• Title/Summary/Keyword: monthly precipitation

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THE STUDY OF FLOOD FREQUENCY ESTIMATES USING CAUCHY VARIABLE KERNEL

  • Moon, Young-Il;Cha, Young-Il;Ashish Sharma
    • Water Engineering Research
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    • v.2 no.1
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    • pp.1-10
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    • 2001
  • The frequency analyses for the precipitation data in Korea were performed. We used daily maximum series, monthly maximum series, and annual series. For nonparametric frequency analyses, variable kernel estimators were used. Nonparametric methods do not require assumptions about the underlying populations from which the data are obtained. Therefore, they are better suited for multimodal distributions with the advantage of not requiring a distributional assumption. In order to compare their performance with parametric distributions, we considered several probability density functions. They are Gamma, Gumbel, Log-normal, Log-Pearson type III, Exponential, Generalized logistic, Generalized Pareto, and Wakeby distributions. The variable kernel estimates are comparable and are in the middle of the range of the parametric estimates. The variable kernel estimates show a very small probability in extrapolation beyond the largest observed data in the sample. However, the log-variable kernel estimates remedied these defects with the log-transformed data.

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A Preliminary Study on the Chemical Compositions of Precipitation in the Rural Area of Kyunggi Province near Demilitarized Zone (비무장지대에 인접한 경기도 농촌지역 강수의 화학적 성분에 관한 기초 연구)

  • 박국태;김창호
    • Journal of Environmental Science International
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    • v.7 no.2
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    • pp.157-164
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    • 1998
  • preliminary study on the chemical compositions of forty seven precipitations from March 1994 to May 1995 In Yeoncheon-gun, which Is adjacent to the southern boundary of demilitarized zone (DMZ) in the northernmost tip of Kyunggi Province has been Performed. The metal cation and anion concentrations were measured by atomic absorption spectrometer and ion chromatography, respectively. pH/lon meter and direct nesslerization method were used for the concentration measurements of $H^+$ ion and $NH_46+$ ions, respectively Based on the data, the quantitative orders of the cation and anion average concentrations were $Ca^{2+}>NH_4^+>Na^+>K^+>Mg^{2+}>H^+ and SO_4^{2+}>Cl^-> NO_3^-$, respectively..The ratio of average total anion concentration to average total cation concentration was 0.97. The average pH value of the precipitations was 5.60. These results, correlation coefficients between the ion concentrations, and monthly variations of pH value and precipitation amount are used for chemical analysis on the environmental Pollution and Pollutant sources In Yeoncheon-gun of Kyunggi province near DMZ.

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Evaluation of the predictive performance for monthly precipitation of a deep learning model for drought forecasting (가뭄 예보를 위한 딥러닝 모델의 월 강수량 예측 성능 평가)

  • Won, Jeongeun;Choi, Jeonghyeon;Kim, Sangdan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.304-304
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    • 2022
  • 가뭄은 인간 활동과 생태계의 다양한 측면에 영향을 미치는 중요한 자연재해 중 하나이다. 가뭄을 사전에 예측하여 필요한 완화 조치를 취하고 환경적 피해를 줄이는 것이 중요하다. 이에 따라 다양한 인공지능 기술을 이용한 가뭄 예측은 수문학, 수자원 관리, 농업 등의 분야에서 중요성이 커지고 있다. 최근에는 딥러닝 알고리즘을 기반으로 하는 중장기 강수예보를 위한 다양한 방법이 제시되고 있다. 이 논문의 목적은 가뭄 예보를 목적으로 월 강수량 예측을 위한 딥러닝 모델의 성능을 평가하는 것이다. 이를 위해 딥러닝 모델인 LSTM(Long Short-Term Memory)을 적용하였으며, 1981-2020년 기간의 월 강수 자료가 모델을 구축하기 위해 사용되었다. 관측자료를 기반으로 학습된 모델을 이용하여 테스트 기간에 대해 월 강수량을 예측하였다. 예측된 강수량을 통해 표준강수지수(Standardized Precipitation Index, SPI)을 산정하고, 예측 정확도를 분석하였다. 이 연구는 가뭄 예보를 위한 딥러닝 모델의 적용 가능성을 보여준다.

