Evaluation of groundwater vulnerability to nitrate in shallow aquifer using multi-layer fuzzy inference system within GIS environment

Pathak, Dhundi Raj; Bhandary, Netra Prakash

doi:10.1016/j.gsd.2020.100470

Cited by 25 publications

(11 citation statements)

References 25 publications

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“…On the one hand, the electrical conductivity (EC), as one of the electrical properties of rocks, and the chloride ions (Cl -) that comes from rock weathering and extensive use of fertilizers, fully reflect the mineralogical quality of the water (Perrin et al, 2008). On the other hand, nitrate (NO 3 -) concentration is among the chief indices of water pollution as its presence in large concentrations presents ecological and human health risks (Pathak & Bhandary, 2020).…”

Section: Evaluation Of the Overall Quality Of Groundwatermentioning

confidence: 99%

Study of Hydrochemical Characteristics in the Middle Moulouya Basin of Morocco

Saadi,

Dimane,

Nouayti

et al. 2024

Ecol. Eng. Environ. Technol.

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This study analyzes the effects of dry land salinity, climate severity, and pollution on groundwater quality in the Middle Moulouya basin. Our research provides insights into certain pollutants and their sources and discusses the impact of saline soil and dry weather. A comprehensive understanding of these factors is essential for managing water resources and promoting sustainable resource use in the area. In fact, the use of a database relating to the major elements, viz. potassium (K + ), calcium (Ca 2+ ), sodium (Na 2+ ), magnesium (Mg 2+ ), bicarbonates (HCO 3 -), sulfates (SO 4 2-, nitrates (NO 3 -), chlorides (Cl -) has proved to be effective to assess the hydrochemical features of groundwaters and their suitability for both aims (i.e., irrigation and drinking). The Middle Moulouya basin's subterranean water is slightly acidic to basic, with a pH range of 6.8 to 7.66 and mild to brackish water at specific sites. Furthermore, in line with the hydrochemistry diagrams, groundwater can be classified into three main types: Ca-Cl, Ca-HCO 3 , and Ca-Mg-Cl type. Moreover, the results pertaining to the overall quality of groundwater regarding Moroccan control standards guidelines indicate that: (i) 32.43% of the groundwater samples are of excellent quality, (ii) 24.32% of the collected water points are of good quality, (iii) 32.43% have medium quality, (iiii) and only 10.82% are of poor and very poor quality (i.e., 5.41% for each class). Finally, based on the Wilcox method, a significant percentage of groundwater sites are suitable for farming.

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Section: Evaluation Of the Overall Quality Of Groundwatermentioning

confidence: 99%

Study of Hydrochemical Characteristics in the Middle Moulouya Basin of Morocco

Saadi,

Dimane,

Nouayti

et al. 2024

Ecol. Eng. Environ. Technol.

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“…Numerous articles have been published using fuzzy methods (Huicheng et al 1999;Afshar et al 2007;Nobre et al 2007;Rezaei et al 2013;Jafari and Nikoo 2019;Pathak and Bhandary 2020;Saranya and Saravanan 2021). Some of the fuzzy logic applications have also been applied to investigations using multi-criteria decision-making methods such as AHP (Sener and Davraz 2013;Yang et al 2017;Mallik et al 2021).…”

Section: Use Of Fuzzy Logic To Refine Zonal Boundariesmentioning

confidence: 99%

Assessment of Alluvial Aquifer Intrinsic Vulnerability by a Generic Drastic Model; A Discussion on Data Adequacy and Pragmatic Results

Taheri¹,

Missimer²,

Maleki³

et al. 2021

Preprint

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DRASTIC is a model that is commonly used to assess vulnerability to groundwater contamination at the landscape scale. When sparse data are available to populate the layers of the model, it can be difficult to ascertain the true usefulness of the model produced map. In this research an alluvial aquifer, the Sahneh aquifer in Kermanshah province of western Iran, was mapped using the generic DRASTIC model. The data available for populating the model layers were generally sparse. The model was validated using a nitrate concentration map constructed from well water measurements within the DRASTIC map area. A Receiver Operating Curve (ROC) analysis was conducted by placing 500 random points in the DRASTIC generated map compared to the nitrate concentration map. The area under the curve was compared and yielded a value of 0.72 or 72% concordance, which means it has good validity. This investigation demonstrates that a generic DRASTIC model can yield acceptable results without modification or increasing its complexity. If the ROC analysis had yielded a value <50%, then the DRASTIC would have been considered to not be useful. A common mistake in the use of DRASTIC is to modify the method to greatly increase its complexity, which may actually decrease, not increase the resultant model usefulness.

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“…CRC is critical for preventing soil erosion and enhancing soil fertility due to its rich nitrogen, potassium, and phosphorus contents 3 , 4 . CRC has a significant impact on agriculture production and can influence biological production and biodiversity by increasing vegetation density and soil fertility 5 , 6 . It can also enhance the speed of enzymatic activities, decrease water consumption, lower soil temperature, and reduce air pollution and harmful gas emissions 7 – 9 .…”

Section: Introductionmentioning

confidence: 99%

Monitoring the impacts of crop residue cover on agricultural productivity and soil chemical and physical characteristics

Kazemi Garajeh,

Hassangholizadeh,

Bakhshi Lomer

et al. 2023

Sci Rep

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To the best of our knowledge, the impacts of crop residue cover (CRC) on agricultural productivity and soil fertility have not been studied by previous researchers. In this regard, this study aims to apply an integrated approach of remote sensing and geospatial analysis to detect CRC and monitor the effects of CRC on agricultural productivity, as well as soil chemical and physical characteristics. To achieve this, a series of Landsat images and 275 ground control points (GCPs) collected from the study areas for the years 2013, 2015, and 2021 were used. A convolutional neural network (CNN), a class of artificial neural network has commonly applied to analyze visual imagery, was employed in this study for CRC detection in two classes (Not-CRC and CRC) for the years 2013, 2015, and 2021. To assess the effects of CRC, the Normalized Difference Vegetation Index (NDVI) was applied to Landsat image series for the years 2015 (22 images), 2019 (20 images), and 2022 (23 images). Furthermore, this study evaluates the impacts of CRC on soil fertility based on collected field observation data. The results show a high performance (Accuracy of > 0.95) of the CNN for CRC detection and mapping. The findings also reveal positive effects of CRC on agricultural productivity, indicating an increase in vegetation density by about 0.1909 and 0.1377 for study areas 1 and 2, respectively, from 2015 to 2022. The results also indicate an increase in soil chemical and physical characteristics, including EC, PH, Na, Mg, HCO3, K, silt, sand, and clay from 2015 to 2022, based on physical examination. In general, the findings underscore that the value of an integrated approach of remote sensing and geospatial analysis for detecting CRC and monitoring its impacts on agricultural productivity and soil fertility. This research can offer valuable insight to researchers and decision-makers in the field of soil science, land management and agriculture.

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Evaluation of groundwater vulnerability to nitrate in shallow aquifer using multi-layer fuzzy inference system within GIS environment

Cited by 25 publications

References 25 publications

Study of Hydrochemical Characteristics in the Middle Moulouya Basin of Morocco

Study of Hydrochemical Characteristics in the Middle Moulouya Basin of Morocco

Assessment of Alluvial Aquifer Intrinsic Vulnerability by a Generic Drastic Model; A Discussion on Data Adequacy and Pragmatic Results

Monitoring the impacts of crop residue cover on agricultural productivity and soil chemical and physical characteristics

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