Spatial downscaling of climate variables using three statistical methods in Central Iran

Spatial downscaling methods are widely used for the production of bioclimatic variables(e.g. temperature and precipitation) in studies related to species ecological niche and drainage basin management and planning. This study applied three different statistical methods, i.e. the moving window regression(MWR), nonparametric multiplicative regression(NPMR), and generalized linear model(GLM), to downscale the annual mean temperature(Bio1) and annual precipitation(Bio12) in central Iran from coarse scale(1 km × 1 km) to fine scale(250 m ×250 m). Elevation, aspect, distance from sea and normalized difference vegetation index(NDVI) were used as covariates to create downscaled bioclimatic variables. Model assessment was performed by comparing model outcomes with observational data from weather stations. Coefficients of determination(R2), bias, and root-mean-square error(RMSE) were used to evaluate models and covariates. The elevation could effectively justify the changes in bioclimatic factors related to temperature and precipitation. Allthree models could downscale the mean annual temperature data with similar R2, RMSE, and bias values. The MWR had the best performance and highest accuracy in downscaling annual precipitation(R2=0.70; RMSE=123.44). In general, the two nonparametric models, i.e. MWR and NPMR, can be reliably used for the downscaling of bioclimatic variables which have wide applications in species distribution modeling.     

Prediction of Seaward Slope Recession in Berm Breakwaters Using M5' Machine Learning Approach

In the design process of berm breakwaters, their front slope recession has an inevitable rule in large number of model tests, and this parameter being studied. This research draws its data from Moghim’s and Shekari’s experiment results. These experiments consist of two different 2D model tests in two wave flumes, in which the berm recession to different sea state and structural parameters have been studied. Irregular waves with a JONSWAP spectrum were used in both test series. A total of 412 test results were used to cover the impact of sea state conditions such as wave height, wave period, storm duration and water depth at the toe of the structure, and structural parameters such as berm elevation from still water level, berm width and stone diameter on berm recession parameters. In this paper, a new set of equations for berm recession is derived using the M5'' model tree as a machine learning approach. A comparison is made between the estimations by the new formula and the formulae recently given by other researchers to show the preference of new M5'' approach.     

Mooring optimization of floating platforms using a genetic algorithm

This paper presents a new procedure for the optimization of the mooring design of floating platforms, in which an automatic design sequence is also established. Regarding the optimization philosophy, the following aspects are dealt with:

• The optimization of the platform heading and its mooring pattern, taking into account the environmental force spreading;

• optimum line length or line tension for each mooring line, associated to the optimization of the mooring line materials and sizes.

Basically, the main goal of this paper is to introduce a new method, which will provide the quickest way to find the best mooring system, defined here as that which minimizes platform responses.A genetic algorithm (GA) is applied in this contribution, and this paper describes exactly the procedure of developing a GA code directed toward the solution of mooring design optimization problems. In order to prove the efficiency and the vast potential of the proposed algorithm as a design tool, sample moorings are analyzed for different environmental conditions and the final results, including the time required to run them, are presented.     

Constraints on Mercury’s Na exosphere: Combined MESSENGER and ground-based data

We have used observations of sodium emission obtained with the McMath-Pierce solar telescope and MESSENGER’s Mercury Atmospheric and Surface Composition Spectrometer (MASCS) to constrain models of Mercury’s sodium exosphere. The distribution of sodium in Mercury’s exosphere during the period January 12-15, 2008, was mapped using the McMath-Pierce solar telescope with the 5″ × 5″ image slicer to observe the D-line emission. On January 14, 2008, the Ultraviolet and Visible Spectrometer (UVVS) channel on MASCS sampled the sodium in Mercury’s anti-sunward tail region. We find that the bound exosphere has an equivalent temperature of 900-1200 K, and that this temperature can be achieved if the sodium is ejected either by photon-stimulated desorption (PSD) with a 1200 K Maxwellian velocity distribution, or by thermal accommodation of a hotter source. We were not able to discriminate between the two assumed velocity distributions of the ejected particles for the PSD, but the velocity distributions require different values of the thermal accommodation coefficient and result in different upper limits on impact vaporization. We were able to place a strong constraint on the impact vaporization rate that results in the release of neutral Na atoms with an upper limit of 2.1 × 10⁶ cm⁻² s⁻¹. The variability of the week-long ground-based observations can be explained by variations in the sources, including both PSD and ion-enhanced PSD, as well as possible temporal enhancements in meteoroid vaporization. Knowledge of both dayside and anti-sunward tail morphologies and radiances are necessary to correctly deduce the exospheric source rates, processes, velocity distribution, and surface interaction.     

