Assessment of bioclimatic comfort conditions based on Physiologically Equivalent Temperature (PET) using the RayMan Model in Iran

In this study thermal comfort conditions are analyzed to determine possible thermal perceptions during different months in Iran through the Physiologically Equivalent Temperature (PET). The monthly PET values produced using the RayMan Model ranged from ?7.6°C to 46.8°C. Over the winter months the thermal comfort condition (18–23°C) were concentrated in southern coastal areas along the Persian Gulf and Oman Sea. Most of the country experienced comfort conditions during the spring months, in particular in April, while during the summer months of July and August no thermal comfort conditions were observed. In November coastal areas of the Caspian Sea had the same physiological stress level of thermal comfort as April. The map produced showing mean annual PET conditions demonstrated the greatest spatial distribution of comfortable levels in the elevation range from 1000 to 2000 meter a.s.l., with annual temperatures of 12–20°C and annual precipitation of under 200 mm. The statistical relationship between PET conditions and each controlling parameter revealed a significant correlation in areas above 2000 meter, annual temperature over 20°C and annual precipitation of 200–400 mm with a correlation coefficient (R ²) of 0.91, 0.97 and 0.96, respectively.     

Modeling and mapping of solar radiation using geostatistical analysis methods in Iran

Because of economic and technical limitations, measuring solar energy received at ground level (R _s ) isn’t possible in all parts of the country, and in only 12% of synoptic stations is this parameter measured and recorded. Thus, it should be estimated and modeled spatially based on other climatic variables using mathematical methods. In this research, many attempts have been made to introduce an air temperature-based model for Rs estimation, and then, based on the output of the mentioned models, several geostatistical methods have been tested, and finally an elegant spatial model is proposed for (Rs) zoning in Iran. In this regard, the relationships between the measured amounts of monthly solar radiation and other climatic parameters, such as a monthly average, maximum and minimum temperature, precipitation, relative humidity, and the number of sunny hours during the period 1970–2010, are examined and modeled. It was revealed that based on the linear relationship between the monthly average air temperatures and solar radiation values recorded in each of the stations, that the best-fit linear model, with R ²  = 0.822, MAE = 1.81, RMSE = 2.51%, and MAPE = 10.08, can be introduced for Rs estimation. Then, using the outputs of the proposed model, the amounts of (R _s ) are estimated in another 171 meteorological stations (a total of 192 stations), and eight geostatistical methods (IDW, GPI, RBF, LPI, OK, SK, UK, and EBK) were investigated for zoning. Comparing the resulting variograms showed that in addition to proof of spatial correlation between solar radiation data, they can be applied for modeling changes in various directions. Analyzing the ratio of the nugget effect on the roof of the variograms showed that the Gaussian model with the lowest ratio (Co/Co + C = 0.883) and (R ²  = 0.972), could model the highest correlation between the data and, therefore, it was used for data interpolation. To select the best geostatistical model, R2, MAE, and RMSE were used. On this basis, it was found that the RBF method with R ²  = 0.904, MAE = 3.02, RMSE = 0.39% is the most effective. Also, the IDW method with R ²  = 0.90, MAE = 3.08, RMSE = 0.391%, compared to other methods is the most effective. In addition, for data validation, correlations between observed and estimated values of solar radiation were studied and found R ²  = 0.86.     

Mapping of the soil texture using geostatistical method (a case study of the Shahrekord plain, central Iran)

Soil texture is a key variable that reflect a number of soil properties such as soil permeability, water holding capacity, nutrient storage and availability, and soil erosion. The main objective of this study was to produce the kriged maps of soils of the Shahrekord region, central Iran. One hundred four soil samples were collected on a 375-m² sampling grid from the depths of 0–30, 30–60, and 60–100 centimeter, and their particle sizes were determined using hydrometer method. The results showed a moderately spatial correlation in the soil particles among sampling soil layers and across the study area. Moreover, increasing clay and therewith observation of heavier soil textures is evident from surface to subsurface layers of the soils in the studied area due to rainfall and/or irrigation agriculture. These findings indicated that study of the soil texture variation with depth can be used as a clue for site-specific management and precision agriculture. Moreover, we suggest further analysis by using other data layers like topographical parameters, land use, parent material, soil erosion, and any other information which might influence the spatial distribution of soil texture.     

