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Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water resources in the USA require estimates of water withdrawals to manage and plan for future demands and sustainable water supplies. This study compiled the most comprehensive conterminous United States water withdrawal data set to date and developed a machine learning framework for estimating public supply withdrawals and associated uncertainty for the period 2000–2020. The modeling approach provides service area resolution estimates to allow for annual and monthly water withdrawal estimation while incorporating a complex array of driving factors that include hydroclimatic, demographic, socioeconomic, geographic, and land use factors. Model results reveal highly variable and lognormally distributed per‐capita water withdrawal, spanning from 30 to 650 gallons per capita per day (GPCD), across community, regional, and national scales, with pronounced seasonal variations. Analysis of estimated withdrawal trends indicates that the national annual average withdrawal experienced a decline at a rate of 0.58 GPCD/year during the period from 2000 to 2020. Model interpretation reveals a complex interplay between public supply withdrawal and key predictors, including population size, warm‐season precipitation, counts of large buildings and houses, and areas of urban and commercial land use. The developed models can forecast future public supply driven by various climate, demographic, and socioeconomic scenarios. Key Points: Consistent, reproducible estimates of monthly water withdrawals were generated at the spatial resolution of USA water service areasSpatial and temporal variability of public supply withdrawal is driven by a complex array of explanatory featuresAn operational machine learning framework was developed to estimate water withdrawals, prediction uncertainty, and feature importance [ABSTRACT FROM AUTHOR]

"The Rise and Fall of the Victorian Three-Volume Novel" by Troy J. Bassett is a comprehensive study that challenges existing knowledge about multivolume fiction in the Victorian era. Bassett's research database, At the Circulating Library (ATCL), provides extensive bibliographic data on Victorian fiction, including information on novels, authors, and publishers. The book analyzes publishing data on 7,272 multivolume works of fiction published between 1837 and 1898, revealing a gradual increase in the number of novels published in this format until its decline in the late 19th century. The study also explores the economic structures and publishing systems that made multivolume fiction profitable for publishers, libraries, and authors. Overall, this book offers valuable insights into the Victorian novel and its relationship to publishing structures and formats. [Extracted from the article]

IN RECENT YEARS, the study and teaching of nineteenth-century women poets have been greatly facilitated: new anthologies have made texts available for general readers and for classroom use, and a [...]

The title of this essay should be read in two ways: as both Victorian and contemporary critics have acknowledged, both Elizabeth Barrett Browning's Sonnets from the Portuguese (1850) and George [...]