Search

The phenomena of drought is common in the world, particularly in Pakistan. Drought in Pakistan has been studied in terms of its spatial and temporal variability, as well as its impact on the El Niño-Southern Oscillation (ENSO) cycle. The objectives of this study are to identify homogeneous rainfall regions and their trend regions, as well as the impact of ENSO cycle. For the analysis, 44 meteorological sites during 1980–2019 are used for monthly rainfall data. The descriptive and exploratory statistics tests (e.g., Pettitt and Mann-Kendall—MK), Sen method, and cluster analysis (CA) are implemented with the annual Standardized Precipitation Index (SPI). The ENSO occurrences were classified based on the Oceanic Nio Index (ONI) for region 3.4. Using the Cophenetic Correlation Coefficient (CCC) and a significance level of 5%, seven approaches were applied to the pluviometric dataset. The CCC > 0.9082 indicates that the Complete approach is the best. According to the CA method, Pakistan has four homogenous rainfall groups (G1, G2, G3, and G4). Descriptive and exploratory statistics yielded lower values for G1 than for the other groups. Pettitt's technique identified the most extreme El Niño years in terms of the drought's spatial and temporal variability. According to the Pettitt test, the wettest months were March, August, September, June, and December. Non-significant increases in Pakistan's annual rainfall were found in the MK test, with exceptions in the southern and northern regions, respectively. No significant rise in Pakistan's rainfall was found using Sen's Sen's approach, especially in the G2, G3, and G4 regions. The severity of the drought in Pakistan is made worse by months, homogeneous groups of rainfall, and El Niño events, all of which require public officials' attention while managing water resources, agriculture, and the country's economy.

The existing global network of continuously operating stand-alone GNSS reference stations provides an opportunity to estimate total electron content (TEC) from raw Global Positioning System (GPS) measurements. The TEC driven from a local GPS network in Pakistan was compared to two international models: IRI-2016 and IRI-PLAS 2017. The performance was analyzed statistically based on residual analysis, RMSE and correlation. It is observed that the TEC estimated by all three methods follows the same diurnal trend where it maximizes around noon ( $$12:00 {-} 14:00 LT$$ ) and reduces in the afternoon ( $$15:00 {-} 17:00 LT$$ ). Both empirical models provide a better estimation of nighttime TEC as compared to daytime TEC and exhibit maximum deviation in the month of April with the lowest deviation in December. The IRI-2016 underestimates TEC by $$5 - 10 TECU,$$ whereas the IRI-PLAS 2017 overestimates TEC by $$10 - 22 TECU$$ . However, the IRI-2016 conforms better to GPS-TEC ( $$\overline{\gamma } = 0.9710$$ ) as compared to IRI-PLAS 2017 ( $$\overline{\gamma } = 0.8337$$ ). The study shows that local GNSS stations in collaboration with TEC estimated from global models may be used in development of an efficient local TEC model over Pakistan which will not only assist in local ionosphere studies but also aid in improving the positioning accuracy.

Rock physics has proven its credibility for the quantitative seismic interpretation of reservoir and reservoir characterization. In this study, we implemented K-means clustering to group data points more objectively and without prior misconceptions into clusters. Furthermore, we used the grouping suggested by the algorithm for our study. We integrated rock physics and K-means cluster analysis to determine a possible hydrocarbon reservoir using three well logs data. Initially, K-means clustering was implemented on density logs and based on the arithmetic mean of each density log cluster, sandstone and shale-dominant parts were identified and separated. Then, rock physics parameters were computed for the sandstone-dominant part of the well logs. Based on the cross-plots of Lame’s constants with density product, and Lame’s constants ratio, additional lithology discrimination was done for the identification of a clean gas-sand zone. In the clean gas-sand zone, two different pore fluids zones were identified based on Vp/Vs ratio, Poisson ratio, P- and S-wave impedances. Finally, statistical analysis was carried out to observe the underlying frequency distribution of rock physics parameters. The integration of cluster analysis and rock physics gave us significant information about the presence of different fluids and the existence of a potential hydrocarbon reservoir.

