Comparative geospatial approach for agricultural crops identification in interfluvial plain - A case study of Sahiwal district, Pakistan

Agricultural crop cover identification is a major issue and time-consuming effort to verify the crop type through surveys of the individual field or using prehistoric methods. To establish the scenario of crop identification, the stage of crop provides diverse spatial information about the variety of crops due to its spectral changes. The main aim of this study was to the identify the crop types and their behavior using remote sensing and geographical information system-based approach. Moreover, two main methods were applied to the Sentinel-2 satellite data in which one is random forest based supervised classification and another was Normalize Difference Vegetation Index (NDVI) density estimation method through the google earth engine to procure the data in time-efficient way. This study also established the comparison between classified and vegetation index based seasonal compositional datasets for wheat, cotton, maize, and fodder crops. Study discussed the best fit technique for crops identification in the light of observed methods. Furthermore, the vegetation index ranges by the zonal statistics of the field samples were established according to crop precision. Results showed that -22.94, -43.72, 20.61, and 32.49 % dissimilarities existed in wheat, fodder, cotton, and maize results respectively, after comparison of both techniques. Although, the accuracy assessment was performed on the classified dataset for validation of results by confusion matrix accuracy assessment process using field sample data. Moreover, the vegetation index was used to evaluate crop land surface temperature to estimate the crop growth stage valuation that revealed noticeably enthralling outcomes. The results determined that the classified accuracies of wheat, cotton, maize and fodder were 84, 80, 81 and 71 % respectively. This study also revealed that the random forest classifier has used more features and information potentially during the classifier trainings but vegetation index just implies the limited number of features such as crop growing status

Assessing public perception and willingness to pay for renewable energy in Pakistan through the theory of planned behavior

With growing urbanization and increasing world population, energy demand also increases. A significant portion of the world’s energy comes from fossil fuels, and these sources of energy are declining rapidly at the current consumption rate. There are also growing environmental concerns on the use of fossil fuels increasing greenhouse gas emissions. In this regard, renewable energy (RE) shows promising solutions which are both sustainable and environmentally friendly. Developed countries and leading organizations are investing heavily in the RE sector. However, the developing world has anxieties over social acceptability and people’s willingness to pay for renewable energy. This study is conducted in Pakistan to understand the public perception and willingness to pay. The Theory of Planned Behavior (TPB) was utilized with background factors such as awareness, perceived advantages, perceived challenges, and moral obligations to examine its influence on people’s willingness to pay. In addition to this, the study also assessed the indirect effects of background factors (awareness, perceived advantages, and perceived challenges) on willingness to pay through public attitude. Furthermore, the indirect relationship between background factors (awareness and moral obligation) and willingness to pay through subjective norms was also examined. A total of 512 samples were gathered from participants and were analyzed through partial least square–structural equation modeling (PLS-SEM) and SPSS. The study findings are very interesting and back up our hypotheses that the background factors (awareness, perceived advantages, and perceived challenges) are positively associated with public attitude and have an indirect effect on willingness to pay through public attitude. Similarly, variables such as awareness and moral obligation are negatively and positively associated with subjective norms, respectively. However, the variables, awareness and moral obligation, have no indirect relationship with willingness to pay through subjective norms. Additionally, the study reveals that the components (attitude and perceived behavior control) of TPB have a significantly positive effect on willingness to pay. The study also concludes that the participants having formal education and knowledge about climate change and renewable energy are inclined toward green energy and are willing to pay, and they are hardly influenced by others' opinions. Furthermore, the study also provides insights for policymakers, suggestions, and recommendations for the future

Source rock geochemical assessment and estimation of TOC using well logs and geochemical data of Talhar Shale, Southern Indus Basin, Pakistan