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Microclimatological Characteristics Observed from the Flux Tower in Gwangneung Forest Watershed (플럭스 타워에서 관측된 광릉 산림 소유역의 미기후학적 특징)

  • Choi Taejin;Lim Jong-Hwan;Chun Jung-Hwa;Lee Dongho;Kim Joon
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.7 no.1
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    • pp.35-44
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    • 2005
  • Microclimate of Gwangneung forest watershed is characterized by analyzing wind, radiation, profiles of air temperature and humidity, soil and bole temperature, precipitation and soil water content measured at and around the flux tower from April 2000 to September 2003. Mountain-valley wind was prevalent due to the topographic effect with dominant wind from east during daytime and relatively weak wind from west during nighttime. Air temperature reaches its peak in July-August whereas monthly-averaged incoming shortwave radiation shows its peak in May due to summer monsoon. Albedo ranges from 0.12 to 0.16 during the growing season. Monthly-averaged bole temperature is in phase with monthly- averaged air temperature which is consistently higher. Monthly-averaged soil temperature lags behind air temperature and becomes higher with leaf fall. With the emergence of leafage in April, maximum temperature level during midday shifts from the ground surface to the crown level of 15-20m in May. Profiles of water vapor pressure show a similar shift in May but the ground surface remains as the major source of water. Vapor pressure deficit is highest in spring and lowest in winter. Monthly averaged surface soil temperatures range from 0 to 20℃ with a maximum in August. Monthly averaged trunk temperatures of the dominant tree species range from -5.8 to 21.6℃ with their seasonal variation and the magnitudes similar to those of air temperature. Annual precipitation amount varies significantly from year to year, of which >60% is from July and August. Vertical profiles of soil moisture show different characteristics that may suggest an important role of lateral movement of soil water associated with rainfall events.

Estimation of Actual Evapotranspiration and Storage Change for the Bokahcheon Upper-middle Watershed (복하천 중상류 유역의 실제증발산량과 저류변화량 산정)

  • Lee, Jeongwoo;Kim, Nam Won;Lee, Jeong Eun
    • Journal of Korea Water Resources Association
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    • v.47 no.7
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    • pp.615-628
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    • 2014
  • The objectives of this study are to estimate the annual and monthly actual evapotranspiration for the Bokhacheon upper-middle watershed using the data from 1996 to 2012 simulated by SWAT-K model, and to evaluate the effect of storage change on the actual evapotranspiration based on water balance estimates. The simulated results of the annual actual evapotranspiration showed the range from 401 mm to 494 mm and the annual mean of 436 mm, about 31% of the annual mean of precipitation. The average monthly estimates of the actual evapotranspiration showed the range of 10 mm/month in Dec to 84 mm/month in Jul. From the analyses of annual mean storage changes according to data length, it was found out that more than four to five years of data of precipitation and runoff are needed to estimate the watershed based actual evapotranspiration with ignorance of the storage change for this study area. Furthermore, annual and monthly relations between the storage change and the difference of precipitation and runoff were derived which can be effectively used for estimating actual evapotranspiration based on water balance analysis.

Estimation and Spatial Distribution of Monthly FDSI Using AMSR2 Satellite Image-based Soil Moisture in South Korea (AMSR2 위성영상 기반 토양수분을 이용한 우리나라 월별 FDSI 산정 및 공간 분포 특성 분석)

  • Chun, Beomseok;Lee, Taehwa;Jeong, Kwangjune;Shin, Yongchul
    • Journal of The Korean Society of Agricultural Engineers
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    • v.64 no.4
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    • pp.31-43
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    • 2022
  • In this study, we estimated the monthly FDSI (Flash Drought Stress Index) for assessing flash drought on South Korea using AMSR2(Advanced Microwave Scanning Radiometer 2) satellite-based soil moisture footprints. We collected the AMSR2 soil moisture and climate-land surface data from April to November 2018 for analyzing the monthly FDSI values. We confirmed that the FDSI values were high at the regions with the high temperature/evapotranspiration while the precipitation is relatively low. Especially, the regions which satisfied an onset of flash drought (FDSI≧0.71) were increased from June. Then, the most of regions suffered by flash drought during the periods (July to August) with the high temperature and evapotranspiration. Additionally, the impacts of landuse and slope degree were evaluated on the monthly FDSI changes. The forest regions that have the steep slope degree showed the relatively higher FDSI values than the others. Thus, our results indicated that the the slope degree has the relatively higher impact on the onset and increasing of flash drought compared to the others.

Acid rain in Kwangiu, Korea (Precipitation intensity and persistent time) (남한의 광주광역시에서 산성비에 관한 연구)

  • 류찬수
    • Journal of Environmental Science International
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    • v.5 no.5
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    • pp.663-676
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    • 1996
  • The analyzed results of observed precipitation and its pH in Kwangiu for 262 days from fan. 1, 1991 to Dec. 31, 1995 are as follows. The annual mean pH was 5.7, and the monthly mean pH values of January-May and November were less than 5.6 in Kwangiu. The ratio of acid rain for these periods was about 48.1%, almost half that of the total observed days. In March, the pH was 5.4 and the ratio of acid precipitation was 69%, an especially serious situation. In the spring, the pH value was 5.5, thus weakly acidic. The pH of precipitation tended to decrease with greater precipitation. The relation between persistent time and pH of precipitation is variable, but if the persistent time is long, the pH is constant and low. It is fortunate that there is an increasing trend of pH in interannual variation, but it is thought important that the amplitude of variation of pH in 1995 was high and the pH value was 4.1 in October and November. Because heavy and persistent precipitation effects the accumulation of acidity, more concern about acid rain is needed.