Thermal comfort and forecast of energy consumption in Northwest Iran

Assessing the climatic characteristics and identifying the climatic parameters of a specific region can play a major role in human welfare. Thermal comfort conditions are among the most significant factors of climatic variables in the northwestern regions of Iran due to the considerable spatial and temporal variations and are vital for environmental, energy and economic management. It is therefore necessary to advance our knowledge of the climatic conditions in order to provide an appropriate tool for managing climatic extremes. This requires charting of the range of clusters of the thermal comfort conditions in this region. In this study, the general atmosphere circulation model HADCM3 and the A1 scenario, downscaled by the LARS-WG model, were employed to simulate the climatic conditions in Iran during the period 2011–2040. The data obtained were compared with sampled data from six Iranian climatic stations for the 30-year period (1961–1990). In order to tabulate this comparison, six clusters per climatic station were defined based on intrinsic similarity of data. Results show an increase in the annual average temperature of these six stations by 1.69 °C for the predicted years, projected from the base years 1961–1990. This factor has resulted in an increment of the annual average thermal comfort temperature inside buildings by a magnitude of 0.52 °C in future decades. When the thermal requirements of the studied region were evaluated based on the real temperature difference and the degree of thermal comfort, it becomes clear that apart from cluster 1, the energy required to reach thermal comfort inside buildings will increase in the future. As a result of this temperature increase, an increase of the energy required to reach the thermal comfort is expected. This new methodology is an interesting tool and needs to be seriously considered by engineers and architects in designing buildings of the future.     

Multiple-point geostatistical modeling based on the cross-correlation functions

An important issue in reservoir modeling is accurate generation of complex structures. The problem is difficult because the connectivity of the flow paths must be preserved. Multiple-point geostatistics is one of the most effective methods that can model the spatial patterns of geological structures, which is based on an informative geological training image that contains the variability, connectivity, and structural properties of a reservoir. Several pixel- and pattern-based methods have been developed in the past. In particular, pattern-based algorithms have become popular due to their ability for honoring the connectivity and geological features of a reservoir. But a shortcoming of such methods is that they require a massive data base, which make them highly memory- and CPU-intensive. In this paper, we propose a novel methodology for which there is no need to construct pattern data base and small data event. A new function for the similarity of the generated pattern and the training image, based on a cross-correlation (CC) function, is proposed that can be used with both categorical and continuous training images. We combine the CC function with an overlap strategy and a new approach, adaptive recursive template splitting along a raster path, in order to develop an algorithm, which we call cross-correlation simulation (CCSIM), for generation of the realizations of a reservoir with accurate conditioning and continuity. The performance of CCSIM is tested for a variety of training images. The results, when compared with those of the previous methods, indicate significant improvement in the CPU and memory requirements.     

不同地质统计方法在确定渗透系数场中的对比研究

应用地质统计方法研究渗透系数场的空间变异性。利用MMR含水层场地实测数据,通过去类分析、特异值处理、正态变换,逐步逼近研究区渗透系数的稳健变差函数,得到三维渗透系数场的几何各向异性套合模型。在此基础上,采用普通克里格法和指示克里格法、高斯序列模拟法和指示序列模拟法分别对数据进行插值和条件模拟。最后结合具体的地质条件,对四种方法在渗透系数场生成中的应用进行对比分析和评价。     

Fractal and geostatistical methods for modeling of a fracture network

The modeling of fracture networks is useful for fluid flow and rock mechanics studies. About 6600 fracture traces were recorded on drifts of a uranium mine in a granite massif. The traces have an extension of 0.20–20 m. The network was studied by fractal and by geostatistical methods but can be considered neither as a fractal with a constant dimension nor a set of purely randomly located fractures. Two kinds of generalization of conventional models can still provide more flexibility for the characterization of the network: (a) a nonscaling fractal model with variable similarity dimension (for a 2-D network of traces, the dimension varying from 2 for the 10-m scale to 1 for the centimeter scale, (b) a parent-daughter model with a regionalized density; the geostatistical study allows a 3-D model to be established where: fractures are assumed to be discs; fractures are grouped in clusters or swarms; and fracturation density is regionalized (with two ranges at about 30 and 300 m). The fractal model is easy to fit and to simulate along a line, but 2-D and 3-D simulations are more difficult. The geostatistical model is more complex, but easy to simulate, even in 3-D.This paper was presented at Emerging Concepts, MGUS-87 Conference, Redwood City, California, 13–15 April 1987.     

