Impact of urbanization on groundwater recharge: altered recharge rates and water cycle dynamics for Arusha, Tanzania
Bibliographic record
Abstract
Abstract The profound effects of urbanization on groundwater recharge rates are investigated by conducting a comprehensive land use and land cover analysis in Arusha, Tanzania, using the WetSpass model. Between 1995 and 2016, the urban area has expanded from 14 to 45% within the study area. This rapid urbanization has resulted in the conversion of forested areas, agricultural land, shrublands, and bare soil into urban zones. Results indicated that under preurban conditions, groundwater recharge from precipitation was ~116 mm/year, which increased to an average of 148 mm/year by 2016. When accounting for anthropogenic factors such as drinking water leakage and on-site sanitation, recharge further increased to 195 mm/year. These supplementary recharge sources, along with reduced evapotranspiration due to land-use changes, contributed to the increase, despite higher surface runoff. These findings underscore the significance of land use and leakage management in urban areas, as well as the spatial variability in groundwater recharge rates across different urban zones, emphasizing the importance of local factors. This study advances the understanding of the intricate relationship between urbanization and groundwater dynamics, and provides insights for future water resource management in rapidly growing urban regions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".