Discussion: A review on the behaviour of helical piles as a potential offshore foundation system

Abstract

Helical piles have emerged as an attractive foundation system for offshore applications with renewed interest from the offshore community. Significant research gap currently exists in transferring this technology offshore and this paper discusses how existing and emerging knowledge can be successfully used to bridge some of the gaps. We focus on the Coupled Eulerian Lagrangian (CEL) large deformation finite element (LDFE) modelling technique that is commercially available and can be used to model the three-dimensional installation process with consideration of strain rate and softening effects in soft offshore clays. A helical pile of L?=?7.5?m long is modelled with one or two large-diameter helices (D?=?2?m) attached to a central shaft of d?=?0.5?m in diameter.The net effect of strain rate and softening is to increase the installation torque. The measured torque is within the range of 200–400?kN.m for the offshore clay and the pile geometry studied. Additional helices increase the uplift force but to a lesser degree than that of the measured torque. Remoulding induced strength reduction is found to be within the range of 25–33% of the intact clay strength. Issues of extracting and reusing offshore helical pile foundations are discussed.     

Hydrogeologic assessment of escalating groundwater exploitation in the Indus Basin, Pakistan

Groundwater development has contributed significantly to food security and reduction in poverty in Pakistan. Due to rapid population growth there has been a dramatic increase in the intensity of groundwater exploitation leading to declining water tables and deteriorating groundwater quality. In such prevailing conditions, the hydrogeological appraisal of escalating groundwater exploitation has become of paramount importance. Keeping this in view, a surface water–groundwater quantity and quality model was developed to assess future groundwater trends in the Rechna Doab (RD), a sub-catchment of the Indus River Basin. Scenario analysis shows that if dry conditions persist, there will be an overall decline in groundwater levels of around 10 m for the whole of RD during the next 25 years. The lower parts of RD with limited surface water supplies will undergo the highest decline in groundwater levels (10 to 20 m), which will make groundwater pumping very expensive for farmers. There is a high risk of groundwater salinization due to vertical upconing and lateral movement of highly saline groundwater into the fresh shallow aquifers in the upper parts of RD. If groundwater pumping is allowed to increase at the current rate, there will be an overall decline in groundwater salinity for the lower and middle parts of RD because of enhanced river leakage.     

Evaluation of Land Suitability for Urban Land‐Use Planning: Case Study Dhaka City

The aim of this research is evaluation of land suitability for urban land‐use planning. Four factors and fourteen criteria were selected for suitability analysis and land‐use planning. Factors and criteria were defined based on literature survey, experts’ opinions, local contexts and availability of data. GIS‐based Analytical Hierarchy Process (AHP) was used as a Multi‐criteria Decision Making model. The study was conducted on a selected area of Dhaka city, which is one of the fastest growing mega‐cities of the world. The research result shows that highly suitable area (13%) should be used for urban residential zone; moderately suitable area (35%) should be designated as mixed use zone; low suitable area (42%) should be reserved for agricultural use and open spaces; and not suitable area (10%) should be protected from any types of activities except agriculture. The research approached an urban land‐use planning at a regional scale.     

Spatial assessment of forest cover and land-use changes in the Hindu-Kush mountain ranges of northern Pakistan

Anthropogenic activities and natural processes are continuously altering the mountainous environment through deforestation, forest degradation and other land-use changes. It is highly important to assess, monitor and forecast forest cover and other land-use changes for the protection and conservation of mountainous environment. The present study deals with the assessment of forest cover and other land-use changes in the mountain ranges of Dir Kohistan in northern Pakistan, using high resolution multi-temporal SPOT-5 satellite images. The SPOT-5 satellite images of years 2004, 2007, 2010 and 2013 were acquired and classified into land-cover units. In addition, forest cover and land-use change detection map was developed using the classified maps of 2004 and 2013. The classified maps were verified through random field samples and Google Earth imagery (Quick birds and SPOT-5). The results showed that during the period 2004 to 2013 the area of forest land decreased by 6.4%, however, area of range land and agriculture land have increased by 22.1% and 2.9%, respectively. Similarly, barren land increased by 1.1%, whereas, area of snow cover/glacier is significantly decreased by 21.3%. The findings from the study will be useful for forestry and landscape planning and can be utilized by the local, provincial and national forest departments; and REDD+ policy makers in Pakistan.     

Health risk of heavy metals from vegetables irrigated with sewage water in peri-urban of Dera Ismail Khan,Pakistan

Health risks of heavy metals in vegetables irrigated with sewage water were investigated in the present study. The findings indicated a massive accumulation of heavy metals in soil and vegetables collected from Dera Ismail khan, Pakistan. The concentration levels of heavy metal in vegetables grown on soil irrigated with untreated sewage water were significantly higher at (P ≤ 0.001) than in vegetables grown on fresh-water-irrigated soil and proceeded the recommended limits of World health organization. Moreover, the findings also indicated that the adults and children consuming such vegetables ingested a large proportion of the selected toxic metals. Health risk index was greater than one for Pb and Cd in all the selected vegetables and was greater than one for Ni in three vegetables like Spinacia oleracea, Benincasa fistulosa and Lactuca sativa. Health risk assessment would be a useful tool for information regarding any threats of heavy metals contamination in vegetables.     

