고정확도의 도시침수 모의를 위해서는 물리적 개념에 기반한 통합적 수치해석이 필요하다. 본 연구에서는 Lee et al. (2015)이 개발한 1차원 하 수관망, 2차원 범람 모형의 국내 적용성을 검토하고, 과거 도시 홍수 사상의 침수 원인 분석을 수행하였다. 본 모형은 이중배수 개념에 기반하여 멘 홀 대신 집수구를 지표면과 하수관망 사이의 교환유량 산정 지점으로 이용하므로 보다 실제와 유사하게 침수 과정을 모의할 수 있을 뿐 아니라 지 표면 범람 해석시 건물에 의한 차단 효과를 고려할 수 있다. 개발된 모형의 적용성은 서울 사당 유역에서 발생한 침수 사상에 대해서 재현 모의를 통 해 검증하였다. 적용 결과, 본 연구에서 개발된 모형은 실제 침수 피해 영역을 실제와 유사하게 모의 하였을 뿐만 아니라 침수 원인을 보다 자세히 분석할 수 있는 장점을 보여주었다.

The relationship between urban spatial structures and GHG-AP integrated emissions was investigated by statistically analyzing those from 25 administrative districts of Seoul. Urban spatial structures, of which data were obtained from Seoul statistics yearbook, were classified into five categories of city development, residence, environment, traffic and economy. They were further classified into 10 components of local area, population, number of households, residential area, forest area, park area, registered vehicles, road area, number of businesses and total local taxes. GHG-AP integrated emissions were estimated based on IPCC(intergovernmental panel on climate change) 2006 guidelines, guideline for government greenhouse inventories, EPA AP-42(compilation of air pollutant emission factors) and preliminary studies. The result of statistical analysis indicated that GHG-AP integrated emissions were significantly correlated with urban spatial structures. The correlation analysis results showed that registered vehicles for GHG (r=0.803, p<0.01), forest area for AP (r=0.996, p<0.01), and park area for AP (r=0.889, p<0.01) were highly significant. From the factor analysis, three groups such as city and traffic categories, economy category and environment category were identified to be the governing factors controlling GHG-AP emissions. The multiple regression analysis also represented that the most influencing factors on GHG-AP emissions were categories of traffic and environment. 25 administrative districts of Seoul were clustered into six groups, of which each has similar characteristics of urban spatial structures and GHG-AP integrated emissions.