Chapter VI: Conclusion remark
Chapter 7 Conclusion remark
Continuous urbanization has caused a negative impact on the hydrological and ecological environments to the global, regional, and local scales. These problems can provoke severe urban disaster and water degradation due to sewer water overflows, spilling pollutants that pose a risk of human health. Hence, urban water sustainability and planning have drawn public attention. These issues could have been solved by applying LID to improve hydrologic process and improve the environment and ecological outcomes. This study developed new modeling tools for simulating and optimizing LID. We hope that these modeling tools will be used to establish effective LIDs strategies to improve urban hydrological systems and management.
The first flush effect (FFE) is one of the greatest issues in the urban environment. Therefore, we applied the SWMM model to suggest optimal LID sizes in urban areas, incorporated with stormwater monitoring. Based on MMFn, we designed LIDs to minimize FFE on urban water stream. SWMM is used along with MATLAB to conduct calibration and sensitivity analysis. This coupled tool simulated discharge and TSS. Representative rainfall scenarios considered the rainfall pattern, IETD, and Huff curves. The value of IETD is 17 hours, while the average rainfall volume and duration are 32.4mm and 8.6 hours, respectively. SWMM simulation showed that EMC has large variability depending on sizes of LID. The optimal size of LID was suggested using MFF.
The optimal size ranged from 1.2 mm to 3.0 mm. In this study, optimal LID plans were designed using the approaches of modeling and stormwater monitoring to improve water quality. We hope that the LID sizes suggested could be informative for effective LID strategies.
The optimization of LID is essential to increase the effeteness of LID facilities. This study developed a new modeling approach by optimizing bioretention in a watershed. Based on different hydrological scenarios with FDC, optimal plans were generated to reduce the effects of each scenario. The constant n and saturated hydraulic conductivity (Ks) can significantly influence the effect of bioretention based on the result of sensitivity analysis. The optimal designs showed the size and soil type of centralized and distributed facilities. The optimizing result demonstrated that the soil texture, location and size are important to improve the performance of bioretention. The developed optimizing tool could be useful for LID installment.
Previous LID modeling software has limitations to calculate detailed water movement.
Therefore, we developed a new LID module by coupling SWMM and HYDRUS-1D (SWMM-H)
182
models to improve simulations of hydrological processes. We evaluated the performances of the LID modules of SWMM-H and SWMM by simulation. The SWMM-H reproduced the observed data onto the pilot-scale green roof system well. However, the simulation of the original SWMM was limited to the unsaturated flow and surface ponding. Scenario analysis presented that the new module of the SWMM-H could reflect the hydrological soil properties well
The water quality module of LID in EPA SWMM is simplified in that water quality simulation only considered the dilution effect by rainfall. To solve this limitation, we modified the LID-water quality module in SWMM. We evaluated the performance of the enhanced LID module to generate water quality and conducted a scenario analysis with climate change scenarios. The water quality module in LID successfully estimated the pollutant loads. These results showed good agreement with the observation. Scenario analysis indicated that the water quality results were significantly influenced by the temporal distribution of rainfall. This modified LID module can be useful to provide effective strategies for better urban water systems and management.
183
CURRICULUM VITAE (2019-12-30) Sangsoo Baek
Education
MS/PhD: Environmental Science and Engineering (present), Ulsan National Institute of Science and Technology (UNIST)
◼ Environmental Monitoring and Modeling laboratory (EM2)
Bachelor of Engineering (Rural and BioSystems Engineering) February, 2015
Chonnam National University
◼ Rural Water Environment Laboratory
Research Experience
United States Department of Agriculture-Agricultural Research Service USDA-ARS, December 2017 – February 2018, Research Assistant, Environmental Microbial and Food Laboratory (EMFL)
United States Department of Agriculture-Agricultural Research Service USDA-ARS, January 2017 - April 2017, Research Assistant, Environmental Microbial and Food Laboratory (EMFL) Research Interests
◼ Low Impact Development (LID) modeling
◼ Agriculture and Urban Watershed modeling.
