $I=\frac{623}{\sqrt{t}+1.4017}$ T : 20 year - $I=\frac{580}{\sqrt{t}+1.3721}$ T : 10 year - $I=\frac{502}{\sqrt{t}+1.3145}$ T : 5 year - $I=\frac{418}{\sqrt{t}+1.2515}$ Pohang : T : 200 year - $I=\frac{468}{\sqrt{t}+1.1468}$ T : 100 year - $I=\frac{429}{\sqrt{t}+1.1605}$ T : 50 year - $I=\frac{391}{\sqrt{t}+1.1852}$ T : 30 year - $I=\frac{362}{\sqrt{t}+1.2033}$ T : 20 year - $I=\frac{339}{\sqrt{t}+1.2229}$ T : 10 year - $I=\frac{299}{\sqrt{t}+1.2578}$ T : 5 year - $I=\frac{257}{\sqrt{t}+1.3026}$ 3. Significant I.D.F. curves derived should be applied to estimate a suitable rainfall intensity and rainfall duration.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.846-851
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• 2006

본 논문은 최근 발생한 집중호우와 이상강우를 고려하여 인천지역에서 사용중인 확률강우강도식에 대한 새로운 확률강우강도식을 제안하였으며, 기상청 자료를 이용하여 지속시간 10분${\sim}$24시간까지의 임의시간 연최대강우량을 산정하였다. 강우지속기간별 확률강우량을 추정하기 위하여 11개의 확률분포형을 적용하였으며 Chi-square 검정방법, Kolmogorov -Smirnov 검정방법, Cramer Von Mises 검정방법으로 적합도 검정과 함께 최근 강우에 대한 경향을 분석하고 실제 발생한 강우 중에서 최대 발생 강우량을 고려하여 적정분포인 GEV 분포를 확률 분포형으로 선정하였다. 확률강우강도식은 최소자승법을 사용하여 Talbot형, Sherman형, Japanese형, 통합형 Ⅰ 및 Ⅱ 형태로 산정하였고, 지역내 하수도 및 하천의 지속시간을 감안하여 확률강우강도식을 결정하였다. 또한 정확성을 고려하여 통합형 Ⅰ을 선택하였고 지속시간에 따른 강우강도식의 확률강우와 관측치를 감안한 강도식을 인천지역의 강우강도식으로 제안하였다.