Composition, porosity, and reservoir potential of the Middle Jurassic Kashafrud Formation, northeast Iran

In the Kopet-Dagh Basin of Iran, deep-sea sandstones and shales of the Middle Jurassic Kashafrud Formation are disconformably overlain by hydrocarbon-bearing carbonates of Upper Jurassic and Cretaceous age. To explore the reservoir potential of the sandstones, we studied their burial history using more than 500 thin sections, supplemented by heavy mineral analysis, microprobe analysis, porosity and permeability determination, and vitrinite reflectance.The sandstones are arkosic and lithic arenites, rich in sedimentary and volcanic rock fragments. Quartz overgrowths and pore-filling carbonate cements (calcite, dolomite, siderite and ankerite) occluded most of the porosity during early to deep burial, assisted by early compaction that improved packing and fractured quartz grains. Iron oxides are prominent as alteration products of framework grains, probably reflecting source-area weathering prior to deposition, and locally as pore fills. Minor cements include pore-filling clays, pyrite, authigenic albite and K-feldspar, and barite. Existing porosity is secondary, resulting largely from dissolution of feldspars, micas, and rock fragments, with some fracture porosity. Porosity and permeability of six samples averages 3.2% and 0.0023 mD, respectively, and 150 thin-section point counts averaged 2.7% porosity. Reflectance of vitrinite in eight sandstone samples yielded values of 0.64-0.83%, in the early mature to mature stage of hydrocarbon generation, within the oil window.Kashafrud Formation petrographic trends were compared with trends from first-cycle basins elsewhere in the world. Inferred burial conditions accord with the maturation data, suggesting only a moderate thermal regime during burial. Some fractures, iron oxide cements, and dissolution may reflect Cenozoic tectonism and uplift that created the Kopet-Dagh Mountains. The low porosity and permeability levels of Kashafrud Formation sandstones suggest only a modest reservoir potential. For such tight sandstones, fractures may enhance the reservoir potential.     

Selection of Less Biased Threshold Angles for SAM Classification Using the Real Value–Area Fractal Technique

The accuracy of classification of the Spectral Angle Mapping (SAM) is warranted by choosing the appropriate threshold angles, which are normally defined by the user. Trial‐and‐error and statistical methods are commonly applied to determine threshold angles. In this paper, we discuss a real value–area (RV–A) technique based on the established concentration–area (C–A) fractal model to determine less biased threshold angles for SAM classification of multispectral images. Short wave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images were used over and around the Sar Cheshmeh porphyry Cu deposit and Seridune porphyry Cu prospect. Reference spectra from the known hydrothermal alteration zones in each study area were chosen for producing respective rule images. Segmentation of each rule image resulted in a RV–A curve. Hydrothermal alteration mapping based on threshold values of each RV–A curve showed that the first break in each curve is practical for selection of optimum threshold angles. The hydrothermal alteration maps of the study areas were evaluated by field and laboratory studies including X–ray diffraction analysis, spectral analysis, and thin section study of rock samples. The accuracy of the SAM classification was evaluated by using an error matrix. Overall accuracies of 80.62% and 75.45% were acquired in the Sar Cheshmeh and Seridune areas, respectively. We also used different threshold angles obtained by some statistical techniques to evaluate the efficiency of the proposed RV–A technique. Threshold angles provided by statistical techniques could not enhance the hydrothermal alteration zones around the known deposits, as good as threshold angles obtained by the RV–A technique. Since no arbitrary parameter is defined by the user in the application of the RV‐A technique, its application prevents introduction of human bias to the selection of optimum threshold angle for SAM classification.     

The role of tourism in rural development: Evidence from Iran

GeoJournal - Tourism can play an important role in diversifying the rural economy and its expanding in rural areas contributes to the sustainability of the population and the economy of these areas...