hydropython/africa-ml-evap-review

Systematic review repository for African evaporation and evapotranspiration studies using machine learning, with Excel library, metadata, and analysis scripts # Africa ML Evapotranspiration Review ## Overview This repository contains a curated dataset and workflow for a systematic review of machine learning studies on evaporation and actual evapotranspiration (ETa) in Africa. It includes: - Raw and cleaned publication data - Python scripts for metadata cleaning, deduplication, and tagging - Screening workflow and PRISMA diagram - Zotero-ready CSV exports for reference management ## Structure - `data/` — Excel/CSV datasets of publications - `scripts/` — Python scripts for processing and tagging - `figures/` — Optional figures, e.g., PRISMA flow diagram - `docs/` — Methodology, notes, inclusion/exclusion criteria ## Usage 1. Review the raw Excel dataset in `data/publications_raw.xlsx` 2. Run scripts in `scripts/` to clean and tag publications 3. Export clean dataset for Zotero or review table preparation ## License This project is licensed under the MIT License.