Runway Location and Orientation Suitability Analysis

The site suitability for construction of water conservation structures is an important step towards groundwater conservation in arid and semi-arid regions. Water is the most crucial for maintaining an environment and ecosystem which is helpful to sustaining all forms of the life. The increasing water scarcity day to day has been one of the common problems over a period of time. On top of it, when the area is a part of rain shadow zone like Ahmednagar district, water conservation activities are become more important. The present study aims to identify the suitable zones for water conservation activity. Multi- criteria evaluation is carried out using Geographic Information System (GIS) techniques to help the choice makers in defining suitable site for construction of water conservation structures. Different layers which were considered for multi-criteria evaluation: slope, land use land cover, soil texture, lithology, soil depth, soil erosion, wells, lineaments and drainage network. Analytical Hierarchy Processes (AHP) is used for weighted sum to find suitable sites for implementation of water conservation activity using selected criterions. The site suitability map was classified into four classes: highly suitable, moderately suitable, less suitable and not suitable with area of 19.19%, 26%, 49.03% and 5.78, respectively. This map will help for selection of suitable sites for construction of Mati Nala Bund (MNB), Check Dam, Cement Nala Bund (CNB) and Continuous Contour Trenches (CCT) for conservation of groundwater resource in the region.

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Waste to energy spatial suitability analysis using hybrid multi-criteria machine learning approach

Environmental Science and Pollution Research ◽

10.1007/s11356-021-15289-0 ◽

2021 ◽

Author(s):

Rami Al-Ruzouq ◽

Mohamed Abdallah ◽

Abdallah Shanableh ◽

Sama Alani ◽

Lubna Obaid ◽

...

Keyword(s):

Machine Learning ◽

Waste To Energy ◽

Learning Approach ◽

Suitability Analysis ◽

Machine Learning Approach

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Suitability Analysis of 17 Probiotic Type Strains of Lactic Acid Bacteria as Starter for Kimchi Fermentation

Foods ◽

10.3390/foods10061435 ◽

2021 ◽

Vol 10 (6) ◽

pp. 1435

Author(s):

Hee Seo ◽

Jae-Han Bae ◽

Gayun Kim ◽

Seul-Ah Kim ◽

Byung Hee Ryu ◽

...

Keyword(s):

Lactic Acid ◽

Lactic Acid Bacteria ◽

Growth Rates ◽

Principal Component ◽

Fermented Foods ◽

Suitability Analysis ◽

Moderate Growth ◽

Health Promoting ◽

Highly Correlated ◽

Type Strains

The use of probiotic starters can improve the sensory and health-promoting properties of fermented foods. This study aimed to evaluate the suitability of probiotic lactic acid bacteria (LAB) as a starter for kimchi fermentation. Seventeen probiotic type strains were tested for their growth rates, volatile aroma compounds, metabolites, and sensory characteristics of kimchi, and their characteristics were compared to those of Leuconostoc (Le.) mesenteroides DRC 1506, a commercial kimchi starter. Among the tested strains, Limosilactobacillus fermentum, Limosilactobacillus reuteri, Lacticaseibacillus rhamnosus, Lacticaseibacillus paracasei, and Ligilactobacillus salivarius exhibited high or moderate growth rates in simulated kimchi juice (SKJ) at 37 °C and 15 °C. When these five strains were inoculated in kimchi and metabolite profiles were analyzed during fermentation using GC/MS and 1H-NMR, data from the principal component analysis (PCA) showed that L. fermentum and L. reuteri were highly correlated with Le. mesenteroides in concentrations of sugar, mannitol, lactate, acetate, and total volatile compounds. Sensory test results also indicated that these three strains showed similar sensory preferences. In conclusion, L. fermentum and L. reuteri can be considered potential candidates as probiotic starters or cocultures to develop health-promoting kimchi products.

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Torrential Flood Water Management: Rainwater Harvesting through Relation Based Dam Suitability Analysis and Quantification of Erosion Potential

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10010027 ◽

2021 ◽

Vol 10 (1) ◽

pp. 27

Author(s):

Bilal Ahmad Munir ◽

Sajid Rashid Ahmad ◽

Raja Rehan

Keyword(s):

Sediment Yield ◽

Soil Loss ◽

Rainwater Harvesting ◽

Suitability Analysis ◽

Valley Bottom ◽

The North ◽

Roughness Index ◽

Dam Site ◽

Very High

In this study, a relation-based dam suitability analysis (RDSA) technique is developed to identify the most suitable sites for dams. The methodology focused on a group of the most important parameters/indicators (stream order, terrain roughness index, slope, multiresolution valley bottom flatness index, closed depression, valley depth, and downslope gradient difference) and their relation to the dam wall and reservoir suitability. Quantitative assessment results in an elevation-area-capacity (EAC) curve substantiating the capacity determination of selected sites. The methodology also incorporates the estimation of soil erosion (SE) using the Revised Universal Soil Loss Equation (RUSLE) model and sediment yield at the selected dam sites. The RDSA technique identifies two suitable dam sites (A and B) with a maximum collective capacity of approximately 1202 million m3. The RDSA technique was validated with the existing dam, Gomal-Zam, in the north of Sanghar catchment, where RDSA classified the Gomal-Zam Dam in a very high suitability class. The SE estimates show an average of 75 t-ha−1y−1 of soil loss occurs in the study area. The result shows approximately 298,073 and 318,000 tons of annual average sediment yield (SY) will feed the dam A and B respectively. The SE-based sediment yield substantiates the approximate life of Dam-A and Dam-B to be 87 and 90 years, respectively. The approach is dynamic and can be applied for any other location globally for dam site selection and SE estimation.

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