A new approach for developing comprehensive agricultural drought index using satellite-derived biophysical parameters and factor analysis method

The accurate assessment of drought and its monitoring is highly depending on the selection of appropriate indices. Despite the availability of countless drought indices, due to variability in environmental properties, a single universally drought index has not been presented yet. In this study, a new approach for developing comprehensive agricultural drought index from satellite-derived biophysical parameters is presented. Therefore, the potential of satellite-derived biophysical parameters for improved understanding of the water status of pistachio (Pistachio vera L.) crop grown in a semiarid area is evaluated. Exploratory factor analysis with principal component extraction method is performed to select the most influential parameters from seven biophysical parameters including surface temperature (T _s), surface albedo (α), leaf area index (LAI), soil heat flux (G _o), soil-adjusted vegetation index (SAVI), normalized difference vegetation index (NDVI), and net radiation (R _n). T _s and G _o were found as the most effective parameters by this method. However, T _s, LAI, α, and SAVI that accounts for 99.6 % of the total variance of seven inputs were selected to model a new biophysical water stress index (BPWSI). The values of BPWSI were stretched independently and compared with the range of actual evapotranspiration estimated through well-known METRIC (mapping evapotranspiration at high resolution with internal calibration) energy balance model. The results showed that BPWSI can be efficiently used for the prediction of the pistachio water status (RMSE of 0.52, 0.31, and 0.48 mm/day on three image dates of April 28, July 17, and August 2, 2010). The study confirmed that crop water status is accounted by several satellite-based biophysical parameters rather than single parameter.     

Computing eddy-current response and current-channeling response of the spheroidal conductor for the separated receiver and transmitter systems

In this article the response of the induced eddy-current in an unlimited conduction spheroidal as well as the response of the current-channeling resulted from the presence of the spheroidal in a weakly conducted medium are derived. The common methods are based on receiving electromagnetic induction response from the homocentric and coaxial receiver and transmitter coils which are exactly over the anomaly. As the spheroidal location is unknown in the practice, it is suggested to measure the electromagnetic induction response in a case that the receiver and the transmitter have an arbitrary situation regarding to the anomaly. In this article, eddy-current response and current-channeling response of the spheroid have been computed in a more general case in which at least one axis of spheroid and the dipole axes of the receiver and transmitter coils are on the same plate; however, none of the coils are laid over the anomaly. Using this method, we can determine the location and the depth of the spheroid through fixing the transmitter’s position and of the receivers’ coil movements.     

Cavity effect on Rayleigh wave dispersion and P-wave refraction

Sinkholes and cavities can represent serious hazards to human safety and urban infrastructures,cause roadbed subsidence,and so on.It is therefore essential to evaluate various sinkholes in different depths and sizes to assess the risk of collapse.This paper evaluates the effect of different cavities on Rayleigh-wave propagation and body(P)wave refraction.Rayleigh(R)wave propagation is analyzed according to the classical multi-channel analysis of surface waves(MASW)method also considering the R-wave backscattering.Synthetic seismic traces are computed by means of finite element modeling(FEM)for cavity and intrusion at different depths and sizes.Furthermore,field acquisition data is used to verify the detection effect of a cavity on R-and P-waves.The results show that the presence of backscattered R-waves and the changes in the R-wave velocity spectrum can help in cavity identification.Additional possible evidence is represented by significant changes in the refraction travel times over the cavity location.It can be concluded that the field data are in good agreement with the synthetic,and it could be effective to consider the results of both R-and P-wave analysis in order to efficiently identify the cavities.     

Investigation of rangeland indicator species using parametric and non-parametric methods in hilly landscapes of central Iran

This study aimed to identify indicator species and explore the most important environmental and management variables contributing to vegetation distribution in a hilly upper dam landscape in Zagros Mountain chain, Iran. A stratified random sampling method was used to collect topographic, edaphic, management and vegetation data. The density and cover percentage of perennial species were measured quantitatively. Indicator species were identified using the two-way indicator species analysis. Besides calculating physiognomic factors in sample sites, 24 soil samples were collected from 0 to 30 cm of soil depth and analyzed in terms of gravel percentage, texture, saturation moisture, organic matter, pH and electrical conductivity in saturation extract, lime percentage, soluble calcium and magnesium, available phosphorus, Cation Exchange Capacity(CEC) and soluble sodium and potassium. Multivariate techniques including Canonical Correspondence Analysis and Multi-Dimensional Scaling were used to explore the relationships of species with environmental and management variables. Seven plants were identified as indicator species due to being significantly correlated with management(grazing or non-grazing) and edaphic variables such as CEC, soil texture, pH, CaCO_3 percentage and physiographic variable including slope, elevation, and convex and concave formations(p 0.05). Overall, overgrazing and its subsequent effects on soil characteristics, loss of vegetation cover and trampling were found as the major causes of deterioration. Sustainable and integrated management practices such as the implementation of appropriate grazing systems were suggested to enhance soil quality and reduce the accelerated erosion in upper dam zones.     

Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis

Natural Resources Research - Groundwater is a vital water source in the rural and urban areas of developing and developed nations. In this study, a novel hybrid integration approach of...     

Experimental Evaluation of A New Developed Algorithm for An Autonomous Surface Vehicle and Comparison with Simulink Results

China Ocean Engineering - Performing repeatable duties automatically was the dreams of human being for centuries. Although full autonomy has long been dreamed of by visionaries, many researches...     

Predictive value of Keetch-Byram Drought Index for cereal yields in a semi-arid environment

The study examines the potential of urban roofs to reduce the urban heat island (UHI) effect by changing their reflectivity and implementing vegetation (green roofs) using the example of the City of Vienna. The urban modelling simulations are performed based on high-resolution orography and land use data, climatological observations, surface albedo values from satellite imagery and registry of the green roof potential in Vienna. The modelling results show that a moderate increase in reflectivity of roofs (up to 0.45) reduces the mean summer temperatures in the densely built-up environment by approximately 0.25 °C. Applying high reflectivity materials (roof albedo up to 0.7) leads to average cooling in densely built-up area of approximately 0.5 °C. The green roofs yield a heat load reduction in similar order of magnitude as the high reflectivity materials. However, only 45 % of roof area in Vienna is suitable for greening and the green roof potential mostly applies to industrial areas in city outskirts and is therefore not sufficient for substantial reduction of the UHI effect, particularly in the city centre which has the highest heat load. The strongest cooling effect can be achieved by combining the green roofs with high reflectivity materials. In this case, using 50 or 100 % of the green roof potential and applying high reflectivity materials on the remaining surfaces have a similar cooling effect.     

A GIS‐based multi‐criteria seismic vulnerability assessment using the integration of granular computing rule extraction and artificial neural networks

This study proposes multi‐criteria group decision‐making to address seismic physical vulnerability assessment. Granular computing rule extraction is combined with a feed forward artificial neural network to form a classifier capable of training a neural network on the basis of the rules provided by granular computing. It provides a transparent structure despite the traditional multi‐layer neural networks. It also allows the classifier to be applied on a set of rules for each incoming pattern. Drawbacks of original granular computing (GrC) are covered, where some input patterns remained unclassified. The study was applied to classify seismic vulnerability of the statistical units of the city of Tehran, Iran. Slope, seismic intensity, height and age of the buildings were effective parameters. Experts ranked 150 randomly selected sample statistical units with respect to their degree of seismic physical vulnerability. Inconsistency of the experts' judgments was investigated using the induced ordered weighted averaging (IOWA) operator. Fifty‐five classification rules were extracted on which a neural network was based. An overall accuracy of 88%, κ = 0.85 and R² = 0.89 was achieved. A comparison with previously implemented methodologies proved the proposed method to be the most accurate solution to the seismic physical vulnerability of Tehran.     

Trends in monthly precipitation over the northwest of Iran (NWI)

Increasing global temperatures during the last century have had their own effects on other climatic conditions, particularly on precipitation characteristics. This study was meant to investigate the spatial and temporal monthly trends of precipitation using the least square error (LSE) approach for the northwest of Iran (NWI). To this end, a database was obtained from 250 measuring stations uniformly scattered all over NWI from 1961 to 2010. The spatial average of annual precipitation in NWI during the period of study was approximately 220.9–726.7 mm. The annual precipitation decreased from southwest to northeast, while the large amount of precipitation was concentrated in the south-west and in the mountainous areas. All over NWI, the maximum and minimum precipitation records occurred from March to May and July to September, respectively. The coefficient of variation (CV) is greater than 44 % in all of NWI and may reach over 76 % in many places. The greatest range of CV, for instance, occurred during July. The spatial variability of precipitation was consistent with a tempo-spatial pattern of precipitation trends. There was a considerable difference between the amounts of change during the months, and the negative trends were mainly attributed to areas concentrated in eastern and southern parts of NWI far from the western mountain ranges. Moreover, limited areas with positive precipitation trends can be found in very small and isolated regions. This is observable particularly in the eastern half of NWI, which is mostly located far from Westerlies. On the other hand, seasonal precipitation trends indicated a slight decrease during winter and spring and a slight increase during summer and autumn. Consequently, there were major changes in average precipitation that occurred negatively in the area under study during the observation period. This finding is in agreement with those findings by recent studies which revealed a decreasing trend of around 2 mm/year over NWI during 1966–2005.