#geochemicalmodeling — Public Fediverse posts

I’m currently open to opportunities related to environmental geochemistry, groundwater, and geochemical modeling.

My background includes PHREEQC-based modeling, reproducible workflows (R, QGIS), environmental data analysis, applied machine learning (exploratory / environmental) and applied research on mine-water impacts on carbonate aquifers.

An example of my applied research and methodology (open access):
https://zenodo.org/records/16741148

Based in Canada (Calgary). Open to discussions and professional connections.

#Hydrogeochemistry #Groundwater #EnvironmentalGeochemistry
#PHREEQC #GeochemicalModeling #ReproducibleResearch #Canada #Alberta #Calgary #YYC

Seven months after publishing the draft of my monograph on Zenodo, it has passed 2,000 downloads.

I take this as a signal of ongoing interest in the topic and in the proposed methodological approach. It also suggests that the framework may be applicable beyond the original case study.

Currently working on the next version with further refinements and extensions.

#Hydrogeochemistry #PHREEQC #GeochemicalModeling #ReproducibleResearch #EnvironmentalGeochemistry #rstats #qgis #SvystunovaGully #mining

🧪 Davis vs Pitzer: stress-testing a geochemical model

In hydrogeochemical modeling, there is a common concern:
are “simpler” activity models reliable for saline waters, or do they break down beyond their formal limits?

In my study, I primarily use minteq.v4.dat (Davies equation) in PHREEQC. Formally, Davies is recommended up to ionic strength ~0.5–0.7, while Pitzer theory is considered the gold standard for brines.

Instead of assuming, I tested it.

What I did
- Recalculated >1000 real water samples
- Compared saturation indices (SI) computed with:
- Davies-based MINTEQ.V4
- Pitzer formulation (pitzer.dat)

What I found
For calcite, results are nearly identical:
- points lie close to the 1:1 line
- median SI differs by <0.1
- no statistically significant difference (Mann–Whitney p = 0.22)

This is not an argument against Pitzer.
It is evidence that Davies-based models can remain robust for certain systems when their

#Hydrogeochemistry #PHREEQC #GeochemicalModeling #ReproducibleResearch #SvystunovaGully

🎨 When visualization becomes part of thinking

In geochemical modeling, diagrams are not decoration — they’re analytical tools.

Every chart and map I create goes through many iterations: filtering, reshaping, and transforming multi-dimensional geochemical data until patterns start to reveal themselves.

Good visualization doesn’t just show results — it creates insight.
It helps trace hidden geochemical transitions, test hypotheses, and understand how contamination evolves through space and chemistry.

🧩 For me, plotting and modeling are inseparable parts of one process — the science of seeing.

📘 All supporting data and modeling results are included in the draft monograph:
🔗 https://zenodo.org/records/16741148

🧪 Modeling & visualization: PHREEQC + R + QGIS

#Geochemistry #GeochemicalModeling #DataVisualization #ScientificGraphics #EnvironmentalScience #GroundwaterQuality #PHREEQC #RStats #QGIS #GeoscienceCommunication #IndependentResearch #SvystunovaGully

🔍 Exploring groundwater chemistry — from ions to equilibrium

This ternary diagram shows how groundwater samples affected by mine water vary in anion composition. Each point represents one sample, colored by its calcite saturation index (SI) from PHREEQC calculations.

Such early-stage exploration helps reveal subtle geochemical trends — where equilibrium breaks down, reactions intensify, and contamination fronts begin to form.

🧪 Data exploration: PHREEQC + R

#Geochemistry #Hydrogeology #MineWater #Groundwater #PHREEQC #DataExploration #EnvironmentalGeochemistry #GeochemicalModeling #DataVisualization #RStats #OpenScience #SvystunovaGully

🔬 Metasomatic Zonation as a Model of Groundwater Contamination

One of the key theoretical bases in my research is the classical metasomatic zonation model (Korzhinskii, 1960s).

I interpret the contamination halo formed by mine waters not as passive dispersion — but as an active metasomatic system, where aggressive fluids drive alteration and re-precipitation reactions within the carbonate aquifer.

Highly mineralized mine waters create a complex interaction front.
Thermodynamic modeling (based on well-monitoring data) allows identification of several geochemical zones partly analogous to Korzhinskii’s metasomatic sequence.

📊 The image shows my preliminary zoning concept.

📘 All calculations and hypotheses are detailed in the draft monograph:
🔗 https://zenodo.org/records/16741148

#Geochemistry #Hydrogeology #PHREEQC #Metasomatism #MineWater #GroundwaterContamination #GeochemicalModeling #IndependentResearch #OpenScience #RStats #QGIS #EnvironmentalGeochemistry #Thermodynamics #Aquifer #Zenodo #SvystunovaGully