• Environmental Engineering Research
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• 제21권3호
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• pp.226-232
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• 2016

Rainfall is one of crucial factors that impact on our environment. Rainfall data is important in water resources management, flood forecasting, and designing hydraulic structures. However, it is not available in some rural watersheds without rain gauges. Thus, effective ways of interpolating the available records are needed. Despite many widely used spatial interpolation methods, few studies have investigated rainfall center characteristics. Based on the theory that the spatial distribution of convective rainfall event has a definite center with maximum rainfall, we present a mathematical interpolation method to estimate convective rainfall distribution and indicate the rainfall center location and the center rainfall volume. We apply the method to estimate three convective rainfall events in Santa Catalina Island where reliable hydrological data is available. A cross-validation technique is used to evaluate the method. The result shows that the method will suffer from high relative error in two situations: 1) when estimating the minimum rainfall and 2) when estimating an external site. For all other situations, the method's performance is reasonable and acceptable. Since the method is based on a continuous function, it can provide distributed rainfall data for distributed hydrological model sand indicate statistical characteristics of given areas via mathematical calculation.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.167-167
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• 2023

Soil organic carbon (SOC) is a critical component of soil health and is crucial in mitigating climate change by sequestering carbon from the atmosphere. Accurate estimation of SOC storage is essential for understanding SOC dynamics and developing effective soil management strategies. This study aimed to investigate the factors influencing the spatial distribution of SOC storage in South Korea, using bulk density (BD) prediction to estimate SOC stock. The study utilized data from 393 soil series collected from various land uses across South Korea established by Korea Rural Development Administration from 1968-1999. The samples were analyzed for soil properties such as soil texture, pH, and BD, and SOC stock was estimated using a predictive model based on BD. The average SOC stock in South Korea at 30 cm topsoil was 49.1 Mg/ha. The study results revealed that soil texture and land use were the most significant factors influencing the spatial distribution of SOC storage in South Korea. Forested areas had significantly higher SOC storage than other land use types. Climate variables such as temperature and precipitation had a relative influence on SOC storage. The findings of this study provide valuable insights into the factors influencing the spatial distribution of SOC storage in South Korea.

• Communications for Statistical Applications and Methods
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• 제17권4호
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• pp.493-505
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• 2010

Developing a test for independence of random variables X and Y against the alternative has an important role in statistical inference. Kochar and Gupta (1987) proposed a class of tests in view of Block and Basu (1974) model and compared the powers for sample sizes n = 8, 12. In this paper, we evaluate Kochar and Gupta (1987) class of tests for testing independence against quadrant dependence in absolutely continuous bivariate Farlie-Gambel-Morgenstern distribution, via a simulation study for sample sizes n = 6, 8, 10, 12, 16 and 20. Furthermore, we compare the power of the tests with that proposed by G$\ddot{u}$uven and Kotz (2008) based on the asymptotic distribution of the test statistics.

• 천문학회보
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• 제41권1호
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• pp.46.1-46.1
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• 2016

The formation process of a current sheet is important for solar flare from a viewpoint of a space weather prediction. We therefore derive the temporal development of the spatial and statistical distribution of electric current density distributed in a flare-producing active region to describe the formation of a current sheet. We derive time sequence distribution of electric current density by applying a nonlinear force-free approximation reconstruction to Active Region 12158 that produces an X1.6-class flare. The time sequence maps of photospheric vector magnetic field used for reconstruction are captured by a Helioseismic and Magnetic Imager (HMI) onboard Solar Dynamic Observatory (SDO) on 10th September, 2014. The spatial distribution of electric current density in NLFFF model well reproduce observed sigmoidal structure at the preflare phase, although a layer of high current density shrinks at the postflare phase. A double power-law profile of electric current density is found in statistical analysis. This may be expected to use an indicator of the occurrence of a solar flare.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2000년도 학술발표회 논문집
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• pp.20-27
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• 2000

The grid-based KlneMatic wave STOrm Runoff Modei (Kim, 1998; Kim, et al., 1998) which predicts temporal variation and spatial distribution of saturated overland flow, subsurface flow and stream flow was evaluated at two watersheds. This model adopts the single overland flowpath algorithm and simulates surface and/or subsurface water depth at each cell by using water balance of hydrologic components. The model programed by C-language uses ASCII-formatted map data supported by the irregular gridded map of the GRASS (Geographic Resources Analysis Support System) GIS and generates the spatial distribution maps of discharge, flow depth and soil moisture of the watershed.

