Analytical solutions for solute transport in groundwater and riverine flow using Green’s Function Method and pertinent coordinate transformation method

Sanskrityayn, Abhishek,Suk, Heejun,Kumar, Naveen Elsevier 2017 Journal of hydrology Vol.547 No.-

<P><B>Abstract</B></P> <P>In this study, analytical solutions of one-dimensional pollutant transport originating from instantaneous and continuous point sources were developed in groundwater and riverine flow using both Green’s Function Method (GFM) and pertinent coordinate transformation method. Dispersion coefficient and flow velocity are considered spatially and temporally dependent. The spatial dependence of the velocity is linear, non-homogeneous and that of dispersion coefficient is square of that of velocity, while the temporal dependence is considered linear, exponentially and asymptotically decelerating and accelerating.</P> <P>Our proposed analytical solutions are derived for three different situations depending on variations of dispersion coefficient and velocity, respectively which can represent real physical processes occurring in groundwater and riverine systems. First case refers to steady solute transport situation in steady flow in which dispersion coefficient and velocity are only spatially dependent. The second case represents transient solute transport in steady flow in which dispersion coefficient is spatially and temporally dependent while the velocity is spatially dependent. Finally, the third case indicates transient solute transport in unsteady flow in which both dispersion coefficient and velocity are spatially and temporally dependent. The present paper demonstrates the concentration distribution behavior from a point source in realistically occurring flow domains of hydrological systems including groundwater and riverine water in which the dispersivity of pollutant’s mass is affected by heterogeneity of the medium as well as by other factors like velocity fluctuations, while velocity is influenced by water table slope and recharge rate. Such capabilities give the proposed method’s superiority about application of various hydrological problems to be solved over other previously existing analytical solutions. Especially, to author’s knowledge, any other solution doesn’t exist for both spatially and temporally variations of dispersion coefficient and velocity.</P> <P>In this study, the existing analytical solutions from previous widely known studies are used for comparison as validation tools to verify the proposed analytical solution as well as the numerical code of the Two-Dimensional Subsurface Flow, Fate and Transport of Microbes and Chemicals (2DFATMIC) code and the developed 1D finite difference code (FDM). All such solutions show perfect match with the respective proposed solutions.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Analytical solut. of 1D transport eq. developed in groundwater and riverine flow. </LI> <LI> Green’s Function Method and pertinent coordinate transformation method are used. </LI> <LI> The spatial dependence of the velocity is linear, non-homogeneous. </LI> <LI> The spatial dependence of dispersion coefficient is square of that of velocity. </LI> <LI> The temporal dependence is linear, exponential and asymptotic. </LI> </UL> </P>

공간패널모형을 활용한 절도 및 폭력범죄와 사회구조적 변인 간의 관계 분석

염윤호 한국형사법무정책연구원 2020 형사정책연구 Vol.123 No.-

This study examined the relationship between crime and social structural variables using a spatial panel dataset collected in Y district, X city from 2015 to 2017. A volume of study has analyzed such a relationship with different statistical tools but failed to consider both cross-sectional and longitudinal features inherent in criminal phenomena. Even panel data analysis models considering both aspects simultaneously failed to consider spatial dependence inherent in the spatial panel dataset. Thus, among various spatial panel data models, this study applied a ‘dynamic spatial Durbin model’ that simultaneously considers both spatial and temporal dependence within variables. In this process, this study analyzed the discriminatory effects of social structural variables on the two types of crime, theft and violent crime. As a result, this study found that each type of crime is temporally and spatially dependent, but the spatial dependence is partially or completely offset by temporal dependence. This indicates that crime in a specific time and space is influenced by crimes in the same space, but with different time rather than crimes in adjacent areas. Moreover, this study estimated that theft decreases as CCTV density, alcohol outlet density, and multi-family housing increase whereas violent crime decreases as population density and multi-family housing increase, and single-household decreases. Based on these results, this study suggested that customized crime prevention activities, such as the installation of CCTVs in the spatial and temporal hotspot of theft, be implemented depending on crime types and socioeconomic conditions.

Spatial Dependence in Local Suicide Ideation and Actual Suicide among the Elderly : A Comparative Study between Men and Women

Kim, Taewan,Jun, Hee-Jung 대한국토·도시계획학회 2021 국토계획 Vol.56 No.4

This study examined spatial dependence in local suicide ideation and suicide rates among the elderly. Further, we compared the difference in spatial dependence between men and women. For the empirical analysis, we used the 2017 Korea Community Health Survey and spatial analysis. The empirical analysis shows that first, both local suicide ideation and actual suicide among the elderly are spatially dependent. Second, the spatial dependence in local suicide ideation is greater for elderly women while the spatial dependence in local actual suicide rates is greater for elderly men. The empirical results suggest that suicide prevention policies among the elderly should be refined to reflect spatial dependence in local suicides and gender differences between local suicide ideation and actual suicide regarding spatial dependence.

스튜던트 T 코퓰라 모델을 이용한 지역별 쌀생산량의 공간적 종속성 추정

김태후,김성섭,서상택 한국농업경제학회 2017 농업경제연구 Vol.58 No.3

This study aims to estimate spatial dependence for rice production yield among eight provinces in South Korea. Student’s T copula is used to estimate the spatial dependence and tail dependence. Yearly historical rice production yield data(1960-2016) for eight provinces are de-trended and normalized as year 2016 to estimate spatial dependence and tail dependence. The result shows that rice production yields for most provinces are strongly correlated to each other. Also, tail dependence shows a strong relationship for each other except some provinces. This implies that crop insurance programs should be partly supported by government due to the possibility of high systemic risk. In addition, regional production yield risk modelling imposing the spatial dependence is proper than an unified aggregate risk modelling.

스튜던트 T 코퓰라 모델을 이용한 지역별 쌀 생산량의 공간적 종속성 추정

김태후 ( Taehoo Kim ),김성섭 ( Seongsup Kim ),서상택 ( Sangtaek Seo ) 한국농업경제학회 2017 The Korean journal of agricultural economics Vol.58 No.3

This study aims to estimate spatial dependence for rice production yield among eight provinces in South Korea. Student’s T copula is used to estimate the spatial dependence and tail dependence. Yearly historical rice production yield data(1960-2016) for eight provinces are de-trended and normalized as year 2016 to estimate spatial dependence and tail dependence. The result shows that rice production yields for most provinces are strongly correlated to each other. Also, tail dependence shows a strong relationship for each other except some provinces. This implies that crop insurance programs should be partly supported by government due to the possibility of high systemic risk. In addition, regional production yield risk modelling imposing the spatial dependence is proper than an unified aggregate risk modelling.

Investigating Spatial Dependence and Spatial Variations in the Customer Satisfaction-Customer Loyalty Relationship

Young Han Bae(배영한),Seung Hun Yu(유승훈),Moon Young Kang(강문영) 한국유통학회 2016 流通硏究 Vol.21 No.4

