TY - JOUR
T1 - Developing sustainable strategies by LID optimization in response to annual climate change impacts
AU - Zamani, Mohammad G.
AU - Saniei, Khashayar
AU - Nematollahi, Banafsheh
AU - Zahmatkesh, Zahra
AU - Moghadari Poor, Mohammad
AU - Nikoo, Mohammad Reza
N1 - Publisher Copyright:
© 2023
PY - 2023/9/1
Y1 - 2023/9/1
N2 - Designing urban runoff drainage systems is prominent in effectively managing floods due to increasing impermeable regions worldwide. However, although urban runoff drainage systems are configured mainly based on rainfall analysis, climate change influences their hydrological properties substantially. This research introduces an innovative methodology to analyze climate variations on optimal low impact developments (LIDs) of urban drainage systems in historical periods based on annual impacts (AIs) in projection periods considering uncertainties assessments. First, Storm Water Management Model (SWMM) is employed for simulating the process of rainfall-runoff considering quality and quantity analyses. This simulation model is coupled with a non-dominated genetic algorithm- II (NSGA-II) optimization algorithm to minimize the cost of LIDs, flood volume, and pollutant load. Then, future runoff and daily rainfall are projected on a yearly basis, including maximum, minimum, and median rainfall, to identify how climate change affects catchment properties. These projections and an ensemble model are obtained based on the Long Ashton Research Station Weather Generator (LARS-WG), which considers uncertainties. After that, the projected daily precipitation is fragmented into hourly segments utilizing the change factor approach (CFA). Finally, the ideal optimum type, size, and placement of the chosen LIDs are determined using the presented simulation-optimization (SO) model. To prove the effectiveness and appropriateness of the presented framework, it is implemented in a real-world study area in Darabad catchment, Tehran, Iran. Results indicate that the developed optimal LIDs are well-designed and sufficient in both the historical and projection periods. The findings also depict that with the current LIDs established for the historical period, the flooding volume and summation of total suspended solid (TSS) and total Nitrogen (TN) removals are decreased by 55.96% and 60.2% compared to when LIDs are not adopted. In addition, employing the developed LIDs based on an ensemble model results in the runoff volume and pollutants removal decline of up to 31.39% and 46.9%, respectively.
AB - Designing urban runoff drainage systems is prominent in effectively managing floods due to increasing impermeable regions worldwide. However, although urban runoff drainage systems are configured mainly based on rainfall analysis, climate change influences their hydrological properties substantially. This research introduces an innovative methodology to analyze climate variations on optimal low impact developments (LIDs) of urban drainage systems in historical periods based on annual impacts (AIs) in projection periods considering uncertainties assessments. First, Storm Water Management Model (SWMM) is employed for simulating the process of rainfall-runoff considering quality and quantity analyses. This simulation model is coupled with a non-dominated genetic algorithm- II (NSGA-II) optimization algorithm to minimize the cost of LIDs, flood volume, and pollutant load. Then, future runoff and daily rainfall are projected on a yearly basis, including maximum, minimum, and median rainfall, to identify how climate change affects catchment properties. These projections and an ensemble model are obtained based on the Long Ashton Research Station Weather Generator (LARS-WG), which considers uncertainties. After that, the projected daily precipitation is fragmented into hourly segments utilizing the change factor approach (CFA). Finally, the ideal optimum type, size, and placement of the chosen LIDs are determined using the presented simulation-optimization (SO) model. To prove the effectiveness and appropriateness of the presented framework, it is implemented in a real-world study area in Darabad catchment, Tehran, Iran. Results indicate that the developed optimal LIDs are well-designed and sufficient in both the historical and projection periods. The findings also depict that with the current LIDs established for the historical period, the flooding volume and summation of total suspended solid (TSS) and total Nitrogen (TN) removals are decreased by 55.96% and 60.2% compared to when LIDs are not adopted. In addition, employing the developed LIDs based on an ensemble model results in the runoff volume and pollutants removal decline of up to 31.39% and 46.9%, respectively.
KW - Annual impacts
KW - Climate change
KW - Long ashton research station weather generator (LARS-WG)
KW - Low impact developments (LIDs)
KW - Non-dominated sorting genetic algorithm- II (NSGA-II)
KW - Storm water management model (SWMM)
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UR - https://www.mendeley.com/catalogue/7e6a21be-25ce-3955-8986-7d59ccd00902/
U2 - 10.1016/j.jclepro.2023.137931
DO - 10.1016/j.jclepro.2023.137931
M3 - Article
AN - SCOPUS:85163850877
SN - 0959-6526
VL - 416
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 137931
ER -