Selection of Optimal Thresholds for Estimation and Simulation Based on Indicator Values of Highly Skewed Distributions of Ore Data

This study strives to outline a geostatistics model for estimation and simulation of the Qolqoleh gold ore deposit located in Saqqez, NW of Iran. Considering that this gold deposit contains high-grade values, accurate evaluation of such values is of high importance, and therefore different methods based on indicator values, such as full indicator kriging (FIK) and sequential indicator simulation (SIS), have been employed to improve the accuracy of estimation and simulation of high-grade values. FIK and SIS cover the full range of grades based on several thresholds on the indicator data. The cumulative distribution function (CDF) is typically used for selection of threshold values. Given the highly skewed distribution of gold grade and its intense fluctuations, the number of thresholds is increased using CDF, which in turn results in a whole lot of calculations. To reduce the volume of calculations, the number–size (N–S) fractal model has been used to select thresholds. From such a model, all optimal thresholds are chosen with respect to geology and the unnecessary thresholds are excluded from selection. Thus, a study of the selection of optimal thresholds for estimation and simulation of a gold ore resource by means of FIK and SIS, respectively, based on thresholds selected using the N–S fractal model is presented. Finally, it is proved that results of these geostatistical methods based on thresholds selection from the N–S model appear to be better-positioned to explain ore grade variability compared to thresholds selected from the CDF and threshold selection from the N–S model is more effective for reducing the volume of required calculations.     

Homogeneity analysis of precipitation series in Iran

Assessment of the reliability and quality of historical precipitation data is required in the modeling of hydrology and water resource processes and for climate change studies. The homogeneity of the annual and monthly precipitation data sets throughout Iran was tested using the Bayesian, Cumulative Deviations, and von Neumann tests at a significance level of 0.05. The precipitation records from 41 meteorological stations covering the years between 1966 and 2005 were considered. The annual series of Iranian precipitation were found to be homogeneous by applying the Bayesian and Cumulative Deviations tests, while the von Neumann test detected inhomogeneities at seven stations. Almost all the monthly precipitation data sets are homogeneous and considered as “useful.” The outputs of the statistical tests for the homogeneity analysis of the precipitation time series had discrepancies in some cases which are related to different sensitivities of the tests to break in the time series. It was found that the von Neumann test is more sensitive than the Bayesian and Cumulative Deviations tests in the determination of inhomogeneity in the precipitation series.     

Deformation analysis of the Lake Urmia causeway (LUC) embankments in northwest Iran: insights from multi-sensor interferometry synthetic aperture radar (InSAR) data and finite element modeling (FEM)

This paper presents deformation analysis of Lake Urmia causeway (LUC) embankments in northwest Iran using observations from interferometry synthetic aperture radar (InSAR) and finite element model (FEM) simulation. 58 SAR images including 10 ALOS, 30 Envisat and 18 TerraSAR-X are used to assess settlement of the embankments during 2003–2013. The interferometric dataset includes 140 differential interferograms which are processed using InSAR time series technique of small baseline subset approach. The results show a clear indication of large deformation on the embankments with peak amplitude of \(>\) 50 mm/year in 2003–2010, increasing to \(>\!\!80\)  mm/year in 2012–2013 in the line of sight (LOS) direction from ground to the satellite. 2D decomposition of InSAR observations from Envisat and ALOS satellites that overlap in the years 2007–2010 shows that the rate of the vertical settlement and horizontal motion is not uniform along the embankments; Both eastern and western embankments show significant vertical motion, while horizontal motion plays a more significant role in eastern embankment than western embankment. The InSAR results are then used to simulate deformation using FEM at two cross-sections at the distance of 4 and 9 km from the most western edge of the LUC for which detailed stratigraphy data are available. Results suggest that consolidation due to dissipation of excess pore pressure in embankments can satisfactory predict settlement of the LUC embankments. Our numerical modeling indicates that nearly half of the consolidation since the construction time of the causeway 30 years ago has been done.     

Experimental investigation into rockfill dam failure initiation by overtopping

Rockfill is the most abundant building material. It is often used for water retention under different contexts, such as dams, embankments or drainage systems. Climate change may cause water levels to rise in reservoirs. As rockfill structures are not able to resist strong overtopping flow, rising water levels will constitute a danger for rockfill dam stability as well as for people living nearby. This work is aimed at the development of an empirical formula that enables calculation of the critical water level of overflow at the crest from the geometrical and physical parameters of a dam. To achieve these objectives, several experimental tests on a rockfill dam model with two different impervious cores, moraine with a sand filter and an empty wooden formwork, were conducted in a hydraulic channel at the hydro-environmental laboratory at École Polytechnique de Montréal. The purpose of these tests was to study the initiation of a riprap failure under the influence of different variables, such as rock size, riprap bank, downstream side slope and bed slope. Results showed linear trends between the critical water level and both the downstream side slope and bed slope. Also, a power trend was observed between the critical level and riprap grain size. A formula that gives the critical overtopping water level was developed from these results.     

High-resolution spatiotemporal distribution of precipitation in Iran: a comparative study with three global-precipitation datasets

High-resolution precipitation datasets are used for numerous applications. However, depending on the procedures for obtaining these products, such as number of observations, quality checking, error-correction procedures, and interpolation techniques, they include many uncertainties. Therefore, the accuracy of these products needs to be evaluated over different regions. In this study, the Iranian National Dataset (INDS), a new 1?×?1 km precipitation dataset based on precipitation data of 1,441 quality-controlled stations for the climatic period from 1961 to 2005, was constructed using the digital elevation model, correlation method, and Kriging interpolation procedure. Iran's annual precipitation values at grids and stations were extracted from Climatic Research Unit (CRU) CL 2.0, CRU TS 3.10.01, and WorldClim datasets, and differences between corresponding values in each of the three datasets and INDS were calculated and analyzed. The coefficient of determination (R ²) between the national network stations' data and the CRU CL 2.0, CRU TS 3.10.01, and WorldClim datasets were 0.50, 0.13, and 0.62, respectively. Moreover, R ² values between the grids of each dataset and INDS were 0.51, 0.40, and 0.60, respectively. To determine the global datasets' efficiency for displaying temporal patterns of precipitation, the monthly values gathered from them at 11 stations (as representative of Iran's various precipitation regimes) were compared with the real values at these stations. The results showed that in term of temporal patterns, the concurrences among the three global datasets and the INDS was more acceptable, especially in the case of CRU CL 2.0. In general, it is concluded that the global datasets could be deployed for the primary assessment of the annual precipitation distribution; however, for more precise studies, use of local data is highly recommended.