• Title/Summary/Keyword: 크리깅 방법

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Combining Bias-correction on Regional Climate Simulations and ENSO Signal for Water Management: Case Study for Tampa Bay, Florida, U.S. (ENSO 패턴에 대한 MM5 강수 모의 결과의 유역단위 성능 평가: 플로리다 템파 지역을 중심으로)

  • Hwang, Syewoon;Hernandez, Jose
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.14 no.4
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    • pp.143-154
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    • 2012
  • As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni$\tilde{n}$o and La Ni$\tilde{n}$a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

Evaluation of High-Resolution QPE data for Urban Runoff Analysis (고해상도 QPE 자료의 도시유출해석 적용성 평가)

  • Choi, Sumin;Yoon, Seongsim;Lee, Byongju;Choi, Youngjean
    • Journal of Korea Water Resources Association
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    • v.48 no.9
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    • pp.719-728
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    • 2015
  • In this study, urban runoff analyses were performed using high resolution Quantitative Precipitation Estimation (QPE), and variation of rainfall and runoff were analyzed to evaluate QPE data for urban runoff analysis. The five drainage districts (Seocho3, 4, 5, Yeoksam and Nonhyun) around Gangnam station were chosen as study area, the area is $7.4km^2$. Rainfall data from KMA AWS (34 stations), SKP AWS (156 stations) and Gwanduk radar were used for QPEs in Seoul area. Four types of QPE(QPE1: KMA AWS, QPE2: KMA+ SKP AWS, QPE3: Gwangduk radar, QPE4: QPE2+QPE3) of 6 events in July 2013 were generated by using Krigging and conditional merging. The temporal and spatial resolution of QPEs are 10 minutes and 250 m, respectively. The complex pipe network were treated as 773 manholes, 772 sub-drainage districts and 1,059 pipelines for urban runoff analysis as input data. QPE2 and QPE4 show spatial variation of rainfall by sub-drainage districts as 1.9 times bigger than QPE1. The peak runoff of QPE2 and QPE4 also show spatial variation as 6 times bigger than Gangnam and Seocho AWS. Thus, the spatial variation of rainfall and runoff could exist in small area such as this study area, and using high-resolution rainfall data is desirable for accurate urban runoff analysis.

The Study on Flood Runoff Simulation using Runoff Model with Gauge-adjusted Radar data (보정 레이더 자료와 유출 모형을 이용한 홍수유출모의에 관한 연구)

  • Bae, Young-Hye;Kim, Byung-Sik;Kim, Hung-Soo
    • Journal of Wetlands Research
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    • v.12 no.1
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    • pp.51-61
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    • 2010
  • Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, it is important to understand the spatial-temporal features of rainfall. In this study, RADAR rainfall was used to calculate gridded areal rainfall which reflects the spatial-temporal variability. In addition, Kalman-filter method, a stochastical technique, was used to combine ground rainfall network with RADAR rainfall network to calculate areal rainfall. Thiessen polygon method, Inverse distance weighting method, and Kriging method were used for calculating areal rainfall, and the calculated data was compared with adjusted areal RADAR rainfall measured using the Kalman-filter method. The result showed that RADAR rainfall adjusted with Kalman-filter method well-reproduced the distribution of raw RADAR rainfall which has a similar spatial distribution as the actual rainfall distribution. The adjusted RADAR rainfall also showed a similar rainfall volume as the volume shown in rain gauge data. Anseong-Cheon basin was used as a study area and the RADAR rainfall adjusted with Kalman-filter method was applied in $Vflo^{TM}$ model, a physical-based distributed model, and ModClark model, a semi-distributed model. As a result, $Vflo^{TM}$ model simulated peak time and peak value similar to that of observed hydrograph. ModClark model showed good results for total runoff volume. However, for verifying the parameter, $Vflo^{TM}$ model showed better reproduction of observed hydrograph than ModClark model. These results confirmed that flood runoff simulation is applicable in domestic settings(in South Korea) if highly accurate areal rainfall is calculated by combining gauge rainfall and RADAR rainfall data and the simulation is performed in link to the distributed hydrological model.

Comparison of Liquefaction Assessment Results with regard to Geotechnical Information DB Construction Method for Geostatistical Analyses (지반 보간을 위한 지반정보DB 구축 방법에 따른 액상화 평가 결과 비교)

  • Kang, Byeong-Ju;Hwang, Bum-Sik;Bang, Tea-Wan;Cho, Wan-Jei
    • Journal of the Korean Geotechnical Society
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    • v.38 no.4
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    • pp.59-70
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    • 2022
  • There is a growing interest in evaluating earthquake damage and determining disaster prevention measures due to the magnitude 5.8 earthquake in Pohang, Korea. Since the liquefaction phenomena occurred extensively in the residential area as a result of the earthquake, there was a demand for research on liquefaction phenomenon evaluation and liquefaction disaster prediction. Liquefaction is defined as a phenomenon where the strength of the ground is completely lost due to a sudden increase in excess pore water pressure caused due to large dynamic stress, such as an earthquake, acting on loose sand particles in a short period of time. The liquefaction potential index, which can identify the occurrence of liquefaction and predict the risk of liquefaction in a targeted area, can be used to create a liquefaction hazard map. However, since liquefaction assessment using existing field testing is predicated on a single borehole liquefaction assessment, there has been a representative issue for the whole targeted area. Spatial interpolation and geographic information systems can help to solve this issue to some extent. Therefore, in order to solve the representative problem of geotechnical information, this research uses the kriging method, one of the geostatistical spatial interpolation techniques, and constructs a geotechnical information database for liquefaction and spatial interpolation. Additionally, the liquefaction hazard map was created for each return period using the constructed geotechnical information database. Cross validation was used to confirm the accuracy of this liquefaction hazard map.

