A method for representing cities in global hydrological models
Abstract. Due to increased computational resources and the availability of fine-scale global data, global hydrological models have begun to run at spatial resolutions that resolve major cities worldwide. Because water supply in cities is achieved by a set of infrastructure, traditional grid-level or basin-level modeling and assessment do not provide reliable and interpretable results for cities. Here, we propose a generic city sub-model for global hydrological models to express the water supply in cities. Using a newly developed global gridded database of city areal extent, we conducted a series of global hydrological simulations focusing on municipal water supply for 11 representative cities. Although the model was uncalibrated and forced with global data, the simulation performed reasonably for these cities. The results improved further when additional data on external water sources were taken into account. The subsequent city-level water assessment provides a single water scarcity score for each city. It is more interpretable than the traditional grid- or basin-level assessment, which typically shows a wide range of scores across grid cells or basins or includes non-urban regions. This study highlights the importance of representing cities in global hydrological models and water scarcity assessments, and the need to develop a comprehensive global database of urban water supply. This study opens a pathway toward city-level global water assessments using generic global hydrological models.
The manuscript addresses an important research question concerning the representation of cities and their water supply networks within a global hydrological model. Although the research problem is relevant and clearly identified, the manuscript lacks sufficient methodological detail, quantitative evaluation, and qualitative analysis to adequately demonstrate the performance and reliability of the proposed approach. In particular, the model outputs require more rigorous statistical comparisons and a clearer discussion of the assumptions and limitations.
I recommend 'reject and resubmit', as substantial improvements are needed to strengthen the scientific rigor, methodological transparency, and overall quality of the manuscript.
The following concerns should be addressed: