Soil erosion is a crucial geo-environmental hazard worldwide that affects water quality and agriculture,decreases reservoir storage capacity due to sedimentation,and increases the danger of flooding and landslides.Thu...Soil erosion is a crucial geo-environmental hazard worldwide that affects water quality and agriculture,decreases reservoir storage capacity due to sedimentation,and increases the danger of flooding and landslides.Thus,this study uses geospatial modeling to produce soil erosion susceptibility maps(SESM)for the Hangu region,Khyber Pakhtunkhwa(KPK),Pakistan.The Hangu region,located in the Kohat Plateau of KPK,Pakistan,is particularly susceptible to soil erosion due to its unique geomorphological and climatic characteristics.Moreover,the Hangu region is characterized by a combination of steep slopes,variable rainfall patterns,diverse land use,and distinct soil types,all of which contribute to the complexity and severity of soil erosion processes.These factors necessitate a detailed and region-specific study to develop effective soil conservation strategies.In this research,we detected and mapped 1013 soil erosion points and prepared 12 predisposing factors(elevation,aspect,slope,Normalized Differentiate Vegetation Index(NDVI),drainage network,curvature,Land Use Land Cover(LULC),rainfall,lithology,contour,soil texture,and road network)of soil erosion using GIS platform.Additionally,GIS-based statistical models like the weight of evidence(WOE)and frequency ratio(FR)were applied to produce the SESM for the study area.The SESM was reclassified into four classes,i.e.,low,medium,high,and very high zone.The results of WOE for SESM show that 16.39%,33.02%,29.27%,and 21.30%of areas are covered by low,medium,high,and very high zones,respectively.In contrast,the FR results revealed that 16.50%,24.33%,35.55%,and 23.59%of the areas are occupied by low,medium,high,and very high classes.Furthermore,the reliability of applied models was evaluated using the Area Under Curve(AUC)technique.The validation results utilizing the area under curve showed that the success rate curve(SRC)and predicted rate curve(PRC)for WOE are 82%and 86%,respectively,while SRC and PRC for FR are 85%and 96%,respectively.The validation results revealed that the FR model performance is better and more reliable than the WOE.展开更多
The present study focuses on building a workflow for structural interpretation and velocity modeling and implementing to Jurassic-Cretaceous succession （Chiltan Limestone and Massive sand of the Lower Goru Formation...The present study focuses on building a workflow for structural interpretation and velocity modeling and implementing to Jurassic-Cretaceous succession （Chiltan Limestone and Massive sand of the Lower Goru Formation）. 2D-Migrated seismic sections of the area are used as data set and in order to confirm the presence of hydrocarbons in the study area, P and S-wave seismic velocities are estimated from single-component seismic data. Some specific issues in the use of seismic data for modeling and hydrocarbon evaluation need to deal with including distinguishing the reservoir and cap rocks, and the effects of faults, folds and presence of hydrocarbons on these rocks. This study has carried out the structural interpretation and modeling of the seismic data for the identification of traps. The results demonstrate existence of appropriate structural traps in the form of horst and grabens in the area. 2D and 3D velocity modeling of the horizons indicates the presence of high velocity zones in the eastern half of the study while relatively low velocity zones are encountered in the western half of the area. Two wells were drilled in the study area （i.e. Fateh-01 and Ichhri-01） and both are dry. Immature hydrocarbons migration is considered as a failure reason for Fateh-01 and Ichhri-01 well.展开更多
Conventional petrophysical investigations are based on P-wave seismic velocity analysis to predict density information, while ignoring the important S-wave velocity. This study is based on S-wave velocity analysis of ...Conventional petrophysical investigations are based on P-wave seismic velocity analysis to predict density information, while ignoring the important S-wave velocity. This study is based on S-wave velocity analysis of density estimation of Meyal Oil Field(Potwar Plateau, Pakistan), which reveals a very high correlation(R=0.87) between predicted and actual density. Since the availability of S-wave velocity(Vs) data increases, it’s highly appreciable to take into account the contribution of Vs in improvement of density estimates. This investigation only focuses on driving new constants(a = 1.92 and b = 0.186) for Gardner’s relationship to estimate density of pure carbonates(Vsh< 10%) in the study area, where the traditional model gave poorer density predictions. The proposed empirical expression with locally extracted unknowns from well log data proved its ability in terms of density prediction(showing very close agreement with measured densities) and best fitting the datasets at low as well as high density values when compared with Gardner’s equation. Based on our analysis, the exploratory study neither intends to replace the well established density estimation models nor to extend information over what information can possibly be extractable from Vp. However, our research does stimulate the growing use of Vs and importance of local unknown constants especially in carbonates reservoir interval to avoid misuse of most widely used Gardner relation in all geological settings.展开更多
The global cryosphere is experiencing accelerated melting due to climate change.Currently,the Karakoram anomaly is under discussion with a debate about the possibility that the anomaly may have recently ended.This stu...The global cryosphere is experiencing accelerated melting due to climate change.Currently,the Karakoram anomaly is under discussion with a debate about the possibility that the anomaly may have recently ended.This study aims to evaluate the up-to-date changes in snow cover in the western Karakoram region.We observed the snow cover changes in Passu and Ghulkin valleys in the Hunza River basin(HRB)of the Karakoram through multitemporal Landsat satellite data between 1995 and 2022.We found a significant reduction in snow cover in these valleys,with an average reduction rate of 0.42 km~2/yr,resulting in a total reduction of~11.46 km~2 between 1995 and 2022.This reduction in snow cover is consistent with the mass loss of glaciers in the Karakoram region in recent years.The decline in snow cover in these valleys is also consistent with the meteorological data.The temperature in summer(June)has significantly increased whereas the precipitation in the accumulation season(March)has decreased.These rapid changes suggest that it is crucially important to monitor the snow cover on a regular basis to support downstream management of snowmelt runoff.In addition,there is a need of planning for mitigation and adaptation strategies for snow-related hazards.展开更多
基金The authors extend their appreciation to Researchers Supporting Project number(RSP2024R390),King Saud University,Riyadh,Saudi Arabia.
