New approach to predict wastewater quality for irrigation utilizing integrated indexical approaches and hyperspectral reflectance measurements supported with multivariate analysis

Mohamed Gad ¹, Reda Abd El Hamed ², Ezzat A El Fadaly ³

¹Hydrogeology, Evaluation of Natural Resources Department, Environmental Studies and Research Institute, University of Sadat City, Minufiya, 32897, Egypt. mohamed.gad@esri.usc.edu.eg.
²Chemistry, Evaluation of Natural Resources Department, Environmental Studies and Research Institute, University of Sadat City, Minufiya, 32897, Egypt.
³Inorganic Chemistry Engineering, Evaluation of Natural Resources Department, Environmental Studies and Research Institute, University of Sadat City, Minufiya, 32897, Egypt.
⁴Department of Environmental Biotechnology, Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Menoufia, 22857, Egypt.
⁵Scientific and Technical Research Center on Arid Regions (CRSTRA), Biskra, 07000, Algeria.
⁶Environmental Research Center (CRE), Annaba, 23000, Algeria.
⁷Institute of Environmental Management, Faculty of Earth Science, University of Miskolc, Miskolc-Egyetemváros, 3515, Hungary. mohamed.hemida@uni-miskolc.hu.
⁸Geology Department, Faculty of Science, Beni-Suef University, Beni-Suef, 65211, Egypt. mohamed.hemida@uni-miskolc.hu.
⁹Applied Science Research Center, Applied Science Private University, Amman, Jordan.
¹⁰Materials Technologies and their applications Lab, Faculty of Science, Beni-Suef University, Beni Suef city, Egypt.
¹¹Department of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. BOX 84428, Riyadh, 11671, Saudi Arabia.
¹²Department of Biology, College of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, 11623, Saudi Arabia.
¹³Agricultural Engineering, Evaluation of Natural Resources Department, Environmental Studies and Research Institute, University of Sadat City, Minufiya, 32897, Egypt.

⁰Hydrogeology, Evaluation of Natural Resources Department, Environmental Studies and Research Institute, University of Sadat City, Minufiya, 32897, Egypt. mohamed.gad@esri.usc.edu.eg.

Scientific Reports +

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May 12, 2025

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Summary

This study integrates water quality indices and hyperspectral data to assess wastewater irrigation quality in Egypt. The findings show high accuracy in predicting water quality parameters using spectral indices and PLSR models, enabling efficient agricultural water management.

Area Of Science

Environmental Science
Agricultural Engineering
Remote Sensing

Background

Reusing wastewater is crucial for agriculture, especially in water-scarce regions.
Assessing irrigation water quality is vital for maintaining agricultural productivity.
Hyperspectral reflectance offers a promising tool for water quality assessment.

Purpose Of The Study

To integrate water quality indices and hyperspectral reflectance for assessing drain water quality in Egypt.
To develop and validate models for predicting key water quality parameters using spectral data.
To evaluate the applicability of the developed methodology for wastewater irrigation schemes.

Main Methods

Collection of 50 drain water samples from the Nile Delta region.
Analysis of water quality parameters and calculation of indices (IWQI, PI).
Measurement of hyperspectral reflectance and development of spectral indices (RSI).
Optimization of Partial Least Squares Regression (PLSR) models for water quality prediction.
Hydrochemical analysis using the Gibbs ratio.

Main Results

Significant spatial variability in water quality was observed, with some drains requiring pretreatment and low overall metal contamination.
Developed spectral indices (RSI) showed strong correlations with Total Chlorophyll (R²=0.73) and Irrigation Water Quality Index (IWQI) (R²=0.67).
Optimized PLSR models accurately estimated Total Chlorophyll (R²=0.87 calibration, R²=0.77 validation) and Biochemical Oxygen Demand (BOD) (R²=0.96 calibration, R²=0.81 validation).
Hydrochemical analysis indicated evaporation dominance in 72% of samples, leading to a Ca-Mg-SO4 facies prevalence.
The methodology demonstrated 89% cross-region accuracy in preliminary tests.

Conclusions

The integrated approach combining water quality indices and hyperspectral data provides an accurate method for assessing wastewater irrigation quality.
The developed spectral indices and PLSR models offer reliable tools for predicting water quality parameters, supporting agricultural water management.
The methodology shows broad applicability for wastewater irrigation schemes, with potential for farmer-adoptable spectral sensors and targeted filtration.

Keywords:

Hydrogeochemistry Multivariate analysis Nile Delta of Egypt PLSR model Wastewater reuse Water quality criteria