Optimal location of additional exploratory drillholes using afuzzy-artificial bee colony algorithm

In most research studies, the problem of locating additional drillhole is simplified, and the ore body is considered as a 2d object. In this study, location of additional drillholes are optimized by considering the third dimension of the ore body, the azimuth and the dip of additional drill holes. A new objective function is defined to address the effect of rock type in locating new drillholes. The optimization problem is solved using a novel fuzzy-artificial bee colony algorithm, called FABC. The parameters of the FABC algorithm is dynamically adjusted using a designed fuzzy inference system with three performance measures as inputs and two outputs. The comparison performance with state-of-the-art optimization algorithm, using a nonparametric hypothesis test, indicates higher performance of the FABC algorithm. The results indicate significantly a decrease of kriging variance by introducing additional drillholes.     

Skill Assessment of Copernicus Climate Change Service Seasonal Ensemble Precipitation Forecasts over Iran

Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems.Recently,the Copernicus Climate Change Service(C3S)database has been releasing monthly forecasts for lead times of up to three months for public use.This study evaluated the ensemble forecasts of three C3S models over the period 1993-2017 in Iran’s eight classified precipitation clusters for one-to three-month lead times.Probabilistic and non-probabilistic criteria were used for evaluation.Furthermore,the skill of selected models was analyzed in dry and wet periods in different precipitation clusters.The results indicated that the models performed best in western precipitation clusters,while in the northern humid cluster the models had negative skill scores.All models were better at forecasting upper-tercile events in dry seasons and lower-tercile events in wet seasons.Moreover,with increasing lead time,the forecast skill of the models worsened.In terms of forecasting in dry and wet years,the forecasts of the models were generally close to observations,albeit they underestimated several severe dry periods and overestimated a few wet periods.Moreover,the multi-model forecasts generated via multivariate regression of the forecasts of the three models yielded better results compared with those of individual models.In general,the ECMWF and UKMO models were found to be appropriate for one-month-ahead precipitation forecasting in most clusters of Iran.For the clusters considered in Iran and for the long-range system versions considered,the Météo France model had lower skill than the other models.     

Evaluation of TIGGE Ensemble Forecasts of Precipitation in Distinct Climate Regions in Iran

The application of numerical weather prediction(NWP) products is increasing dramatically. Existing reports indicate that ensemble predictions have better skill than deterministic forecasts. In this study, numerical ensemble precipitation forecasts in the TIGGE database were evaluated using deterministic, dichotomous(yes/no), and probabilistic techniques over Iran for the period 2008–16. Thirteen rain gauges spread over eight homogeneous precipitation regimes were selected for evaluation.The Inverse Distance Weighting and Kriging methods were adopted for interpolation of the prediction values, downscaled to the stations at lead times of one to three days. To enhance the forecast quality, NWP values were post-processed via Bayesian Model Averaging. The results showed that ECMWF had better scores than other products. However, products of all centers underestimated precipitation in high precipitation regions while overestimating precipitation in other regions. This points to a systematic bias in forecasts and demands application of bias correction techniques. Based on dichotomous evaluation,NCEP did better at most stations, although all centers overpredicted the number of precipitation events. Compared to those of ECMWF and NCEP, UKMO yielded higher scores in mountainous regions, but performed poorly at other selected stations.Furthermore, the evaluations showed that all centers had better skill in wet than in dry seasons. The quality of post-processed predictions was better than those of the raw predictions. In conclusion, the accuracy of the NWP predictions made by the selected centers could be classified as medium over Iran, while post-processing of predictions is recommended to improve the quality.     

Recognition of shallow karst water resources and cave potentials using thermal infrared image and terrain characteristics in semi-arid regions of Iran

Shallow karst water resources and caves may influence land surface temperatures due to cold transfer property of rocks and evaporation from buried karst. The objective of this research was to develop a method for recognition of karst areas based on evaluating the surface characteristics that manifest itself by low land surface temperature in the satellite images. Investigation of thermal ETM⁺ image of the study region in Iran showed that parts of carbonate rocks that bear karst water are relatively cooler compared to areas with similar terrain conditions. Relational modeling provided useful information on spatial distribution of areas that have the potential to hold karst water resources and/or caves. Further inspection of ASTER images, along with geotechnical, geophysical and geological field surveys verified the approach. Significant correlation was found between electrical resistivity and thermal band values. The method may be used as a primary exploratory tool for shallow karst water explorations in similar areas.     

