A scenario-based approach for urban water management in the context of the COVID-19 pandemic and a case study for the Tabriz metropolitan area, Iran

The world's poorest countries were hit hardest by COVID-19 due to their limited capacities to combat the pandemic. The urban water supply and water consumption are affected by the pandemic because it intensified the existing deficits in the urban water supply and sanitation services. In this study, we develop an integrated spatial analysis approach to investigate the impacts of COVID-19 on multi-dimensional Urban Water Consumption Patterns (UWCPs) with the aim of forecasting the water demand. We selected the Tabriz metropolitan area as a case study area and applied an integrated approach of GIS spatial analysis and regression-based autocorrelation assessment to develop the UWCPs for 2018, 2019 and 2020. We then employed GIS-based multi-criteria decision analysis and a CA-Markov model to analyze the water demand under the impacts of COVID-19 and to forecast the UWCPs for 2021, 2022 and 2023. In addition, we tested the spatial uncertainty of the prediction maps using the Dempster Shafer Theory. The results show that the domestic water consumption increased by 17.57% during the year 2020 as a result of the COVID-19 pandemic. The maximum increase in water consumption was observed in spring 2020 (April-June) when strict quarantine regulations were in place. Based on our results, the annual water deficit in Tabriz has increased from similar to 18% to about 30% in 2020. In addition, our projections show that this may further increase to about 40-45% in 2021. Relevant stakeholders can use the findings to develop evidenceinformed strategies for sustainable water resource management in the post-COVID era. This research also makes other significant contributions. From the environmental perspective, since COVID-19 has affected resource management in many parts of the world, the proposed method can be applied to similar contexts to mitigate the adverse impacts and developed better informed recovery plans. (C) 2021 Elsevier B.V. All rights reserved.