Cargando…

Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain

BACKGROUND: The presence of nitrate is one of the factors limiting the quality of groundwater resources, particularly in arid and semi-arid climates. Therefore, the knowledge about the distribution of nitrate in groundwater and its source has an effective role in protecting health. The study aimed t...

Descripción completa

Detalles Bibliográficos
Autores principales: Kazemi, Elham, Karyab, Hamid, Emamjome, Mohammad-Mehdi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5699197/
https://www.ncbi.nlm.nih.gov/pubmed/29201382
http://dx.doi.org/10.1186/s40201-017-0287-x
_version_ 1783280902390939648
author Kazemi, Elham
Karyab, Hamid
Emamjome, Mohammad-Mehdi
author_facet Kazemi, Elham
Karyab, Hamid
Emamjome, Mohammad-Mehdi
author_sort Kazemi, Elham
collection PubMed
description BACKGROUND: The presence of nitrate is one of the factors limiting the quality of groundwater resources, particularly in arid and semi-arid climates. Therefore, the knowledge about the distribution of nitrate in groundwater and its source has an effective role in protecting health. The study aimed to optimize an interpolation method to predict the nitrate concentration and assessment of aquifer vulnerability in Qazvin plain. METHODS: One hundred sixty-two deep wells in Qazvin plain aquifer were randomly selected and nitrate concentration was analyzed in four different lands including agricultural, residential, steppe and mixed-use areas. Interpolation was done by IDW, Spline, Kriging and National neighbor methods using ArcGIS software. To select the best interpolation method, errors of predicted values were determined by Mean Relative Error (RME) and Root Mean Square Error (RMSE). For analysis of potential vulnerability of aquifer to nitrate pollution due to agricultural activity and sewage leaks, hazard factors and control factors were used for identification of hazard indexes (HI) using IPNOA and IPNOC model. RESULTS: The results showed that in 8.82% and 18.52% of samples in agricultural and residential areas, the detected nitrate was above the acceptable level at 50 mg/L. National neighbor method with the lowest RME and Spline method with the lowest RMSE were provided the most accurate estimates of nitrates in the aquifer. The highest hazard was obtained in agricultural areas (HI = 6.11). Also, the most influential parameters on aquifer vulnerability were mineral fertilizer (HF(f) = 3), organic fertilizers (HF(m) = 3), irrigation systems (CF(i) = 1.04) and tillage patterns (CF(ap) = 1.04). CONCLUSIONS: According to the results, National neighbor with the lowest RME was preferable than the other spatial interpolation methods for prediction of nitrate concentration in the aquifer. This method provided similar spatial distribution maps of nitrate in groundwater and that was an efficient method for assessing water quality. Hazard index as a result of agricultural activities (IPNOA) was ranged from “very low” to “low” which was in accordance with detected and predicted nitrate concentration in the aquifer. In addition he hazard of nitrate contamination from household (IPNOC) was in very low (class 2).
format Online
Article
Text
id pubmed-5699197
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-56991972017-12-01 Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain Kazemi, Elham Karyab, Hamid Emamjome, Mohammad-Mehdi J Environ Health Sci Eng Research Article BACKGROUND: The presence of nitrate is one of the factors limiting the quality of groundwater resources, particularly in arid and semi-arid climates. Therefore, the knowledge about the distribution of nitrate in groundwater and its source has an effective role in protecting health. The study aimed to optimize an interpolation method to predict the nitrate concentration and assessment of aquifer vulnerability in Qazvin plain. METHODS: One hundred sixty-two deep wells in Qazvin plain aquifer were randomly selected and nitrate concentration was analyzed in four different lands including agricultural, residential, steppe and mixed-use areas. Interpolation was done by IDW, Spline, Kriging and National neighbor methods using ArcGIS software. To select the best interpolation method, errors of predicted values were determined by Mean Relative Error (RME) and Root Mean Square Error (RMSE). For analysis of potential vulnerability of aquifer to nitrate pollution due to agricultural activity and sewage leaks, hazard factors and control factors were used for identification of hazard indexes (HI) using IPNOA and IPNOC model. RESULTS: The results showed that in 8.82% and 18.52% of samples in agricultural and residential areas, the detected nitrate was above the acceptable level at 50 mg/L. National neighbor method with the lowest RME and Spline method with the lowest RMSE were provided the most accurate estimates of nitrates in the aquifer. The highest hazard was obtained in agricultural areas (HI = 6.11). Also, the most influential parameters on aquifer vulnerability were mineral fertilizer (HF(f) = 3), organic fertilizers (HF(m) = 3), irrigation systems (CF(i) = 1.04) and tillage patterns (CF(ap) = 1.04). CONCLUSIONS: According to the results, National neighbor with the lowest RME was preferable than the other spatial interpolation methods for prediction of nitrate concentration in the aquifer. This method provided similar spatial distribution maps of nitrate in groundwater and that was an efficient method for assessing water quality. Hazard index as a result of agricultural activities (IPNOA) was ranged from “very low” to “low” which was in accordance with detected and predicted nitrate concentration in the aquifer. In addition he hazard of nitrate contamination from household (IPNOC) was in very low (class 2). BioMed Central 2017-11-21 /pmc/articles/PMC5699197/ /pubmed/29201382 http://dx.doi.org/10.1186/s40201-017-0287-x Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Kazemi, Elham
Karyab, Hamid
Emamjome, Mohammad-Mehdi
Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain
title Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain
title_full Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain
title_fullStr Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain
title_full_unstemmed Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain
title_short Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain
title_sort optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with ipnoa and ipnoc method in qazvin plain
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5699197/
https://www.ncbi.nlm.nih.gov/pubmed/29201382
http://dx.doi.org/10.1186/s40201-017-0287-x
work_keys_str_mv AT kazemielham optimizationofinterpolationmethodfornitratepollutioningroundwaterandassessingvulnerabilitywithipnoaandipnocmethodinqazvinplain
AT karyabhamid optimizationofinterpolationmethodfornitratepollutioningroundwaterandassessingvulnerabilitywithipnoaandipnocmethodinqazvinplain
AT emamjomemohammadmehdi optimizationofinterpolationmethodfornitratepollutioningroundwaterandassessingvulnerabilitywithipnoaandipnocmethodinqazvinplain