Effect of heat treatment on dynamic properties of selected rock types taken from the Salt Range in Pakistan

Temperature is one of the variables that influence the elasto-plastic behavior and integrity of rock outcrops. Fluctuations in temperature can trigger alteration of some of the mineral properties and impact the brittle-plastic transition. Initiation and propagation of thermally induced tension cracks tend to weaken most rock types. The principal goal of this study was to anticipate impacts of thermal stress-strain cycles on the dynamic response of representative rock units exposed in the Khewra Gorge of the Salt Range Punjab of Pakistan. Ten types of sedimentary rock units were sampled, including marl, dolomite, three types of limestone, and five different sandstones exhibiting varying characteristics in outcrop. Boulder specimens were collected from the field and transported to the laboratory to prepare 50 drill cores that could be subjected to thermal cycling between 50 and 200 °C in increments of 50 °C. Room temperature core samples were tested using an Erudite resonance frequency meter to measure their Q-factors and the resonance frequency (F_r) at an applied loading frequency of 7 KHz with 0.01 V output voltage. Results suggest that thermal cycling tends to reduce the dynamic Young’s modulus (E_d) and Q-factor. Other parameters, such as damping ratio (ξ), specific damping capacity (Ψ), and loss factor (?) appeared to increase with increasing temperature cycles, likely as a result of developing thermally induced tensile fractures. The resultant values of the null hypothesis (t-critical and t-stats) suggests that the null hypothesis can be discarded because there was no observable difference between the measured and expected values for the cores tested. The observations and data emanating from this study might be useful in designing low-level radioactive waste landfills, nuclear waste repositories, and deep underground excavations where the increased temperature could alter the mechanical behavior of the parent rock mass.     

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.     

Floods: impacts on livelihood,economic status and poverty in the north-west region of Pakistan

Natural Hazards - Climate change-induced floods have diversified effects on the physical and economic system of the dwelling societies. These effects mainly hit agricultural livelihood and...     

Simultaneous perturbation stochastic approximation for tidal models

The Dutch continental shelf model (DCSM) is a shallow sea model of entire continental shelf which is used operationally in the Netherlands to forecast the storm surges in the North Sea. The forecasts are necessary to support the decision of the timely closure of the moveable storm surge barriers to protect the land. In this study, an automated model calibration method, simultaneous perturbation stochastic approximation (SPSA) is implemented for tidal calibration of the DCSM. The method uses objective function evaluations to obtain the gradient approximations. The gradient approximation for the central difference method uses only two objective function evaluation independent of the number of parameters being optimized. The calibration parameter in this study is the model bathymetry. A number of calibration experiments is performed. The effectiveness of the algorithm is evaluated in terms of the accuracy of the final results as well as the computational costs required to produce these results. In doing so, comparison is made with a traditional steepest descent method and also with a newly developed proper orthogonal decomposition-based calibration method. The main findings are: (1) The SPSA method gives comparable results to steepest descent method with little computational cost. (2) The SPSA method with little computational cost can be used to estimate large number of parameters.     

Deciphering heavy metal contamination zones in soils of a granitic terrain of southern India using factor analysis and GIS

Soil contamination by heavy metals has been a major concern for last few decades due to increase in urbanization and industrialization. The main objective of this research was to identify the heavy metal contaminated zones in the study area. Twenty five soil samples collected throughout the agriculture, residential and industrial areas were analysed by X-ray Fluorescence Spectrometer (XRF) for trace metals and major oxides. These metals can affect the quality of soil and infiltrate through the soil, thereby causing groundwater pollution. Based on the chemical analysis of major oxides (SiO_2, Al₂O_3, ?Fe₂O_3, MnO, MgO, CaO, Na₂O, K₂O, TiO₂, and P₂O₅) and their distribution; it is observed that these soils are predominantly siliceous type with slight enrichment of alumina component in the study area. Correlation matrix (CM) and factor analysis (FA) is employed to the heavy metal variables, viz., Ba, Cr, Cu, Ni, Pb, Rb, Sr, V, Y, Zn and Zr of the soil to determine the dominant factors contributing to the soil contamination in the area. In the analysis, five factors emerged as significant contributors to the soil quality. The total contribution of these five factors is about 90%. The contribution of the first factor is about 45% and has significant positive loadings of Co, Cr, Cu, Ni and Zn. The contribution of second factor is 22% and has significant positive loadings of Rb, Sr and Y. The contribution of third, fourth and fifth factors is 10, 8 and 5% and show positive loadings for lead, molybdenum and barium respectively to the soil contamination. The spatial variation maps deciphering different zones of heavy metal concentration in the soil were generated in a GIS (geographic information system) based environment using ArcGIS 9.3.1. The results reveal that heavy metal contamination in the area is mainly due to anthropogenic activities.     

