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.     

Influence of mid-latitude circulation on upper Indus basin precipitation: the explicit role of irrigation

Since much of the flow of the Indus River originates in the Himalayas, Karakoram and Hindu Kush Mountains, an understanding of weather characteristics leading to precipitation over the region is essential for water resources management. This study examines the influence of upper level mid-latitude circulation on the summer precipitation over upper Indus basin (UIB). Using reanalysis data, a geopotential height index (GH) is defined at 200 hPa over central Asia, which has a significant correlation with the precipitation over UIB. GH has also shown significant correlation with the heat low (over Iran and Afghanistan and adjoining Pakistan), easterly shear of zonal winds (associated with central Asian high) and evapotranspiration (over UIB). It is argued that the geopotential height index has the potential to serve as a precursor for the precipitation over UIB. In order to assess the influence of irrigation on precipitation over UIB, a simplified irrigation scheme has been developed and applied to the regional climate model REMO. It has been shown that both versions of REMO (with and without irrigation) show significant correlations of GH with easterly wind shear and heat low. However contrary to reanalysis and the REMO version with irrigation, the REMO version without irrigation does not show any correlation between GH index and evapotranspiration as well as between geopotential height and precipitation over UIB, which is further confirmed by the quantitative analysis of extreme precipitation events over UIB. It is concluded that although atmospheric moisture over coastal Arabian sea region, triggered by wind shear and advected northward due to heat low, also contribute to the UIB precipitation. However for the availability of necessary moisture for precipitation over UIB, the major role is played by the evapotranspiration of water from irrigation. From the results it may also be inferred that the representation of irrigated water in climate models is unavoidable for studying the impact of global warming over the region.     

A new class of bulk viscous universe with time dependent deceleration parameter and Λ-term

A new class of exact solutions of Einstein’s field equations with a bulk viscous fluid for an LRS Bianchi type-Ia obtained by using a time dependent deceleration parameter and cosmological term Λ. The coefficient of bulk viscosity is assumed to be a power function of mass density (ξ=ξ ₀ ρ ⁿ ). We have obtained a general solution of the field equations from which six models of the universe are derived: exponential, polynomial and sinusoidal form respectively. The behaviour of these models of the universe are also discussed in the frame of reference of recent supernovae Ia observations.      

A Comparative Study of Pollutant Removal Stability in Hybrid Wetland Columns

This study investigated the effects of two alternative substrates(wood mulch and zeolite) on the performance of three laboratory-scale hybrid wetland systems that had identical system components and configurations.Each system consisted of a vertical flow(VF) wetland column,followed by a horizontal flow(HF) column and a vertical flow column.The substrates employed were wood mulch,gravel and zeolite,and Phragmites australis were planted in each column.The systems received synthetic wastewater,with pollutant loadings in the range of 8.5-38.0 g/(m2·d) total nitrogen(TN) and 4.0-46.4 g/(m2·d) biological oxygen demand(BOD5).Wood mulch and zeolite substrates showed higher efficiencies in terms of removing nitrogenous compounds and biodegradable organics.The supply of organic carbon from the organic mulch substrates enhanced denitrification,while adsorption of influent ammoniacal nitrogen(NH4-N) in zeolite played a major role in the removal of nitrogenous species in the wetland columns.Overall,the average percentage removals of TN and BOD5 reached >66% and >96% respectively,indicating stable performances by the hybrid wetland systems under the experimental loading ranges.Mathematical models were developed,based on the combination of Monod kinetics and continuously-stirred tank reactor(CSTR) flow patterns to describe the degradation of nitrogenous compounds.Predictions by the models closely matched the experimental data,indicating the validity and potential application of Monod kinetics in the modelling and design of treatment wetlands.     

Prediction of copper content in waste dump of Sarcheshmeh copper mine using visible and near-infrared reflectance spectroscopy

The pore structure characteristics of soil are closely related to soil engineering properties. For saline soil distributed in seasonally frozen areas, existing studies have focused on the influence of freeze–thaw cycles on pore structure, while the influence of soluble salt in the soil is not well understood. This study aims to explore the influence of salt content and salt type on the pore structure of freeze-thawed soil. Soil samples with different salt contents (0–2%) and types (bicarbonate salt and sulfate salt) were subjected to 10 freeze–thaw tests, and their pore size distributions (PSDs) were obtained by mercury intrusion porosimetry tests. In addition, the PSDs were quantitatively analyzed by fractal theory. For both salts, the PSDs of the tested soil samples were bimodal after the freeze–thaw cycles, and the porosity of saline soil samples increased with increasing salt content overall. However, the contents of various types of pores in soil samples with two salt types were quite different. The variation in bicarbonate salt content mainly affected the mesopore and macropore contents in the soil samples, and their change trends were opposite to each other. For soil samples with sulfate salt, the porosity and macropore content increased significantly when the salt content exceeded 1%. In addition, the pore structures in saline soil presented fractal characteristics after the freeze–thaw cycles, and the fractal dimension was positively correlated with macropore content. This study may provide references for understanding the engineering properties of saline soil in seasonally frozen areas at the microscale.     

A novel approach for ports’ container terminals’ risk management based on formal safety assessment: FAHP-entropy measure—VIKOR model

Natural Hazards - Maritime transport, which requires complex, large, and long port systems, is a major system in the world trade, and since such systems face different risks, various methods have...     

Assessing desertification by using soil indices

Desertification generally refers to land degradation in arid, semiarid, and dry semi-humid climatic zones. It involves five principal processes: vegetation degradation, water erosion, wind erosion, salinization and waterlogging, and soil crusting and compaction. The aim of this study is assessing desertification using soil criteria. For this purpose, nine indices including sodium absorption ratio (SAR), soil gypsum percentage, soil texture, the content of HCO₃ ^?, the percentage of the organic matter, electrical conductivity (EC), pH, the content of the soil sodium, and chloride were used. The soil samples were taken in the north of Zayandeh-Rood River in Isfahan province of Iran, using soil data randomly sampled in a depth of 0–20 cm. After assessing the normality of the samples using Kolmogorov-Smirnov test, indices were imported into GIS environment and interpolated with IDW and normal and discrete kriging methods for delineating soil characteristics maps based on MEDALUS model. In this model, the data were firstly changed from 100 to 200. Thus 100 and 200 are estimated as the best and worst quality, respectively. Then the final map of soil criteria has been created by geometric mean of its indicators. The results showed that the maximum area is related to the medium class of desertification and is equal to 44,746 ha. The areas of severe and very severe classes of desertification are equal to 30,949 and 351 ha, respectively. The results also revealed that the indices of the organic matter and soil gypsum percentage are the most influential indices which affect desertification phenomenon.     

ODM: an analytical solution-based tool for reacting oxygen diffusion modelling in mine spoils

A simple one-dimensional analytical solution is presented to model oxygen diffusion through the pore space of mine spoils containing pyrite. The model incorporates volumetric oxygen consumption terms due to pyrite oxidation, oxidation of Fe ²⁺ to Fe ³⁺ and bacterial activity. Based on this analytical solution, a graphical user interface (GUI) tool is programmed and designed in MATLAB software. This tool can be used to model transport of oxygen through the mine spoils either with or without a cap. Results of several simulation scenarios of sensitivity analysis showed a significant change in oxygen concentration with varying effective diffusion coefficient of oxygen transport model and simulation time. Efficiency and flexibility of the tool developed here is verified by modelling oxygen transport through the pore space of a coal waste pile (case A) and a copper mine tailings (case B). Maximum depth of oxygen diffusion is obtained approximately equal to 2 and 1.5 m through the cases A and B, respectively.