Flood frequency analysis based on simulated peak discharges

Flood frequency approaches vary from statistical methods, directly applied on the observed annual maximum flood series, to adopting rainfall–runoff simulation models that transform design rainfalls to flood discharges. Reliance on statistical flood frequency analysis depends on several factors such as the selected probability distribution function, estimation of the function parameters, possible outliers, and length of the observed flood series. Through adopting the simulation approach in this paper, watershed-average rainfalls of various occurrence probabilities were transformed into the corresponding peak discharges using a calibrated hydrological model. A Monte Carlo scheme was employed to consider the uncertainties involved in rainfall spatial patterns and antecedent soil moisture condition (AMC). For any given rainfall depth, realizations of rainfall spatial distribution and AMC conditions were entered as inputs to the model. Then, floods of different return periods were simulated by transforming rainfall to runoff. The approach was applied to Tangrah watershed in northeastern Iran. It was deduced that the spatial rainfall distribution and the AMCs exerted a varying influence on the peak discharge of different return periods. Comparing the results of the simulation approach with those of the statistical frequency analysis revealed that, for a given return period, flood quantiles based on the observed series were greater than the corresponding simulated discharges. It is also worthy to note that existence of outliers and the selection of the statistical distribution function has a major effect in increasing the differences between the results of the two approaches.     

Evaluation of Tailings from a Porphyry Copper Mine based on Joint Simulation of Contaminants

Natural Resources Research - Tailings from porphyry copper mines contain environmentally harmful amounts of elements such as copper, molybdenum, lead and cobalt. Geostatistical simulation of...     

ODM: an analytical solution-based tool for reacting oxygen diffusion modelling in mine spoils

A simple one-dimensional analytical solution is presented to model oxygen diffusion through the pore space of mine spoils containing pyrite. The model incorporates volumetric oxygen consumption terms due to pyrite oxidation, oxidation of Fe ²⁺ to Fe ³⁺ and bacterial activity. Based on this analytical solution, a graphical user interface (GUI) tool is programmed and designed in MATLAB software. This tool can be used to model transport of oxygen through the mine spoils either with or without a cap. Results of several simulation scenarios of sensitivity analysis showed a significant change in oxygen concentration with varying effective diffusion coefficient of oxygen transport model and simulation time. Efficiency and flexibility of the tool developed here is verified by modelling oxygen transport through the pore space of a coal waste pile (case A) and a copper mine tailings (case B). Maximum depth of oxygen diffusion is obtained approximately equal to 2 and 1.5 m through the cases A and B, respectively.     

Influence of mid-latitude circulation on upper Indus basin precipitation: the explicit role of irrigation

Since much of the flow of the Indus River originates in the Himalayas, Karakoram and Hindu Kush Mountains, an understanding of weather characteristics leading to precipitation over the region is essential for water resources management. This study examines the influence of upper level mid-latitude circulation on the summer precipitation over upper Indus basin (UIB). Using reanalysis data, a geopotential height index (GH) is defined at 200 hPa over central Asia, which has a significant correlation with the precipitation over UIB. GH has also shown significant correlation with the heat low (over Iran and Afghanistan and adjoining Pakistan), easterly shear of zonal winds (associated with central Asian high) and evapotranspiration (over UIB). It is argued that the geopotential height index has the potential to serve as a precursor for the precipitation over UIB. In order to assess the influence of irrigation on precipitation over UIB, a simplified irrigation scheme has been developed and applied to the regional climate model REMO. It has been shown that both versions of REMO (with and without irrigation) show significant correlations of GH with easterly wind shear and heat low. However contrary to reanalysis and the REMO version with irrigation, the REMO version without irrigation does not show any correlation between GH index and evapotranspiration as well as between geopotential height and precipitation over UIB, which is further confirmed by the quantitative analysis of extreme precipitation events over UIB. It is concluded that although atmospheric moisture over coastal Arabian sea region, triggered by wind shear and advected northward due to heat low, also contribute to the UIB precipitation. However for the availability of necessary moisture for precipitation over UIB, the major role is played by the evapotranspiration of water from irrigation. From the results it may also be inferred that the representation of irrigated water in climate models is unavoidable for studying the impact of global warming over the region.     

Determination of Realistic and Statistical Value of the Information Gathered from Exploratory Drilling

Unlike other branches of geosciences, exploratory drilling has not been investigated within the framework of an information system; so, the expression “value of exploratory drilling information” (despite its common usage) is vague. This article presents a model for the evaluation of value of the information gathered from exploratory drilling after studying different mineral exploration and exploratory drilling systems within the framework of an “information system.” Although this model does not present the economic value of information, it is a suitable tool for comparing different drilling patterns. The model was verified on the basis of drilling data for the Gol-Gohar XIIA anomaly.     

