Mazdak Arabi’s research while affiliated with Colorado State University and other places

This study aims to characterize single‐family household water consumption utilizing smart‐metered subdaily water use data from more than 700 single‐family households across the state of Arizona in the United States for the water year 2022. Using statistical evidence, we identify factors that drive household water consumption such as the number of occupants, appliance efficiency, and the presence of a swimming pool. Furthermore, climate and other regional drivers of water use are investigated. The analysis encompasses mixed‐effects regression models to assess water use patterns on daily, weekly, monthly, and seasonal time‐steps. The findings show that approximately 64% of water consumption in Arizona was used for outdoor purposes. Households with a swimming pool use approximately 56% more water overall than those without a pool. Even indoor water use is nearly 26% greater in households with a swimming pool. Deep analysis of smart‐metered water use data offers greater insights into the efficiency levels of appliances in a household. Households with high‐efficiency appliances use about 18.5% less water than households without high‐efficiency appliances. Analysis indicates that log‐linear mixed‐effects regression models provide the most robust assessments for relating water consumption with household and regional factors. This study helps water managers identify and implement water conservation and demand reduction strategies in single‐family neighborhoods.

While numerous studies have investigated demand management policies as a means of mitigating the impacts of climate change and population growth, little attention has been given to the interaction of spatial population patterns and water institutions that affect water shortages. In this article, we develop a methodology to evaluate how population location under alternative water institutions and climate scenarios impacts water demands, shortages, and derived economic values. We apply this methodology to the South Platte River Basin (SPRB) in Northeastern Colorado under three scenarios with ∼1,800 simulations. Results suggest that while water rights institutions have a negligible impact on total volumetric shortages relative to climate change, they have substantial distributional and economic implications. Results also suggest that continuous population growth in upstream cities yields the lowest water shortages if per capita use decreases with urbanization. However, if we assume that per capita demands do not decrease with population density, an equal distribution of population to upstream and downstream regions yields the lowest water shortage and highest economic value. These findings indicate the need that planning efforts must account for return flows and development patterns throughout a watershed in order to reduce water shortages and promote economic prosperity.

The Flood Potential Portal ( https://floodpotential.erams.com/ ) has been developed for the contiguous United States, as a practitioner‐focused tool that uses observational data (streamgages) to enhance understanding of how floods vary in space and time, and assist users in making more informed peak discharge predictions for infrastructure design and floodplain management. This capability is presented through several modules. The Mapping module provides tools to explore variability using multiple indices, and provides detailed information, figures, and algorithms describing and comparing flooding characteristics. The Cross‐Section Analysis module allows users to cut regional‐scale sections to interpret the role of topography in driving flood variability. The Watershed Analysis module provides multiple methods for quantifying expected peak discharge magnitudes and flood frequency relationships at user‐selected locations, including the integration of observed trends in flood magnitudes due to climate change and other sources of nonstationarity into decision making. The Streamgage Analysis module performs streamgage flood‐frequency analyses. These modules are based in part on the flood potential method, through the use of 207 zones of similar flood response defined using more than 8200 streamgages with watershed areas <10,000 km ² . Regression models that define each zone had high explained variance (average R ² = 0.93). An example is provided to illustrate use of the Flood Potential Portal for the design of a hypothetical bridge replacement.

Coastal urban areas like New York City (NYC) are more vulnerable to urban pluvial flooding particularly because the rapid runoff from extreme rainfall events can be further compounded by the co-occurrence of high sea-level conditions either from tide or storm surge leading to compound flooding events. Present-day urban pluvial flooding is a significant challenge for NYC and this challenge is expected to become more severe with the greater frequency and intensity of storms and sea-level rise (SLR) in the future. In this study, we advance NYC’s assessment of present and future exposure to urban pluvial flooding through simulating various storm scenarios using a citywide hydrologic and hydraulic model. This is the first citywide analysis using NYC’s drainage models focusing on rainfall-induced flooding. We showed that the city’s stormwater system is highly vulnerable to high-intensity short-duration “cloudburst” events, with the extent and volume of flooding being the largest during these events. We further showed that rainfall events coupled with higher sea-level conditions, either from SLR or storm surge, could significantly increase the volume and extent of flooding in the city. We also assessed flood exposure in terms of the number of buildings and length of roads exposed to flooding as well as the number of the affected population. This study informs NYC’s residents of their current and future flood risk and enables the development of tailored solutions to manage increasing flood risk in the city.