최근 마케팅에서 고객 관련 지수와 기업의 재무 성과에 대한 연구가 활발하다. 이러한 연구들은 고객 관련 지수가 기업의 수익성에 긍정적으로 영향을 미친다고 밝혔다. 고객 관련 지수 중에서 특히 고객 충성도가 기업의 수익성에 가장 중요한 요인이고, 고객 만족도가 고객 충성도에 가장 큰 기여를 하는 요인이라고 알려져 있다. 그러나, 최신 연구에서 고객 만족도가 반드시 고객 충성도로 연결 되지는 않는다는 사실이 밝혀졌다. 이 같은 사실은 고객 만족도와 고객 충성도 데이터에서 공간 의존성과 공간 변화성을 고려하지 않았기 때문으로 설명될 수 있다. 고객 만족도와 고객 충성도의 관계에 대한 기존 연구들은 전통적으로 고객의 만족도와 충성도에 대한 공간 의존성과 다양한 지리적 공간과 상품 카테고리에 대한 공간 변화성에 대해 고려하지 않았었다. 따라서 이러한 모델로부터 도출한 모수들은 편향되고 일관성이 없는 문제가 있을 수 있다. 이러한 문제를 해결하고자, 본 연구에서는 공간 의존성과 공간 변화성을 반영한 공간 모형들을 사용하여 다양한 상품 카테고리에 대해서 고객 만족도와 고객 충성도의 관계에 대해 입증하였다. 본 연구를 통해 고객 만족도가 고객 충성도에 긍정적으로 영향을 미치지만, 이러한 긍정적 관계는 지리적 공간에 따라서 변화하고, 특히 상품 카테고리에 따라 변화한다는 사실을 확인했다. 본 연구의 결과는 학문적인 시사점 및 정부와 기업의 유통 정책/전략 수립에 근거를 제시한다. For recent decades, a plethora of research in marketing literature has explored the relationship between customer (or market) metrics and firm financial performance. These studies have found that customer metrics have a positively significant impact on firm profitability. The literature has identified that among customer metrics, customer loyalty is one of the most important drivers for firm profitability, and customer satisfaction is a key antecedent to customer loyalty. However, the literature is challenged by the finding that customer satisfaction does not always equate to customer loyalty. This challenge may be due to researchers’ failure to identify the spatial dependence and spatial variation in customer satisfaction-loyalty data. Research on the customer satisfaction-loyalty relationship, in general, employs classical global empirical models that do not account for spatial dependence across customers’ satisfaction-loyalty behavior or spatial variation in customers’ behavior across different geographic spaces and product categories. Therefore, the parameter estimates of customer satisfaction obtained from these models could be biased and inconsistent, which leads to inconsistent empirical results. To remedy this problem, we employ global and multi-level spatial regression models to examine the customer satisfaction-customer loyalty relationship across different product categories, given that these spatial models can effectively handle spatial dependence and spatial variation. The empirical results indicate that customer satisfaction is a very significant antecedent to customer loyalty, and its impact is positive after controlling for spatial dependence. However, the strength of this positive customer satisfaction-loyalty association varies over geographic space and, more importantly, product category. These results provide significant academic and managerial implications for retailers.

지역간 건강 불평등의 공간적 분포: 3대 사망원인을 중심으로

강승엽(Kang, Seung Yeoup),전희정(Jun, Hee Jung) 한국지역개발학회 2021 한국지역개발학회 학술대회 Vol.2021 No.11

This study aims to analyze the spatial dependencies in three leading causes which is consist of malignant neoplasm, heart disease and pneumonia of mortality to examine health inequalities across the country. We used local mortality rate data and spatial analysis to assess the longitudinal patterns in local health inequities. The empirical analysis shows that local mortality rates are spatially dependent. Also, each disease has shown different spatial dependence. Cancer and Heart disease`s Moran`s I index were decreased whereas Pneumonia`s spatial dependence has increased. Clusters were shown different patterns. If Moran’s I index is high, cluster is make a huge cluster were located specific location but if not, cluster are spread out. It means that health inequities is getting worse in pneumonia case. Mortality change rate also has spatial dependence. We also observed that the spatial clusters are located differently. In cancer case, localities with more improved health statuses are concentrated in the non capital regions, while the spatial clusters of localities with less improved health statuses are concentrated in the capital region. That is, there is a spatial intersection between the clusters for unhealthy localities and those for localities with improved health statuses, thereby suggesting that health inequities between localities have declined. However, Heart disease and pneumonia showed opposite phenomena. Some part of disease`s the health inequities between localities are still robust, along with regional disparities in Korea. These results suggest that it is necessary to consider spatial aspects in public health policies and that collaborative efforts should be made for more successful policy outcomes to prevent regional health inequities.