文摘Soil erosion is a crucial geo-environmental hazard worldwide that affects water quality and agriculture,decreases reservoir storage capacity due to sedimentation,and increases the danger of flooding and landslides.Thus,this study uses geospatial modeling to produce soil erosion susceptibility maps(SESM)for the Hangu region,Khyber Pakhtunkhwa(KPK),Pakistan.The Hangu region,located in the Kohat Plateau of KPK,Pakistan,is particularly susceptible to soil erosion due to its unique geomorphological and climatic characteristics.Moreover,the Hangu region is characterized by a combination of steep slopes,variable rainfall patterns,diverse land use,and distinct soil types,all of which contribute to the complexity and severity of soil erosion processes.These factors necessitate a detailed and region-specific study to develop effective soil conservation strategies.In this research,we detected and mapped 1013 soil erosion points and prepared 12 predisposing factors(elevation,aspect,slope,Normalized Differentiate Vegetation Index(NDVI),drainage network,curvature,Land Use Land Cover(LULC),rainfall,lithology,contour,soil texture,and road network)of soil erosion using GIS platform.Additionally,GIS-based statistical models like the weight of evidence(WOE)and frequency ratio(FR)were applied to produce the SESM for the study area.The SESM was reclassified into four classes,i.e.,low,medium,high,and very high zone.The results of WOE for SESM show that 16.39%,33.02%,29.27%,and 21.30%of areas are covered by low,medium,high,and very high zones,respectively.In contrast,the FR results revealed that 16.50%,24.33%,35.55%,and 23.59%of the areas are occupied by low,medium,high,and very high classes.Furthermore,the reliability of applied models was evaluated using the Area Under Curve(AUC)technique.The validation results utilizing the area under curve showed that the success rate curve(SRC)and predicted rate curve(PRC)for WOE are 82%and 86%,respectively,while SRC and PRC for FR are 85%and 96%,respectively.The validation results revealed that the FR model performance is better and more reliable than the WOE.
文摘The present study focuses on building a workflow for structural interpretation and velocity modeling and implementing to Jurassic-Cretaceous succession （Chiltan Limestone and Massive sand of the Lower Goru Formation）. 2D-Migrated seismic sections of the area are used as data set and in order to confirm the presence of hydrocarbons in the study area, P and S-wave seismic velocities are estimated from single-component seismic data. Some specific issues in the use of seismic data for modeling and hydrocarbon evaluation need to deal with including distinguishing the reservoir and cap rocks, and the effects of faults, folds and presence of hydrocarbons on these rocks. This study has carried out the structural interpretation and modeling of the seismic data for the identification of traps. The results demonstrate existence of appropriate structural traps in the form of horst and grabens in the area. 2D and 3D velocity modeling of the horizons indicates the presence of high velocity zones in the eastern half of the study while relatively low velocity zones are encountered in the western half of the area. Two wells were drilled in the study area （i.e. Fateh-01 and Ichhri-01） and both are dry. Immature hydrocarbons migration is considered as a failure reason for Fateh-01 and Ichhri-01 well.
文摘Conventional petrophysical investigations are based on P-wave seismic velocity analysis to predict density information, while ignoring the important S-wave velocity. This study is based on S-wave velocity analysis of density estimation of Meyal Oil Field(Potwar Plateau, Pakistan), which reveals a very high correlation(R=0.87) between predicted and actual density. Since the availability of S-wave velocity(Vs) data increases, it’s highly appreciable to take into account the contribution of Vs in improvement of density estimates. This investigation only focuses on driving new constants(a = 1.92 and b = 0.186) for Gardner’s relationship to estimate density of pure carbonates(Vsh< 10%) in the study area, where the traditional model gave poorer density predictions. The proposed empirical expression with locally extracted unknowns from well log data proved its ability in terms of density prediction(showing very close agreement with measured densities) and best fitting the datasets at low as well as high density values when compared with Gardner’s equation. Based on our analysis, the exploratory study neither intends to replace the well established density estimation models nor to extend information over what information can possibly be extractable from Vp. However, our research does stimulate the growing use of Vs and importance of local unknown constants especially in carbonates reservoir interval to avoid misuse of most widely used Gardner relation in all geological settings.
基金supported by ICIMODfunded by the governments of Afghanistan,Australia,Austria,Bangladesh,Bhutan,China,India,Myanmar,Nepal,Norway,Pakistan,Sweden,and Switzerland。
文摘The global cryosphere is experiencing accelerated melting due to climate change.Currently,the Karakoram anomaly is under discussion with a debate about the possibility that the anomaly may have recently ended.This study aims to evaluate the up-to-date changes in snow cover in the western Karakoram region.We observed the snow cover changes in Passu and Ghulkin valleys in the Hunza River basin(HRB)of the Karakoram through multitemporal Landsat satellite data between 1995 and 2022.We found a significant reduction in snow cover in these valleys,with an average reduction rate of 0.42 km~2/yr,resulting in a total reduction of~11.46 km~2 between 1995 and 2022.This reduction in snow cover is consistent with the mass loss of glaciers in the Karakoram region in recent years.The decline in snow cover in these valleys is also consistent with the meteorological data.The temperature in summer(June)has significantly increased whereas the precipitation in the accumulation season(March)has decreased.These rapid changes suggest that it is crucially important to monitor the snow cover on a regular basis to support downstream management of snowmelt runoff.In addition,there is a need of planning for mitigation and adaptation strategies for snow-related hazards.