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A Study on the Simulation of Daily Precipitation Considering Spatial Probability Characteristics (공간적(空間的) 확률구조(確率構造)를 고려(考慮)한 일강수량(日降水量)의 모의발생(模擬發生)에 관한 연구(硏究))

  • Lee, Jae Joon;Lee, Won Hwan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.6 no.3
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    • pp.31-42
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    • 1986
  • The probabilistic model was developed to give a spatial simlation of precipitation series to solve the problem of future need of water resources. The simulation of daily precipitation series at the sub-base stations was induced from the spatial structure of rainfall occurrence probability between the base station and the sub-base stations in the watershed. In this study Hadong was chosen as the base station in Seomjin river basin and Imsil, Boseong, Soonchang, Dongbok, and Gurye were also selected as the sub-base stations. The results of this study are as follows; 1) The separation technique of spatial precipitation state showed effectiveness in the spatial simulation method because the occurrence probability by each precipitation state (Wet-Wet, Dry-Wet, Wet-Dry, and Dry- Dry system) represented the stable value. 2) The daily precipitation series of the sub-base stations which were simulated from those of the base station showed that the simulated annual mean precipitations were similar to the observed data, but the precipitations in summer were decreased slightly. 3) The correlogram and power spectrum of the simulated monthly precipitation for the sub-base stations showed those of the observed sample with good agreement.

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Evaluation and Comparison of Meteorological Drought Index using Multi-satellite Based Precipitation Products in East Asia (다중 위성영상 기반 강우자료를 활용한 동아시아 지역의 기상학적 가뭄지수 비교 분석)

  • Mun, Young-Sik;Nam, Won-Ho;Kim, Taegon;Hong, Eun-Mi;Sur, Chanyang
    • Journal of The Korean Society of Agricultural Engineers
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    • v.62 no.1
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    • pp.83-93
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    • 2020
  • East Asia, which includes China, Japan, Korea, and Mongolia, is highly impacted by hydroclimate extremes such drought, flood, and typhoon recent year. In 2017, more than 18.5 million hectares of crops have been damaged in China, and Korea has suffered economic losses as a result of severe drought. Satellite-derived rainfall products are becoming more accurate as space and time resolution become increasingly higher, and provide an alternative means of estimating ground-based rainfall. In this study, we verified the availability of rainfall products by comparing widely used satellite images such as Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with ground stations in East Asia. Also, the satellite-based rainfall products were used to calculate the Standardized Precipitation Index (SPI). The temporal resolution is based on monthly images and compared with the past 30 years data from 1989 to 2018. The comparison between rainfall data based on each satellite image products and the data from weather station-based weather data was shown by the coefficient of determination and showed more than 0.9. Each satellite-based rainfall data was used for each grid and applied to East Asia and South Korea. As a result of SPI analysis, the RMSE values of CHIRPS were 0.57, 0.53 and 0.47, and the MAE values of 0.46, 0.43 and 0.37 were better than other satellite products. This satellite-derived rainfall estimates offers important advantages in terms of spatial coverage, timeliness and cost efficiency compared to analysis for drought assessment with ground stations.

Spatial Downscaling of Grid Precipitation Using Support Vector Machine Regression (SVM 회귀 모형을 활용한 격자 강우량 상세화 기법)

  • Moon, Heewon;Baik, Jongjin;Hwang, Sukhwan;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.47 no.11
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    • pp.1095-1105
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    • 2014
  • A spatial downscaling method using the Support Vector Machine (SVM) Regression for 25 km Tropical Rainfall Measuring Mission (TRMM) Monthly precipitation is proposed. The nonlinear relationship among hydrometeorological variables and precipitation was effectively depicted by the SVM for predicting downscaled grid precipitation. The accuracy of spatially downscaled precipitation was estimated by comparing with rain gauge data from sixty-four stations and found to be improved than the original TRMM data in overall. Especially the positive bias of the original TRMM data was effectively removed after the downscaling procedure. The spatial distributions of 25 km and 1 km grid precipitation were generally similar, while the local spatial trend was better detected by 1 km grid precipitation. The downscaled grid data derived from the proposed method can be applied in hydrological modelling for higher accuracy and further be studied for developing optimized downscaling method incorporation other regression methods.