ABSTRACT:

Interbasin water transfers (IBTs) can have a significant impact on the environment, water availability, and economies within the basins importing and exporting water, as well as basins downstream of these water transfers. The lack of comprehensive data identifying and describing IBTs inhibits understanding of the role IBTs play in supplying water for society, as well as their collective hydrologic impact. We develop three connected datasets inventorying IBTs in the United States and Canada, including their features, geospatial details, and water transfer volumes. We surveyed the academic and gray literature, as well as local, state, and federal water agencies, to collect, process, and verify IBTs in Canada and the United States. Our comprehensive IBT datasets represent all known transfers of raw water that cross subregion (US) or subdrainage area (CA) boundaries, characterizing a total of 641 IBT projects. The infrastructure-level data made available by these data products can be used to close water budgets, connect water supplies to water use, and better represent human impacts within hydrologic and ecosystem models.

ABSTRACT:

The United States is the largest producer of goods and services in the world. Rainfall, surface water supplies, and groundwater aquifers represent a fundamental input to economic production. Despite the importance of water resources to economic activity, we do not have consistent information on water use for specific locations and economic sectors. A national, spatially detailed database of water use by sector would provide insight into U.S. utilization and dependence on water resources for economic production. To this end, we calculate the water footprint of over 500 food, energy, mining, services, and manufacturing industries and goods produced in the United States. To do this, we employ a data intensive approach that integrates water footprint and input-output techniques into a novel methodological framework. This approach enables us to present the most detailed and comprehensive water footprint analysis of any country to date. This study broadly contributes to our understanding of water in the U.S. economy, enables supply chain managers to assess direct and indirect water dependencies, and provides opportunities to reduce water use through benchmarking. In fact, we find that 94% of U.S. industries could reduce their total water footprint more by sourcing from more water-efficient suppliers in their supply chain than they could by converting their own operations to be more water-efficient.

ABSTRACT:

Groundwater wells are critical infrastructure that enable the monitoring, extraction, and use of groundwater, which has important implications for the environment, water security, and economic development. Despite the importance of wells, a unified database collecting and standardizing information on the characteristics and locations of these wells across the United States has been lacking. To bridge this gap, we have created a comprehensive database of groundwater well records collected from state and federal agencies, which we call the United States Groundwater Well Database (USGWD). Presented in both tabular form and as vector points, the USGWD comprises over 14.2 million well records with attributes such as well purpose, location, depth, and capacity for wells constructed as far back as 1763 to 2023. Rigorous cross-verification steps have been applied to ensure the accuracy of the data. The USGWD stands as a valuable tool for improving our understanding of how groundwater is accessed and managed across various regions and sectors within the United States.

ABSTRACT:

Electricity generation in the United States entails significant water usage and greenhouse gas emissions. However, accurately estimating these impacts is complex due to the intricate nature of the electric grid and the dynamic electricity mix. Existing methods to estimate the environmental consequences of electricity use often generalize across large regions, neglecting spatial and temporal variations in water usage and emissions. Consequently, electric grid dynamics, such as temporal fluctuations in renewable energy resources, are often overlooked in efforts to mitigate environmental impacts. The U.S. Department of Energy (DOE) has initiated the development of resilient energyshed management systems, requiring detailed information on the local electricity mix and its environmental impacts. This study supports DOE's goal by incorporating geographic and temporal variations in electricity mix of local electric grid to better understand the end user environmental impacts. We offer hourly estimates of the US electricity mix, detailing fuel types, water withdrawal intensity, and water consumption intensity for each grid balancing authority. While our primary focus is on evaluating water intensity factors, our dataset and programming scripts for historical and real-time analysis also include evaluations of carbon dioxide (equivalence) intensity within the same modeling framework. This integrated approach offers a comprehensive understanding of the environmental footprint associated with electricity generation and use, enabling informed decision-making to effectively reduce Scope 2 water usage and emissions.

The attached dataset provides static data from 2018 to 2022, as detailed in the publication: Siddik, M. A. B., Shehabi, A., Rao, P., & Marston, L. T. (2024). Spatially and Temporally Detailed Water and Carbon Footprints of U.S. Electricity Generation and Use. Water Resources Research, 60(12), e2024WR038350.