Spatio-Temporal Characteristics of Droughts in Korea: Construction of Drought Severity-Area-Duration Curves (가뭄의 시공간적 분포 특성 연구: 가뭄심도-가뭄면적-가뭄지속기간 곡선의 작성)

  • Kim, Bo Kyung;Kim, Sang Dan;Lee, Jae Soo;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1B
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    • pp.69-78
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    • 2006
  • The rainfall depth-area-duration analysis which is used to characterize precipitation extremes for specification of so-called design storms, provides a basis for evaluation of drought severity when storm depth is replaced by an appropriate measure of drought severity. So we propose a method for constructing drought severity-area-duration curves in this study. Monthly precipitation data over the whole Korea are used to compute SPI. Such SPIs are abstracted to several independent spatial components from EOF analysis. Using Kriging method, these spatial components are used to constitute grid-based SPI data set over the whole Korea including Jeju island with $6km{\times}6km$ resolution. After identifying main drought events, the drought severity-area-duration curves for these events over 32-year period of record are finally constructed. As a result, such curves show the similar shape with storm-based curves in the sense that the drought severity (or rainfall depth) is inversely proportional to drought area from the curves, but drought-based curves are different from storm-based curves in the sense that the drought severity decreasing rate with respect to drought area is much less than depth decreasing rate.

Recent Changes in Bloom Dates of Robinia pseudoacacia and Bloom Date Predictions Using a Process-Based Model in South Korea (최근 12년간 아까시나무 만개일의 변화와 과정기반모형을 활용한 지역별 만개일 예측)

  • Kim, Sukyung;Kim, Tae Kyung;Yoon, Sukhee;Jang, Keunchang;Lim, Hyemin;Lee, Wi Young;Won, Myoungsoo;Lim, Jong-Hwan;Kim, Hyun Seok
    • Journal of Korean Society of Forest Science
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    • v.110 no.3
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    • pp.322-340
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    • 2021
  • Due to climate change and its consequential spring temperature rise, flowering time of Robinia pseudoacacia has advanced and a simultaneous blooming phenomenon occurred in different regions in South Korea. These changes in flowering time became a major crisis in the domestic beekeeping industry and the demand for accurate prediction of flowering time for R. pseudoacacia is increasing. In this study, we developed and compared performance of four different models predicting flowering time of R. pseudoacacia for the entire country: a Single Model for the country (SM), Modified Single Model (MSM) using correction factors derived from SM, Group Model (GM) estimating parameters for each region, and Local Model (LM) estimating parameters for each site. To achieve this goal, the bloom date data observed at 26 points across the country for the past 12 years (2006-2017) and daily temperature data were used. As a result, bloom dates for the north central region, where spring temperature increase was more than two-fold higher than southern regions, have advanced and the differences compared with the southwest region decreased by 0.7098 days per year (p-value=0.0417). Model comparisons showed MSM and LM performed better than the other models, as shown by 24% and 15% lower RMSE than SM, respectively. Furthermore, validation with 16 additional sites for 4 years revealed co-krigging of LM showed better performance than expansion of MSM for the entire nation (RMSE: p-value=0.0118, Bias: p-value=0.0471). This study improved predictions of bloom dates for R. pseudoacacia and proposed methods for reliable expansion to the entire nation.

Development of an anisotropic spatial interpolation method for velocity in meandering river channel (비등방성을 고려한 사행하천의 유속 공간보간기법 개발)

  • You, Hojun;Kim, Dongsu
    • Journal of Korea Water Resources Association
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    • v.50 no.7
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    • pp.455-465
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    • 2017
  • Understanding of the two-dimensional velocity field is crucial in terms of analyzing various hydrodynamic and fluvial processes in the riverine environments. Until recently, many numerical models have played major roles of providing such velocity field instead of in-situ flow measurements, because there were limitations in instruments and methodologies suitable for efficiently measuring in the broad range of river reaches. In the last decades, however, the advent of modernized instrumentations started to revolutionize the flow measurements. Among others, acoustic Doppler current profilers (ADCPs) became very promising especially for accurately assessing streamflow discharge, and they are also able to provide the detailed velocity field very efficiently. Thus it became possible to capture the velocity field only with field observations. Since most of ADCPs measurements have been mostly conducted in the cross-sectional lines despite their capabilities, it is still required to apply appropriate interpolation methods to obtain dense velocity field as likely as results from numerical simulations. However, anisotropic nature of the meandering river channel could have brought in the difficulties for applying simple spatial interpolation methods for handling dynamic flow velocity vector, since the flow direction continuously changes over the curvature of the channel shape. Without considering anisotropic characteristics in terms of the meandering, therefore, conventional interpolation methods such as IDW and Kriging possibly lead to erroneous results, when they dealt with velocity vectors in the meandering channel. Based on the consecutive ADCP cross-sectional measurements in the meandering river channel. For this purpose, the geographic coordinate with the measured ADCP velocity was converted from the conventional Cartesian coordinate (x, y) to a curvilinear coordinate (s, n). The results from application of A-VIM showed significant improvement in accuracy as much as 41.5% in RMSE.