Interactive effect of nitrogen fertilizer and hydrocarbon pollution on soil biological indicators   总被引：2，自引：1，他引：1  

Somayeh Emami  Ahmad Ali Pourbabaei  Hossein Ali Alikhani 《Environmental Earth Sciences》2014,72(9):3513-3519

The investigation of the impact of different forms of nitrogen fertilizer (NO₃-N and NH₄-N) on microbial parameters, enzyme activities and phytotoxicity in a petroleum-contaminated soil was evaluated by an incubation study. The tested enzymes, microbial activity and seed germination index showed different patterns in response to both petroleum and nitrogen fertilizer addition and time of incubation. The results apparently showed that the contamination of soil with petroleum has a negative effect on soil ecosystem. Nitrogen fertilizer could improve inhibition of petroleum hydrocarbons in soil. Nevertheless, nitrogen fertilizer had no significant effect on urease activity in the petroleum-contaminated soil. As compared to NO₃-N, the addition of NH₄-N to the soil resulted in a greater impact on soil performance as attested by the recovery of the soil germination capability and higher values of the respiration. The application of nitrogen fertilizer may be suggested as a good strategy for restoring soils in regions affected by the same problem.  相似文献   

Geomorphic analysis reveals active tectonic deformation on the eastern flank of the Pir Panjal Range,Kashmir Valley,India     

Shabir Ahmad  M. I. Bhat  Christopher Madden  B. S. Bali 《Arabian Journal of Geosciences》2014,7(6):2225-2235

There are plenty of faults that show evidence that they are active. Most of the valley’s floor is occupied by unconsolidated Karewa deposits, in particular on the south–southwest of the Kashmir Valley. In such situations, geomorphic data can reveal the location of active faults. Accordingly, we tried to identify geomorphic indices in SW of the Kashmir Valley (Veshav, Rambiara, and Romushi drainage basins), which revealed the area to be potentially tectonically active. This active faulting was further substantiated by drainage anomalies and field investigations, which provides evidence for an emergent out-of-sequence NE-dipping active reverse fault (identified first time on ground) named the Balapur Fault (BF). The BF can be traced over at least 40 km along the southwest side of the Kashmir Valley. The existence of the active Balapur Fault and of two other inferred faults north of the Panjal Thrust or Murree Thrust presents a picture of a more complex strain-partitioning regime in the Kashmir Himalayas than is usually visualized.  相似文献   

Remote Sensing based assessment of glacial lake growth on Milam glacier,Goriganga basin,Kumaon Himalaya     

K. Babu Govindha Raj  K. Vinod Kumar  Rakesh Mishra  Muneer Ahmad Mukhtar 《Journal of the Geological Society of India》2014,83(4):385-392

The climate change of the twentieth century had an evident effect on glacier environments of the Himalaya. Temporal images of Indian Remote Sensing satellites provide an opportunity to monitor the recession of glacier and development of glacial lakes in the Himalayan cryosphere with a cost to time benefit ratio. The recession of Milam glacier and subsequent growth of a proglacial lake near the snout was analysed using Resourcesat-1 and Resourcesat-2 data. The recession of 480 m during 2004 to 2011 and growth of 47 epiglacial ponds over Milam glacier shows the glacier is in a state of imbalance and losing the ice by downwasting.  相似文献   

Hydrogeochemical assessment of groundwater in Kashmir Valley,India     

G H Jeelani  Rouf Ahmad Shah  Aadil Hussain 《Journal of Earth System Science》2014,123(5):1031-1043

Groundwater samples (n = 163) were collected across Kashmir Valley in 2010 to assess the hydrogeochemistry of the groundwater in shallow and deep aquifers and its suitability for domestic, agriculture, horticulture, and livestock purposes. The groundwater is generally alkaline in nature. The electrical conductivity (EC) which is an index to represent the total concentration of soluble salts in water was used to measure the salinity hazard to crops as it reflects the TDS in groundwater ranging from 97 to 1385 μS/cm, except one well in Sopore. The average concentration of major ions was higher in shallow aquifers than in deeper aquifers. In general, Ca²⁺ is the dominant cation and HCO \(_{3}^{-}\) the dominant anion. Ca–HCO₃, Mg–HCO₃, Ca–Mg–HCO₃, Na–HCO₃ were the dominant hydrogeochemical facies. High concentration of HCO₃ and pH less than 8.8 clearly indicated that intense chemical weathering processes have taken place in the study area. The groundwater flow pattern in the area follows the local surface topography which not only modifies the hydrogeochemical facies but also controls their distribution. The groundwater in valley flows into four directions, i.e., SW–NE, NE–W, SE-NW and SE–NE directions. The results suggest that carbonate dissolution is the dominant source of major ions followed by silicate weathering and ion-exchange processes. The concentrations of all the major ions determined in the present study are within the permissible limits of WHO and BIS standards. The results of Total Hardness, SAR, Na%, Kelly Index, USDA classification, Magnesium absorption ratio, residual sodium carbonate, and PI suggested that groundwater is good for drinking, livestock, and irrigation purposes.  相似文献   