For continuous updates and the latest version of the data product, please visit the following link: https://industrialapplications.lbl.gov/water-impact-tool

ABSTRACT:

Civil infrastructure underpins urban receipts of food, energy, and water (FEW) produced in distant watersheds. In this study, we map flows of FEW goods from watersheds of the contiguous United States to major population centers and highlight the critical infrastructure that supports FEW flows. To do this, we draw upon detailed records of agriculture, electricity, and public water supply production and couple them with commodity flow and infrastructure information. We also compare the flows of virtual water embedded in food and energy commodity flows with physical water flows in inter-basin water transfer projects around the country. We found that the virtual blue water transfers through crops and electricity to major US cities was 53 billion and 8 billion m3 in 2017, respectively, while physical interbasin water transfers for crops, electricity, and public supply water averaged 20.8 billion m3. Highways are the primary infrastructure used to import virtual water associated with food and fuel into cities, although waterways and railways are most utilized for long-distance transport. All of the 204 watersheds in the contiguous US support the food, energy, and/or water supplies of major US cities, with dependencies stretching far beyond each city’s borders. Still, most cities source the majority of their FEW and embedded water resources from nearby watersheds. Infrastructure such as water supply dams and inland ports serve as important buffers for both local and supply-chain sourced water stress. These findings can inform efforts to reduce water resources and infrastructure risks in domestic supply chains.

ABSTRACT:

Agriculture plays a vital role in the US, generating billions of dollars in revenue and providing essential resources such as food, fiber, and fuel. At the same time, this sector consumes more water than all other sectors combined, and contributes significantly to greenhouse gas emissions. Accurately mapping cropland areas at a high spatial resolution, and understanding cultivation trends are crucial for promoting sustainable land management. However, it is not always clear where these crops are cultivated at a fine spatial resolution. Existing data sources either provide extensive temporal coverage with low spatial detail or vice versa. To address this, we employed a data-fusion approach, combining strengths of existing data sources. We produced annual irrigated and harvested areas for 30 major crops in the US from 1981 to 2019 at 2.5 arc minutes by combining county level US Department of Agriculture records with gridded land use datasets. We evaluated our dataset by comparing it with existing large-scale gridded cropland data, revealing alignment and divergence across data products depending on the year, area, and crop. Our dataset serves as a critical tool for analyzing and understanding long-term trends in cropland cultivation, thereby contributing to more informed and sustainable agricultural practices

ABSTRACT:

Irrigated agriculture depends on surface water and groundwater, but we do not have a clear picture of how much water is consumed from these sources by different crops across the US over time. Current estimates of crop water requirements are insufficient in providing the spatial granularity and temporal depth required for comprehensive long-term analysis. To fill this data gap, we utilized crop growth models to quantify the monthly crop water consumption - distinguishing between rainwater, surface water, and groundwater - of 30 of the most widely irrigated annual crops in the US from 1981 to 2019 at 2.5 arc minutes. These 30 crops represent approximately 95% of US irrigated cropland. We found that the average annual total crop water consumption for these 30 irrigated crops in the US was 154.2 km3 (70% blue, 30% green). Corn and alfalfa accounted for approximately 16.7 km3 and 24.8 km3 of average annual blue crop water consumption, respectively, which is nearly two-fifths of the blue crop water consumed in the US. Surface water consumption decreased by 41.2%, while groundwater consumption increased by 6.8%, resulting in a 17.3% decline in blue water consumption between 1981 and 2019. We find good agreement between our results and existing modeled evapotranspiration (ET) products, remotely sensed ET estimates (OpenET), and water use data from the U.S. Geological Survey and U.S. Department of Agriculture. Our dataset and model can help assess the impact of irrigation practices and water scarcity on crop production and sustainability.

ABSTRACT:

This resource includes city-level aggregated residential water consumption data from single-family households and analysis code accompanying the manuscript "Patterns and Predictors of Residential Indoor Water Use Across Major US Cities". The dataset comprises daily water consumption patterns aggregated from 26,441 single-family households across 39 major US metropolitan statistical areas in the conterminous US. While the original data was collected at 5-second intervals using Flume's smart water monitoring sensors at individual households, this public dataset provides city-level daily aggregations to protect privacy. The data captures both total indoor water use and specific end uses (e.g., shower and toilet), along with aggregated household characteristics (e.g., house size and value), appliance presence (e.g., humidifiers and reverse osmosis systems), and daily climate variables (temperature, precipitation), the latter obtained from the Parameter-elevation Regression on Independent Slopes Model (PRISM). Two Jupyter Notebooks are included: one implementing functional data analysis to identify distinct usage patterns across city clusters, and another executing mixed-effects random forest analysis to investigate the influence of household features, appliances, and weather on water consumption patterns.