Groundwater suitability analysis for drinking using GIS based fuzzy logic

Mallik, Santanu; Mishra, Umesh; Paul, Niladri

doi:10.1016/j.ecolind.2020.107179

Cited by 37 publications

(7 citation statements)

References 37 publications

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“…Due to the ability of the fuzzy method to reduce uncertainties and its other advantages, some other researchers have tried to combine or compare the traditional methods with the fuzzy inference system so that a group of researchers have used both the drinking water quality index and the fuzzy inference system to compare or combine the results and have better and acceptable results. They have achieved more than the previous obedience [20][21][22][23][24][25]5].…”

Section: Introdoctionmentioning

confidence: 90%

Evaluation and zonation of groundwater quality in terms of drinkability, using Fuzzy Logic and Schoeller deterministic method. (Northern Dezful - Andimeshk Plain)

Shakour,

Chitsazan,

Mirzaee

2023

Preprint

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In the Northern Dezful-Andimeshk plain, the primary source of drinking water is groundwater, which has got low quality in some places. Thus, groundwater quality in this area needs an accurate evaluation. In this research, fuzzy and Schoeller deterministic method assessed the Northern Dezful-Andimeshk plain drinking water, and the results of both methods were used to zone and compare the drinking quality of the plain groundwater in the Arc GIS environment. The deterministic method classifies drinking water quality from good to bad. According to this method, 56.81% of the total area of the plain has good quality, 20.83% of the total area has acceptable, 18.77% of the total area has inappropriate quality, and 3.57% of the total area has bad quality. However, in the fuzzy method, groundwater in 21.6% of the total area of the plain with a confidence percentage of 70–81% is desirable, in 75.23% of the total area of the plain with a confidence percentage of 32–70% is acceptable, and 3.69% of the total area of the plain with drinking confidence of 20–22% is nonacceptable. The results showed that the fuzzy method is better than Schoeller deterministic method because it reduces uncertainties and increases accuracy in the evaluation and increases flexibility in the threshold limits of water quality parameters. and provides a quantitative and qualitative assessment of drinking water, also the zoning map obtained from this method is more compatible with environmental and pollution realities.

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Section: Introdoctionmentioning

confidence: 90%

Evaluation and zonation of groundwater quality in terms of drinkability, using Fuzzy Logic and Schoeller deterministic method. (Northern Dezful - Andimeshk Plain)

Shakour,

Chitsazan,

Mirzaee

2023

Preprint

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“…After generating the fuzzy membership functions, the fuzzy overlay analysis is performed using ArcMap 10.8. Recent studies have utilized fuzzy overlay analysis for different applications (Hasanloo et al,2019;Mallik et al, 2021). Using the fuzzy overlay tool in ArcMap, a multicriteria overlay analysis can examine the likelihood that a phenomenon belongs to many sets.…”

Section: Flood Exposure Indexmentioning

confidence: 99%

Geo-Spatial Analysis of Built-Environment Exposure to Flooding: Iowa Case Study

Alabbad¹,

Demir²

2024

Preprint

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Flooding is the most frequent type of natural disaster, inducing devastating damages at large and small spatial scales. Flood exposure analysis is a critical part of flood risk assessment. While most studies analyze the exposure elements separately, it is crucial to perform a multi-parameter exposure analysis and consider different types of flood zones to gain a comprehensive understanding of the impact and make informed mitigation decisions. This research analyzes the population, properties, and road networks exposed to the 100, 200, and 500-year flood events at the county level in the State of Iowa using geospatial analytics. We also proposed a flood exposure index at the county level using fuzzy overlay analysis to help find the most impacted county. During flooding, results indicate that the county-level percentage of displaced population, impacted properties, and road length can reach up to 46%, 41%, and 40%, respectively. We found that the most exposed buildings and roads are laid in residential areas. Also, 25% of the counties are designated as very high-exposure areas. This study can help many stakeholders identify vulnerable areas and ensure equitable distribution of investments and resources toward flood mitigation projects.

