Abstract
The Mitidja alluvial aquifer in northern Algeria is an important drinking, industrial, and agricultural water source. Unfortunately, nitrate contamination has led to a decrease in water quality in several areas that benefit from this source. This study employed geographic information system and statistical modeling methods to evaluate the origin, evolution, and spatiotemporal distribution of groundwater nitrate in the aquifer and investigate the influence of different hydrogeological parameters on its extent. Control points were established across various regions of the Mitidja groundwater aquifer. A total of 1185 nitrate concentrations were measured at 316 sampling points between June 1985 and May 2015. The results showed variable rates, with the 50 mg/L nitrate consumption limit exceeded in 423 samples at 84 observation points. Statistical modeling showed that nitrate concentration was related to groundwater characteristics (aquifer nature, water table depth, and thickness of saturated zone) and human activities (land use, agricultural practices, and population density). Analysis of the nitrate distribution showed that the eastern and western watersheds experienced the greatest contamination. The significant nitrate concentrations in the eastern area were correlated with urban contamination, including uncontrolled urbanization, high population density, and industrial activity, while the primary origin of nitrate in the western area was correlated with agricultural activity, particularly fertilizers. The findings of this study can aid local government and water agencies in the development and implementation of regulations to help mitigate increases in nitrate concentrations.
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Data availability
The dataset used during the current study are available from the corresponding author on reasonable request.
Change history
17 November 2021
A Correction to this paper has been published: https://doi.org/10.1007/s10661-021-09472-6
Abbreviations
- ABH:
-
Agency of Hydrographical Basins
- ANRH:
-
Agence Nationale des Ressources Hydrauliques (National Water Resources Agency)
- DEA:
-
Direction d’Environnement d’Alger (Environmental Direction of Algiers)
- DEAH:
-
Direction des Études et Aménagement Hydrauliques (Directorate of Hydraulic Studies and Facilities)
- DEMRH:
-
Direction des Études de Milieu et de la Recherche Hydraulique (Direction of Environmental Studies and Hydraulic Research)
- GIS:
-
Geographic information system
- GPI:
-
Grand Périmètre Irrigué (Large irrigated perimeter)
- INSID:
-
Institut National du Sol, Irrigation et du Drainage (National Institute for Soil, Irrigation and Drainage)
- MADR:
-
Ministère d’Agriculture et de Développement Rural (Agricultural and Rural Development Ministry)
- MCL:
-
Maximum concentration level (mg/L)
- ONID:
-
Office National d’Irrigation et Drainage (National Office of Irrigation and Drainage)
- SEAAL:
-
Société des Eaux et d’Assainissement d’Alger (Algiers Water and Sanitation Company)
- UAS:
-
Useful agricultural surface
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Acknowledgements
We thank El Hadi BEZINI and Ahmed BELAOUNI from the Biological Department of Djelfa University for their feeding support on statistical modeling. We also thank Rabah Talabolma from the National Office of Irrigation and Drainage (ONID) and Omar Adel Lagoun, engineer in geography, for their support for GIS modeling and mapping. Data used in this paper were collected by many departments. We would therefore like to thank the following: Larbi Arzeki from Water and Sanitation Society of Algiers (SEAAL); Mohamed Djeni and Bahia Bellahcen from Agricultural Service Direction of Blida and Algiers; Ouardi and Ahmed Merhoune from Water Resources Direction of Algiers and Blida; Belaidi and Farida Khemissi from National Water Resources Agency of Blida (ANRH); Myassa Stof, Mohamed Kessira, Omar Tizerarine, and Arbi Kiousse from Agricultural and Rural Development Ministry (MADR); Moussa Yaalaoui and Fadeli from Water Resources Ministry (MRE); and Zahida and Djamel Zareb from National Institute for Soil, Irrigation and Drainage (INSID).
