Corpus-Based Semantic Analysis of al-Māʾ in the Qur’an: Islamic Ecological Contexts

This study aims to analyze the use of the term al-Mā’ in the Qur’an through a digital corpus-based approach by mapping its distribution, contextual usage, and semantic variations as a basis for interpretation from the perspective of Islamic ecology. The study employs a corpus-based qualitative descriptive approach using the Quranic Arabic Corpus (QAC) as the data source. Data identification was conducted through a search for the stem ماء, yielding 59 tokens distributed across 57 verses and 39 surahs. The analysis consisted of concordance analysis, frequency and distribution analysis, and token-level semantic categorization. The results show that the use of al-Mā’ can be classified into seven categories: Life and Ecological Growth (28.8%), Provision and Sustenance (25.4%), Punishment and Destruction (16.9%), Creation and Biological Origin (10.2%), Figurative/Symbolic (8.5%), Purification (6.8%), and Divine Sign and Power (3.4%). These findings indicate that the meaning of al-Mā’ is not limited to water as a material entity but is also associated with life, environmental continuity, provision, purification, creation, and symbolism. The corpus-based approach provides a more systematic empirical basis for understanding the contextual diversity of al-Mā’ in the Qur’an and supports an ecological reading from an Islamic perspective.