• Journal of Environmental Impact Assessment
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• v.29 no.6
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• pp.403-413
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• 2020

A mathematical model comprised with eight simultaneous quasi-linear partial differential equations was suggested to provide optimal chlorination strategy. Upstream weighted finite element method was employed to construct multidimensional numerical code. The code was verified against measured concentrations in three type of reactors. Boundary conditions and reaction rate were calibrated for the sixteen cases of experimental results to regenerate the measured values. Eight reaction rate coefficients were estimated from the modeling result. The reaction rate coefficients were expressed in terms of pH and temperature. Automatic optimal algorithm was invented to estimate the reaction rate coefficients by minimizing the sum of squares of the numerical errors and combined with the model. In order to minimize the concentration of chlorine and pollutants at the final usage sites, a real-time predictive control system is imperative which can predict the water quality variables from the chlorine disinfection process at the water purification plant to the customer by means of a model and operate the disinfection process according to the influent water quality. This model can be used to build such a system in water treatment plants.

• Journal of Korea Soil Environment Society
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• v.1 no.1
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• pp.89-102
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• 1996

An integrated model is presented to describe underground flow and mass transport, using a multicomponent multiphase approach. The comprehensive governing equation is derived considering mass and force balances of chemical species over four phases(water, oil, air, and soil) in a schematic elementary volume. Compact and systemati notations of relevant variables and equations are introduced to facilitate the inclusion of complex migration and transformation processes, and variable spatial dimensions. The resulting nonlinear system is solved by a multidimensional finite element code. The developed code with dynamic array allocation, is sufficiently flexible to work across a wide spectrum of computers, including an IBM ES 9000/900 vector facility, SP2 cluster machine, Unix workstations and PCs, for one-, two and three-dimensional problems. To reduce the computation time and storage requirements, the system equations are decoupled and solved using a banded global matrix solver, with the vector and parallel processing on the IBM 9000. To avoide the numerical oscillations of the nonlinear problems in the case of convective dominant transport, the techniques of upstream weighting, mass lumping, and elementary-wise parameter evaluation are applied. The instability and convergence criteria of the nonlinear problems are studied for the one-dimensional analogue of FEM and FDM. Modeling capacity is presented in the simulation of three dimensional composite multiphase TCE migration. Comprehesive simulation feature of the code is presented in a companion paper of this issue for the specific groundwater or flow and contamination problems.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.77-77
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• 2017

전 세계적인 인구증가와 도시화로 메가시티가 점차 증가하고 있으며, 2016년 기준 37개의 메가시티 중 60% 이상(23개)이 아시아 지역에 집중되어 있다. 통상, 메가시티는 불투수율이 높고 인구가 밀집되어 있어 수재해로 인한 피해규모가 크며, 인구증가에 따른 용수부족 및 수질악화로 인해 수자원 확보가 어렵다. 특히, 아시아 지역은 몬순의 영향으로 수자원의 변동성이 크며, 최근 기후시스템의 변화는 몬순의 시 공간적 변동을 증대시킬 것으로 전망된다. 즉, 아시아 몬순지역에 위치하는 메가시티는 기후변화에 더욱 취약하며 이에 따른 수자원 확보 및 수자원 관리의 어려움은 더욱 가중될 것으로 예상된다. 본 연구에서는 AR5 기후변화 시나리오를 활용하여 아시아 몬순지역 내 메가시티를 대상으로 미래기간에 대한 기온, 강수량, 유출량을 전망하고 그 특성을 분석하고자 한다. 국가별 인구 통계자료를 기반으로 아시아 몬순지역 내 존재하는 19개 메가시티를 선정하였다. 기후전망을 위해 테일러 다이어그램을 활용하여 GCMs의 몬순모의 성능을 평가하였으며, 아시아 몬순특성을 잘 반영하는 다수의 GCMs을 선정하였다. 아시아 메가시티를 평가하고자 이중선형보간기법(Bilinear method)을 적용하여 $0.5^{\circ}$ 간격의 공간해상도로 상세화하였으며, Delta method를 이용하여 편의보정을 수행하였다. GCM 모의자료의 편의를 산정하기 위해 APHRODITE의 일단위 강수자료를 이용하였으며, VIC (Variable Infiltration Capacity) 모형을 이용하여 유출량 분석을 수행하였다. 평가결과 각 메가시티의 평균기온, 강수 및 유출량이 모든 미래기간 2020s, 2050s, 2080s에서 다르게 나타났다. 해안/내륙, 경 위도 등 메가시티의 지리적 위치에 따른 변화특성 분석을 수행하였으며, 각 메가시티에 대한 여름 및 겨울철 몬순의 변화 특성을 분석하였다.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.73-81
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• 2013

Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.