A multiple-point geostatistical method based on geological vector information

The reproduction of the non-stationary distribution and detailed characteristics of geological bodies is the main difficulty of reservoir modeling. Recently developed multiple-point geostatistics can represent a stationary geological body more effectively than traditional methods. When restricted to a stationary hypothesis, multiple-point geostatistical methods cannot simulate a non-stationary geological body effectively, especially when using non-stationary training images (TIs). According to geologic principles, the non-stationary distribution of geological bodies is controlled by a sedimentary model. Therefore, in this paper, we propose auxiliary variables based on the sedimentary model, namely geological vector information (GVI). GVI can characterize the non-stationary distribution of TIs and simulation domains before sequential simulation, and the precision of data event statistics will be enhanced by the sequential simulation’s data event search area limitations under the guidance of GVI. Consequently, the reproduction of non-stationary geological bodies will be improved. The key features of this method are as follows: (1) obtain TIs and geological vector information for simulated areas restricted by sedimentary models; (2) truncate TIs into a number of sub-TIs using a set of cut-off values such that each sub-TI is stationary and the adjacent sub-TIs have a certain similarity; (3) truncate the simulation domain into a number of sub-regions with the same cut-off values used in TI truncation, so that each sub-region corresponds to a number of sub-TIs; (4) use an improved method to scan the TI or TIs and construct a single search tree to restore replicates of data events located in different sub-TIs; and (5) use an improved conditional probability distribution function to perform sequential simulation. A FORTRAN program is implemented based on the SNESIM.     

Simulation of global warming effect on outdoor thermal comfort conditions

In the coming decades, global warming and increase in temperature, in different regions of the world, may change indoor and outdoor thermal comfort conditions and human health. The aim of this research was to study the effects of global warming on thermal comfort conditions in indoor ambiences in Iran. To study the increase in temperature, model for assessment of greenhouse-gas induced climate change scenario generator compound model has been used together with four scenarios and to estimate thermal comfort conditions, adaptive model of the American Society of Heating, Refrigerating and Air-conditioning Engineers has been used. In this study, Iran was divided into 30 zones, outdoor conditions were obtained using meteorological data of 80 climatological stations and changes in neutral comfort conditions in 2025, 2050, 2075 and 2100 were predicted. In accordance with each scenario, findings from this study showed that temperature in the 30 zones will increase by 2100 to between 3.4 °C and 5.6 °C. In the coming decades and in the 30 studied zones, neutral comfort temperature will increase and be higher and more intense in the central and desert zones of Iran. The low increase in this temperature will be connected to the coastal areas of the Caspian and Oman Sea in southeast Iran. This increase in temperature will be followed by a change in thermal comfort and indoor energy consumption from 8.6 % to 13.1 % in air conditioning systems. As a result, passive methods as thermal inertia are proposed as a possible solution.     

Multivariate geostatistical methods of mean annual and seasonal rainfall in southwest Saudi Arabia

A multivariate geostatistics (cokriging) is used for regional analysis and prediction of rainfall throughout the southwest region of Saudi Arabia. Elevation is intruded as a covariant factor in order to bring topographic influences into the methodology. Sixty-three representative weather stations are selected for a 21-year period covering different microclimate conditions. Results show that on an annual basis, there is no significant change using elevation. On the seasonal basis, the cokriging method gave more information about rainfall occurrence values, its accuracy related to the degree of correlation between elevation and rainfall by season. The prediction of spring and winter rainfall was improved owing to the importance of orographic processes, while the summer season was not affected within its monsoon climatology. In addition, fall season shows inverse and weak correlation of elevation with rainfall. Cross-validation and cokriging variances are also used for more accuracy of rainfall regional estimation. Moreover, even though the correlation is not significant, the isohyet values of cokriged estimates provided more information on rainfall changes with elevation. Finally, adding more secondary variables in addition to elevation could improve the accuracy of cokriging estimates.     