Effect of ENSO on annual maximum floods and volume over threshold in the southwestern region of Iran

In this paper, the effects of the El Niño-Southern Oscillation (ENSO) on the annual maximum flood (AMF) and volume over threshold (VOT) in two major neighbouring river basins in southwest Iran are investigated. The basins are located upstream of the Dez and Karun-I dams and cover over 40?000 km² in total area. The effects of ENSO on the frequency, magnitude and severity (frequency times magnitude) of flood characteristics over the March–April period were analysed. ENSO indices were also correlated with both AMF and VOT. The results indicate that, in the Dez and Karun basins, the El Niño phenomenon intensifies March–April floods compared with neutral conditions. The opposite is true in La Niña conditions. The degree of the effect is more intense in the El Niño period.     

Efficiency of standardized image processing in the fragmentation prediction in the case of Sungun open-pit mine

The paper proposes a standardized image-processing procedure with the use of sieve analysis results for calibration which is utilized to measure the size distribution of fragmentation at Sungun mine. Through this procedure, a number of 19 bench blasting in various levels have been initially selected as the target of the study for each, multiple photos were taken immediately after blast from suitable perspectives and locations of the muckpiles surfaces. The number of image sampling was chosen adequately high to achieve further reliability of the whole photography procedure. Then fragments of each muckpile were separately mixed by a loader, where another image sampling from these new muckpiles, bucket of loaders, and haulage trucks was performed. For the purpose of sieve analysis, seven sieves with the mesh sizes between 1.27 cm (0.5 in) and 25.4 cm (10 in) were designed, manufactured, and then installed at Sungun semi-industrial laboratory. Additionally, three mass samples of the mixed fragments were randomly chosen among the 19 muckpiles for sieving. During image analysis stage, “sieve shift” and “mass power” factors, required to obtain standardized size distribution, were precisely assigned when the results obtained by the image analysis software was in accordance with the sieving results. In order to validate the reliability of the image processing, a comparative analysis of the achieved results was made with the results of the original Kuz–Ram model [Cunningham (1983) The Kuz–Ram model for prediction of fragmentation from blasting. In: Proceedings of the first international symposium on rock fragmentation by blasting, Lulea, Sweden, pp 439–454]. Finally, the image-processing procedure was found to be more efficient, with results close-matched to the real results of the sieve analysis.     

Latest Tournaisian–late Viséan foraminiferal biozonation (MFZ8–MFZ14) of the Valiabad area,northwestern Alborz (Iran): geological implications

The Mobarak Formation in the Valiabad area (northwestern Alborz, Iran) is composed of bioclastic, oolitic and sandy limestone interbedded with black shale, and is disconformably underlain and overlain by the Cambrian Lalun and Permian Dorud formations, respectively. In this study, 104 foraminiferal species belonging to 12 families and 33 genera were determined. Among them, six genera and nine species are reported for the first time in Iran. Analysis of the foraminiferal assemblages has identified eight local biozones, which can be correlated with the MFZ8 to MFZ14 zones of the Viséan stratotypes in Belgium. The Valiabad equivalents of these biozones are essentially characterized by (1) Eoparastaffella ex gr. rotunda‐‘florigena’–Lysella cf. gadukensis; (2) Eoparastaffella simplex–Lapparentidiscus bokanensis; (3) Ammarchaediscus; (4) Uralodiscus–Glomodiscus; (5) Glomodiscus–Archaediscus; (6) Pojarkovella–Mstinia fallax; (7) Mstinia bulloides–Pseudoendothyra; and (8) Howchinia gibba–Howchinia bradyana–Tubispirodiscus attenuatus. Consequently, the Valiabad section appears to be one of the most complete Viséan sections in Iran. Some taxonomic precisions are provided about the principal taxa. Biogeographically, (1) the MFZ8–MFZ11 biozones are extended to all the shelves of the Palaeotethys (from Ireland to South China) and Urals oceans; nevertheless, due to the complete evolution of archaediscoids, they seem more related to the Perigondwanan assemblages from Sinai and Taurus (including the Antalya Nappes); (2) the MFZ12 assemblage appears relatively endemic; and (3) the impoverished assemblages of the biozones MFZ13‐14 have marked affinities with the Kazakhstan Block. It is currently impossible to indicate precisely if these variations are related with a drift of the Alborz region to the north, or to a change of oceanic currents. Moreover, the double affinity highlights the narrowness of the Palaeotethys in Iran during the Viséan. Copyright © 2014 John Wiley & Sons, Ltd.     