Diatom-derived palaeoconductivity estimates for Lake Awassa, Ethiopia: evidence for pulsed inflows of saline groundwater

A 6,500-year diatom stratigraphy has been used to infer hydrochemical changes in Lake Awassa, a topographically closed oligosaline lake in the Ethiopian Rift Valley. Conductivity was high from ~6400-6200 BP, and from 5200-4000 BP, with two brief episodes of lower conductivity during the latter period. Although the timing of the conductivity changes is similar to the timing of lake-level change in the nearby Zwai-Shalla basin, their directions are the reverse of that expected from a climatic cause. Dissolution of the tephras which precede both phases of high conductivity cannot explain the increases in salinity, because rhyolitic tephras are only sparingly soluble. Instead, the pulsed input of groundwater made saline by the reaction of silicate minerals and volcanic glass with carbonic acid, formed from the solution of carbon dioxide degassed from magma under the Awassa Caldera, is suggested as a plausible mechanism for the observed change in lake chemistry. Diatom-inferred hydrochemistry cannot therefore be used to reconstruct climate change in Lake Awassa.     

Tectonic Imprints of the Hazara Kashmir Syntaxis on the Mesozoic Rocks Exposed in Munda,Mohmand Agency,Northwest Pakistan

Two well-developed mesoscopic folds, D_2 and D_3, which postdate the middle amphibolite metamorphism, were recognized in the western hinterland zone of Pakistan. NW–SE trending D_2 folds developed during NE–SW horizontal bulk shortening followed by NE–SW trending D_3 folds, which developed during SE–NW shortening. Micro- to mesoscopically the NW–SE trending S2 crenulation cleavage, boudins and mineral stretching lineations are overprinted by D_3. The newly established NW–SE trending micro- to mesoscopic structures in Munda termed D_2, which postdated F_1/F_2, is synchronously developed with F3 structures in the western hinterland zone of Pakistan. We interpret that D_2 and D_3 folds are counterclockwise rotated in the tectonic event that has evolved the Hazara Kashmir Syntaxis after the main phase Indian plate and Kohistan Island Arc collision. Chlorite replacement by biotite in the main matrix crenulation cleavages indicates prograde metamorphism related with D_2. The inclusion of muscovite and biotite in garnet porphyroblasts and the presence of staurolite in these rocks indicate that the Barrovian metamorphic conditions predate D_2 and D_3. We interpret that garnet, staurolite and calcite porphyroblasts grew before D_2 because the well developed S2 crenulation cleavage wraps around these porphyroblasts.     

Impact analysis of climate change on Kolahoi Glacier in Liddar Valley,north-western Himalayas

Glaciers are among the most conspicuous and dynamic features on the earth’s surface and are also highly sensitive to changes in climatic parameters. Glaciers in the Kashmir Himalayas have been reported to be retreating due to climate forcing. Kolahoi Glacier is one of the largest and important glaciers of the Kashmir Himalayas and is the main source of Liddar River, which is the largest tributary of the Jhelum River system. In the present study, an analysis to assess the response of Kolahoi Glacier to the changing climate was carried out using the Survey of India (SoI) map and multi-temporal Landsat satellite data. The results show a significant change in the spatial extent of Kolahoi Glacier. The total area of this glacier has reduced from 12.21 km² in 1962 to 11.61 km² in 2010. An analysis of meteorological data (temperature and precipitation) shows that the average annual temperature increased from 9.1 °C in 1980–1989 to 10.3 °C in 2000–2009, while the precipitation decreased from 1329.44 to 1126.89 mm during the same period. The results suggest that this glacier will be annihilated completely if the same retreating trend continues.     

A high‐resolution multi‐proxy stalagmite record from Mechara,Southeastern Ethiopia: palaeohydrological implications for speleothem palaeoclimate reconstruction

An annually laminated stalagmite from Southeastern Ethiopia grew for 443±8 yr starting at 5023 yr BP (±160 yr) as determined by lamina‐tuned U‐Th dating. The speleothem shows three growth phases: (1) an initial phase where the stalagmite has a candlestick shape, deposited by relatively slow rate drip water; (2) a middle growth phase where laminae grow on the flanks, suggesting faster drip rates; and (3) a final growth phase where the speleothem becomes narrower owing to a decrease in drip water supply towards the end of deposition. Morphometry, annual growth rate, fluorescence index, and ²³⁴U/²³⁸U isotope ratio show marked differences between the growth phases, while δ¹³C and δ¹⁸O do not show significant variation, except within the third phase towards the top of the stalagmite, where they have higher values. The study indicates that the multiproxy approach is crucial as the different proxies respond to single climate forcing in different manners. Our results can be widely applied to speleothem studies distinguishing the relative importance of the various proxies in recording cave ‘external’ (climate, hydrology) and cave ‘internal’ (e.g. evaporation) processes. Copyright © 2006 John Wiley & Sons, Ltd.