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“…To evaluate the accuracy and effectiveness of OK models, the study utilized the crossvalidation technique, considering predictive errors such as mean error (ME), root mean square error (RMSE), mean standardized error (MSE), root mean square standardized error (RMSSE), and average standard error (ASE). Model selection was determined based on the following criteria: the lowest ME and MSE (approaching zero), identical RMSE and ASE values, and an RMSSE value close to one, indicating the most suitable model (Mallik et al, 2020;Sebei et al, 2020). These errors' mathematical expressions are as follows (Eqs 2-4):…”

Section: Kriging Interpolation For Studied Variablesmentioning

confidence: 99%

Geospatial evaluation and bio-remediation of heavy metal-contaminated soils in arid zones

Mohamed,

Jalhoum,

Hendawy

et al. 2024

Front. Environ. Sci.

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Introduction: Soil pollution directly impacts food quality and the lives of both humans and animals. The concentration of heavy metals in Egypt’s drain-side soils is rising, which is detrimental to the quality of the soil and crops. The key to reducing the detrimental effects on the ecosystem is having accurate maps of the spatial distribution of heavy metals and the subsequent use of environmentally sustainable remediation approaches. The objective of this work is to assess soil contamination utilizing spatial mapping of heavy metals, determine contamination levels using Principal Component Analysis (PCA), and calculate both the contamination severity and the potential for bioremediation in the soils surrounding the main drain of Bahr El-Baqar. Furthermore, evaluating the capacity of microorganisms (bacteria, fungi, and “Actinomycetes) to degrade heavy elements in the soil.Methodology: 146 soil sample locations were randomly selected near the Bahr El-Baqar drain to examine the degree of soil pollution Ordinary Kriging (OK), method was used to map and analyze the spatial distribution of soil contamination by seven heavy metals (Cr, Fe, Zn, Cd, Pb, As, and Ni). Modified contamination degree (mCd) and PCA were used to assess the research area’s soil pollution levels. The process involved isolating, identifying, and classifying the microorganisms present in the soil of the study area. The study findings showed that variography suggested the Stable model effectively matched pH, SOM, and Cd values. Furthermore, the exponential model proved suitable for predicting Fe, Pb and Ni, while the spherical model was appropriate for Ni, Cr, and Zn.Results: The study revealed three levels of contamination, with an extremely high degree (EHDC) affecting approximately 97.49% of the area. The EHDC exhibited average concentrations of heavy metals: 79.23 ± 17.81 for Cr, 20,014.08 ± 4545.91 for Fe, 201.31 ± 112.97 for Zn, 1.33 ± 1.37 for Cd, 40.96 ± 26.36 for Pb, 211.47 ± 13.96 for As, and 46.15 ± 9.72 for Ni. Isolation and identification of microorganisms showed a significant influence on the breakdown of both organic and inorganic pollutants in the environment. The study demonstrated exceptionally high removal efficiency for As and Cr, with a removal efficiency reached 100%, achieved by Rhizopus oryzae, Pseudomonas aeruginosa, and Bacillus thuringiensis.Conclusion: This study has designated management zones for soil contamination by mapping soil pollutants, geo-identified them, and found potential microorganisms that could significantly reduce soil pollution levels.

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Groundwater suitability analysis for drinking using GIS based fuzzy logic

Cited by 37 publications

References 37 publications

Evaluation and zonation of groundwater quality in terms of drinkability, using Fuzzy Logic and Schoeller deterministic method. (Northern Dezful - Andimeshk Plain)

Evaluation and zonation of groundwater quality in terms of drinkability, using Fuzzy Logic and Schoeller deterministic method. (Northern Dezful - Andimeshk Plain)

Geo-Spatial Analysis of Built-Environment Exposure to Flooding: Iowa Case Study

Geospatial evaluation and bio-remediation of heavy metal-contaminated soils in arid zones

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