Assessment of Groundwater on the Basis of the CCME WQI Model (on the Example of Amudarya District)

Rajabova Nilufar Davlatboy kizi*, Sherimbetov Vafabay Khalilullaevich and Md Galal Uddin

International Research Journal of Agricultural Science and Soil Science

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Research Article - International Research Journal of Agricultural Science and Soil Science ( 2025) Volume 14, Issue 1

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Assessment of Groundwater on the Basis of the CCME WQI Model (on the Example of Amudarya District)

Rajabova Nilufar Davlatboy kizi¹^*, Sherimbetov Vafabay Khalilullaevich¹ and Md Galal Uddin²

¹Department of Ecology, National University of Uzbekistan, Tashkent,, Uzbekistan
²Department of Ecology, University of Galway, Galway, Ireland

^*Corresponding Author:
Rajabova Nilufar Davlatboy kizi, Department of Ecology, National University of Uzbekistan, Tashkent,, Uzbekistan, Email: nilufarrajabova171@gmail.com

Received: 02-Mar-2024, Manuscript No. IRJAS-25-128714; Editor assigned: 05-Mar-2024, Pre QC No. IRJAS-25-128714 (PQ); Reviewed: 19-Mar-2024, QC No. IRJAS-25-128714; Revised: 17-Mar-2025, Manuscript No. IRJAS-25-128714 (R); Published: 24-Mar-2025, DOI: 10.14303/2276-6502.2025.34

Abstract

This experimentation is directed at determining the ecological status of groundwater (object) formed in Amudarya district of the Republic of Karakalpakstan, by developing a quality index with the CCME WQI model, to evaluate the object (the quality index was analyzed by months). In this small-scale ecosystem, agricultural activities based on a slightly wrong strategy and low-level industrial enterprises exist, which is one of the main factors affecting the decline of groundwater quality in this area.

Keywords

CCMEWQI, Groundwater, Excellent, Good, Fair, Marginal, Poor, Ecological factors

Introduction

Regular monitoring and evaluation is necessary to maintain a "good" status of groundwater quality. Dr. Galal Uddin, a researcher at the University of Galway, said Water Quality Index (WQI) models are one of the most common and convenient ways to assess water quality (Chabuk A, et al., 2020). The WQI consists of five components, the indicator selection technique is one of the most important components and wrongly selected indicators lead to significant uncertainty (Oseke FI, et al., 2021).

Maintaining a positive status of groundwater quality is an important issue worldwide as water quality gradually deteriorates due to various factors, including natural, anthropogenic or a combination of both (Pham H, et al., 2017). Groundwater is one of the important issues in maintaining the natural state of ecosystems (Ram A, et al., 2021). Recently, many studies have shown that the water environment is decreasing day by day due to water pollution (Uddin MG, et al., 2017). The use of WQI models in water quality monitoring for the purpose of water resources management is one of the most convenient approaches (Uddin MG, et al., 2022).

A number of tools and methods are used in many scientific literatures to monitor and evaluate water quality (Uddin MG et al., 2024). WQI is a widely used, simple mathematical model that converts a wide range of water quality indicators into a unitless numerical expression (Venkatramanan S, et al., 2016). Its use for management and monitoring purposes is growing rapidly. To date, more than thirty WQI models have been developed by organizations and researchers of different countries of the world. Currently, many studies are using state-of-the-art innovative methods such as artificial intelligence and several other algorithmic approaches to optimize model uncertainty in WQI model development.

Materials and Methods

The CCME WQI is based on a formula developed by the Council of Environment Canada and the British Columbia Ministry of Environment, Lands and Parks and modified by Alberta Environment. The index is based on a combination of three factors: Scope, Frequency and the Amplitude. After determining the parameters that provide information about the object, F1, F2 and F3, which make up the index, are calculated (Tables 1-3).