Assessment of organic carbon content (TOC) by geophysical logs has been a challenging task in the formation evaluation of shale gas. This research is conducted to estimate the unconventional hydrocarbon (shale-gas) potential of Talhar Shale in the Southern Indus Basin (SIB), Pakistan. In this study, total organic carbon content (%) was estimated through well logs by different methods and then correlated with well cuttings/core data to determine the best method for estimation of TOC content especially when well cuttings/core data are not available. The Talhar Shale’s thermal maturity, as well as the organic content, were assessed from geochemical analyses. Talhar Shale of Dangi-01 well has good to very good source potential whereas Chak7A-01 well has fair-good. According to Ven Krevalen cross-plot, Talhar Shale of Dangi-01 well has type III kerogen; it can only produce gas while Chak7A-01 has type II/III kerogen which produces both oil and gas. The TOC was estimated using two methods i.e., Schmoker’s and Hester’s and Multivariate Fitting methods. The estimated TOC is then correlated with well cuttings data and concluded that the Multivariate Fitting method is selected as an optimized method for estimation of TOC because it shows strong correlation values of 0.93 and 0.91 in both wells respectively for Talhar Shale SIB, Pakistan

Floods and flood management and its socio-economic impact on Pakistan: A review of the empirical literature

Flood is one of the most damaging natural disasters as the recent floods have shown their serious impact on Pakistan. Flood control and regulation policies are essential to reduce the risks of economic downturn, a threat to human existence, and to sustain the ecology. The severity of flood catastrophe activities represents a constant and severe issue in the world. Floods are rising year by year in severity and duration, causing negative impacts on the social and economic conditions of the nation concerned. While the frequency of floods cannot be avoided, their adverse impacts can be considerably reduced by adopting careful planning and efficient training. This paper reviews the socioeconomic impact of floods, and the existing condition of flood control policies outlines the flood protection problems and discusses opportunities for successful and efficient flood control in Pakistan. The paper also intends to propose several suggestions for efficient and sustainable flood control in Pakistan

Significance of real-time petro-physical data for an optimal remote geosteering operation in complex geological reservoirs

In the last decade, the oil industry has transitioned from primarily drilling vertical wells to a majority of extended reach complex horizontal wells with help of geosteering techniques for better reservoir and production efficiencies. The overall objective of geosteering and well placement has helped to maximize reservoir contact by the keeping well trajectory in the pay zone with the help of quality real-time data, especially in these uncertain times of pandemic due to COVID-19. This paper illustrates the immense impact of real-time data feeds (special logging tools/images) at operation centers with the full remote expert support of multidisciplinary teams. The proper data communication mechanism is also helpful to share the information across asset teams in a timely manner to drill complex wells remotely. To achieve the desired geosteering objective, experts monitor and evaluate the real-time petro-physical data of a landing well and design the well path accordingly to stay in the pay zone/horizon. During this collaborative and integrated geosteering process, the geological and petro-physical variables like the reservoir architecture, permeability and porosity distribution, and fluid contacts are also being used to update the reservoir models in real-time, based on the latest subsurface information for better reservoir management, operational performance and timely decision making

Correction: Ahmad et al. Estimating the Total Volume of Running Water Bodies Using Geographic Information System (GIS): A Case Study of Peshawar Basin (Pakistan). Sustainability 2022, 14, 3754

The authors would like to make the following corrections to the published paper [...

Groundwater budgeting of Nari and Gaj formations and groundwater mapping of Karachi, Pakistan

Groundwater depletion is an emerging problem worldwide due to changes in climate and an increase in urbanization. Two significant water-bearing formations, the Oligocene-aged Nari and the Miocene-aged Gaj, were utilized as a case study exposed near Karachi, Pakistan. Groundwater budgeting was performed through a classical equation. The inflow of groundwater in the formations was calculated by thermo-pluviometric data and water loss of Hub Dam. The potential of evapotranspiration (PET) was calculated by the Thornthwaite method. The groundwater inflow from Hub Dam was estimated by using 20 years of annual water loss data by removing PET. The total mean annual inflow of groundwater in the formations was 2414.12 US Gallons per Second (gps). The annual mean outflow was estimated by calculation of groundwater usage for industries and domestic purposes and the mean annual groundwater outflow was 5562.61 US gps and an annual deficit of groundwater was 3148.5 US gps. The research is composed of validating the groundwater budget. Direct Current Electrical Resistivity (DCER) and static water level data from existing industrial wells were used for groundwater maps. The DCER data indicates A-Type and K-Type sub-surface with high resistivity in the three-layer model. The average water table of residential areas in 2019 was 60 m and in industrial areas was 130 m. The oscillation of the groundwater table over the last 20 years and the deficit of the groundwater budget shows an alarming condition for the future. If the same scenario persists, then by 2025, the water table will decline up to 140 m.Validerad;2022;Nivå 2;2022-11-03 (sofila)</p

