ArticleScientific reports2025
New approach to predict wastewater quality for irrigation utilizing integrated indexical approaches and hyperspectral reflectance measurements supported with multivariate analysis.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Groundwater quality assessment for agricultural utilizing indexical and machine learning techniques in Ouled Djellal Aquifer, Southern Algeria.Scientific reports · 2026Article
- Analysis of river water quality in Rourkela Odisha using multiple indices to inform sustainable water management.Scientific reports · 2026Article
- Integrated GIS-machine learning approach to irrigation water quality assessment in coastal aquifers.Scientific reports · 2026Article
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11 authors.
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Abstract
Irrigation water quality is critical to maintaining agricultural output. Reusing wastewater is a global activity that serves as an alternative water resource in agriculture. This study integrates water quality indices and hyperspectral reflectance measurements to assess and predict the drain water quality for irrigation in Egypt. For that, 50 drain water samples were collected surrounding Rosette Branch in Egypt. Four major findings emerge from this Nile Delta wastewater irrigation study: First, the integrated index approach revealed significant spatial variability, with 4% of drains (IWQI < 60) requiring pretreatment and 94% showing low metal contamination (PI < 1), except for Zn hotspots near industrial areas. Second, the newly developed spectral indices such RSI
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