◼ Environmental & Harmful algae modeling
◼ Deep learning & Machine learning Honors and Awards
⚫ Best research award, Korea Water Resource Association, 2018
(우수발표
논문상, 수자원학회, 2018)
⚫ 1st prize at EDISON challenge, Ministry of Science and ICT, 2018 (EDSION software
경진대회 대상, 과학기술정보통신부장관, 2018)
⚫ 3rd prize at Graduate's Paper Competition organized by Ulsan Development Institute (UDI) in Ulsan, Korea, 2015
(대학원
논문경진대회 3등상, 울산발전연구원, 2015)
184
⚫ Talent award of Korea, Deputy prime minister & Ministry of Education, Republic of Korea, 2014
(대한민국인재상,
사회부총리 겸 교육부장관, 2014)
Patent
5. Algae classification and cell counting based on deep learning, 10-2018-0036656 4. SWMM-HYDRS model C-2018-013862
3. SWMM LID water quality simulation C-2018-013861
2. Program for designing optimal plan of Low Impact Development (LID), C-2017- 002245, 2017.01.25
1. Sensitivity and auto-calibration code for the watershed models, C-2016-034099, 2016.12.23 Publication (International)
First author: 9 (Accepted :6, revision :2, under review :2) Co-author: 11 (Accepted :9, revision :1, under review:1)
21. Ather Abbas, Sangsoo Baek, Minjeong Kim, Olivier Ribolzi, Norbert Silvera, Joong-Hyuk Min, Laurie Boithias, Kyung Hwa Cho, Surface and sub-surface flow estimation at high temporal resolution using deep neural networks, Journal of Hydrolology, under review (Co-first author) 20. Sang-Soo Baek, Mayzonee Ligaray, Jongcheol Pyo, Jong-Pyo Park, Joo-Hyon Kang, Jong Ahn Chun, Kyung Hwa Cho*, A novel water quality module of the SWMM model for assessing Low Impact Development (LID) in Urban watersheds, Journal of Hydrology, In revision (first author).
19. Minjeong Kim, Sangsoo Baek, JongCheol Pyo, Gahyun Baek, Jingyeong Shin, Jaai Kim, Mayzonee Ligaray, Changsoo Lee, Young Mo Kim*, Kyung Hwa Cho*, Influence of Combined Sewage Overflow (CSO) on Microbial Risk at a Korean Coastal Beach, Under Review (Co-author)
18. SangSoo Baek, JongCheol Pyo*,Yakov Pachepsky, Yongeun, Park, Chi-Yong Ahn, Young- Hyo Kim, Jong Ahn Chun and Kyung Hwa Cho*, (2019) Identification and enumeration of cyanobacteria species with the deep neural network, Harmful algae, In revision (Co-first author) 17. JongCheol Pyo, Hongtao Duan, Mayzonee Ligaray, Minjeong Kim, Sangsoo Baek, Yong Sung Kwon, Hyuk Lee, Taegu Kang, Kyunghyun Kim, YoonKyung Cha, Kyung Hwa Cho*, (2019) An integrative remote sensing application of stacked autoencoder for atmospheric correction and cyanobacteria estimation using hyperspectral imagery, Remote Sensing of Environment, In revision (Co-author)
16. SangSoo Baek, Yakov Pachepsky, Jong Ahn Chun, Kwang-Sik Yoon, Yongeun Park*, Kyung Hwa Cho*, (2019), Assessment of a Low Impact Development (LID) practice using the coupled SWMM and HYDRUS models, Journal of environment management, in revision, (first author)
185
15. JongCheol Pyo; Hongtao Duan, Sang-Soo Baek, Taegyun Jeon, Yong Sung Kwon, Hyuk Lee, Kyung Hwa Cho, (2019), A convolutional neural network regression for quantifying harmful algae using hyperspectral imagery, Remote Sensing of Environment, Accepted (Co-author) 14. Sanghun Park, Sang-Soo Baek, JongCheol Pyo, Yakov Pachepsky, Jonkwan Park *, Kyung Hwa Cho*, (2019) Deep neural networks for modeling fouling growth and flux decline during NF/RO membrane filtration, Journal of Membrane Science, Accepted (Co-first author)
13. Jeung, M., Sang-Soo Baek., Beom, J., Cho, K., Her, Y., & Yoon, K. (2019). Evaluation of Random Forest and Regression Tree Methods for estimation of Mass First Flush Ratio in Urban Catchments. Journal of Hydrology. (Co-author)
12. SangSoo Baek, Junho Jeon, Hyuk Lee, Jongkwan Park *, Kyung Hwa Cho *, (2019) Investigating influence of Hydrological regime on organic matters characteristic in a Korean Watershed, Water, 11(3), 512.(first-author)
11. Jongkwan Park, Kwanho Jeong, Sangsoo Baek, Sanghun Park, Mayzonee Ligaray, Tzyy Haur Chong, Kyunghwa Cho*, (2019) Modeling of NF/RO membrane fouling and flux decline using real-time observations, Journal of Membrane Science, Journal of Membrane Science, 576, 66-77.