Burden prediction in blasting operation using rock geomechanical properties

Burden prediction is a vital task in the production blasting. Both the excessive and insufficient burden can significantly affect the result of blasting operation. The burden which is determined by empirical models is often inaccurate and needs to be adjusted experimentally. In this paper, an attempt was made to develop an artificial neural network (ANN) in order to predict burden in the blasting operation of the Mouteh gold mine, using considering geomechanical properties of rocks as input parameters. As such here, network inputs consist of blastability index (BI), rock quality designation (RQD), unconfined compressive strength (UCS), density, and cohesive strength. To make a database (including 95 datasets), rock samples are used from Iran’s Mouteh goldmine. Trying various types of the networks, a neural network, with architecture 5-15-10-1, was found to be optimum. Superiority of ANN over regression model is proved by calculating. To compare the performance of the ANN modeling with that of multivariable regression analysis (MVRA), mean absolute error (E _a), mean relative error (E _r), and determination coefficient (R ²) between predicted and real values were calculated for both the models. It was observed that the ANN prediction capability is better than that of MVRA. The absolute and relative errors for the ANN model were calculated 0.05 m and 3.85%, respectively, whereas for the regression analysis, these errors were computed 0.11 m and 5.63%, respectively. Moreover, determination coefficient of the ANN model and MVRA were determined 0.987 and 0.924, respectively. Further, a sensitivity analysis shows that while BI and RQD were recognized as the most sensitive and effective parameters, cohesive strength is considered as the least sensitive input parameters on the ANN model output effective on the proposed (burden).     

Statistical landslide susceptibility assessment of the Mansehra and Torghar districts,Khyber Pakhtunkhwa Province,Pakistan

This paper presents laboratory experiments and numerical simulations of effects of submerged obstacles on tsunami-like solitary wave and its run-up. This study was carried out for the breaking and non-breaking solitary waves on 1:19.85 uniform slope which contains a submerged obstacle. New laboratory experiments are performed to describe the mitigation of tsunami amplitude and run-up under the effect of submerged obstacles. We are based on experimental results obtained to validate the numerical model. The numerical modeling using COULWAVE aims essentially to show the effect of the obstacle on the shape of solitary wave and the limit of this effect. Using a multiple nonlinear regression, we have determined a model to estimate height of run-up according to the amplitude of the wave and the obstacle peak depth.     

Prediction of riverine suspended sediment discharge using fuzzy logic algorithms, and some implications for estuarine settings

The ability of fuzzy logic algorithms to model relationships between stream flow and suspended sediment discharge was investigated using daily measurements of stream flow and suspended sediment discharge for the Escanaba River mouth station, situated on the shore of Lake Michigan and operated by the US Geological Survey. Three different configurations of inputs were applied, whereby the inputs were fuzzified into fuzzy subsets of variables by means of triangular membership functions. The relationships between inputs and suspended sediment discharge (output) were represented by a set of fuzzy rule expressed in IF–THEN format. The weighted average method served for defuzzification. The commonly used sediment rating curve was also applied to the data, and its performance compared with that of the three models by means of statistical analyses. For all three models, suspended sediment discharge predicted by the fuzzy logic algorithm was in satisfactory agreement with observations. Furthermore, the fuzzy logic algorithms performed better than the sediment rating curve, particularly at higher rates of suspended sediment discharge (in this study, more than 50  × 10⁶ g/day). Considered collectively, the use of fuzzy logic algorithms is suggested as a simple and effective approach for better prediction of suspended sediment discharge, also for estuaries.     

Nonlinear analysis of laterally loaded rigid piles in cohesive soil

This article presents a method for the nonlinear analysis of laterally loaded rigid piles in cohesive soil. The method considers the force and the moment equilibrium to derive the system equations for a rigid pile under a lateral eccentric load. The system equations are then solved using an iteration scheme to obtain the response of the pile. The method considers the nonlinear variation of the ultimate lateral soil resistance with depth and uses a new closed‐form expression proposed in this article to determine the lateral bearing factor. The method also considers the horizontal shear resistance at the pile base, and a bilinear relationship between the shear resistance and the displacement is used. For simplicity, the modulus of horizontal subgrade reaction is assumed to be constant with depth, which is applicable to piles in overconsolidated clay. The nonlinearity of the modulus of horizontal subgrade reaction with pile displacement at ground surface is also considered. The validity of the developed method is demonstrated by comparing its results with those of 3D finite element analysis. The applications of the developed method to analyze five field test piles also show good agreement between the predictions and the experimental results. The developed method offers an alternative approach for simple and effective analysis of laterally loaded rigid piles in cohesive soil. Copyright © 2011 John Wiley & Sons, Ltd.