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ABSTRACT This article combines methods from existing techniques to identify multiple changepoints in non‐Gaussian autocorrelated time series. A transformation is used to convert a Gaussian series into a non‐Gaussian series, enabling penalized likelihood methods to handle non‐Gaussian scenarios. When the marginal distribution of the data is continuous, the methods essentially reduce to the change of variables formula for probability densities. When the marginal distribution is count‐oriented, Hermite expansions and particle filtering techniques are used to quantify the scenario. Simulations demonstrating the efficacy of the methods are given and two data sets are analyzed: 1) the proportion of home runs hit by Major League Baseball batters from 1920 to 2023 and 2) a six‐dimensional series of tropical cyclone counts from the Earth's basins of generation from 1980 to 2023. In the first series, beta marginal distributions are used to describe the proportions; in the second, Poisson marginal distributions seem appropriate. 

Abstract Agricultural land cover in the U.S. Midwest is a major source of nutrient pollution that has led to impairment of stream water quality. This study examines the impact of a forested state park on nutrient concentrations within an agriculturally dominated watershed. Water samples were collected over a 2‐year study period from eight stream sampling sites along four creeks and processed for total nitrogen (TN), nitrate (), total phosphorus (TP), and orthophosphate (). Hydrology, channel morphology, and remotely sensed land cover and vegetation data were also collected and analyzed within the study area. Results indicate that water quality responses to a forested state park vary between TN, , TP, and , and water quality variables are uniquely influenced by watershed and stream characteristics. The greatest water quality benefits most frequently occurred within the two smallest study streams with the greatest residence times and proportion of watershed areas within the forested state park. Overall, the greatest improvements to water quality occurred during periods of low stream discharge and when riparian vegetation was greenest. The results of this study suggest that conservation of forested areas within agriculturally dominated watersheds can provide water quality improvements in the U.S. Midwest. Targeting watersheds that drain small streams with long residence times for conservation may be most beneficial to improving water quality. 

Abstract Elevated nutrient and suspended sediment concentrations often result in negative environmental impacts within freshwater environments. Studies that directly compare suspended sediment and bioavailable nutrients between predominantly agricultural and predominantly urban watersheds during baseflow conditions are largely lacking. The purpose of this study was to determine the impacts of land cover, stream discharge, and wastewater treatment plant (WWTP) discharge on nutrient and sediment concentrations, across a large land cover gradient in Southwest Ohio streams. Weekly baseflow samples were collected from eight streams over 1 year from November, 2016 through November, 2017. Total suspended sediment, nitrate, and phosphate concentrations were measured. Results indicate that agricultural land cover and WWTPs increase nitrate and phosphate concentrations in the study area. Total suspended sediment and nitrate concentrations increased with discharge, and discharge was a relatively weak predictor of phosphate concentrations. Seasonal water quality trends varied by parameter and land use also had unique impacts on seasonal water quality trends. Results suggest that to improve water quality in the study area, efforts should focus on improving WWTP effluent treatment and agricultural land management.