Drought Forecasting in a Semi-arid Watershed Using Climate Signals:a Neuro-fuzzy Modeling Approach

Large-scale annual climate indices were used to forecast annual drought conditions in the Maharlu-Bakhtegan watershed,located in Iran,using a neuro-fuzzy model.The Standardized Precipitation Index（SPI） was used as a proxy for drought conditions.Among the 45 climate indices considered,eight identified as most relevant were the Atlantic Multidecadal Oscillation（AMO）,Atlantic Meridional Mode（AMM）,the Bivariate ENSO Time series（BEST）,the East Central Tropical Pacific Surface Temperature（NINO 3.4）,the Central Tropical Pacific Surface Temperature（NINO 4）,the North Tropical Atlantic Index（NTA）,the Southern Oscillation Index（SOI）,and the Tropical Northern Atlantic Index（TNA）.These indices accounted for 81% of the variance in the Principal Components Analysis（PCA） method.The Atlantic surface temperature（SST：Atlantic） had an inverse relationship with SPI,and the AMM index had the highest correlation.Drought forecasts of neuro-fuzzy model demonstrate better prediction at a two-year lag compared to a stepwise regression model.     

Application of the WEPP model to determine sources of run‐off and sediment in a forested watershed

This study investigates critical run‐off and sediment production sources in a forested Kasilian watershed located in northern Iran. The Water Erosion Prediction Project (WEPP) watershed model was set up to simulate the run‐off and sediment yields. WEPP was calibrated and validated against measured rainfall–run‐off–sediment data. Results showed that simulated run‐off and sediment yields of the watershed were in agreement with the measured data for the calibration and validation periods. While low and medium values of run‐off and sediment yields were adequately simulated by the WEPP model, high run‐off and sediment yield values were underestimated. Performance of the model was evaluated as very good and satisfactory during the calibration and validation stages, respectively. Total soil erosion and sediment load of the study watershed during the study period were determined to be 10 108 t yr^?1 and 8735 t yr^?1, respectively. The northern areas of the watershed with dry farming were identified as the critical erosion prone zones. To prioritize the subwatersheds based on their contribution to the run‐off and sediment production at the watershed's main outlet, unit response approach (URA) was applied. In this regard, subwatersheds close to the main outlet were found to have the highest contribution to sediment yield of the whole watershed. Results indicated that depending on the objective of land and water conservation practices, particularly, for controlling sediment yield at the main outlet, critical areas for implementing the best management practices may be identified through conjunctive application of WEPP and URA. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimal design of flood-control multi-reservoir system on a watershed scale

Flood events have the highest damage costs and losses among natural hazards. There are different types of measures to mitigate flood damage costs and their negative consequences. Application of flood-control reservoirs or detention dams, as one of the main measures, may decrease devastating flood effects or even may cause to intensify flood damages in the watershed by a poor design with tremendous construction costs. Optimal design of a flood-control multi-reservoir system can simultaneously minimize investment costs of constructions and potential flood damage costs. This study proposes a simulation-based optimization approach to optimize the design of multi-reservoirs for flood control in the watershed by coupling the MIKE-11 hydrodynamic model and the NSGA-II multi-objective optimization model. The present approach provides the Pareto optimal solutions between two conflict objectives of minimizing total investment costs and the expected flood damage costs in the watershed. Application of the proposed model for a small watershed in central part of Iran as a case study shows that optimal designs of multi-reservoir systems can efficiently reduce construction costs, flood peaks and their corresponding damage costs at the downstream reaches of the basin.