The recent advances in satellite based ionosphere monitoring provided more evidence about earthquake (EQ) precursors from lithosphere ionosphere coupling mechanism. In this paper, we investigate ionospheric anomalies associated with the December 19, 2009, Taiwan EQ (Mw = 6.4), that occurred on UT = 13:02 h. Seismo ionospheric anomalies are evaluated during 31 days (20 day before followed by 10 days after the EQ) in the data of French Satellite Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions (DEMETER) and validated from Global Navigation Satellite System (GNSS) retrieved Total Electron Content (TEC). The day time values of ISL (Langmuir Probe) and IAP (Ion Analyzer) from DEMETER point to significant ionospheric perturbations within 5 days associated with EQ day. Moreover, GNSS stations of International GNSS Service (IGS) within EQ preparation zone also validate anomalies in ionosphere prior/after the Mw 6.4, Taiwan EQ. Moreover, spatial and temporal analyses of daily ionospheric indices from DEMETER and GNSS point to simultaneous enhancement in electron density, ion density, electron temperature and TEC related to the main shock during quiet geomagnetic storm (Dst

Global Navigation Satellite System (GNSS)–based Earthquake (EQ) anomalies in the ionosphere and troposphere provide explicit evidences to study the coupling between seismic events, atmosphere, and ionosphere in epicentral breeding regions consequent to the EQ day in the preparation period. EQs are still not predicted, but the space-based EQ anomalies aid in the development of monitoring pre- and post-seismic precursors around the seismogenic zone and associated fault lineament regions. In this paper, tropospheric and ionospheric anomalies are investigated for the July 06, 2019, Mw 7.1 California EQ from GNSS tropospheric delays and Total Electron Content (TEC), respectively. We noticed that atmospheric and ionospheric anomalies from GNSS stations within 5–10 days before the main shock and storm-induced ionospheric variations occur beyond the 5th day after the EQ. Similarly, synchronized and collocated lower atmospheric anomalies are also recorded in the long-term temporal values of SO2 and SO4 within 1-month before and after July 2019, which validates the existence of Lithosphere-Atmosphere–Ionosphere Coupling (LAIC) over the EQ epicenter. On the other hand, EQ anomalies occur during quiet geomagnetic storm activity (Kp 3. All these atmospheric and ionospheric perturbations support the development in EQ precursors with satellite measurements, which are indispensable towards the forecasting of future EQ.

Southern Lower Indus basin is an oil and gas prone basin, which is important for producing hydrocarbon in Pakistan. Due to limited Rock-Eval pyrolysis data availability in the prospective shale gas basin, the organic facies geochemical characteristics study is a challenging task for researchers. The primary objective of this study is an evaluation of the Lower Goru Formation organic facies hydrocarbon potential by geochemical data and its subsurface facies distribution study by well tops and seismic data. The study area is situated at the Southern Lower Indus basin of Pakistan that is considering the prospective shale gas basin with immense unconventional hydrocarbon potential. In the present study, Rock-Eval pyrolysis data analysis along with the integration of both seismic and well tops data were conducted for investigation of source rock generation potential of organic facies variability within the Lower Goru Formation. The geochemical approaches used in the current study show that the Lower Goru Formation encountered in, bears fair to excellent total organic carbon (TOC) content values of 0.50–3.60% in Well-A and 0.10–4.69% in Well-B. Additionally, the results of Rock-Eval pyrolysis data show that interbedded shales of the Lower Goru Formation contain different types of kerogen (III, II–III, and II) with variable generation potential of oil and gas.

The comparative analysis of measured and modelled Vertical Total Electron Content (VTEC) in low, mid and high latitude assists in the correction of Global Positioning System (GPS) measurements. In this study, we compare VTEC from GPS and International Reference Ionosphere (IRI) models (2007, 2012 and 2016) over mid latitude Sukkur (Lat $27.7^{\circ}~\text{N}$ , Long $68.8^{\circ}~\text{E}$ ) region in Pakistan during the final phase of the solar cycle 24 (2019–2020). We investigated the comparison in the form of ionospheric VTEC deviation during diurnal, monthly and seasonal analyses in measured and modelled values over the mid latitude region. The diurnal analysis shows that the measured VTEC in low magnetic activity days’ correlates with IRI-2016 as compared to IRI-2007 and IRI-2012. Whereas, IRI-2016 matches more than IRI-2007 and IRI-2012 in monthly values with minimum deviation. Moreover, the seasonal variations depict maximum variability in the spring season between measured and modelled VTEC over Sukkur. Similarly, maximum correlation ( $R>9.0$ ) is noted between measured and modelled VTEC in low magnetic activity days than high solar activity days, whereas the correlation is $R