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Appendices
Appendix 1. Kolmogorov–Smirnov’s normality test and Mann–Whitney U test to examine the effects of aquifer nature (unconfined and confined) on groundwater nitrate concentration
Aquifer nature | Sampling points | Samples | Kolmogorov–Smirnov’s normality test | Mann–Whitney U test | ||
---|---|---|---|---|---|---|
p value | Decision | p value | Mean (mg/L) | |||
Unconfined | 235 | 1037 | < 0.0001 | Non-Normal | < 0.0001 | 40,28b |
Confined | 81 | 148 | < 0.0001 | Non-Normal | 24,18a |
Appendix 2. Kruskal–Wallis test to examine the effects of saturated zone thickness (0–20 m, 20–120 m, and 120–140 m) on groundwater nitrate concentration. A post hoc Conover-Iman test with Bonferroni correction was used to determine the significance level (p = 0.0167). Significant differences (p ≤ 0.0167) indicated by different letters
Saturated zone class (m) | Samples | Kolmogorov–Smirnov’s normality test | Kruskal–Wallis’s test | Conover-Iman’s test | ||
---|---|---|---|---|---|---|
p value | Distribution | p value | Average rank (mg/L) | Groups | ||
0–20 | 51 | 0.4060 | Normal | < 0.0001 | 334,03 | c |
20–120 | 304 | 0.0092 | Non-normal | 222,29 | b | |
120–236 | 89 | 0.0552 | Non-normal | 159,31 | a |
Appendix 3. Kruskal–Wallis test to examine the effects of water table depth (< 5 m, 5–30 m, and > 30 m) on groundwater nitrate concentration. A post hoc Conover-Iman’s test with Bonferroni correction was used to determine the significance level (p = 0.0167). Significant differences (p ≤ 0.0167) indicated by different letters
Water tables class | Sampling points | Samples | Kolmogorov–Smirnov’s normality test | Kruskal–Wallis’s test | Conover-Iman’s test | ||
---|---|---|---|---|---|---|---|
p value | Distribution | p value | Average rank (mg/L) | Groups | |||
< 5 | 5 | 41 | 0.2361 | Normal | < 0.0001 | 345,06 | c |
5–30 | 41 | 203 | < 0.0001 | Non-normal | 260,50 | b | |
> 30 | 60 | 206 | < 0.0001 | Non-normal | 167,22 | a |
Appendix 4. Normality on distribution test and Kruskal–Wallis test to examine the effects of land use (residential, agricultural, and other) on groundwater nitrate concentration. A post hoc Conover-Iman’s test with Bonferroni correction was used to determine the significance level (p = 0.0167). Significant differences (p ≤ 0.0167) indicated by different letters
Land | Observations | Frequency > MCL (%) | Kolmogorov–Smirnov’s normality test | Kruskal–Wallis’s test | Conover-Iman test | ||
---|---|---|---|---|---|---|---|
p value | Decision | p value | Average rank (mg/L) | Groups | |||
Residential | 70 | 41.43 | 0.0459 | Non-normal | 0.0024 | 163,41 | b |
Agricultural | 246 | 32.93 | 0.0051 | Non-normal | 167,65 | b | |
Other | 10 | 10.00 | 0.2605 | Normal | 62,05 | a |
Appendix 5. Kruskal–Wallis test to examine the difference between nitrate concentrations unregistered at a catchment scale. A post hoc Conover-Iman test with Bonferroni correction was used to determine significant differences (p ≤ 0.005), indicated by different letters
Watershed | Sampling point | Samples | Rate > MCL (%) | Kolmogorov–Smirnov’s normality test | Kruskal–Wallis test | Conover-Iman test | ||
---|---|---|---|---|---|---|---|---|
p value | Decision | p value | Average rank | Groups | ||||
Coastal Cap Matifou | 73 | 345 | 53.62 | 0.0006 | Non-normal | < 0.0001 | 748,17 | c |
El Harrach | 113 | 335 | 32.54 | < 0.0001 | Non-normal | 526,78 | b | |
Mazafran | 79 | 208 | 13.46 | < 0.0001 | Non-normal | 435,75 | a | |
Oued Chiffa | 31 | 139 | 17.99 | 0.1774 | Normal | 520,98 | ab | |
Oued Djer Bouroumi | 20 | 158 | 48.10 | < 0.0001 | Non-normal | 664,95 | c |
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LAGOUN, A.M., BOUZID-LAGHA, S., BENDJABALLAH-LALAOUI, N. et al. Geographic information system–based approach and statistical modeling for assessing nitrate distribution in the Mitidja aquifer, Northern Algeria. Environ Monit Assess 193, 631 (2021). https://doi.org/10.1007/s10661-021-09427-x
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DOI: https://doi.org/10.1007/s10661-021-09427-x