Time-lapse self-potential, electric resistivity tomography, streamflow, groundwater-level, and weather-station datasets for the lower Rio Grande, southeast New Mexico, May–October, 2022

This data release contains time-lapse self-potential, electric resistivity tomography, hydrographic, and weather data acquired during a geoelectric monitoring survey of the lower Rio Grande riverbed in the Mesilla Basin of southeast, New Mexico. The monitoring survey was performed by the U.S. Geological Survey (USGS) in cooperation with New Mexico State University (NMSU), Elephant Butte Irrigation District (EBID), and hydroGEOPHYSICS, Inc (HGI). The data and corresponding data processing codes are described in the larger work citation, a journal article titled “Geoelectric Monitoring of the Electric-potential Field of the Lower Rio Grande Before, During, and After Intermittent Streamflow, May–October, 2022.” The monitoring site was located at geospatial coordinates (32.0628 N, 106.6635 W) in the lower Rio Grande riverbed between Vado, N. Mex. and Anthony, N. Mex. about 23 river-kilometers (km) downstream from Mesilla Diversion Dam in Mesilla, N. Mex. The geoelectric monitoring period began at 07:59 am Mountain Standard Time (MST) on May 21, 2022, when the river was completely dry, continued through the irrigation season when streamflow in the river was provided by reservoir releases from upstream dams, and ended at about 12:31 pm MST on October 4, 2022, when the riverbed was again dry. Self-potential (SP) monitoring and time-lapse electric resistivity tomography (ERT) were performed by the USGS and NMSU along linear cross-sections spanning the riverbed and a portion of the west flood plain to monitor the transient hydraulic connectivity between the river and the Rio Grande alluvial aquifer during the irrigation season. SP data were acquired by the USGS and consisted of 1-minute and 15-minute measurements of voltage differences between a reference electrode on the west flood plain and an array of 29 electrodes that spanned the west flood plain and riverbed to the base of the east bank. Time-lapse ERT data were acquired by NMSU on an array of 56 electrodes that spanned the west flood plain and riverbed and that were separated laterally from one another by 1.3 m along the ERT trench. ERT data were measured on May 18, May 20, and June 3, 2022, prior to the arrival of streamflow at the monitoring site, and in rapid succession on June 4, 2022, between the time of streamflow arrival at 10:08 am MST and 13:48 pm MST, and processed for interpretation by HGI. Hydrographic data consisted of 30-minute measurements of streamflow at a gage 19.8 km upstream from the geoelectric monitoring site, and groundwater-level data in an observation well about 1,440 meters from the monitoring site on the east flood plain, were monitored by EBID, in addition to weather data measured at an EBID weather station about 1,440 meters (m) from the monitoring site on the west flood plain. Weather data consisted of 30-minute measurements of surface air temperature, soil temperature, vapor pressure, precipitation, relative humidity, net solar radiation, wind speed, and barometric pressure. The weather data were used to compute a model of potential evaporation for comparison with time-series of SP data. The hydrographic and weather data cover the time period beginning at 07:59 am MST on May 21, 2022, and ending between 19:26 pm and 19:54 pm MST on September 4, 2022.

Tags: anthony, berino-road, desert-southwest, electric-resistivity, electric-resistivity-tomography, electrical-resistivity-imaging, elephant-butte-irrigation-district, ephemeral-rivers, geophysical-monitoring, geophysics, geoscientificinformation, gradient-self-potential, groundwater, groundwater-and-surface-water-interaction, hydraulic-connectivity, hydrology, inlandwaters, inverse-modeling, lower-rio-grande, mesilla, mesilla-basin, mesquite, new-mexico, new-mexico-highway-226, potential-evaporation, rio-grande, rivers, self-potential, streamflow, surface-water, surface-water-and-groundwater-exchanges, united-states, usgs-63a20e8cd34e176674f51d51
Organization: Department of the Interior