• 대한공간정보학회지
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• 제12권3호
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• pp.43-50
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• 2004

본 연구에서 교통수요 예측기법 중 통행량 분포기법의 이론적 배경에 대하여 광주광역시를 중심으로 컴퓨터 시뮬레이션을 통하여 분석 평가하고 모형에 내재되어 있는 매개변수의 특성변화를 연구하여 통행량 분포모형의 적용 타당성을 찾고자 하는데 연구의 목적이 있다. 본 연구에서는 통행분포모형의 정립을 목적으로 광주시의 20개 대존 중에서 도심지역에 해당되는 9개 존을 중심으로 한 통행목적별, 수단별, 출발 도착통행량 모형을 정립하였다. 여기에서는 기준 년도를 1996년으로 하고 2001년까지의 통행량을 분석하고 2008년도까지의 통행분포량을 예측하였다.

• 한국환경과학회지
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• 제27권7호
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• pp.499-507
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• 2018

Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

• Journal of Communications and Networks
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• 제18권5호
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• pp.725-734
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• 2016

For multi-mode radar signals in complex electromagnetic environment, different modes of one emitter tend to be deinterleaved into several emitters, called as "extension", when processing received signals by use of existing sorting methods. The "extension" problem inevitably deteriorates the sorting performance of multi-mode radar signals. In this paper, a novel method based on spatial data mining is presented to address above challenge. Based on theories of data field, we describe the distribution information of feature parameters using potential field, and makes partition clustering of parameter samples according to revealed distribution features. Additionally, an evaluation criterion based on cloud model membership is established to measure the relevance between different cluster-classes, which provides important spatial knowledge for the solution of the "extension" problem. It is shown through numerical simulations that the proposed method is effective on solving the "extension" problem in multi-mode radar signal sorting, and can achieve higher correct sorting rate.

• 대한토목학회논문집
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• 제29권3B호
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• pp.269-279
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• 2009

대유역에서 계획홍수량 추정은 ARF, 강우 시공간분포 및 강우-유출 모형의 매개변수 등에서 많은 불확실성이 발생한다. 과거 동시 강우사상을 이용한 계획홍수량의 추정은 이들 불확실성을 개선할 수 있다. 본 연구는 과거 동시 강우사상과 저류 함수모형을 이용하여 대유역의 홍수량을 추정하는 방법을 제시하였다. 과거 동시 강우사상의 시공간분포를 이용하여 계획 강우량과 강우의 시공간분포를 산정하였고 비선형 강우-유출 반응을 재현할 수 있는 저류함수모형을 이용하여 홍수량을 추정하였다. 추정된 계획홍수량은 실측홍수량에 의한 빈도분석 결과와 비교하여 본 연구에서 제시한 홍수량 추정기법의 적용성을 평가하였다. 본 연구의 결과는 실측홍수량의 빈도해석과 비슷한 결과를 얻었으며 이는 대유역의 홍수량 추정에서 본 연구의 홍수량 추정과정을 충분히 이용할 수 있음을 보여준다.

• 한국지리정보학회지
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• 제23권4호
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• pp.16-41
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• 2020

실제 공간의 분포 또는 양적 속성을 대변하는 지리정보 입력은 지구시스템 모의 내에서 주요 관심사가 되고 있다. 많은 연구에서 다양한 격자 해상도에서의 지표면 특성에 대한 부정확한 추정이 모델링 결과를 크게 바꾸는 것으로 나타났다. 따라서, 이 논문은 도시지역 건물들의 분포와 면적·체적 속성을 반영하기 위해서, 항공라이다로 수집된 3DPC(three-dimensional point cloud) 샘플링 체계에 Monte Carlo Integration(MCI) 기법 기반 공간확률(spatial probability)을 적용을 제안하였다. 건물 식별과 관련해 공간확률(SP) 임계치, 격자 크기, 3차원점군 밀도 세 인자의 결정규칙 적용 결과가 비교되었다. 연구 결과, 건물의 격자가 커짐에 따라 식별되는 건물의 면적 속성이 증가하였다. 공간 모델링 및 분석의 신뢰성을 높이기 위해서는 샘플링 체계에서의 결정규칙을 사용하여 건물의 면적 속성을 조정하는 것이 권장된다. 제안된 방법은 모델링 분야가 요구하는 크고 작은 격자의 변화에서도 일정하게 건물 면적 속성이 유지되도록 지원할 것이다.