Assessing Groundwater Level Declination in Dhaka City and Identifying Adaptation Options for Sustainable Water Supply
Bibliographic record
Abstract
Dhaka city, having a population of about 18 million, depends heavily on groundwater as a source of quality water. However, the city is encountering a rapid depletion of groundwater, and its groundwater-based water supply is at risk of failure. This study was carried out to analyze the groundwater depletion scenarios occurring from 1970 to 2019 in the city and to find suitable options to sustain its water supply. The trends in groundwater levels (GWLs) were quantified by the non-parametric Sen’s slope and their significances were assessed by the modified Mann-Kendall test. Contour maps of GWL were generated to develop the contemporary GWL scenario in the city. Key informant interviews (KIIs) with the Dhaka Water Supply and Sewerage Authority (DWASA) officials, groundwater experts and researchers, in addition to semi-structured interviews with the DWASA consumers were conducted to assess current adaptation practices and to develop potential adaptation options. The effectiveness of the options was assessed by strengths, weaknesses, opportunities and threats (SWOT) analysis and the options were ranked through a normalization process of the weights given by the KIIs for future adaptabilities. The GWLs were found to be decreasing all over the city, varying from 0.6–2.4 m/year. The contour maps demonstrated that the groundwater of the central area had depleted more than the peripheral areas. The locations vulnerable to severe groundwater depletion were identified to be the Khilgaon, Sobujbagh, Motijheel, Dhanmondi, and Sutrapur areas and some parts of the Cantonment and Mirpur areas. Potential options identified were adopting more surface water treatment plants, rainwater harvesting, implementing a block tariff system, reducing non-revenue water, metering water consumption, and promoting public awareness. Spatially-varying adaptation strategies were also suggested for different zones. Some measures adopted by DWASA were not supported by the respondents.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".