Impact of seasonal variations on soil electrical conductivity as an earthquake precursor along the Margalla Fault Line, Islamabad

Naeem, Zainab; Begum, Shaheen

doi:10.1016/j.soildyn.2020.106233

Cited by 1 publication

(1 citation statement)

References 54 publications

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“…In contrast, counselling and information on the massive Covid-19 pandemic did not affect farmers' income, as seen at the p-value (0.0691> 0.05) for the extension factor and p (0.0701> 0.05) as presented in Figure 4. Earthquake and liquefaction as a natural event have reduced all the potential in society, especially farmers who rely on their livelihoods from farming activities (Kamyab et al, 2019;Naeem and Begum, 2020;Basir-Cyio et al, 2021). In an uncertain situation, government assistance in the form of food, shelter, and clothing accompanied by strategic policies can accelerate recovering the socio-economic conditions of communities affected by earthquakes and Liquefaction (Pathak and Ahmad, 2018;Su and Le Dé, 2020).…”

Section: Farmers' Income After the Earthquake And Liquefactionmentioning

confidence: 99%

Sustaining farmers life affected by the natural disaster; an implication during the covid-19 pandemic

Cyio

Anshary

Mahfudz

et al. 2021

Preprint

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Purpose This study aims to measure two investigate and identify effect of treatment factors: Organic Material and Triple Super Phosphate Fertilizer and also to study four main components: Extension (X1), Agricultural Production Facilities (X2), Government Assistance (X3), and Covid-19 dissemination (X4) information. Materials and methods The data collected through surveys and interviews include; (i) soil characteristics data and (ii) socio-economic conditions of farmers affected by the disaster and the Covid-19 pandemic. The statistical analysis used is Principal Component Analysis (PCA) using the Paleontological Statistics (PAST) application.Result and Discussion The result showed the M3 P3 treatment combination gave the highest effect: pH-H2O (6.13), P-total (52.28 mg/100g), P-available (28.62 ppm), plant dry weight (713.75 g/plot), P-uptake (0.58 g/plant), and Corncob (6.2 t/ha). The main component, the most effective factor to the successive variation X2 (PC-1) 75.55%; X3 (PC-2) 18.22%; and X4 (PC-3) 3.94%, while X1 (PC-4) did not result in variation (2.28%). The probability analysis showed farmers post-Earthquake income was affected by production facilities provisions (X2) p (0.015) < µ(0.05) and Government aid (X3) p (0.035) <µ(0.05) and amidst pandemic (X3) p (0.028) <µ (0.05) by government aid, with Correlation Value of each Jono Oge (R) 0.91 and Toaya (R) 0.64, indicating main component factor in Jono Oge is higher at (0.91) since land was displaced by Liquefaction while (0.64) in Toaya—the ground failure was by Earthquake.

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