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environmental-data

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Water Stress Risk Index — Sub-Saharan Africa

Climate Scenario Analysis: Current vs 2°C vs 4°C Warming

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The Story Behind This Project

I grew up without clean running water in Zimbabwe. This project is an attempt to quantify what that experience looks like at scale.

Water insecurity is not an abstract concept to me. It shaped how I ate, how my family planned, and how I understood the relationship between environment and human survival. This analysis is my attempt to use data science to understand the scope of that problem across Sub-Saharan Africa and model how climate change will make it worse.

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What This Project Does

This project builds a Water Stress Risk Index for 15 Sub-Saharan African countries using real climate and population data. It models how water stress levels change under two climate warming scenarios and classifies each country by vulnerability level.

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Key Findings

• Zimbabwe currently sits at High risk and reaches Critical status under both 2°C and 4°C warming scenarios
• Niger, Mali, and Somalia are already at Critical stress levels under current conditions
• At 4°C warming, over 53% of modeled countries reach Critical water stress status
• Countries with the lowest clean water access tend to cluster at the highest stress levels — confirming that infrastructure gaps and climate vulnerability compound each other
• DRC, Angola, and Madagascar represent relatively lower risk zones and potential models for regional water resilience

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Visualizations

The project produces four charts:

1. Current Water Stress Index — horizontal bar chart showing stress levels by country with critical threshold marked
2. Climate Scenario Comparison — side by side comparison of current, 2°C, and 4°C stress levels for all 15 countries
3. Clean Water Access vs Stress Index — scatter plot revealing the relationship between infrastructure access and climate vulnerability
4. Risk Distribution at 4°C Warming — pie chart showing the proportion of countries at each risk level under worst case warming

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Data Sources

• FAO AQUASTAT — Global water stress indicators
• World Bank Open Data — Population and development indicators
• NOAA Climate Data — Rainfall and drought indices

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Methodology

Water stress is modeled using a composite index combining:

• Annual rainfall levels
• Population pressure on water resources
• Existing clean water infrastructure access

Climate scenario projections apply empirically grounded stress multipliers:

• 2°C warming — 15% increase in baseline water stress
• 4°C warming — 35% increase in baseline water stress

Stress indices are capped at 1.0 representing maximum critical stress. Countries are classified into four risk tiers: Low, Moderate, High, and Critical.

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Risk Classification Results

Country	Current	2°C Warming	4°C Warming
Zimbabwe	High	Critical	Critical
South Africa	Critical	Critical	Critical
Kenya	High	Critical	Critical
Ethiopia	High	High	Critical
Nigeria	Moderate	High	High
Tanzania	Moderate	Moderate	High
Mozambique	Moderate	Moderate	Moderate
Zambia	Moderate	Moderate	Moderate
Mali	Critical	Critical	Critical
Niger	Critical	Critical	Critical
Chad	High	Critical	Critical
Somalia	Critical	Critical	Critical
Madagascar	Moderate	Moderate	Moderate
Angola	Low	Low	Moderate
DRC	Low	Low	Low

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Tools and Libraries

• Python 3.14
• NumPy — numerical computation
• Pandas — data manipulation
• Matplotlib — visualization
• Seaborn — statistical graphics

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Connection to Research

This project sits at the intersection of two research frameworks that I find deeply compelling:

Professor Braden Allenby's work on Earth systems engineering challenges engineers to design solutions that account for long-term ecological consequences at planetary scale. This analysis attempts to apply that systems-level thinking to water infrastructure by modeling not just current stress but future trajectories under climate pressure.

Professor Margaret Garcia's research on water infrastructure resilience and community-centered environmental solutions reflects exactly the kind of interdisciplinary approach this project attempts. Understanding which communities face the most severe water stress under climate change is the first step toward designing resilient infrastructure that serves them.

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Author

Mashanda Marcuzee
Mechanical Engineering — Trinity College
Graduate Studies in Business Analytics — Bentley University
Co-founder, Zi-Farm (2020) — Food security initiative, Zimbabwe

"Engineering is not simply about machines or calculations. It is about designing solutions even within constraints."

master