Geology Reports⌕ Search
Home/Archive/USGS

USGS · 70219218

Variable seepage meter efficiency in high-permeability settings

Donald O. Rosenberry·Jose M Nieto-Lopez·Richard M. Webb·Sascha Muller
View original source ↗Export metadata ↓

Abstract

The efficiency of seepage meters, long considered a fixed property associated with the meter design, is not constant in highly permeable sediments. Instead, efficiency varies substantially with seepage bag fullness, duration of bag attachment, depth of meter insertion into the sediments, and seepage velocity. Tests conducted in a seepage test tank filled with isotropic sand with a hydraulic conductivity of about 60 m/d indicate that seepage meter efficiency varies widely and decreases unpredictably when the volume of the seepage bag is greater than about 65 to 70 percent full or less than about 15 to 20 percent full. Seepage generally decreases with duration of bag attachment even when operated in the mid-range of bag fullness. Stopping flow through the seepage meter during bag attachment or removal also results in a decrease in meter efficiency. Numerical modeling indicates efficiency is inversely related to hydraulic conductivity in highly permeable sediments. An efficiency close to 1 for a meter installed in sediment with a hydraulic conductivity of 1 m/d decreases to about 60 and then 10 percent when hydraulic conductivity is increased to 10 and 100 m/d, respectively. These large efficiency reductions apply only to high-permeability settings, such as wave- or tidally washed coarse sand or gravel, or fluvial settings with an actively mobile sand or gravel bed, where low resistance to flow through the porous media allows bypass flow around the seepage cylinder to readily occur. In more typical settings, much greater resistance to bypass flow suppresses small changes in meter resistance during inflation or deflation of seepage bags.

Explore related subjects

WaterArticle

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Donald O. Rosenberry, Jose M Nieto-Lopez, Richard M. Webb, Sascha Muller. 2020-11-21. Variable seepage meter efficiency in high-permeability settings. https://doi.org/10.3390/w12113267

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Investigating hydrologic alteration under historical and future scenarios in the Mobile River and Perdido River basins using the cubist algorithm

This study investigates the impacts of human activities and climate variability on hydrologic alterations in the Mobile River and Perdido River Basins of Alabama. The research uses a machine learning approach, specifically cubist models, to quantify and predict changes in flow duration curves (FDCs) under both historical (1980–2009) and future climate scenarios. Future climate projections include the Representative Concentration Pathways (RCP 4.5 and RCP 8.5) and the Shared Socioeconomic Pathways (SSP2 4.5 and SSP5 8.5), evaluated for two future periods: 1980–2069 and 1980–2099. The models incorporate a wide range of covariates, including basin geomorphology, aquifer characteristics, land cover, water storage, environmental factors, solar radiation, census data, and water use data. Under the baseline period (1980–2009), most level 12 hydrologic unit codes (HUC12s) in both basins showed alterations, with substantial differences observed between pre- and post-alteration FDCs. The model performance varied, with a Nash–Sutcliffe Efficiency between 0.91 and 0.95 for testing and between 0.98 and 0.99 for training during the baseline period. Future projections under the RCP 4.5 and RCP 8.5 scenarios generally differed significantly from baseline conditions across all flow regimes ( p < 0.05). In contrast, SSP2 4.5 showed comparatively limited statistical significance, while SSP5 8.5 exhibited significant departures from baseline conditions across all flow regimes, reflecting the greater influence of high-emissions climate forcing on projected hydrologic alterations. Overall, the RCP scenarios projected more widespread statistically significant changes than the corresponding SSP scenarios at the same forcing level, particularly when comparing RCP4.5 with SSP2-4.5, while both RCP8.5 and SSP5-8.5 consistently indicated greater hydrologic alterations than their moderate-emissions counterparts. These findings highlight the importance of considering different flow regimes when assessing the impacts of climate variability on streamflow. This study contributes to the understanding of hydrologic alterations in the Mobile River and Perdido River Basins, providing insights for water resource management and ecological conservation efforts in the region.

Alabama↗
USGS2026

Estimating the importance of floating surface material to the total phosphorus transport in Silver Creek, Wisconsin using Particle Image Velocimetry

Various techniques are used to estimate nutrient delivery in streams that combine flow and water-quality data. However, the transport of surface floating material is difficult to measure, and is therefore typically neglected when stream sampling and in the estimated nutrient delivery. Here, we describe an approach to estimate the amount of material (duckweed ( Lemna genus), filamentous algae, and other macrophyte fragments) and associated nutrients (in this case, phosphorus, P) transported on the surface of Silver Creek, Wisconsin, to determine if this material is an important transport mechanism and if historical P loads were underestimated. This approach includes estimating the transport of surface material using 10 s videos collected every 15 min from a downward-looking camera installed beneath a bridge. The average velocity of the surface material was first determined using Large-Scale Particle Image Velocimetry (LSPIV), which uses short videos to analyze surface particle movement. The amount of surface material in each video was then computed using computer-vision techniques. The P load associated with the transported surface material was then estimated by combining surface velocities, coverage of floating material, and laboratory-measured P content. Surface material transported ~9–11% of the total summer P load and ~4–7% of the annual load in Silver Creek.

Wisconsin↗
USGS2026

Characterizing the long-term (1981–2023) temperature and precipitation dynamics in the Trans-Mountain regions of Kazakhstan, Central Asia

Mountain regions are highly climate-sensitive, yet long-term observational evidence of elevation and seasonal climate dynamics in Central Asia remains limited. This study examines spatiotemporal trends in temperature (Tmean, Tmax, Tmin, and diurnal temperature range [DTR]) and precipitation across Kazakhstan’s transmountain regions using 74 meteorological stations (1981–2023). Data were analyzed using the Mann–Kendall test and Sen’s slope estimator, stratified across six elevation zones from lowlands (<400 m) to high mountains (>1500 m). Results reveal a robust, spatially coherent warming signal across all zones. Annual Tmean increased at a median rate of ~0.30 °C decade −1 , peaking at 0.36 °C decade −1 above 1500 m, corresponding to an absolute increase exceeding 1.5 °C. Warming exhibited strong seasonal and diurnal asymmetries. Spring warmed most rapidly, with Tmean increasing >0.60 °C decade −1 (approaching 3 °C total). Winter warming was driven by Tmin increases (up to 0.44 °C decade −1 ), causing widespread DTR contraction, whereas summer warming was driven by Tmax increases, expanding DTR at higher elevations. Tmin showed the strongest elevation amplification overall. In stark contrast, precipitation trends were weak, spatially heterogeneous, and largely non-significant. Annual changes ranged from −6.63 to +14.35 mm decade −1 , with seasonal tendencies indicating modest, non-significant winter/spring wetting and summer drying. Ultimately, the results demonstrate a profound decoupling between strong, elevation-dependent warming and weak precipitation changes. The acute amplification of temperature, particularly during spring and summer at high elevations, has severe implications for snowmelt timing, glacier mass balance, evapotranspiration demand, and long-term water security in Kazakhstan.

Water↗