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In December 2021, we installed four groundwater monitoring wells in Imperial Beach, California, to study the effects of sea level variability and implications for flood risks. We collected time series of groundwater table elevation (GWT) relative to a fixed vertical datum and local land surface elevation from 8 December 2021 through 14 May 2024. In each groundwater monitoring well, a single unvented pressure sensor (RBR Solo) was attached to Kevlar line and submerged ~1 m below the GWT. From 8 December 2021 through 21 November 2023, total pressure was recorded at 1 Hz; from 22 November 2023 through 14 May 2024, sampling occurred at 0.1 Hz. Gaps in sampling are a result of battery failures leading to data loss. To estimate hydrostatic pressure from total pressure measurements we subtracted atmospheric pressure measurements that were collected every 6 min from NOAA's National Data Buoy Center (NDBC) station SDBC1-9410170 at the San Diego airport and linearly interpolated to match sensor samples. Hydrostatic pressure is converted to sensor depth below the water table. We determined an average well water density, ρ, using intermittent vertical profiles of conductivity-temperature-depth (CTD) and the TEOS-10 conversion (Roquet et al. 2015). This object includes MATLAB (.mat) and HDF5 (.h5) files that contain the raw total pressure measurements from unvented RBR solos. The original Ruskin files (.rsk) are not included and have been converted to MATLAB files without loss of fidelity. Intermittent CTD profiles used to estimate well water density structure are included as CSV files. GWT that have been processed using atmospheric pressure and vertical datum measurements are included as HDF5 files. The object has five main directories, one for each of the four groundwater wells and one for data downloaded from other sources for archival and reproducibility purposes. Code for generating these files may be found on the GitHub repository (https://github.com/aubarnes/ImperialBeachGroundwater) or on Zenodo (https://doi.org/10.5281/zenodo.14969632). Code run with Python v3.12.7 Pastas v1.5.0 UTide v0.3.0 GSW v3.6.19 NumPy v1.26.4 Pandas v2.1.4 MatPlotLib v3.9.2 SciPy v 1.13.1 requests v2.32.3 intake v0.7.0 datetime pickle os 

Saltwater intrusion (SWI) into coastal freshwater systems is a growing concern in the face of climate change‐driven sea level rise and hydrologic variability. Saltwater contamination of surface freshwater in the coastal California Pajaro Valley exemplifies this concern, where surface water cannot be diverted for agriculture if it is too saline. Closures at the mouth of the Pajaro River Lagoon, a bar‐built estuary in the Pajaro Valley, are associated with SWI. Closures and SWI are driven by a combination of offshore climate, coastal hydrodynamics, estuarine dynamics, inland hydrology, and infrastructure and management. Here, we describe the Pajaro Valley coastal water system and identify the oceanic and inland hydrologic drivers of SWI using available observational data between 2012 and 2020. We use time series and exploratory statistical analyses of coastal total water levels (TWLs), slough stage and salinity, river discharge, and contextual knowledge from local water managers. We observe that wet season lagoon closure and SWI events follow high oceanic TWLs coupled with low stage and discharge in the inland freshwater network, revealing how both wave and inland flow conditions govern lagoon closures and coincident SWI. This study yields novel empirical findings and a methodology for connecting coastal oceanography, estuarine coupled hydro‐ and morpho‐dynamics, inland hydrology, and water management practices relevant to climate change adaptation in human‐modified coastal water systems. 

Abstract Many faculty of color (FOC) lack the necessary social and professional support structures to facilitate their successful advancement on the tenure track. We present Flourish, a network for pre‐tenure social and personality psychologists of color, as a case study to illustrate how an affinity group model can aid in supporting FOC. We demonstrate that using social support to diffuse social identity threats can increase belonging and academic fit and, as a result, promote the success of early career FOC. As a field, psychological science has the potential to transcend the boundaries of academic institutions by leveraging our theories, methods, and applied expertise to build infrastructure to better support FOC. Attracting and retaining a diverse faculty workforce addresses racial inequities in higher education, diversifies research output, and makes our science more representative and reproducible. Thus, investing in affinity groups is essential for developing accessible social support systems and increasing role models for future scholars of color. 

Abstract Rising groundwater tables due to sea level rise (SLR) pose a critical but understudied threat to low‐lying coastal regions. This study uses field observations and dynamic modeling to investigate drivers of groundwater variability and to project flooding risks from emergent groundwater in Imperial Beach, California. Hourly groundwater table data from four monitoring wells (2021–2024) reveal distinct aquifer behaviors across soil types. In transmissive coastal sandy soils, groundwater levels are dominated by ocean tides, with secondary contributions from non‐tidal sea level variability and seasonal recharge. In this setting, we calibrated an empirical groundwater model to observations, and forced the model with regional SLR scenarios. We project that groundwater emergence along the low‐lying coastal road will begin by the 2060s under intermediate SLR trajectories, and escalate to near‐daily flooding by 2100. Over 20% of San Diego County's coastline shares similar transmissive sandy geology and thus similar flooding risk. Results underscore the urgency of integrating groundwater hazards into coastal resilience planning, as current adaptation strategies in Imperial Beach—focused on surface flooding—are insufficient to address infrastructure vulnerabilities from below. This study provides a transferable framework for assessing groundwater‐driven flooding in transmissive coastal aquifers, where SLR‐induced groundwater rise threatens critical infrastructure decades before permanent inundation. 

Abstract We analyze variability in 15-season optical lightcurves from the doubly imaged lensed quasar SDSS J165043.44+425149.3 (SDSS1650), comprising five seasons of monitoring data from the Maidanak Observatory (277 nights in total, including the two seasons of data previously presented in Vuissoz et al.), five seasons of overlapping data from the Mercator telescope (269 nights), and 12 seasons of monitoring data from the US Naval Observatory, Flagstaff Station at lower cadence (80 nights). We update the 2007 time-delay measurement for SDSS1650 with these new data, finding a time delay of $\mathrm{\Delta }{t}_{\mathrm{AB}}=-{55.1}_{-3.7}^{+4.0}$days, with image A leading image B. We analyze the microlensing variability in these lightcurves using a Bayesian Monte Carlo technique to yield measurements of the size of the accretion disk atλ_rest= 2420 Å, finding a half-light radius of log(r_1/2/cm) = ${16.19}_{-0.58}^{+0.38}$assuming a 60° inclination angle. This result is unchanged if we model 30% flux contamination from the broad-line region. We use the width of the Mgiiline in the existing Sloan Digital Sky Survey spectra to estimate the mass of this system’s supermassive black hole, findingM_BH= 2.47 × 10⁹M_⊙. We confirm that the accretion disk size in this system, whose black hole mass is on the very high end of theM_BHscale, is fully consistent with the existing quasar accretion disk size–black hole mass relation.