Prediction of Land Cover Change Using Markov and Cellular Automata Models: Case of Al-Ain,UAE, 1992-2030   总被引：1，自引：0，他引：1  

M. M. Yagoub  Abdallah Ahmad Al Bizreh 《Journal of the Indian Society of Remote Sensing》2014,42(3):665-671

The UAE has witnessed rapid urban development and economic growth in recent years. With its ambitious vision to become one of the advanced nations by 2021, planners and policy-makers need to know the most likely direction of future urban development. In this study, remotely sensed imagery coupled with cellular automata models were used to predict land cover in Al Ain, the second largest city in the Emirate of Abu Dhabi. Markov and cellular automata models were used for 1992 and 2006 to predict land cover in 2012. Land Use and Land Cover maps for the study area were derived from 1992, 2006, and 2012 Landsat satellite images (TM, ETM⁺). The models achieved an overall accuracy of approximately 80 %. A Markov model was applied for 2006 and 2012 to predict land cover in 2030. The results conformed to the general trend of the Al Ain Master Plan 2030. This study demonstrates that remote sensing, with the availability of free Landsat data, is a viable technology that could be used to help in the prediction process especially in developing countries, where data availability is a problem.  相似文献   

Markov CA,Multi Regression,and Multiple Decision Making for Modeling Historical Changes in Kirkuk City,Iraq     

Najat Qader Omar  Mohd Sanusi S. Ahamad  Wan Muhd Aminuddin Wan Hussin  Narimah Samat  Siti Zubaidah Binti Ahmad 《Journal of the Indian Society of Remote Sensing》2014,42(1):165-178

The cellular automata (CA) model is an important tool in land use change studies. Swift increases in population and long-term expectations of rapid urbanization have led to extensive land use change, and normal living conditions have affected the natural resources of the land. This paper highlights and analyzes the historical urban changes in Kirkuk City, Iraq, considering repeated changes undergone by the state such change as government infrastructures, wars, and economic blockade. In this paper, an integrated model, built-in multi regression model, and multi-criteria evaluation were considered to improve the representation of CA transition rules. Environmental and socioeconomic factors were used to produce Suitable Maps (SMs). These SMs were practicalities to create factor layers and weight usage, rating method process for variance expert decision-making groups, and geographic information systems for the periods 1984, 1990, 2000, and 2010. The roots of the equation (R²) values are compared and these values are chosen to produce a good model of suitable maps. The approach used in this study provides a mechanism for monitoring suitability maps in Kirkuk. Furthermore, the model Markov CA is implemented and evaluated. The results indicate that the model, its related concepts performs sufficiency  相似文献   

Gravitational clustering of galaxies in an expanding universe     

Naseer Iqbal  Farooq Ahmad  M. S. Khan 《Journal of Astrophysics and Astronomy》2006,27(4):373-379

We inquire the phenomena of clustering of galaxies in an expanding universe from a theoretical point of view on the basis of thermodynamics and correlation functions. The partial differential equation is developed both for the point mass and extended mass structures of a two-point correlation function by using thermodynamic equations in combination with the equation of state taking gravitational interaction between particles into consideration. The unique solution physically satisfies a set of boundary conditions for correlated systems and provides a new insight into the gravitational clustering problem.  相似文献   

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

Ishfaq Ahmad  Umer Saeed  Muhammad Fahad  Asmat Ullah  M. Habib ur Rahman  Ashfaq Ahmad  Jasmeet Judge 《Journal of the Indian Society of Remote Sensing》2018,46(10):1701-1711

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.  相似文献   

Dispersive thermohaline convection near salt domes: a case at Napoleonville Dome,southeast Louisiana,USA     

Zahra Jamshidzadeh  Frank T. -C. Tsai  Hasan Ghasemzadeh  Seyed Ahmad Mirbagheri  Majid Tavangari Barzi  Jeffrey S. Hanor 《Hydrogeology Journal》2015,23(5):983-998

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Estimation of rainfall threshold and its use in landslide hazard mapping of Kuala Lumpur metropolitan and surrounding areas     

Omar F. Althuwaynee  Biswajeet Pradhan  Noordin Ahmad 《Landslides》2015,12(5):861-875

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