공간통계기법을 이용한 암 발생율과 지리・환경적 특성과의 연관성 분석

이석호,김감영 한국지도학회 2019 한국지도학회지 Vol.19 No.3

Cancer has long been the leading cause of death for Koreans, mainly due to environmental factors. Despite the high mortality caused by cancer, Korean studies on how geographical and environmental factors affect cancer are insufficient. The purpose of this study is to understand how the incidence of major cancers including thyroid, colorectal, stomach, lung, liver, prostate, and breast cancers differs according to geographical and environmental factors from a spatial perspective. For this purpose, Cancer incidence calculated at the si-gun-gu level was used as dependent variables, and 13 variables that were expected to affect cancer development were selected as independent variables. Global and local Moran's I statistics were used to identify spatial dependency and clustering of the dependent variables. OLS and spatial regression models were used to identify factors that affect cancer development. Global Moran’s I statistics and LISA cluster maps show spatial autocorrelation in spatial patterns of cancer development. The OLS regression analysis was performed to identify variables affecting cancer development. Since age effect was strong in most cancers, it was controlled. After confirming that spatial dependence is clearly shown in the residuals of OLS model, spatial regression analyses were performed to model spatial dependency. The results showed that the spatial regression models are suitable for explaining the incidence for all types of cancer. In particular, considering the spatial dependency, it was confirmed that factors affecting cancers may be different from those of OLS regression analysis. The results of this study showed that spatial statistical analysis can more accurately identify geographical and environmental factors affecting cancer development. These findings provide useful information on how to improve local environments to prevent cancer. 암은 오랫동안 한국인의 주된 사망원인이었으며, 주로 환경적 요인이 암 발생에 영향을 주고 있다. 암으로 인한 높은사망률에도 불구하고, 어떠한 지리적 및 환경적 요인이 암 발생에 영향을 주는지에 대한 국내 사례 연구는 부족한 실정이다. 본 연구의 목적은 공간적 관점에서 갑상선암, 대장암, 위암, 폐암, 간암, 전립선암, 유방암을 포함한 주요 암의 발생률이 지리・환경적요인에 따라 어떻게 다르게 나타나는지를 파악하는 것이다. 이를 위하여, 시군구 수준에서 계산된 암 발생률을 종속변수로 활용하였고, 암 발병에 영향을 미칠 것으로 기대되는 13가지 독립변수를 선정하였다. 종속변수의 공간적 의존성 및 군집을 확인하기 위하여전역적, 국지적 Moran ’ s I 통계량을 이용하였고, 암 발병에 영향을 미치는 요인을 파악하기 위하여 OLS 및 공간회귀모형들을활용하였다. 전역적 Moran 통계량과 LISA Cluster map을 통하여 암 발생의 공간적 패턴에서 공간적 자기상관을 확인할 수 있었다. 다음 OLS 회귀 분석을 통하여 암 발생에 영향을 미치는 변수들을 파악하였다. 이때 대부분의 암에서 연령 효과가 강하게 나타났기때문에 이를 통제하였다. OLS 모형의 잔차에서 공간적 의존성이 명확하게 나타남을 확인 한 후, 공간적 의존성을 모형화하기위하여 공간회귀분석을 수행하였다. 분석 결과 모든 유형 별 암에 대한 발생률을 설명하는데 있어 공간회귀분석이 적합한 것으로나타났다. 특히 공간적 의존성을 고려할 경우 암별로 영향을 주는 요인이 OLS 분석 결과와 상이할 수 있음을 확인하였다. 본연구 결과는 공간통계분석을 통하여 암 발생에 영향을 주는 지리 환경적 요인을 보다 정확하게 식별할 수 있음을 보여주었다. 이러한 결과는 암을 예방하기 위하여 지역의 환경을 요인을 어떻게 개선할 것인지에 대한 유용한 정보를 제공한다.

