Application of fuzzy analytic hierarchy process and geospatial technology to identify groundwater potential zones in north-west region of Bangladesh

Sresto, Mizbah Ahmed; Siddika, Sharmin; Haque, Md. Nazmul; Saroar, Mustafa

doi:10.1016/j.envc.2021.100214

Cited by 34 publications

(12 citation statements)

References 40 publications

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“…At the moment, a great deal of theoretical frameworks is available for these evaluation methods. Among these are the fuzzy integrated evaluation model [7], the comprehensive index evaluation method [8], the hierarchical analysis method [9], the Grey relational analysis method [10], the principal component analysis method [11], and the artificial neural network method [12]. To construct an evaluation index system of agricultural eco-environmental quality for the study of sustainable development of an agro-ecosystem, literature [13][14][15] and others have used a combination of hierarchical analysis, the Delphi method, a multilevel fuzzy evaluation model, and other methods.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] An Evaluation Model of Agricultural Entrepreneurial Ecological Environment Quality Oriented to Public Health Topic Using the Optimized Neural Network Algorithm

Meng

Zhang

Ren

2022

Journal of Environmental and Public Health

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As the primary industry, agriculture is a prerequisite for human survival and a basic industry of the national economy. As a result, the growth of agriculture is vital for the nation's socioeconomic development. e construction of ecological civilization and the reform and innovation of farmers' digital entrepreneurial behavior in the region are intimately correlated with the agricultural eco-environmental quality. erefore, it is crucial for us to improve control and maintenance of the agricultural eco-environment. A requirement for directing the sustainable growth of the agricultural economy is evaluating and identifying the quality of the regional eco-environment and the issues it faces. In view of this, the study employs Jiangsu Province as a research example, builds a comprehensive index evaluation system, and uses the modi ed BP neural network to evaluate the agricultural eco-environmental quality in the target area between 2010 and 2020. First, the evaluation system is constructed from four dimensions: ecological resource status, environmental pollution degree, eco-environmental protection e orts, and agricultural development level, and 14 in uencing factors are then screened out as speci c secondary evaluation indicators. Second, a GA-BP model will be applied to comprehensively assess the quality of the agricultural eco-environment in the province over the past 10 years. e comprehensive score of the province's agricultural eco-environmental quality was calculated, and the quality level was classi ed by this. Meanwhile, the indicators' scores were paired with an analysis of each contributing factor's degree of change. e ndings indicate that from 2010 to 2020, Jiangsu Province's agricultural eco-environment demonstrated a favorable trend, a reasonably high-quality level, and a tendency of continuous improvement from bad to good. e results of each indicator measuring the quality of the agricultural environment uctuated, but overall they showed an upward trend. Finally, in order to o er a reference for agricultural eco-environment control and protection and a good ecological environment for farmers' digital entrepreneurship in the near future, countermeasures and suggestions are proposed for the restoration of the agricultural eco-environment in Jiangsu Province referring to the results of the research and the problems already present in the area.

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Section: Introductionmentioning

confidence: 99%

[Retracted] An Evaluation Model of Agricultural Entrepreneurial Ecological Environment Quality Oriented to Public Health Topic Using the Optimized Neural Network Algorithm

Meng

Zhang

Ren

2022

Journal of Environmental and Public Health

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“…For example, bodies of water are clearly detected, when high-resolution images are analyzed (Carroll et al, 2009). Artificial intelligence such as analytical hierarchy process (AHP) based on fuzzy algorithms is a more appropriate approach than conventional AHP and weighted criteria (Huang et al, 2013;Sresto et al, 2021;Yeh et al, 2009b;Yifru et al, 2020).…”

Section: Groundwater Potential Zone (Gwpz)mentioning

confidence: 99%

Groundwater Potential Zone Classification Using Geospatial Approach

Hardanto

Mustofa

Ardiansyah

2023

JTEP-L

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Groundwater is an important process in the watershed hydrological system. Serayu watershed, the largest in Central Java Province, has bio-physic spatial variability that influences groundwater recharging. The aim is to derive the groundwater potential zone of the Serayu watershed. Five thematic maps used and applied for groundwater potential analysis, were lithology, land use land cover, lineament density, drainage density, and slope gradient. Distribution of Lithology data, Digital Elevation Model (DEM), and Landsat 8 image were analyzed to thematic raster with 1 x 1 km resolution. Weighted index was calculated regarding the relation of five influence parameters then were overlaid and calculated by using QGIS-calculator. Groundwater classified into five categories, namely poor, low, moderate, good, and very good. Based on the final groundwater potential map, 0.02% of 3,727 km2 is poor category, however most of Serayu watershed have moderate to good (48.77 and 29.77 %, respectively). The percentage of very good (10.57%) and low (10.87%) classes were rather similar. Spatial variability of groundwater distribution indicates the complex characteristics of the Serayu watershed, so more serious attention from the perspective of research and management of water resources in the future, is needed. Keywords: Groundwater, Multi-criteria, QGIS, Recharging, Serayu watershed.

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“…Flat areas (0-2 • ) are in the center, representing 42.55% of the basin area (Table 6). These zones are associated with very high groundwater potential due to the high infiltration rates and low runoff (Table 5) [112,113]. In contrast, steeper slopes (15-30 • and >30 • ) are found surrounding the flat area, most of them located towards the SSM, which is characterized as a complex terrain [114].…”

Section: Slopementioning

confidence: 99%

“…(3) Other Multi-Criteria Decision Making techniques could be applied for better results. Among the most employed for identifying GWPZs are Multi Influencing Factor Analysis (MIF) [14,72,98,143], Analytical Networking Process (ANP) [103,144,145], and Fuzzy-Analytic Hierarchy Process [113,131,146,147]. (4) Thematic maps often generalize the nature of the site, so a variation on a local scale could be found.…”

Section: Limitations Of the Studymentioning

confidence: 99%

Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches

Uc-Castillo

Cruz

Ramos-Leal

et al. 2022

Water

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Groundwater occurrence in semi-arid regions is variable in space and time due to climate patterns, terrain features, and aquifer properties. Thus, accurate delineation of Groundwater Potential Zones (GWPZs) is essential for sustainable water resources management in these environments. The present research aims to delineate and assess GWPZs in a semi-arid basin of San Luis Potosi (SLP), Mexico, through the integration of Remote Sensing (RS), Geographic Information System (GIS), and Analytic Hierarchy Process (AHP). Seven thematic layers (geology, lineament density, land use and land cover, topographic wetness index (TWI), rainfall, drainage density, and slope) were generated in raster format. After the AHP procedure and rank assignment, the thematic layers were integrated using the raster calculator to obtain the GWPZs map. The results indicated that 68.21% of the area is classified as low groundwater potential, whereas 26.30% is classified as moderate. Validation was done by assessing the water residence time data from 15 wells distributed in the study area. Furthermore, the Receiver Operating Characteristics (ROC) curve was obtained, indicating a satisfactory accuracy prediction (AUC = 0.677). This study provides valuable information for decision-makers regarding the conservation and sustainable management of groundwater resources.

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Application of fuzzy analytic hierarchy process and geospatial technology to identify groundwater potential zones in north-west region of Bangladesh

Cited by 34 publications

References 40 publications

[Retracted] An Evaluation Model of Agricultural Entrepreneurial Ecological Environment Quality Oriented to Public Health Topic Using the Optimized Neural Network Algorithm

[Retracted] An Evaluation Model of Agricultural Entrepreneurial Ecological Environment Quality Oriented to Public Health Topic Using the Optimized Neural Network Algorithm

Groundwater Potential Zone Classification Using Geospatial Approach

Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches

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