(Co-author)
10. Dong jin Jeon, Seo Jin Ki, Sang-Soo Baek, YoonKyung Cha, Kyung Hwa Cho, Kwang-Sik Yoon, Hyun Suk Shin, Joon Ha Kim* (2017) Assessing the efficiency of aggregate low impact development (LID) at a small urbanized sub-catchment under different storm scenarios, Desalination and Water Treatment, Accepted, (Co-author)
9. JongCheol Pyo, Yakov Pachepsky, SangSoo Baek, YongSeong Kwon, Kim MinJeong, Hyuk Lee, Sanghyun Park, YoonKyung Cha, Rim Ha, Gibeom Nam, Yongeun Park *, Kyung Hwa Cho
*, Optimizing the bio-optical algorithm for estimating Chlorophyll-a and Phycocyanin concentrations in inland waters in Korea, Remote Sensing, (2017), 9, 542 (Co-author)
8. Ligaray, M., Kim, M., Baek, S., Ra, J. S., Chun, J. A., Park, Y., Cho, K. H. (2017). Modeling the Fate and Transport of Malathion in the Pagsanjan-Lumban Basin, Philippines. Water, 9(7), 451.
(Co-author)
7. JongCheol Pyo, Yakov Pachepsky, Minjeong Kim, Sang-Soo Baek, Hyuk Lee, YoonKyung Cha, Kyung Hwa Cho, Yongeun Park, (2017). The SWAT module to simulate the dynamics of multi-algal systems, Environmental Modelling and Software , (Co-author)
6. Sangsoo Baek, Mayzonee Ligaray, Jeong-Pyo Park, Hyun-Suk Shin, Kwon Yongsung, Joseph Brascher, Kyung Hwa Cho, (2017). Developing a Hydrologic Assessment Tool for Designing Bioretention in a watershed, Environmental Modelling and Software , (first-author)
186
5. Jongcheol Pyo, Sang-Soo Baek, Minjeong Kim, Sanghun Park, Hyuk Lee, Kyung Hwa Cho*, (2016). Optimizing Agricultural Best Management Practices in a Lake Erie Watershed, Journal of American Water Resources Association, (Co-author)
4. Ligaray, M1., Baek, S. S1., Kwon, H. O., Choi, S. D., & Cho, K. H. (2016). Watershed-scale modeling on the fate and transport of polycyclic aromatic hydrocarbons (PAHs). Journal of Hazardous Materials, 320, 442-457. (Co-first author)
3. Kim, M., Baek, S., Ligaray, M., Pyo, J., Park, M., & Cho, K. H. (2015). Comparative studies of different imputation methods for recovering streamflow observation. Water, 7(12), 6847-6860.
(Co-author)
2.Baek, S. S., Choi, D. H., Jung, J. W., Lee, H. J., Lee, H., Yoon, K. S., & Cho, K. H. (2015).
Optimizing low impact development (LID) for stormwater runoff treatment in urban area, Korea:
Experimental and modeling approach. Water research (first-author)
1.Baek, S. S., Choi, D. H., Jung, J. W., Yoon, K. S., & Cho, K. H. (2015). Evaluation of a hydrology and run-off BMP model in SUSTAIN on a commercial area and a public park in South Korea. Desalination and Water Treatment, 55(2), 1-13. (first-author)
Publication (Domestic) First author: 1 (Accepted :1) Co-author: 2 (Accepted :2)
3. Sangsoo Baek․Hanna Choi․Jongkwan Park†, Low Impact Development Modeling:
Literature Review and Suggestion for Future Work,2019, J. Korean Soc. Environ. Eng., 41(5), 292~299
Review Paper
2.
최동호, 정재운, 윤광식, 백상수, 유승화, 범진아 원단위와 LID시설규모 산정을 위한 상업지역과 위락시설지역의 유출율 분석, 2015, 한국수처리학회지, 23(3), 53-64
1. Jung, J. W., Park, H. N., Choi, D. H., Baek, S. S., Yoon, K. S., Baek, W. J., Beam, J. A., and Lim, B. J. Analysis of First Flush of Recreation Park and Removal Rate According to Rainfall- Runoff Storage Depth. Journal of Korean Society on Water Environment 2013; 29(5): 648-655.
187
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