WQI range	Ranking of water quality	Remarks
95-100	Excellent	Water quality is protected with a virtual absence of threat or impairment; conditions very close to natural or pristine levels.
80-94	Good	Water quality is protected with only a minor degree of threat or impairment; conditions rarely depart from natural or desirable levels.
65-79	Fair	Water quality is usually protected but occasionally threatened or impaired; conditions sometimes depart from natural or desirable levels.
45-64	Marginal	Water quality is frequently threatened or impaired; conditions often depart from natural or desirable levels.
0-44	Poor	Water quality is almost always threatened or impaired; conditions usually depart from natural or desirable levels.

Table 1. Classification of water quality based on CCME-WQI values.

Calculate the index:

Step 1. Calculating the scope value (F1).

Results and Discussions

		Months
Parameters	BIS standards	March	April	May
PH	6.5	8	7.9	7.9
TDS	500	1730	1730	1480
Cl-	200	276.5	354.2	327.6
SO4-2	200	264	230	177.6
NO3-	45	10.4	14.2	0

Table 2. The condition of groundwater in Amudarya district (2022).

		Months
Parameters	BIS standards	March	April	May
PH	6.5	7.7	7.7	8
TDS	500	1 200	1 700	1 280
Cl-	200	221	380	308.6
SO4-2	200	271	334	0
NO3-	45	10.2	10.7	9.9

Table 3. The condition of groundwater in Amudarya district (2021).

Conclusion

Based on the CCME WQI model, the analysis of 5 parameters data of the object showed negative results. Appropriate measures should be developed to improve the ecological status of groundwater. For example, it is necessary to use agroecosystems in agriculture wisely, to grow green plants that improve the soil fertility and of course to develop monthly and annual indices of groundwater in this area.

References

Chabuk A, Al-Madhlom Q, Al-Maliki A, Al-Ansari N, Hussain HM, et al (2020). Water quality assessment along Tigris River (Iraq) using Water Quality Index (WQI) and GIS software. Arab J Geosci. 13:1-23.
[Crossref] [Google Scholar]
Oseke FI, Anornu GK, Adjei KA, Eduvie MO (2021). Assessment of water quality using GIS techniques and water quality index in reservoirs affected by water diversion. Water-Energy Nexus. 4:25-34.
[Crossref] [Google Scholar]
Pham H, Rahman MM, Nguyen NC, Le Vo P, Le van T, et al (2017). Assessment of surface water quality using the water quality index and multivariate statistical techniques-A case study: The upper part of Dong Nai river basin, Vietnam. J Water Sustain. 7(4):225-245.
[Google Scholar]
Ram A, Tiwari SK, Pandey HK, Chaurasia AK, Singh S, et al (2021). Groundwater quality assessment using Water Quality Index (WQI) under GIS framework. Appl Water Sci. 11:1-20.
[Crossref] [Google Scholar]
Uddin MG, Moniruzzaman M, Khan M (2017). Evaluation of groundwater quality using CCME water quality index in the Rooppur Nuclear Power Plant Area, Ishwardi, Pabna, Bangladesh. Am J Environ Prot. 5(2):33-43.
[Google Scholar]
Uddin MG, Nash S, Rahman A, Olbert AI (2022). A comprehensive method for improvement of Water Quality Index (WQI) models for coastal water quality assessment. Water Res. 219:118532.
[Crossref] [Google Scholar] [PubMed]
Uddin MG, Nash S, Rahman A, Dabrowski T, Olbert AI (2024). Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches. Environ Res. 242:117755.
[Crossref] [Google Scholar] [PubMed]
Venkatramanan S, Chung SY, Ramkumar T, Rajesh R, Gnanachandrasamy G (2016). Assessment of groundwater quality using GIS and CCME WQI techniques: A case study of Thiruthuraipoondi city in Cauvery deltaic region, Tamil Nadu, India. Desal Water Treat. 57(26):12058-12073.
[Crossref] [Google Scholar]