Potassium induced salinity tolerance in wheat (Triticum aestivum L.)

Water culture experiments were conducted to study the response of ten wheat genotypes to external K application (10 mmol KCI dm^?3) at seedling stage under saline condition (0 and 100 mmol NaCl dm^?3). The data showed that there was an increase in the shoot and root length with the application of external K. The increase was more pronounced under control than under saline conditions. The better performing genotypes under two treatments were Bhitai, NIAB-41, NIAB-I076 and Khirman. The enhanced growth of these genotypes under saline condition might be due to the quick response to external K application, resulting in high K/Na ratio. The results indicated that the genotypes, which have the ability of enhanced K/Na discrimination, might perform better under saline conditions when sufficient potassium is applied in the rooting medium.     

Urban development and flooding in Houston Texas, inferences from remote sensing data using neural network technique

The effects of urban development on the natural ecosystem and its link to the increased flooding in Houston, Texas were evaluated. Houston is suitable for this type of analysis due to its 1.95 million population, large geographic area and fast growth rate. Using neural network techniques, four Landsat Thematic Mapper images were grouped into five land use classes for the period 1984 to 2003: vegetation, bare ground, water, concrete and asphalt. Results show that asphalt and concrete increased 21% in the time period 1984–1994, 39% in 1994–2000 and 114%, from 2000 to 2003, while vegetation suffered an overall decrease. When change detection data are compared with runoff ratio data, a relationship between increased runoff and urban development is apparent, which indicates increased chances of flooding. Initial results of this work are made available to the public in GIS format via internet using Arc Internet Map Server (ArcIMS) at .     

Selection of hazardous waste dumpsites based on parameters effecting soil adsorption capacity – a case study

A careful selection of waste dumpsites, particularly hazardous ones, is very important for sustainable water resources management. Several laboratory experiments were carried out on the field samples to study adsorption capacity using p-dichlorobenzene (a solvent used in various industrial processes) as the test contaminant. The effect of parameters such as organic matter, clay, and iron and aluminium oxides, which are known to influence the soil adsorption capacity, are studied in the present work. Several soil samples from the Patancheru Industrial Area (Hyderabad, India) were collected and characterized. Only three soils, which had a comparatively high percentage of organic matter, clay, iron and aluminium oxide contents were used for the adsorption studies. The results clearly indicated a decrease in the adsorption capacity of the soils by as much as 75% when organic matter was removed. The other parameters such as clay and iron and aluminium oxides also play an important role in adsorption (57 and 39.8% reduction respectively). It was observed that out of the selected factors organic matter in the soils has the maximum effect regarding the adsorption of p-dichlorobenzene. Since the selected soils contain comparatively more organic matter, clay and iron and aluminium oxides in the selected industrial area, these can be used as sites for dumping hazardous waste, which can be further treated by methods like bioremediation.     

Complexity measurement of regional groundwater resources system using improved Lempel-Ziv complexity algorithm

In this paper, the self-adaptive artificial fish swarm algorithm (SAAFSA) is used to optimize the coarse graining of segment numbers, which are used in the Lempel-Ziv complexity algorithm. This approach improves the Lempel-Ziv complexity (LZC) algorithm of equal probability coarse graining. As a case study, the complexities of monthly series of groundwater depth were analyzed at seven farms in the Hongxinglong Administration. GIS technology was used to create spatial distributions of monthly groundwater depths. A projection pursuit model based on the SAAFSA was established and used for complexity attribution analysis at selected farms with different degrees of complexity. The three selected farms, Hongqiling, 852, and Youyi, each represent a certain degree of complexity. Further analysis shows that precipitation, evaporation, temperature, and human activities are the primary factors that cause complexity variations in local groundwater depth. The results reveal the evolution of the complexity characteristics of local groundwater depth and provide scientific evidence for the need to effectively allocate regional water resources. Additionally, the proposed method can be applied in complexity analyses of other hydrologic features, as well as in research regarding nonlinear time series in economic, engineering, medical, and signal analyses.     

Practical Incorporation of Multivariate Parameter Uncertainty in Geostatistical Resource Modeling

There is a need to bridge theory and practice for incorporating parameter uncertainty in geostatistical simulation modeling workflows. Simulation workflows are a standard practice in natural resource and recovery modeling, but the incorporation of multivariate parameter uncertainty into those workflows is challenging. However, the objectives can be met without considerable extra effort and programming. The sampling distributions of statistics comprise the core theoretical notion with the addition of the spatial degrees of freedom to account for the redundancy in the spatially correlated data. Prior parameter uncertainty is estimated from multivariate spatial resampling. Simulation-based transfer of prior parameter uncertainty results in posterior distributions which are updated by data conditioning and the model domain extents and configuration. The results are theoretically tractable and practical to achieve, providing realistic assessments of uncertainty by accounting for large-scale parameter uncertainty, which is often the most important component impacting a project. A simulation-based multivariate workflow demonstrates joint modeling of intrinsic shale properties and uncertainty in estimated ultimate recovery in a shale gas project. The multivariate workflow accounts for joint prior parameter uncertainty given the current well locations and results in posterior estimates on global distributions of all modeled properties. This is achieved by transferring the joint prior parameter uncertainty through conditional simulations.     

Seismic stratigraphy of the Mianwali and Bannu depressions,north-western Indus foreland basin

International Journal of Earth Sciences - Regional seismic reflection profiles, deep exploratory wells, and outcrop data have been used to study the structure and stratigraphic architecture of the...     

Application of Artificial Intelligence to Estimate Oil Flow Rate in Gas-Lift Wells

Natural Resources Research - Optimization and monitoring schemes for oil well and reservoir system require accurate estimation of production rate. Real-time monitoring is conducted typically using...     

Physical and geometrical parameters of VCBS XIII: HIP 105947

The best physical and geometrical parameters of the main sequence close visual binary system(CVBS), HIP 105947, are presented. These parameters have been constructed conclusively using Al-Wardat's complex method for analyzing CVBSs, which is a method for constructing a synthetic spectral energy distribution(SED) for the entire binary system using individual SEDs for each component star. The model atmospheres are in its turn built using the Kurucz(ATLAS9) line-blanketed plane-parallel models. At the same time, the orbital parameters for the system are calculated using Tokovinin's dynamical method for constructing the best orbits of an interferometric binary system. Moreover, the mass-sum of the components, as well as the ?θ and ?ρ residuals for the system, is introduced. The combination of Al-Wardat's and Tokovinin's methods yields the best estimations of the physical and geometrical parameters. The positions of the components in the system on the evolutionary tracks and isochrones are plotted and the formation and evolution of the system are discussed.