Geology topics

Annalise G. Blum

Publications and source records attributed to Annalise G. Blum.

6 recordsLinked to original sources

USGS2022

Methods for computing 7Q2 and 7Q20 low-streamflow statistics to account for possible trends

Low-streamflow statistics, such as the annual minimum 7-day streamflow (which is the 7-day streamflow likely to be exceeded in 9 out of 10 years on average [7Q10]), that are computed by using the full historical streamflow record may not accurately represent current conditions at sites with statistically significant trends in low streamflow over time. Recent research suggests that using a contemporary subset of the historical streamflow record (specifically, the most recent 30 years) to compute an estimate of 7Q10 more accurately represents current streamflow conditions when a statistically significant trend in the streamflow record is present. This report presents the results of a Monte Carlo simulation experiment on artificial low-streamflow records, derived from the characteristics of streamflows at 174 U.S. Geological Survey streamgages, to test whether a similar approach is appropriate for the computation of the annual minimum 7-day streamflow exceeded in 1 out of 2 years on average (7Q2) and the annual minimum 7-day streamflow exceeded in 19 out of 20 years on average (7Q20). The results indicate that using the most recent 30-year subset of the low-streamflow record also may be the best approach when computing 7Q2 and 7Q20 at sites where a statistically significant trend in low streamflows is detected.

Open-File Report↗

USGS2020

Causal effect of impervious cover on annual flood magnitude for the United States

Despite consensus that impervious surfaces increase flooding, the magnitude of the increase remains uncertain. This uncertainty largely stems from the challenge of isolating the effect of changes in impervious cover separate from other factors that also affect flooding. To control for these factors, prior study designs rely on either temporal or spatial variation in impervious cover. We leverage both temporal and spatial variation in a panel data regression design to isolate the effect of impervious cover on floods. With 39 years of data from 280 U.S. streamgages, we estimate that a one percentage point increase in impervious basin cover causes a 3.3% increase in annual flood magnitude (95%CI: 1.9%, 4.7%) on average. Using 2,109 streamgages, some of which have upstream regulation and/or overlapping basins, we estimate a larger effect: 4.6% (CI: 3.5%, 5.6%). The approach introduced here can be extended to estimate the causal effects of other drivers of hydrologic change.

Geophysical Research Letters↗

USGS2020

Low streamflow trends at human-impacted and reference basins in the United States

We present a continent-scale exploration of trends in annual 7-day low streamflows at 2482 U.S. Geological Survey streamgages across the conterminous United States over the past 100, 75, and 50 years (1916–2015, 1941–2015 and 1966–2015). We used basin characteristics to identify subsets of study basins representative of reference basins with streamflow relatively free from human effects (n = 259), and predominantly agricultural basins (n = 78), regulated basins (n = 220), and urban basins (n = 121). Trend significance was computed using the Mann-Kendall test considering short- and long-term persistence. Lag-one autocorrelation tests of detrended 7-day low streamflows for all gage classes show that time-series independence is not an appropriate assumption for annual low streamflow data at many basins. Among all study gages, upward trends (wetter conditions) in 7-day low streamflows outnumbered downward trends (drier conditions) approximately 2–1 for the 75- and 100-year trend periods—50-year trends indicated roughly equal numbers of increases and decreases. Increases in 7-day low streamflow were consistently observed for all time periods throughout much of the northeastern quadrant of the conterminous U.S. including western New England and the Mid-Atlantic, the southeastern Great Lakes basin, northern Ohio River basin, and the Upper Mississippi River and eastern Missouri River basins. Decreases in 7-day low streamflow were consistently observed for all time periods at many gages in the southeastern U.S. and in the northwestern U.S. in much of Idaho and northwestern Washington. Overall, we observed greater percentages of statistically significant trends at gages with human-induced influences than at reference gages. Low-flow trends at agricultural gages were regionally consistent with trends at reference gages. Regulated basins had many statistically significant upward trends for all three time periods tested, which may be attributed in part to substantial increases in dam-related storage prior to 1970. Urban gages had the greatest percentage of significant decreases in 7-day low flows compared to all other gage classes even though most urban gages saw upward trends in mean annual flows. Urban gages also had the greatest percentage of significant increases in low flows second only to regulated gages, highlighting that urban development can increase or decrease low streamflows depending on the basin-specific development.

Conterminous United States↗

USGS2019

Updating estimates of low-streamflow statistics to account for possible trends

Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estimating low-streamflow statistics are needed. Here we investigate simple approaches to select a recent subset of the low-flow record to update the commonly used statistic of 7 Q 10, the annual minimum 7-day streamflow exceeded in 9 out of 10 years on average. Informed by low-streamflow records at 174 US Geological Survey streamgages, Monte Carlo simulation experiments evaluate competing approaches. We find that a strategy which estimates 7 Q 10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7 Q 10 estimators compared to use of the full record. This simple rule-based approach has potential as the basis for a framework for updating frequency-based statistics in the context of possible trends.

Hydrologic Sciences Journal↗

USGS2018

Seasonal streamflow extremes are key drivers of Brook Trout young‐of‐the‐year abundance

To manage ecosystems in the context of climate change, we need to understand the relationship between extreme events and population dynamics. Floods and droughts are projected to occur more frequently, but how aquatic species will respond to these extreme events remains uncertain. Based on counts of Brook Trout ( Salvelinus fontinalis ) collected over 28 yr at 115 sites in Shenandoah National Park, we developed mixed‐effects models to (1) assess how well extreme streamflow, as compared to mean flows and total precipitation, can explain young‐of‐the‐year (YOY) abundance, (2) identify potential nonlinear relationships between seasonal environmental covariates and abundance using nonlinear generalized additive mixed models, and (3) explore likely impacts of expected future weather and streamflow conditions. We found that (1) using covariates of streamflow extremes improved prediction of YOY abundance compared to use of mean seasonal flow values or precipitation as a proxy, (2) warmer maximum daily spring temperatures were associated with increased YOY abundance up to about 1.5 standard deviations, above which abundance declined, and (3) a strong negative effect of extreme winter streamflow, unlikely to be offset by possibly positive effects from other seasons, is expected to have a detrimental impact on Brook Trout populations given predicted increases in winter precipitation. Because YOY abundance is a strong determinant of population dynamics for these short‐lived species, extreme events will have the potential to exert a strong influence on population persistence of Brook Trout in a changing climate. Management actions that maximize resiliency of populations in response to extreme events, such as restoration of habitat connectivity, should be prioritized to buffer negative impacts.

Virginia↗

USGS2017

On the probability distribution of daily streamflow in the United States

Daily streamflows are often represented by flow duration curves (FDCs), which illustrate the frequency with which flows are equaled or exceeded. FDCs have had broad applications across both operational and research hydrology for decades; however, modeling FDCs has proven elusive. Daily streamflow is a complex time series with flow values ranging over many orders of magnitude. The identification of a probability distribution that can approximate daily streamflow would improve understanding of the behavior of daily flows and the ability to estimate FDCs at ungaged river locations. Comparisons of modeled and empirical FDCs at nearly 400 unregulated, perennial streams illustrate that the four-parameter kappa distribution provides a very good representation of daily streamflow across the majority of physiographic regions in the conterminous United States (US). Further, for some regions of the US, the three-parameter generalized Pareto and lognormal distributions also provide a good approximation to FDCs. Similar results are found for the period of record FDCs, representing the long-term hydrologic regime at a site, and median annual FDCs, representing the behavior of flows in a typical year.

Hydrology and Earth System Sciences↗