Geology ReportsSearch

USGS · 70249273

Geoelectric monitoring of the electric potential field of the Lower Rio Grande before, during, and after Intermittent Streamflow, May–October, 2022

Abstract

Understanding the intermittent hydraulic connectivity between ephemeral streams and alluvial aquifers is a key challenge for managing water resources in arid environments. The lower Rio Grande flows for short, discontinuous periods during the irrigation season through the Mesilla Basin in southeastern New Mexico and southwestern Texas. Hydraulic connections between the Rio Grande and the Rio Grande alluvial aquifer in the Mesilla Basin vary spatially and temporally and are not well understood. Self-potential (SP) monitoring and time-lapse electric resistivity tomography (ERT) were therefore performed along linear cross-sections spanning the riverbed and flood plain for more than 4 months to monitor the transient hydraulic connection between the river and the alluvial aquifer by measuring time-lapse changes in the electric potential field in the riverbed and flood plain. The monitoring period began on 21 May 2022, when the riverbed was completely dry, continued through the irrigation season while streamflow was provided by reservoir releases from upstream dams, and ended on 4 October 2022, when the riverbed was again dry. SP monitoring data show (1) a background condition in the dry riverbed consisting of (a) a positive electric potential anomaly with a maximum amplitude of about +100 mV attributed predominantly to a subsurface vertical salt concentration gradient and (b) diurnal electric potential fluctuations with amplitudes of 40,000–90,000 mV attributed to near-surface heat conduction driven by weather variability, in addition to (2) a streaming potential anomaly during the irrigation season with a maximum amplitude of about −3500 mV whose transient behavior clearly exhibited a change from the background anomaly to depict exclusively losing streamflow conditions that persisted through the irrigation season. Time-lapse ERT monitoring results depict rapid infiltration of streamflow into the subsurface and imply the river and Rio Grande alluvial aquifer established a full hydraulic connection within a few hours after streamflow arrival at the monitoring site. SP monitoring data show an apparent transition from hydraulic connection to disconnection at the end of the irrigation season and indicate that the transitional phase between connection and disconnection may last substantially longer than the transition from disconnection to connection. The combination of SP and ERT monitoring demonstrated herein shows the potential for broader applications of time-lapse monitoring of hydraulic intermittency and near-surface heat fluxes in different rivers.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 31.706194150636207° to 32.56208160667184° latitude; -107.01035654785272° to -106.246806743165° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Scott Ikard, Kenneth C. Carroll, Dale F. Rucker, Andrew Teeple, Jason D. Payne, Chia-Hsing Tsai, Erek H. Fuchs, Ahsan Jamil. 2023-04-23. Geoelectric monitoring of the electric potential field of the Lower Rio Grande before, during, and after Intermittent Streamflow, May–October, 2022. https://doi.org/10.3390/w15091652

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

KEEP EXPLORING

Related USGS reports

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

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

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