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Record W4392291599 · doi:10.18280/ijdne.190113

Evaluation of Rainwater Harvesting Systems for Drinking Water Quality in Iraq

2024· article· en· W4392291599 on OpenAlexvenueno aff
Ahmed S. Al-Fahal, Ahmed Ahmed, Akram K. Mohammed, Wesam S. Mohammed-Ali

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2024
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsRainwater harvestingEnvironmental scienceWater qualityWater resource managementEnvironmental engineeringQuality (philosophy)Environmental planningEngineeringEcologyBiology

Abstract

fetched live from OpenAlex

Rainwater harvesting is one of the solutions to avoid water loss in the future because it provides sufficient supply and is more economical when compared to other conventional types.The shortage of water supply become a concern due to the growing population as well as the environmental pollution.Rainwater harvesting is seen as the most accessible and easy-to-use resource for drinking and other domestic uses.The current study consists of two main parts; the first part is a hydrological study that includes studying the possibility of benefiting from the amount of rainfall and developing future plans to benefit from this collected water and how to manage it through the implementation of water harvesting technology by collecting rainwater from the roofs to provide part of the population's water needs instead of its wastage and loss.The second part is an environmental study that includes a study of evaluating the quality of water collected through the harvesting of rainwater technology and comparing it with World Health Organization (WHO) specifications for water-drinking purposes.Rainwater samples were analyzed in the environmental laboratory to compare with (WHO) World Health Organization specifications.Samples were obtained at, (28.3, 84.9, and 33.96) liters, respectively, where the average is (49.05) liters.The depths of rain were recorded in the measuring cylinder (5, 14.6, and 9) mm, respectively, where the average is (9.53) mm; the measurement is a negative indicator compared to the expected (26.15) mm.The variables identified (total hardness, calcium, nitrates, sulfates, chlorides, and dissolved substances).Furthermore, 33.33, 0.80, 35.67, 8.83, and 95.0) mg/L, respectively, while the pH (7.97) and conductivity (µs/cm 170.13) were within the specification and the Temperature (23.60℃) and turbidity 10.47 NTU)) It was not in conformity with the specification, as the specification refers to placing in heat (20℃) and turbidity (5 NTU).The current study discloses that the overall quality of water is quite satisfactory as per WHO specifications.The harvesting of rainwater system offers an adequate amount of water and energy savings through lower consumption.Furthermore, considering the cost of fixing and maintenance expenditures, the system is effective and economical.This current study provides the environmental benefits of rainwater harvesting and identifies its probable boundaries and its role in developing a more sustainable water resource management under climate change.This study contributes to improving adaptability strategies of rainwater harvesting for sustainable water resources management under changing climate.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.583
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.290
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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