Water resource management research in Benin: a systematic review
Bibliographic record
Abstract
Benin has been the subject of numerous investigations in the complex realm of water resource management, encompassing hydrological, engineering, economic, ecological, and sociological facets. However, noticeable gaps exist, warranting a comprehensive review of the existing knowledge. This study offers a systematic review on the trends in water management research within Benin. Scholarly papers were carefully selected from reputable academic databases, including Web of Science, WorldCat, Google Scholar, the Directory of Open Access Journals (DOAJ), Science Direct, and Scopus. The selection criteria were stringent, focusing on English keywords, journal articles, and conference papers centered on water management or its associated challenges in the Benin context. The selection process entailed a two-phase screening protocol, commencing with an initial assessment based on titles, followed by subsequent screening based on abstracts and keywords. The chosen studies then underwent a thorough bibliometric analysis. The findings of this review reveal a noticeable surge in research activity related to water resource management in Benin in recent decades. These studies predominantly concentrate on rural areas. The breadth of research topics covers a wide spectrum, including water pricing reform, water policy formulation, water-related conflicts, the application of integrated water resource management, agro-dam management, challenges inherent in water resource management, water quality assessment, agricultural water usage, assessment of water availability, utilization of Geographic Information System (GIS), and the development of basin information system platforms. A majority of the examined articles emphasize water management and water availability. This review underscores the growing interest within the scientific community in exploring water resource management issues in rural Benin. Ineffective water management in Benin can be attributed to various factors, including inadequate financial support, deficient coordination among stakeholders in the water sector, a lack of transparency, suboptimal management of hydraulic infrastructure, inadequate dissemination and implementation of established legal and institutional frameworks, overlapping roles among actors involved in water resource management, and a notable scarcity of data. These findings highlight the urgent need for further research initiatives and policy interventions in these domains, with the overarching goal of enhancing the state of water management in Benin.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.024 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".