Geospatial assessment of soil erosion intensity and sediment yield: a case study of Potohar Region,Pakistan

Estimation of spatial extent of soil erosion, one of the most serious forms of land degradation, is critical because soil erosion has serious implications on soil fertility, water ecosystem, crop productivity and landscape beauty. The primary objective of the current study was to assess and map the soil erosion intensity and sedimentation yield of Potohar region of Pakistan. Potohar is the rainfed region with truncated and complex topography lying at the top of the Indus Basin, the world’s largest irrigation networks of canals and barrages. Spatially explicit Revised Universal Soil Loss Equation (RUSLE) Model integrated with Remote Sensing-GIS techniques was used for detecting/mapping of erosion prone areas and quantification of soil losses. The results show that the Potohar region is highly susceptible to soil erosion with an average annual soil loss of 19 tons ha^?1 year^?1 of which the maximum erosion (70–208 tons ha^?1 year^?1) was near the river channels and hilly areas. The sediment yield due to the erosion is as high as 148 tons ha^?1 year^?1 with an average of 4.3 tons ha^?1 year^?1. It was found that 2.06% of the total area falls under severe soil erosion, 13.34% under high erosion, 15.35% under moderate soil erosion while 69.25% of the area lies in the low (tolerable) soil erosion. Chakwal and Jhelum districts of the region are seriously affected by erosion owing to their topography and soil properties. The information generated in this study is a step forward towards proper planning and implementation of strategies to control the erosion and for protection of natural resources. It is, hence, necessary that suitable water harvesting structures be made to control water to prevent soil erosion and provision of water in the lean season in this region. Tree plantation and other erosion control practices such as strip cropping can also minimize soil erosion in this region.     

Socio-economic drivers of deforestation in Roghani Valley,Hindu-Raj Mountains,Northern Pakistan

Deforestation and associated ecological disturbances are the issues of global concern.Researchers have investigated a number of driving forces which accelerate the rate of deforestation at local and regional levels.These include poverty,population growth,market demand and prices,political instability,agricultural expansion and changes in property right and ownership regimes.This paper seeks to explore the impacts of population growth,changing tenure system and other socioeconomic factors on the forest cover of Roghani Valley,located in Hindu Raj Mountains,Northern Pakistan.The present study is mainly based on information collected through participatory observation,selfadministered interviews and questionnaire survey.Geographical Information System（GIS） database is also used for mapping and quantification.The results reveal that in the past three to four decades the study area has been subjected to severe deforestation and about half of the forest area has been converted into barren land.Thus,the area under natural forests decreased from 2099 to 1444 hectares in four decades.This large-scale deforestation is attributed to both proximate and under lying causes particularly traditional land tenure system and demographic development.Consequently,forest resources have been degraded and a number of plant species have disappeared from the forests of the study area while several others are in the process of disappearance.     

Yield Forecasting of Spring Maize Using Remote Sensing and Crop Modeling in Faisalabad-Punjab Pakistan

Real time, accurate and reliable estimation of maize yield is valuable to policy makers in decision making. The current study was planned for yield estimation of spring maize using remote sensing and crop modeling. In crop modeling, the CERES-Maize model was calibrated and evaluated with the field experiment data and after calibration and evaluation, this model was used to forecast maize yield. A Field survey of 64 farm was also conducted in Faisalabad to collect data on initial field conditions and crop management data. These data were used to forecast maize yield using crop model at farmers’ field. While in remote sensing, peak season Landsat 8 images were classified for landcover classification using machine learning algorithm. After classification, time series normalized difference vegetation index (NDVI) and land surface temperature (LST) of the surveyed 64 farms were calculated. Principle component analysis were run to correlate the indicators with maize yield. The selected LSTs and NDVIs were used to develop yield forecasting equations using least absolute shrinkage and selection operator (LASSO) regression. Calibrated and evaluated results of CERES-Maize showed the mean absolute % error (MAPE) of 0.35–6.71% for all recorded variables. In remote sensing all machine learning algorithms showed the accuracy greater the 90%, however support vector machine (SVM-radial basis) showed the higher accuracy of 97%, that was used for classification of maize area. The accuracy of area estimated through SVM-radial basis was 91%, when validated with crop reporting service. Yield forecasting results of crop model were precise with RMSE of 255 kg ha^?1, while remote sensing showed the RMSE of 397 kg ha^?1. Overall strength of relationship between estimated and actual grain yields were good with R² of 0.94 in both techniques. For regional yield forecasting remote sensing could be used due greater advantages of less input dataset and if focus is to assess specific stress, and interaction of plant genetics to soil and environmental conditions than crop model is very useful tool.     

Investigation of seasonal droughts and related large-scale atmospheric dynamics over the Potwar Plateau of Pakistan

As a result of climate change and unsustainable land use management in the recent past, droughts have become one of the most devastating climatic hazards whose impacts may prolong from months to years. This study presents analysis of droughts for two major cropping seasons, i.e., Kharif (May–September) and Rabi (October–April), over the Potwar Plateau of Pakistan. The analysis is performed using various datasets viz. observational, reanalysis, and Regional Climate Models (RCMs), for the past (1981–2010) and future (2011–2100) time periods. The following two methods for the identification of dry and wet years, also referred to as drought and wetness, are applied: (1) the percentile rank approach and (2) the drought indices, Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI). Future projections of droughts are investigated using RCM (RegCM4.4 and RCA4) outputs from CORDEX South Asia domain under two Representative Concentration Pathway (RCP) scenarios, RCP4.5 and RCP8.5. Generally, the indices show non-significant decreasing trends of drought severity in the recent past for all cases; however, significant increasing trends are observed for annual (0.006) and Kharif (0.007) cases under RCP4.5 scenario. The analysis of large-scale atmospheric dynamics suggests the significant role of low-level geopotential height anomalies over Tibetan Plateau (northwest of Pakistan) during Kharif (Rabi) season in controlling drought occurrence by transporting moisture from the Bay of Bengal (Arabian Sea). Moreover, composites of vertically integrated moisture transport, moisture flux convergence/divergence, and precipitable water anomalies show their marked contribution in maintaining the drought/wetness conditions over the Potwar region.