Spatial-temporal difference between nitrate in groundwater and nitrogen in soil based on geostatistical analysis

The study of temporal and spatial variations of nitrate in groundwater under different soil nitrogen environments is helpful to the security of groundwater resources in agricultural areas. In this paper,based on 320 groups of soil and groundwater samples collected at the same time, geostatistical analysis and multiple regression analysis were comprehensively used to conduct the evaluation of nitrogen contents in both groundwater and soil. From May to August, as the nitrification of groundwater i...     

Assessment of weathering processes effect on engineering properties of Alvand granitic rocks (west of Iran), based on weathering indices

The Alvand batholith is one of the largest plutonic bodies in the west of Iran. In this research, several physico-mechanical tests have been performed on granodiorite and porphiroid monzogranite consisting of five degrees of weathering in Hamedan area, west of Iran. Furthermore, weathering process of Alvand granitoid is studied by chemical analysis and petrographical studies. The results indicated that engineering properties of weathered granodiorite and monzogranite vary over the wide range depending on the degree of weathering. On the other hand, this research is focused on the assessment of relationship between weathering indices and uniaxial compressive strength. For this reason, some of the most important weathering indices are reviewed. It should be noted that, application of these chemical, engineering and petrographical indices are good quantitative indicators for describing the degree of weathering. Using these indices for the assessment of uniaxial compressive strength of granodiorite and monzogranite rocks, yields suitable and meaningful results.     

Comparison of three geostatistical methods for hydrofacies simulation: a test on alluvial sediments

The hydrodispersive properties of porous sediments are strongly influenced by the heterogeneity at fine scales, which can be modeled by geostatistical simulations. In order to improve the assessment of the properties of three different geostatistical simulation methods (Sequential indicator simulation, SISIM; Transition probability geostatistical simulation, T-PROGS; Multiple point simulation, MPS) a comparison test at different scales was performed for a well-exposed aquifer analogue. In the analysed volume (approximately 30,000?m³) four operative hydrofacies have been recognised: very fine sand and silt, sand, gravelly sand and open framework gravel. Several equiprobable realizations were computed with SISIM, MPS and T-PROGS for a test volume of approximately 400?m³ and for the entire volume, and the different outcomes were compared with visual inspection and connectivity analysis of the very or poorly permeable structures. The comparison of the different simulations shows that the geological model is best reproduced when the simulations are realised separately for each highest rank depositional element and subsequently merged. Moreover, the three methods yield different images of the volume; in particular MPS is efficient in mapping the geometries of the most represented hydrofacies, whereas SISIM and T-PROGS can account for the distribution of the less represented facies.     

Estimation of regionalized phenomena by geostatistical methods: lake acidity on the Canadian Shield

 This paper describes a geostatistical technique based on conditional simulations to assess confidence intervals of local estimates of lake pH values on the Canadian Shield. This geostatistical approach has been developed to deal with the estimation of phenomena with a spatial autocorrelation structure among observations. It uses the autocorrelation structure to derive minimum-variance unbiased estimates for points that have not been measured, or to estimate average values for new surfaces. A survey for lake water chemistry has been conducted by the Ministère de l'Environnement du Québec between 1986 and 1990, to assess surface water quality and delineate the areas affected by acid precipitation on the southern Canadian Shield in Québec. The spatial structure of lake pH was modeled using two nested spherical variogram models, with ranges of 20 km and 250 km, accounting respectively for 20% and 55% of the spatial variation, plus a random component accounting for 25%. The pH data have been used to construct a number of geostatistical simulations that produce plausible realizations of a given random function model, while 'honoring' the experimental values (i.e., the real data points are among the simulated data), and that correspond to the same underlying variogram model. Post-processing of a large number of these simulations, that are equally likely to occur, enables the estimation of mean pH values, the proportion of affected lakes (lakes with pH≤5.5), and the potential error of these parameters within small regions (100 km×100 km). The method provides a procedure to establish whether acid rain control programs will succeed in reducing acidity in surface waters, allowing one to consider small areas with particular physiographic features rather than large drainage basins with several sources of heterogeneity. This judgment on the reduction of surface water acidity will be possible only if the amount of uncertainty in the estimation of mean pH is properly quantified. Received: 3 March 1997 · Accepted: 16 November 1998     