This paper presents the performance of the latest version of the International Reference Ionosphere (IRI-2016) model for estimating the Total Electron Content (TEC) variations in the mid-latitudinal Turkish regions during low solar activity years (2015–2018). Moreover, TEC is estimated from dual-frequency Global Navigation Satellite System (GNSS) receivers operating in different regions of Turkey: Zonguldak (41.44 °N, 31.77 °E), Ankara (39.88 °N, 32.75 °E) and Antalya (36.88 °N, 30.66 °E). The diurnal, monthly and seasonal variations in the measured TEC are compared with the prediction of modelled TEC. The results reveal minimum variations in the diurnal TEC after midnight hours 21:00–24:00 Universal Time ( $\text{UT}=\text{LT}+3{:}00~\text{hrs}$ ) and maximum TEC enhancement during the daytime from 9:00–15:00 UT (12:00–18:00 LT). The monthly mean TEC from measured and modelled estimation depicts the highest and lowest values in April and December during the years 2015–2018, respectively. Moreover, the low and high seasonal variations are observed in equinoxes and winter solstice, respectively. Furthermore, it is observed that IRI-2016 model underestimates the measured values, especially during the daytime (12:00–18:00 LT) at each station. The correlation coefficient between the measured and modelled TEC is found in the range ( $R=0.81\text{--}0.85$ ) during the years 2015–2018, which exhibits a high positive correlation over the regions. The model predicted TEC is showing a good agreement with measured TEC of the ionospheric dynamics over the regions, which manifests the radio signals accuracy over the mid-latitude regions, particularly Turkey.

Continuous wavelet transformation (CWT) as a new mathematical tool has provided deep insights for the identification of localized anomalous zone in the time series data set. In this study, a three-layer geological model is investigated by CWT to locate seismic reflections temporally and spatially. This model consists of three layers, where the third layers of the anticline structure are assumed to act as a pure sandstone hydrocarbon reservoir with 10% porosity. The equation of Gassmann has been implemented for the pore fluid substitution in the reservoir. Synthetic seismic data are generated for the three-layer geological model. Due to the presence of noise, it is always difficult to interpret seismic data. But, CWT has the ability of noise reduction, improving the visualization of a data set and locating the anomalies in terms of scalogram and 3D CWT coefficients. Synthetic seismic data of the geological structure are transformed by CWT. The successful transformation of P-wave velocity, synthetic seismic data and acoustic impedance inversion provided evidence to distinguish different interfaces accurately. CWT has successfully located seismic reflections by localizing high-energy spectrum within the cone of influence. Three high-energy spectrums have been identified at 0.8 s, 1 s and 1.07 s, and it exactly matches the seismic data and three-layer geological model.

Aluminum (Al) and manganese (Mn) toxicity commonly coexists in acid soil, so the crop cultivars suitable for planting in acid soil should show high tolerance to both elements simultaneously. However, it is still not clear if the toxicity of Mn and Al on plant growth is antagonistic or synergistic, and the plants with Al tolerance are also tolerant to Mn toxicity. In this study, three barley genotypes (one Tibetan wild and two cultivated), differing in Al tolerance, were characterized for growth and physiological responses to Al or Mn toxicity as well as the combined treatment of the two toxic elements. Interestingly, it has been found that the combined treatment of both metals was less affected in comparison with Al or Mn treatment alone, in terms of plant growth, Al or Mn concentration in plant tissues, and photosynthetic parameters, indicating antagonistic interaction of Al and Mn for their effect on plant growth and physiological traits. The results also showed that there was a dramatic difference among barley genotypes in Mn toxicity tolerance and XZ16 showed much higher tolerance than other two genotypes. High Mn tolerance is mainly described to less Mn uptake and lower Mn concentration in plants, and Mn tolerance is independent of Al tolerance.