The influence of Covid-19 Pandemic and Climate Change on Water Use and Supply: Experience of Istanbul, Turkiye

The article is highly original in that it is the first time a DPSIR framework has been used to study the effects of Covid-19 and climate change on water consumption.

Some parts of the article are written too long. A shorter and simpler narrative style will be correct in terms of attracting the reader's attention.

Due to one of the sample areas of the article is Istanbul, it would be more accurate to replace the municipality of Bolu street disinfection photo in Figure 5 with a photo from Istanbul.

Weather conditions and climate change are two different things. There is a big misconception in the article about these two subjects. Weather condition is the atmospheric conditions that comprise the state of the atmosphere in terms of temperature, wind, clouds, precipitation, which is very temporary and unstable. But climate is the average weather in a place over many years. Climate change is a shift in those average conditions, that is accelerated in recent years due to environmental problems.

The introduction begins with the importance of water and water management, which is good. Climate change must be defined and explained along with its effect on the water circle. Pandemic and climate change have to be discussed more about their origins and related effects on settlements. Some research claims that pandemic is also a result of climate change. Make sense of the connection between. So, the title of the article should be "The Impacts of Covid-19 Pandemic & Climate Change on Water Environment: The Case of Istanbul and London."

Towards the end of the introduction, some unclear sentences appear. In line 117, "... unexpected situations such as the Covid-19..." What else? Every situation that is examined must be written here. In the line 118-119, specify the dates that data compiled. "previous years" is not a certain phrase. In lines 121-122, is there an implication for Covid-19 lockdown? Which lockdown? When? These paragraphs should be rewritten clearly.

DPSIR is abbreviated for what? Explain the methodology.

In the figures, there are some graphics shared with meaningful data compiled from related authorities (some of them are not cited). In order to make sense of the metadata, this information should be selected between the exact dates. Istanbul's water consumption is between 2000-2020, but population and water consumption are between 2000-2019. The water reservoir level is between 2000-2021, etc. (?)

Since this is a comparison article, the same data should be shared and interpreted for London, too. And before this, it should be explained why these two cities were chosen as case studies. What are the common and comparable features?

The authors present a paper, in which they examined how unexpected situations such as the Covid-19 pandemic might affect water usage and availability. Although the paper is well-written and well-structured, I do have some concerns about the paper, which merit further attention.

My first comment relates to the usage of the DPSIR framework. I agree with authors that the application of the DPSIR framework for signaling differences in water consumption patterns during the pandemic. Since climate change and covid-19 are two different drivers (van der Voorn et al, 2020) which manifest themselves at different time scales, including their impacts, there lies a major challenge in obtaining some separate evidence that the pandemic restrictions affected human activity in Istanbul for which they examined air quality parameters, and these suggest air pollution in Istanbul was lower in 2020 than in 2019 indicating decreased human activity consistent with Covid-19 restrictions. However, in order to distinguish between the impacts of these two drivers, I believe the current set of indicators is not sufficient and therefore, I have two suggestions for improvement:

• In order to provide more evidence on “waste”, the authors could consider Wastewater-Based Epidemiology, which could be especially informative given that asymptomatic and oligosymptomatic infections are unlikely to be detected during clinical surveillance  see e.g., Bivins et al (2020) and Bhattacharya et al (2021)
• Since people were in lockdown, they may have ordered products and services online. This would increase (slightly) traffic patterns and at least demand for transportation, which in turn increase CO2 emissions.

In addition, looking at the different time scales to be considered, the DPSIR framework depicted in Figure 1 seems to be a static representation of its DPSIR components. So, in light of the research objective, a more dynamic representation would be required to capture the dynamics across different time scales.

My second concern relates to the comparability of the Turkish case with other cases. In my opinion, there are indeed limited comparisons possible, if not impossible between Istanbul and other countries at present due to lack of data availability, as the authors stated. However, it is not just because of a lack of data but also different national characteristics in terms of socio-ecological, socio-economic, socio-technical, and governance aspects. Hence, it requires a solid framework for comparison, which accounts for these differences and similarities, to make any statements on comparability. These aspects could be interpreted as coping capacities. Van der Voorn and de Jong et al (2021) developed a framework for such a comparative analysis.

My final concern relates to the need for new management plans. This would require adaptive management methodologies like for example the Backcasting Adaptive Management methodology (van der Voorn et al, 2012, 2017) or a comprehensive multi-target backcasting approach (van der Voorn et al 2020), which combines the strengths of multicriteria analysis, nexus approaches and backcasting, for supporting a transition to zero GHG emissions The former methodology can help decision makers to develop robust adaptive management plans, whereas the latter allows them to conduct a qualitative environmental assessment of scenarios to identify conflicts and synergies in regard to a broad range of environmental targets (e.g., reduction of biodiversity loss, viable habitats for flora and fauna). I would like to encourage the authors to elaborate on how these methodologies could expand the DPSIR framework in light of the research objective of the paper.

Recommended literature

Bhattacharya, P., Kumar, M., Islam, M.T. et al. Prevalence of SARS-CoV-2 in Communities Through Wastewater Surveillance—a Potential Approach for Estimation of Disease Burden. Curr Pollution Rep 7, 160–166 (2021). https://doi.org/10.1007/s40726-021-00178-4

van der Voorn, T.; de Jong, M. Cope or Perish? Managing Tipping Points in Developing Coping Strategies for Emergency Response during the First Wave of the COVID-19 Outbreak in Europe. COVID 2021 , 1 , 39-70. https://doi.org/10.3390/covid1010005

Bivins A, North D, Ahmad A, Ahmed W, Alm E, Been F, et al. Wastewater-based epidemiology: global collaborative to maximize contributions in the fight against COVID-19. Environ Sci Technol. 2020;54(13):7754–7. https://doi.org/10.1021/acs.est.0c02388

Tom van der Voorn, Caroline van den Berg, Prosun Bhattacharya, Jaco Quist. Never Waste a Crisis: Drawing First Lessons from the COVID-19 Pandemic to Tackle the Water Crisis. ACS ES&T Water 2021, 1 (1) , 8-10. https://doi.org/10.1021/acsestwater.0c00041

Van der Voorn, T., Quist, J., Pahl-Wostl, C. et al. Envisioning robust climate change adaptation futures for coastal regions: a comparative evaluation of cases in three continents. Mitig Adapt Strateg Glob Change 22, 519–546 (2017). https://doi.org/10.1007/s11027-015-9686-4

Tom van der Voorn, Claudia Pahl-Wostl, Jaco Quist, (2012) Combining backcasting and adaptive management for climate adaptation in coastal regions: A methodology and a South African case study,

Futures, https://doi.org/10.1016/j.futures.2011.11.003 .