Satellite detection of earthquake thermal infrared precursors in Iran

Stress accumulated in rocks in tectonically active areas may manifest itself as electromagnetic radiation emission and temperature variation through a process of energy transformation. Land surface temperature (LST) changes before an impending earthquake can be detected with thermal infrared (TIR) sensors such as NOAA-AVHRR, Terra/Aqua-MODIS, etc. TIR anomalies produced by 10 recent earthquakes in Iran during the period of Jun 2002–Jun 2006 in the tectonically active belt have been studied using pre- and post-earthquake NOAA-AVHRR datasets. Data analysis revealed a transient TIR rise in LST ranging 2–13°C in and around epicentral areas. The thermal anomalies started developing about 1–10 days prior to the main event depending upon the magnitude and focal depth, and disappeared after the main shock. In the case of moderate earthquakes (<6 magnitude) a dual thermal peak instead of the single rise has been observed. This may lead us to understand that perhaps pre-event sporadic release of energy from stressed rocks leads to a reduction in magnitude of the main shock. This TIR temperature increment prior to an impending earthquake can be attributed to degassing from rocks under stress or to p-hole activation in the stressed rock volume and their further recombination at the rock–air interface. A precise correlation of LST maps of Bam and Zarand with InSAR-generated deformation maps also provides evidence that the thermal anomaly is a ground-related phenomenon, not an atmospheric one.     

Application of geostatistical methods in gold geochemical anomalies identification (Montemor-O-Novo, Portugal)

The study described herein concerns the application of geostatistical methods to data soil from Montemor-O-Novo area (Southern Portugal). In the area, the gold mineralised zones (Banhos, Caeiras, Falés, Gamela, Malaca and Monfurado) are characterised by different geological settings and mineralogical assemblages. A total of 1211 soil samples were collected in Montemor-O-Novo area and analysed for Cu, Pb, Zn, As, Ba and Au by atomic absorption spectrometry.To account for spatial structure, simple and cross variograms were computed for the main directions of the grid sampling. From the experimental variograms a linear model of coregionalization composed of three structures, a nugget effect and two anisotropic spherical structures, was fitted to each of the six variables. The coregionalization matrices deduced from the theoretical model show the relationships between the variables at different scales. These matrices were compared with those obtained by principal component analysis (PCA).This methodology was the basis for estimating the corresponding spatial components (Y0, Y1 and Y2) using factorial kriging analysis (FKA). Maps of raw data, Y0, Y1 and Y2 were made for each variable.The use of multivariate analysis permit the study of the spatial structure intrinsic to geochemical data and the identification and refinement of significant anomalies related to Au-bearing mineral deposits.     

基于DEM的广西旅游气候舒适度时空分异研究

基于数字高程模型(DEM)和3S技术,以广西壮族自治区1981-2010年74个气象观测点的气象常规观测数据为基础,对广西各地区地形下温度、相对湿度、风速、温湿指数、风寒指数、着衣指数和综合旅游舒适度指数等时空分布特征进行分析研究,并结合2015年广西307个2A级旅游景区时空分布进行评价,结果表明：在时间差异上,广西大部分地区最佳旅游时间为1月、2月、3月、10月和11月,此时全区大部分地区气温保持在15~25 ℃之间,处于非雨季期;4月、12月在气候舒适上为较适合旅游的季节;由于广西地处南疆,雨热同期,高温多雨的6、7、8月在气候舒适度上为最不适合旅游月份;就季节而言,旅游气候舒适度排序为冬季＞秋季＞春节＞夏季。在空间差异上,6个月旅游舒适期地区仅占广西面积的0.12%,仅在桂西西林县西面和桂北资源县北面零星分布,没有2A级以上旅游景区分布其中;7个月旅游舒适期地区主要分布在桂西、桂西南和桂西北地区,桂北资源县、桂南博白县和合浦县、桂南贺州市、梧州市均有分布,占广西面积的36.78%,共有72个2A级旅游景区分布其中,占23.5%的景区数量比例;舒适期为8个月的地区分布最广,占广西区面积的63.1%,共有235个2A级以上旅游景区,占2015年2A级以上景区数量的76.5%,主要分布在桂中、桂南和桂北地区。