Datasets:
metadata
license: cc-by-4.0
task_categories:
- tabular-classification
- tabular-regression
language:
- en
tags:
- agriculture
- africa
- synthetic-data
- sub-saharan-africa
- irrigation
- water-management
- synthetic
size_categories:
- 10K<n<100K
data_type: synthetic
⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.
Irrigation Access and Efficiency - Sub-Saharan Africa
Synthetic dataset capturing irrigation infrastructure, access, and water use efficiency among smallholder farmers. Covers irrigation types, water sources, costs, and productivity impacts across diverse farming systems.
Dataset Statistics
| Scenario | Records |
|---|---|
| Low Burden | 4,000 |
| Moderate Burden | 5,000 |
| High Burden | 6,000 |
| Total | 15,000 |
Key Metrics:
- 10 countries with varying irrigation rates
- Years: 2018-2025
- 55 columns covering infrastructure, efficiency, and economics
- Irrigated cropland: 3-6% of total
- Water use efficiency: 30-50% below potential
Column Descriptions
| Column | Description |
|---|---|
record_id |
Unique record identifier |
irrigation_id |
Unique irrigation record identifier |
country |
Country name |
year |
Year of record |
farm_size_ha |
Farm size in hectares |
farm_type |
Farm classification |
has_irrigation |
Has irrigation (boolean) |
annual_rainfall_mm |
Annual rainfall (mm) |
rainfall_variability_pct |
Rainfall variability (%) |
drought_frequency |
Drought frequency |
water_stress_months |
Water stress months per year |
irrigation_type |
Irrigation system type |
water_source |
Water source |
energy_source |
Energy source for pumping |
ownership |
Ownership type |
area_irrigated_ha |
Area irrigated (ha) |
rainfed_area_ha |
Rainfed area (ha) |
irrigation_pct |
Percentage of farm irrigated |
irrigation_capacity_m3_day |
System capacity (m³/day) |
system_age_years |
System age (years) |
system_condition |
System condition |
installation_cost_usd |
Installation cost (USD) |
annual_maintenance_usd |
Annual maintenance (USD) |
subsidy_received |
Subsidy received (boolean) |
subsidy_amount_usd |
Subsidy amount (USD) |
financing_access |
Financing access (boolean) |
water_applied_mm |
Water applied (mm) |
crop_water_requirement_mm |
Crop water requirement (mm) |
application_efficiency_pct |
Application efficiency (%) |
effective_water_mm |
Effective water (mm) |
water_productivity_kg_m3 |
Water productivity (kg/m³) |
conveyance_efficiency_pct |
Conveyance efficiency (%) |
distribution_uniformity_pct |
Distribution uniformity (%) |
irrigation_efficiency_index |
Overall efficiency index |
energy_cost_usd_season |
Energy cost per season (USD) |
labor_hours_season |
Labor hours per season |
irrigation_frequency |
Irrigation frequency |
scheduling_method |
Scheduling method |
primary_crop |
Primary irrigated crop |
yield_increase_pct |
Yield increase (%) |
cropping_intensity |
Cropping intensity |
seasons_irrigated |
Seasons irrigated per year |
total_water_use_m3 |
Total water use (m³) |
water_withdrawal_m3_ha |
Water withdrawal (m³/ha) |
water_user_association |
WUA member (boolean) |
permit_obtained |
Water permit obtained (boolean) |
water_conflicts |
Water conflicts (boolean) |
groundwater_depth_m |
Groundwater depth (m) |
pump_capacity_hp |
Pump capacity (HP) |
maintenance_quality |
Maintenance quality |
technology_level |
Technology level |
technical_support |
Technical support (boolean) |
water_scarcity_impact |
Water scarcity impact (boolean) |
expansion_potential |
Expansion potential (boolean) |
investment_return_years |
Investment return period (years) |
irrigation_category |
Irrigation category |
scenario |
Burden scenario |
Usage Example
import pandas as pd
# Load the dataset
df = pd.read_csv('irrigation_access_efficiency_africa_moderate_burden.csv')
# Irrigation access by country
access = df.groupby('country')['has_irrigation'].mean() * 100
print(f"Irrigation access by country:\n{access}")
# Efficiency by irrigation type
efficiency = df[df['has_irrigation']].groupby('irrigation_type')['irrigation_efficiency_index'].mean()
print(efficiency)
# Compare yields: irrigated vs rainfed
yield_comparison = df.groupby('has_irrigation')['yield_increase_pct'].mean()
print(yield_comparison)
Research Sources
- FAO 2024: Only 3-6% of cropland under irrigation in SSA
- World Bank 2023: Water use efficiency 30-50% below potential
- IWMI 2023: Small-scale irrigation expanding 2-3% annually
- AfDB 2023: Irrigation potential utilization 20-40%
- AGRA 2023: Solar-powered irrigation growing 15% annually
Author: Electric Sheep Africa