References
- Akaike, H., 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19 (6), 715–722. doi:https://doi.org/10.1109/TAC.1974.1100705
- Barreto, W., et al., 2010. Multi-objective evolutionary approach to rehabilitation of urban drainage systems. Journal of Water Resources Planning and Management, 136 (5), 547–554. doi:https://doi.org/10.1061/(ASCE)WR.1943-5452.0000070
- Bureau of Technical Affairs and Standards. (2016) Flood damage assessment. No. 164, Management and Planning Organization, Ministry of Energy, Islamic Republic of Iran.
- Cunha, M.C., et al., 2016. Optimal location and sizing of storage units in a drainage system. Environmental Modelling & Software, 83 (2016), 155e166. doi:https://doi.org/10.1016/j.envsoft.2016.05.015
- Deb, K., et al. (2000) A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA2 KanGAL Report 200001.
- Fontanazza, C.M., et al., 2011. Uncertainty evaluation of design rainfall for urban flood risk analysis. Water Science and Technology, 63 (11), 2641–2650. doi:https://doi.org/10.2166/wst.2011.169
- Fu, G. and Butler, D., 2014. Copula-based frequency analysis of overflow and flooding in urban drainage systems. Journal of Hydrology, 510, 49–58. doi:https://doi.org/10.1016/j.jhydrol.2013.12.006
- Hui, R., Jachens, E., and Lund, J., 2016. Risk‐based planning analysis for a single levee. Water Resources Research, 52 (4), 2513–2528. doi:https://doi.org/10.1002/2014WR016478
- Jun, C., et al., 2017. Bivariate frequency analysis of rainfall intensity and duration for urban stormwater infrastructure design. Journal of Hydrology, 553, 374–383. doi:https://doi.org/10.1016/j.jhydrol.2017.08.004
- Martínez, C., et al., 2018. Multi-objective evaluation of urban drainage networks using a 1D/2D flood inundation model. Water Resources Management, 32 (13), 4329–4343. doi:https://doi.org/10.1007/s11269-018-2054-x
- MGCE. (2011a) Tehran stormwater management master plan, Vol 2, part 3: urban food hydrology & sediment load, December 2011. Mahab Ghods Consultant Engineers, Technical and development deputy of Tehran municipality, Tehran, Iran
- MGCE. (2011b) Tehran stormwater management master plan, Vol 4: existing main drainage network, part 2: hydraulic modeling and capacity assessment, December 2011, Mahab Ghods Consultant Engineers,Technical and development deputy of Tehran municipality, Tehran, Iran.
- MGCE. (2011c) Tehran stormwater management master plan, Vol 2: basic Studies, Part1: meteorology, December 2011, Mahab Ghods Consultant Engineers, Technical and development deputy of Tehran municipality, Tehran, Iran
- Mohammadiun, S., et al., 2019. Effects of bottleneck blockage on the resilience of an urban stormwater drainage system. Hydrological Sciences Journal, 65 (2), 281–295. doi:https://doi.org/10.1080/02626667.2019.1690657
- Nelson, R.B., 1998. An introduction to copulas. 2nd ed. 233 Springer Street, New York, NY 10013, USA: Springer.
- Rasekh, A., Afshar, A., and Afshar, M.H., 2010. Risk-cost optimization of hydraulic structures:Methodology and case study. Journal of Water Resources Management, 24 (11), 2833–2851. doi:https://doi.org/10.1007/s11269-010-9582-3
- Rossman, L. and Huber, W. (2016) Storm water management model reference manual US EPA office of research and development, Washington DC, EPA/600/R-15/162A
- Rupa, C. and Mujumdar, P.P., 2018. Dependence structure of urban precipitation extremes. Advances in Water Resources. doi:https://doi.org/10.1016/j.advwatres.2018.08.003
- Sklar, M., 1959. Fonctions de r´epartition `a n dimensions et leurs marges. Publications of Statistics of the University of Paris, 8, 229–231.
- Storn, R. and Price, K., 1995. DE a simple and efficient adaptive scheme for global optimization over continuous space, Technical Report TR-95-012, ICSI.
- Sun, S.A., Djordjevic, S., and Khu, S.T., 2011. A general framework for flood risk-based storm sewer network design. Urban Water Journal, 8 (1), 13–27. doi:https://doi.org/10.1080/1573062X.2010.542819
- Tung, Y.K., 2017. Uncertainty analysis and risk‐based design of detention basin without damage function. Water Resources Research, 53 (5), 3576–3598. doi:https://doi.org/10.1002/2016WR020079
- USACE, 2008. Hydrologic modeling system HEC-HMS, Quick start guide, version 3.2. Davis, CA: Institute for Water Resources Hydrologic Engineering Center.
- USACE, 2016. HEC-RAS river analysis system, 2D modeling user’s manual, version 5.0. Davis: CPD-68A, Hydrologic Engineering Center.
- Vojinovic, Z., et al., 2014. Multi-objective rehabilitation of urban drainage systems under uncertainties. Journal of Hydroinformatics, 16 (5), 1044–1061. doi:https://doi.org/10.2166/hydro.2014.223
- Yazdi, J., 2017. Check dam layout optimization on the stream network for flood mitigation: surrogate modelling with uncertainty handling. Hydrological Sciences Journal, 62 (10), 1669–1682. doi:https://doi.org/10.1080/02626667.2017.1346376
- Yazdi, J., et al., 2018. Assessment of different MOEAs for rehabilitation evaluation of Urban Stormwater Drainage Systems–Case study: eastern catchment of Tehran. Journal of Hydro-environment Research, 21, 76–85. doi:https://doi.org/10.1016/j.jher.2018.08.002
- Yazdi, J., 2018. Water quality monitoring network design for urban drainage systems, an entropy method. Urban Water Journal, 15 (3), 227–233. doi:https://doi.org/10.1080/1573062X.2018.1424215
- Yazdi, J., Doostparast Torshizi, A., and Zahraie, B., 2016a. Risk based optimal design of detention dams considering uncertain inflows. Stochastic Environmental Research and Risk Assessment, 30 (5), 1457–1471. doi:https://doi.org/10.1007/s00477-015-1171-9
- Yazdi, J., Zahraie, B., and Salehi Neyshabouri, S.A.A., 2016b. A stochastic optimization algorithm for optimizing flood risk management measures including rainfall uncertainties and nonphysical flood damages. Journal of Hydrologic Engineering, 21 (5), 04016006. doi:https://doi.org/10.1061/(ASCE)HE.1943-5584.0001334
- Zhou, Y., et al., 2019. Urban flood risk assessment using storm characteristic parameters sensitive to catchment-specific drainage system. Science of the Total Environment, 659 (1), 1362–1369. doi:https://doi.org/10.1016/j.scitotenv.2019.01.004