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Detention reservoirs are employed in urban drainage systems to reduce peak flows downstream of reservoirs. In addition to the volume of detention reservoirs, their operational policies could significantly affect their performance. This paper presents a framework for the real-time coordinated operation of detention reservoirs using deep-learning-based rainfall nowcasting data. Considering the short concentration time of urban basins, the real-time operating policies of urban detention reservoirs should be developed quickly. In the proposed framework, a cellular automata (CA)-based optimization algorithm is linked with the storm water management model (SWMM) to optimize real-time operating policies of gates at the inlets and outlets of detention reservoirs. As CA-based optimization models are not population-based, their computational costs are much less than population-based metaheuristic optimization techniques such as genetic algorithms. To evaluate the applicability and efficiency of the framework, it is applied to the east drainage catchment (EDC) of Tehran metropolitan area in Iran. The results illustrate that the proposed framework could reduce the overflow volume by up to 60%. For complete flood control in the study area, in addition to the real-time operation of detention reservoirs, constructing five tunnels with a total length of 13200 m is recommended. To evaluate the performance of the CA-based optimization model, its results are compared with those obtained from the non-dominated sorting genetic algorithm III (NSGA-III). It is shown that the CA-based model provides similar results with only 5% of the run-time of NSGA-III. A sensitivity analysis is also performed to evaluate the effects of optimization models' parameters on their performance. • Developing a new framework for coordinated operation of urban detention reservoirs. • Using deep-learning-based rainfall nowcasting data for real-time flood management. • Linking a stormwater simulation model with the cellular automata optimization model. • Applying the framework to the east drainage catchment of the Tehran metropolitan area. • Illustrating that the adaptive framework reduces the overflow volume by up to 60%. [ABSTRACT FROM AUTHOR]

In this paper, a new framework is developed for evaluating the resilience of urban drainage systems (UDSs) under floods by proposing and quantifying some technical and socio-ecological (SE) criteria. The proposed criteria are used to quantify the seven principles of building resilience in socio-ecological systems. The criteria mainly focus on preserving diversity and multiplicity in a UDS, managing variables that gradually change over time (slow variables), improving structural and functional connectivity, maintaining system adaptability, encouraging learning, broadening participation, and promoting polycentric governance systems. For evaluating the efficiency of the proposed framework, it is applied to a real-world case study of improving resilience of the UDS in the eastern part of Tehran metropolitan area. Three scenarios for flood management are proposed based on the Low Impact Development (LID) practices which are simulated using the Storm Water Management Model (SWMM). The Entropy method is used to consider the uncertainty in the relative importance of different criteria in estimating the flood resilience. The estimated values for the proposed criteria regarding the current drainage system in the study area show its undesirable condition in many sub-catchments. The results also show that using around 2.3 km2 of LID practices in this urban watershed can significantly improve the resilience in many sub-catchments (nearly, 30%) and reduce the total volume of the overflow (about 50%). The results also show that using the flood management scenarios, improving connectivity is the most influential factor that enhances the general resilience of the system. • A new framework evaluates the resilience of urban drainage systems under floods. • Socio-ecological (SE) criteria are proposed and quantified to evaluate resilience. • SE criteria are defined based on population, land cover and habitat characteristics. • An Entropy-based method is used to incorporate the uncertainty of criteria's weights. • To evaluate the proposed framework, it is applied to a real-world case study. [ABSTRACT FROM AUTHOR]

