HASSA Brown Bag Lunch Series Spring 2025 - March

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Student-Brown-Bag-Presentations

When

1 – 2 p.m., March 17, 2025

Where

Hi everyone!
 
This month's Brown Bag Lunch will be the Monday after spring break, March 17, from 1PM to 2PM in Harsh 110. 
 
This month we have four outstanding undergraduate students presenting the first drafts of their El Dia posters. The abstracts for their posters are provided below. These students include:
Annalisa Minke, Brian Thompson, Renad Yaser, and Steven Billington
 
We ask that students, staff, and faculty volunteer to attend this event to provide our presenters with feedback on their posters. If you plan on attending, please put your name on the google sheet (link below). 
 
 
If you have any questions or concerns, please reach out to Tyler (tmaio123@arizona.edu). 
 
Annalisa Minke

A statistical analysis of applying Haar wavelets to predict planetary boundary layer decoupling

The modeling of the planetary boundary layer (PBL) is essential to the prediction of local weather phenomena; however, the complexities of the PBL make it very difficult and computationally expensive to model. One of the complexities is the existence of multiple mixing layers beneath the PBL. These mixing layers, which are thought to form under optically-dense clouds, restrict the transport of aerosols, water, and energy throughout the PBL. Measuring the mixing layers through active remote sensing has proven to be a robust method given an adequate algorithm. However, these algorithms tend to be very complicated and computationally dense, and most LiDAR data is too sparse to determine spatial and temporal resolution. Using a Haar wavelet, a simplified algorithm was produced. The algorithm’s output is accurate some days and overestimates other days. The prediction of decoupling using this algorithm is highly aligned with the presence of clouds indicating that the simplified prediction of decoupling could be used even if the raw values need adjusting.

 

Brian Thompson

Establishing a baseline of seasonal and storm event changes in water chemistry in Cienega Creek Natural Preserve prior to mining activities

It is important to establish a baseline of water quality in a watershed prior to the initiation of mining operations to better assess potential future minis-related impacts. This can be accomplished by collecting storm water and baseflow samples at multiple sites along potentially-affected creeks and ephemeral washes. Cienega Creek Natural Preserve is a protected riparian corridor in Pima County, Arizona, that is a reservoir of biodiversity and endangered aquatic species. A large porphyry copper mine is in the final stages of being permitted an d will be established on a ridgeline above one of the major ephemeral tributaries of Cienega Creek. My research involves using water sample data collected from 2008 – 2025 to track seasonal and storm event changes in basic water chemistry (e.g. pH, alkalinity), as well as cations, anions, and dissolved metals, to establish a water chemistry baseline prior to mining activities. For metals - both suspended and dissolved - initial results show increasing levels over time as land has begun to be cleared for the development of mining activities. Previous research has shown that metal concentrations peak during storm runoff as metals are suspended and dissolved on or near the soil surface but results from my research indicate that metal concentrations (particularly zinc and copper) appear to be increasing as land clearance and ridgeline modification continues. These results could have negative implications for aquatic life in Cienega Creek.

Renad Alsufyani

Estimating groundwater recharge using a chloride mass balance (CMB) approach on the Umm Er Radhuma aquifer in the Rub' al Khali area of Saudi Arabia

The recharge rate of groundwater resources provides crucial insights for sustainable water management, ensuring the protection of this vital resource for future generations. My research focused on estimating groundwater recharge using a chloride mass balance (CMB) approach on the Umm Er Radhuma aquifer in the Rub' al Khali area of Saudi Arabia, where a few studies have been conducted. CMB is a practical and cost-effective approach since it depends only on annual precipitation, chloride concentration in that precipitation, and chloride concentration in the groundwater. The result suggests that the average groundwater recharge flux in the Umm Er Radhuma aquifer is 0.567 mm/yr. Given the extremely low estimated groundwater recharge, the region is likely to have high rates of evapotranspiration, limited precipitation, and geology that restricts infiltration. Although this result shows limited recharge, it also presents a favorable opportunity for well-organized and efficient groundwater management planning, particularly since the Rub' al Khali region is sparsely populated, and has significant groundwater supplies that have not yet been fully developed. Since precipitation in Saudi Arabia is infrequent, this estimation was based on a single rainfall event; if we examine more rainfall data, the result may give us a more comprehensive understanding of the long-term trend of groundwater recharge.

 

Steven Billington

Examining the difference in gridded reanalysis of climate forcing and the meteorological station observations and its implication for land-surface fluxes simulations

Climate drives the growth dynamics of terrestrial plants, which in turn impacts the water, carbon, and energy exchange between the atmosphere and the land. When applying the land-surface model to understand the land and climate interactions, climate forcing data with different spatial resolutions may introduce simulation uncertainty, but it is seldom quantified. To address this uncertainty, we aim to integrate gridded-based and meteorology station-monitored climate forcing data with the community land model (CLM5.0) to assess the differences in two data sources and their impacts on carbon, water, and energy flux simulations at a site level. Forcing data is observational data that can be used to run CLM5.0. We analyzed the differences between two data sources at the Maricopa site. One is the Analysis of the record of recalibration (AORC) climate forcing data with the spatial resolution of 30 arc seconds (about 800m). The other is the meteorological data monitored from The Arizona Meteorological Network (AZMet) for the Maricopa site. We analyzed the difference in diurnal variability, seasonality, and interannual variability in temperature, precipitation, wind, surface pressure, relative humidity, and solar radiation. Then we used this data to drive the CLM to simulate the guayule growth at the Maricopa site between 2017 and 2020. Finally, we assessed how these differences in climate forcing data may affect simulated water, energy, and carbon fluxes at the Maricopa site.

 

 

Cheers, HASSA Officers

Jessica Meyer  | President/Co-president
Tyler Maio  |  Vice President/Co-President
Eden Harper  |  Treasurer
Ander Ortiz  |  Outreach Chair
Brandolyn Baeza  |  Social Chair
Jack Flanigan  |  Undergraduate Representative
Natalie Yurek  |  Secretary
 
 

Contacts