An integrated study for seismic structural interpretation and reservoir estimation of Sawan gas field, Lower Indus Basin, Pakistan

The information about the subsurface structure, type of fluids present in the reservoir, and physical properties of the rocks is essential for identifying potential leads. The integrated approach of petrophysical analysis, seismic data interpretation, seismic attributes analysis, lithology, mineralogy identification, and Gassmann fluid substitution were used for this purpose. The structural interpretation with the help of seismic data indicated the extensional regime with horst and graben structures in the study area. The two negative flower structures are cutting the entire Cretaceous deposits. The depth contour map also indicate favorable structures for hydrocarbon accumulation. The four possible reservoir zones in the Sawan-01 well and two zones in the Judge-01 well at B sand and C sand levels are identified based on well data interpretation. The main lithology of the Lower Goru Formation is sandstone with thin beds of shale. The clay types confirm the marine depositional environment for Lower Goru Formation. The water substitution in the reservoir at B sand and C sand levels indicated increased P-wave velocity and density. The water substitution affected the shear wave velocity varies slightly due to density changes. The cross plots of P-impedance versus Vp/Vs ratio differentiate the sandstone with low P-impedance and low Vp/Vs ratio from shaly sandstone with high values in the reservoir area. The P-impedance and S-impedance cross plot indicate increasing gas saturation with a decrease in impedance values. The low values of Lambda-Rho and Mu-Rho indicated the gas sandstone in the cross plot

Geothermal Exploration Using Remote Sensing, Surface Temperature, and Geophysical Data in Lunayyir Volcanic Field, Saudi Arabia

Energy consumption worldwide has undergone a recent shift, with hydrocarbons, coal, and new energy sources taking center stage. However, fossil fuels face criticism due to their negative impacts on the environment through air pollution. Geothermal energy is a clean, renewable, and eco-friendly alternative that can be harnessed for power generation. The Lunayyir volcanic field is located in the western part of Saudi Arabia and has been identified as a potential geothermal resource. In this study, a comprehensive analysis of the gravity, magnetic, and land surface temperature data collected over the study area is conducted to investigate the geothermal potential. The gravity data are processed using standard techniques to correct for instrument drift, diurnal variations, and topographic effects and to filter out high-frequency noise. The magnetic data are processed using standard procedures. Analysis of the gravity data shows that the Lunayyir volcanic field is characterized by a series of gravity anomalies, which can be interpreted as indicative of the presence of subsurface geologic structures that are similar in geothermal areas, such as faults, fractures, and intrusions. The magnetic data, on the other hand, show that the volcanic field has a relatively low magnetic susceptibility, which is consistent with the presence of volcanic rocks implying shallow heat sources. Landsat satellite data are utilized to calculate the land surface temperature through the use of GIS software. Additionally, the normalized difference vegetation index (NDVI) is calculated using the near-infrared and red bands of the Landsat satellite. The land surface temperature of the year 2007 shows the relatively high temperature at the surface as compared to 2000 and 2021, which is an indication of volcanic activities in the subsurface. It is suggested that these structures may provide conduits for hot fluids, which could potentially be exploited for geothermal energy production. The obtained results emphasize the importance of combining different geophysical datasets to obtain a better understanding of underground geology and geothermal systems. In general, this study improves the assessment of the Lunayyir volcanic field in the western part of Saudi Arabia for geothermal energy