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Source code for: 'Flooding Projections due to Groundwater Emergence Caused by Sea Level Variability' Data available through this citation: Barnes, Austin T.; Merrifield, Mark A.; Bagheri, Kian; Levy, Morgan C.; Davani, Hassan (2025). Data from: Flooding Projections due to Groundwater Emergence Caused by Sea Level Variability. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0N29XB3 v1.0.1 includes minor patches for figure creation. 

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 

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. 

Participants of the Institute for Scientist and Engineer Educators’ (ISEE) Professional Development Program (PDP) work in Design Teams to create inquiry activities that foster student learning of relevant STEM content and practices. These teams implement the inquiry activities in one or more teaching venues (i.e., a context in which Design Team members act as instructors or facilitators with actual learners or students). One such venue is the Akamai Internship Program’s PREP Course. Concurrent with running the PDP, ISEE supported the development of frameworks to help Akamai interns understand the projects they undertake during their internship. Two frameworks were developed: one focused on scientific explanations and the other on engineering solutions. This paper describes how PDP inquiry activities and the ISEE Frameworks come together in a mutually supportive manner during the Akamai PREP Course. This synergy becomes apparent as we examine the sequential placement of PREP sessions whereby the frameworks both push interns to make sense of their experiences with such activities (e.g., revisiting the explanation framework after a science-oriented inquiry) and prepare interns for effective engagement in upcoming inquiry activities (e.g., using the solution framework before an engineering-oriented inquiry). Recommendations include using a similar pairing of inquiry activities and frameworks in other teaching venues. 

As part of the Institute for Scientist and Engineer Educators Professional Development Program (PDP), our team designed an activity for the Akamai internship program’s Preparation for Research Experiences and Projects (PREP) course. The activity focused on content around different renewable energy and storage technologies, and the widely applicable engineering practice of optimization through iteration and evaluating trade-offs. Here we describe the overall activity, with primary emphasis on how the PDP backward design process and integration of the Equity & Inclusion (E&I) theme led us to design and implement a unique model we call the “expert training model” that has important E&I implications. We found that an educational activity design that focuses on E&I considerations, such as identifying multiple ways to productively participate and developing learners’ identity in STEM, simultaneously satisfies criteria for being an engaging and authentic STEM experience. We also reflect on potential pitfalls and ways to improve and adapt this model. 

ISEE Professional Development Program Teaching Teams, Akamai interns, and Akamai staff all participate in a multi-day Preparation for Research Experiences and Projects (PREP) course at the start of the annual Akamai Internship Program. One of the goals for the PREP course is to establish an inclusive, collaborative community amongst the varied participants. Integrated with the inquiry activities taught by Teaching Teams are several Akamai-designed and facilitated activities whose purpose is to build community as well as an understanding of and sensitivity towards an inclusive work environment. These activities include an opening icebreaker, a career pathways discussion, workplace integration role-plays, a workplace inclusion discussion, and a closing celebration dinner. This paper highlights specific connections between the Institute for Scientist and Engineer Educators’ Equity & Inclusion strand and the collaborative activities that engage Teaching Teams, interns, and staff during the Akamai PREP course. 

The Akamai Internship in Hawai‘i and the Professional Development Program (PDP) address key issues of sustaining a diverse, equitable, and inclusive STEM workforce in industry and academia. Established in 2002, the Akamai program builds capacity to overcome the brain-drain workforce problem that Hawaiʻi faces by connecting local undergraduate students with internship opportunities in the STEM industries on the islands of Maui and Hawaiʻi. The PDP provides opportunities for graduate students, early-career scientists and industry leaders to learn effective andragogical practices for teaching science and engineering to the next generation at the undergraduate level. A unique, grounding aspect of the Akamai program across all cohorts is a week-long course preparing interns to work with their local industry partners and build an inclusive community. The course is co-led by Akamai program staff and PDP alumni in collaboration with PDP design teams who run complementary inquiry learning activities. Since the first cohort of 2003, 451 interns and around 100 design team members have participated in Akamai. Of the 451 interns who participated in the Akamai program, at least 8 participants have become PDP design team members. The purpose of this panel discussion is to feature four of those alumni that participated in both Akamai and PDP programs. The panelists will share the factors that influenced them to become a PDP instructor as well as highlight the impacts that both programs had in shaping their respective life and career pathways. 

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