Spatial processes of regional innovation in Guangdong Province, China: empirical evidence using a spatial panel data model

Ting Li,Wenying Fu 기술경영경제학회 2015 ASIAN JOURNAL OF TECHNOLOGY INNOVATION Vol.23 No.3

Spatial processes are highly relevant phenomena in innovation studies. Regional innovation isboth influenced by heterogeneous regional attributes and the neighbouring innovation factors. Spatial econometrics are developed to explicitly cope with the issues of spatial dependence. This paper aims to reveal the spatial processes of regional innovation at the city scale byincluding the spatial terms in panel data specification. The research region, GuangdongProvince, has developed into one of innovation hubs in China. Panel data set in 21municipalities in Guangdong Province over the period of 2001– 2013 has been established. The spatial panel data model shows that regional innovation in Guangdong is driven byR&D expenditure input. Besides, inflow of external knowledge boosts the innovation outputthrough foreign investment stock and imported goods, and it strengthens its role asinnovation impetus for the neighbouring cities with the spatial spillover effect. Meanwhile,the depth and width of knowledge accumulated by specialisation economy anddiversification economy contribute to innovation both for the city itself and theneighbouring cities. Overall, the paper has succeeded in revealing the effect of spatialdependence of innovation output, as well as the ‘spilling over’ of the innovation factors ondistance-based spatial relations.

패널공간 중력모형을 이용한 우리나라 수산물 수출의 결정요인 분석

양이석,안경애,김태영 한국유통경영학회 2017 유통경영학회지 Vol.20 No.5

Exports of fishery products are affected by various factors such as the economy of the other country, exchange rate fluctuations, demand fluctuations, FTAs, non-tariff barriers, and tariff rates. Nevertheless, there is still a lack of studies on the trade of fisheries products that take into account the effects of such exports. And this is essential for establishing and evaluating aquatic export strategy. It is also necessary to consider spatial dependence, since trade flows between specific countries can also affect trade flows in neighboring countries. Therefore, in this study, factors affecting the changes in the export of fishery products were analyzed considering the change of the market conditions in the country and the inside and outside, and the influence on them was analyzed. We tried to analyze the determinants of export of fishery products in 20 exporting countries of Korea from 2000 to 2014 using the spatial panel gravity model under consideration of spatial dependence. The results show that exports are increased with increased GDP and population, and decreased distance between the countries, which meets the basic theory of gravity model. Spatial dependence among exporting parties are presence significantly negatively, which implies that increase in export between certain parties can decrease exports of other neighboring parties. We also found that tariff, non-tariff barrier, and exchange rate are major factors affecting export of fishery products among the countries. 수산물 수출은 상대국의 경제상황, 환율변동, 수요변동, FTA 체결, 비관세장벽 및 관세율 등과 같은 다양한 요인의 영향을 받는다. 그럼에도 불구하고 이러한 수출의 결정요인에 대한 종합적 영향을 고려한 수산물 교역에 대한 연구는 아직 부족한 편이다. 따라서 본 연구에서 국·내외 시장여건의 변화를 고려하여 수산물 수출변화에 영향을 주는 요인을 파악하고 분석하는 것은 수산물 수출전략의 수립 및 평가에 필수적이라 할 수 있다. 또한 특정 국가 간의 무역흐름이 주변 국가의 무역흐름에도 영향을 줄 수 있으므로 공간적 종속성을 고려할 필요가 있다. 따라서 본 연구에서는 공간적 종속성을 고려한 패널 공간중력모형(Spatial Gravity Model)을 이용하여 2000년부터 2014년까지의 우리나라 수출 상대국 20개국을 대상으로 수산물 수출의 결정요인을 분석하고 시사점을 도출하고자 한다. 분석결과 수산물 수출은 GDP와 인구의 증가, 교역국가 간의 거리 감소에 따라 증가하는 것으로 나타나 중력모형의 기본 이론에 부합하게 나타났다. 교역국가간의 음(-)의 공간적 종속성이 존재하며, 이는 특정 무역 당사국간의 수출 증가가 다른 주변국간의 수출을 감소시키는 음(-)의 파급효과를 미치고 있음을 의미한다. 끝으로 관세와 비관세장벽 그리고 환율 변수가 수산물 수출에 영향을 미치는 중요한 요소로 분석되었다.