Modeling Water-Energy-Food (WEF) nexus is necessary for integrated water resources management (IWRM), especially in urban areas. This paper presents a new urban water metabolism-based methodology for WEF nexus modeling and management. A behavioral simulation model is used to incorporate the characteristics of stakeholders in an urban area. Modified versions of the Borda count, Copeland rule, and fallback bargaining procedures are implemented to choose the socially acceptable management scenarios. Finally, the selected scenarios' effectiveness is evaluated using the fairness and total utility indices. The applicability of the proposed methodology is evaluated by applying it to the Kan River basin, Tehran, Iran, which is suffering from some water and environmental issues. The considered management scenarios include adding new water sources, leakage control plans, using rubber dams for enhancing groundwater recharge, revising water allocation priorities, and developing semi-centralized or decentralized reuse strategies for reclaimed wastewater. Results illustrate that considering different fluxes (i.e., water quantity, pollutants, energy, greenhouse gases (GHG), and materials) is as important as incorporating the social characteristics of stakeholders. Simulating the socially acceptable scenario shows that the aquifer's average water level improves by 3 (m), and its average nitrate concentration reduces by 16 (m g / L) in comparison with the business as usual (BAU) scenario. In addition, by implementing different water reuse strategies, which are energy-intensive, total energy consumption is reduced by 5% due to less groundwater pumping. Also, the selected scenario decreases GHG emissions by 18% and increases the sequestrated carbon dioxide by 20%. In conclusion, the proposed decision support tool can provide policies for sustainable water resources management considering water quality and quantity issues, energy usage, and GHG emission. [Display omitted] • A Novel urban water metabolism framework is proposed that considers the WEF nexus. • The urban water metabolism model is linked to a behavioral simulation model. • Some modified social choice methods are proposed to select the consensus scenarios. • The selected scenario improves groundwater quality and quantity in the study area. • The selected scenario decreases energy usage and green house gases emission. [ABSTRACT FROM AUTHOR]

Distributed Constraint Optimization (DCOP)-based approaches, as the distributed version of constraint optimization, provide a framework for coordinated decision making by a team of agents. In this paper, an agent-based DCOP model is developed to allocate water and reclaimed wastewater to demands considering the conflicting interests of involved stakeholders. One of the well-known DCOP algorithms, ADOPT1, is modified to incorporate an agent responsible for monitoring and conserving water resources. This new algorithm considers the social characteristics of agents and a new form of interaction between agents. For the first time in the literature, a real-world water and reclaimed wastewater allocation problem is formulated as a DCOP and solved using the Modified ADOPT (MADOPT) algorithm. To evaluate the MADOPT algorithm, it is applied to a water and reclaimed wastewater allocation problem in Tehran, Iran. The results illustrate the applicability and efficiency of the proposed methodology in dealing with large-scale multi-agent water resources systems. It is also shown that agents' selfishness and social relationships could affect their water use policies. • A multi-agent model is presented for urban water and treated wastewater management. • A modified version of Asynchronous Distributed Constraint Optimization is proposed. • The algorithm considers a monitoring agent which exists in environmental systems. • The algorithm is applied to a large-scale real-world environmental system. • The results illustrate the applicability and efficiency of the proposed methodology. [ABSTRACT FROM AUTHOR]

The municipal solid waste (MSW) landfills experience a large post-closure settlement over time. Waste settlement significantly impairs utilities, structures, and the other facilities constructed on top of a landfill. This study presents the settlement mechanisms and the methods of estimating MSW landfill settlements. Since the waste materials exhibit engineering properties which vary depending on many factors such as the location, time, climate, this study also presents the data related to the landfill characteristics, waste composition, waste moisture content, and other physical and chemical properties of waste. In addition, this paper discusses the findings of a settlement investigation conducted at a municipal solid waste landfill in Tehran. In this research, based on the collected field data and data obtained from the available literature, a technical management tool for MSW closed landfills has been developed using MATLAB, which aims to predict time dependent settlement under self-weight and surcharge loads in landfills considering various related parameters, leachate, gas generation, and moisture distribution, coefficients of compression, whilst it calculates different properties of wastes, and determines the landfill slope stability under various conditions. This user-friendly program captures the variation of the model parameters with time. The results of the verification process indicate that the results from the technical management tool have been in a very good agreement with the measured field settlement data, collected from Tehran landfill. Moreover, the results of sensitivity analysis of the model in regard to variation of input parameters indicate that there are two prominent characteristics, having significant impacts on the overall landfill settlement. These characteristics are the landfill height and the compressibility parameters. The outcomes of this study can improve the confidence for design and construction on MSW landfills. It may reduce the uncertainty when predicting the landfill settlement and enable to apply the landfill redevelopment techniques more effectively and efficiently. Studying the creep settlement properties under the co-effect of stress, biodegradation and temperature for predicting the total landfill settlement is recommended for future studies. Image 1 • Variation of waste and landfill parameters lead to different settlement behaviour. • Understanding the long-term settlement process is crucial for landfill redevelopment. • Landfill modelling demonstrates the settlement process and influential parameters. • Field settlement data collection is essential for model verification. • Landfill height and compressibility characters significantly affect the overall landfill settlement. [ABSTRACT FROM AUTHOR]