Dataset Information

Fragmented patterns of flood change across the United States.

ABSTRACT: Trends in the peak magnitude, frequency, duration, and volume of frequent floods (floods occurring at an average of two events per year relative to a base period) across the United States show large changes; however, few trends are found to be statistically significant. The multidimensional behavior of flood change across the United States can be described by four distinct groups, with streamgages experiencing (1) minimal change, (2) increasing frequency, (3) decreasing frequency, or (4) increases in all flood properties. Yet group membership shows only weak geographic cohesion. Lack of geographic cohesion is further demonstrated by weak correlations between the temporal patterns of flood change and large-scale climate indices. These findings reveal a complex, fragmented pattern of flood change that, therefore, clouds the ability to make meaningful generalizations about flood change across the United States.

SUBMITTER: Archfield SA

PROVIDER: S-EPMC5129637 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Fragmented patterns of flood change across the United States.

Archfield S A SA Hirsch R M RM Viglione A A Blöschl G G

Geophysical research letters 20161009 19

Trends in the peak magnitude, frequency, duration, and volume of frequent floods (floods occurring at an average of two events per year relative to a base period) across the United States show large changes; however, few trends are found to be statistically significant. The multidimensional behavior of flood change across the United States can be described by four distinct groups, with streamgages experiencing (1) minimal change, (2) increasing frequency, (3) decreasing frequency, or (4) increas ...[more]

PMID: 27917010

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Project description:Research on spatial non-stationarity of land-cover classification accuracy has been ongoing for over two decades with most of the work focusing on single date maps. We extend the understanding of thematic map accuracy spatial patterns by: (1) quantifying spatial patterns of map-reference agreement for class-specific land-cover change rather than class-specific land cover for both omission and commission expressions of map error; (2) reporting goodness-of-fit estimates for the empirical models, which have been lacking in previous assessments, and; (3) using the empirical model results to map the locations of the relative likelihoods of map-reference agreement for specific land-cover change classes. We evaluated 10 map-based explanatory variables in single and multivariable logistic regression models to predict the likelihood of agreement between map and reference land-cover change (2001-2011) labels using the National Land Cover Database (NLCD) 2011 land cover and accuracy data. Logistic models for omission error had better goodness-of-fit estimates than models for commission error. For the omission error models, the explanatory variable, density of the mapped class-specific change in the immediate neighbourhood surrounding the sample pixel, produced the best model fit results (Tjur coefficient of discrimination, D, ranged from 0.59 to 0.98) compared to multivariable models and all other single explanatory variable models. Maps of the predicted likelihood of map-reference agreement produced from the best fitting omission error models provide a spatially explicit description of spatial variation of classification uncertainty at both local and regional scales. Application of the models indicated higher likelihoods of agreement (>50%) comprised a greater proportion of the land-cover change class area than the proportion of the land-cover change class with lower likelihoods of agreement. NLCD users can apply reported equations to map land-cover change uncertainty.

Project description:Importance:Benzodiazepines are implicated in a growing number of overdose-related deaths. Objectives:To quantify patterns in outpatient benzodiazepine prescribing and to compare them across specialties and indications. Design, Setting, and Participants:This serial cross-sectional study (January 1, 2003, through December 31, 2015) used nationally representative National Ambulatory Medical Care Survey data. The yearly population-based sample of outpatient visits among adults, ranging from 20?884 visits in 2003 (representing 737 million visits) to 24?273 visits in 2015 (representing 841 million visits) was analyzed. Prescribing patterns were examined by specialty and indication and used to calculate the annual coprescribing rate of benzodiazepines with other sedating medications. Data were analyzed from July 1, 2017, through November 30, 2018. Main Outcomes and Measures:Annual benzodiazepine visit rate. Results:Among the 386 457 ambulatory care visits from 2003 through 2015, a total of 919 benzodiazepine visits occurred in 2003 and 1672 in 2015, nationally representing 27.6 million and 62.6 million visits, respectively. The benzodiazepine visit rate doubled from 3.8% (95% CI, 3.2%-4.4%) to 7.4% (95% CI, 6.4%-8.6%; P?<?.001) of visits. Visits to primary care physicians accounted for approximately half of all benzodiazepine visits (52.3% [95% CI, 50.0%-54.6%]). The benzodiazepine visit rate did not change among visits to psychiatrists (29.6% [95% CI, 23.3%-36.7%] in 2003 to 30.2% [95% CI, 25.6%-35.2%] in 2015; P?=?.90), but increased among all other physicians, including primary care physicians (3.6% [95% CI, 2.9%-4.4%] to 7.5% [95% CI, 6.0%-9.5%]; P?<?.001). The benzodiazepine visit rate increased slightly for anxiety and depression (26.6% [95% CI, 22.6%-31.0%] to 33.5% [95% CI, 28.8%-38.6%]; P?=?.003) and neurologic conditions (6.8% [95% CI, 4.8%-9.5%] to 8.7% [95% CI, 6.2%-12.1%]; P?<?.001), but more so for back and/or chronic pain (3.6% [95% CI, 2.6%-4.9%] to 8.5% [95% CI, 6.0%-11.9%]; P?<?.001) and other conditions (1.8% [95% CI, 1.4%-2.2%] to 4.4% [95% CI, 3.7%-5.2%]; P?<?.001); use did not change for insomnia (26.9% [95% CI, 19.3%-36.0%] to 25.6% [95% CI, 15.3%-39.6%]; P?=?.72). The coprescribing rate of benzodiazepines with opioids quadrupled from 0.5% (95% CI, 0.3%-0.7%) in 2003 to 2.0% (95% CI, 1.4%-2.7%) in 2015 (P?<?.001); the coprescribing rate with other sedating medications doubled from 0.7% (95% CI, 0.5%-0.9%) to 1.5% (95% CI, 1.1%-1.9%) (P?<?.001). Conclusions and Relevance:The outpatient use of benzodiazepines has increased substantially. In light of increasing rates of overdose deaths involving benzodiazepines, understanding and addressing prescribing patterns may help curb the growing use of benzodiazepines.

Dataset Information

Fragmented patterns of flood change across the United States.

Publications

Fragmented patterns of flood change across the United States.

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