| Title | Combining urban metabolism and reinforcement learning concepts for sustainable water resources management: A nexus approach |
|---|---|
| ID_Doc | 66312 |
| Authors | Emamjomehzadeh, O; Kerachian, R; Emami-Skardi, MJ; Momeni, M |
| Title | Combining urban metabolism and reinforcement learning concepts for sustainable water resources management: A nexus approach |
| Year | 2023 |
| Published | |
| Abstract | 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 stake-holders in an urban area. Modified versions of the Borda count, Copeland rule, and fallback bargaining pro-cedures 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 stake-holders. 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 (mg/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. |
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