Browsing by Author "Wang, Yung-Chieh"

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Application of System Dynamics on Shallow Multipurpose Artificial Lakes: A Case Study of Detention Pond at Tainan, Taiwan
(2010-06-01)
Chu, Hone-Jay
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Chang, Liang-Cheng
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Lin, Yu-Pin
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Wang, Yung-Chieh
;
Chen, Yu-Wen
This study designs a multipurpose urban shallow artificial lake, including water supply, flood detention, and water environment preservation. It is expected to not only preserve a healthy water environment but to also retain water conservation and flood detention. This study adopts system dynamics (SD) to analyze the relationship between different purposes of water resources utilization. Furthermore, different operation strategies effects can be simulated by SD through a proposed urban multipurpose shallow artificial lake system. The results demonstrate the dynamic effects of strategies managers propose such as demand analysis, inflow control, and water quality improvement in this case study for Taiwan. SD aids lake system prediction and understanding temporally in sequential planning for water supply, environmental preservation, and flood detention. The SD model will hopefully serve as a reference to study different features before artificial lakes constructing.
Geostatistical approaches and optimal additional sampling schemes for spatial patterns and future sampling of bird diversity
(2008-03-01)
Lin, Yu-Pin
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Yeh, Ming-Sheng
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Deng, Dong-Po
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Wang, Yung-Chieh
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土木工程學系
Aim To evaluate geostatistical approaches, namely kriging, co-kriging and geostatistical simulation, and to develop an optimal sampling design for mapping the spatial patterns of bird diversity, estimating their spatial autocorrelations and selecting additional samples of bird diversity in a 2450 km(2) basin. Location Taiwan. Methods Kriging, co-kriging and simulated annealing are applied to estimate and simulate the spatial patterns of bird diversity. In addition, kriging and co-kriging with a genetic algorithm are used to optimally select further samples to improve the kriging and co-kriging estimations. The association between bird diversity and elevation, and bird diversity and land cover, is analysed with estimated and simulated maps. Results The Simpson index correlates spatially with the normalized difference vegetation index (NDVI) within the micro-scale and the macro-scale in the study basin, but the Shannon diversity index only correlates spatially with NDVI within the micro-scale. Co-kriging and simulated annealing simulation accurately simulate the statistical and spatial patterns of bird diversity. The mean estimated diversity and the simulated diversity increase with elevation and decrease with increasing urbanization. The proposed optimal sampling approach selects 43 additional sampling sites with a high spatial estimation variance in bird diversity. Main conclusions Small-scale variations dominate the total spatial variation of the observed diversity due to a lack of spatial information and insufficient sampling. However, simulations of bird diversity consistently capture the sampling statistics and spatial patterns of the observed bird diversity. The data thus accumulated can be used to understand the spatial patterns of bird diversity associated with different types of land cover and elevation, and to optimize sample selection. Co-kriging combined with a genetic algorithm yields additional optimal sampling sites, which can be used to augment existing sampling points in future studies of bird diversity.
Monitoring and estimating the flow conditions and fish presence probability under various flow conditions at reach scale using genetic algorithms and kriging methods
(2011-02-10)
Lin, Yu-Pin
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Wang, Cheng-Long
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Yu, Hsiao-Hsuan
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Huang, Chung-Wei
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Wang, Yung-Chieh
The combination of current velocity and water depth influences stream flow conditions, and fish activities prefer particular flow conditions. This study develops a novel optimal flow classification method for identifying types of stream flow based on the current velocity and the water depth using a genetic algorithm. It is applied to the Datuan stream in northern Taiwan. Fish were sampled and their habitat investigated at the study site during the spring, summer, fall and winter of 2008-2009. The current velocity, water depth and maps of the presence probability of fish were estimated by ordinary and indicator kriging. The optimal classification results were compared with the classification results obtained using the Froude number and empirical methods. The flow classification results demonstrate that the proposed optimal flow classification method that considers depth-velocity and optimally identified criteria for classifying flow types, yields a current velocity and water depth of 0.32 (m/s) and 0.29 (m), respectively, and classifies the flow conditions in the study area as pool, run, riffle and slack The variography results of the current velocity and the water depth data reveal that seasonal flows are not spatially stationary among seasons in the study area. Kriging methods and a two-dimensional hydrodynamic model (River 2D) with empirical and optimal flow classification methods are more effective than the Froude number method in classifying flow conditions in the study area. The flow condition classifications and probability maps were generated by River 2D, ordinary kriging and indicator kriging, to quantify the flow conditions preferred by Sicyopterus japonicus in the study area. However, the proposed optimal classification method with kriging and River 2D is an effective alternative method for mapping flow conditions and determining the relationship between flow and the presence probability of target fish in support of stream restoration. (C) 2010 Elsevier B.V. All rights reserved.