Satellite-based rainfall estimation and discharge measurement of Middle Indus River,Pakistan

The impacts of floods and droughts are intensified by climate change, lack of preparedness, and coordination. The average rainfall in study area is ranging from 200 to 400 mm per year. Rain gauge generally provides very accurate measurement of point rain rates and the amounts of rainfall but due to scarcity of the gauge locations provides very general information of the area on regional scale. Recognizing these practical limitations, it is essential to use remote sensing techniques for measuring the quantity of rainfall in the Middle Indus. In this research, Tropical Rainfall Measuring Mission (TRMM) estimation can be used as a proxy for the magnitude of rainfall estimates from classical methods (rain gauge), quantity, and its spatial distribution for Middle Indus river basin. In order to use TRMM satellite data for discharge measurement, its accuracy is determined by statistically comparing it with in situ gauged data on daily and monthly bases. The daily R ² value (0.42) is significantly lower than monthly R ² value (0.82), probably due to the time of summation of TRMM 3-hourly precipitation data into daily estimates. Daily TRMM data from 2003 to 2012 was used as input forcing in Soil and Water Assessment Tool (SWAT) hydrological model along with other input parameters. The calibration and validation results of SWAT model give R ² = 0.72 and 0.73 and Nash-Sutcliffe coefficient of efficiency = 0.69 and 0.65, respectively. Daily and monthly comparison graphs are generated on the basis of model discharge output and observed data.     

A comparative study between sequential Gaussian simulation and kriging method grade modeling in open-pit mining

Grade estimation is very important in designing open pits. In the process of grade estimation, underestimation can result in loss of economic ore, whereas overestimation would unnecessarily increase stripping ratio. Normally, kriging method, which suffers from underestimation and/or overestimation due to smoothing effect, is used for grade estimation. To overcome drawbacks of the kriging method, more efficient techniques such as conditional simulation can be applied. In this paper, utilizing sequential Gaussian conditional simulation, grade models were constructed for Sungun copper deposit situated in the North West of Iran. According to the obtained results, it was observed that conditional simulation can effectively cope with the weakness of kriging method. Also, it was observed that as compared to the kriging method, grade distribution, resulted from the conditional simulation, is almost identical to that of the real exploration data. Accordingly, using conditional simulation, the amount of mineable ore was significantly increased, and also, average net present value as the mines’ most important economic indicator was improved by 40%.     

Cadmium (Cd) concentration in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis>) grown in Cd-spiked soil varies with the doses and biochar feedstock

Biochar is considered a promising amendment for the reduction of metal concentration in plants; however, the effects of biochar in terms of dose and feedstock on metal uptake by plants remain widely unclear. In the current study, three individual biochars were prepared at 450 °C from different feedstocks (wheat straw, sukh chain (Pongamia pinnata), and cotton sticks). The main aim was to evaluate their ability to remediate cadmium (Cd)-spiked soil in terms of growth response and Cd uptake by wheat (Triticum aestivum) tissues. Biochars were separately applied at 0, 1, and 2% (w/w) in Cd-spiked soil and wheat was grown until maturity in pots and then morphological and physiological parameters and Cd concentrations in grains, roots, and shoots were determined. The post-harvest soil was analyzed for extractable Cd concentrations. Plants grown in Cd-spiked soil treated with biochars had higher seed germination, lengths of roots, shoots, and spikes, grains per spike and leaf relative water contents, chlorophyll contents, and dry weight of roots, shoots, and grains as compared to the untreated control. Biochar treatments significantly decreased the Cd concentrations in shoots, roots, and grains as well as total Cd uptake by grains. Soil extractable Cd concentrations were significantly decreased with biochar treatments. The application of 2.0% wheat straw biochar was the most efficient treatment in increasing grain yield and decreasing Cd in grains as well as soil extractable Cd than the other two biochars and doses applied.     

Geological setting and timing of the Chah Zard breccia-hosted epithermal gold–silver deposit in the Tethyan belt of Iran

The breccia-hosted epithermal gold–silver deposit of Chah Zard is located within a high-K, calc-alkaline andesitic to rhyolitic volcanic complex in the central part of the Urumieh-Dokhtar Magmatic Arc (UDMA), west central Iran. The total measured resource for Chah Zard is ∼2.5 million tonnes of ore at 12.7 g/t Ag and 1.7 g/t Au (28.6 t Ag, 3.8 t Au), making it one of the largest epithermal gold deposits in Iran. Magmatic and hydrothermal activity was associated with local extensional tectonics in a strike-slip regime formed in transtensional structures of the Dehshir-Baft strike-slip fault system. The host rocks of the volcanic complex consist of Eocene sedimentary and volcanic rocks covered by Miocene sedimentary rocks. LA-ICP–MS U–Pb zircon geochronology yields a mean age of 6.2 ± 0.2 Ma for magmatic activity at Chah Zard. This age represents the maximum age of mineralization and may indicate a previously unrecognized mineralization event in the UDMA. Breccias and veins formed during and after the waning stages of explosive brecciation events due to shallow emplacement of rhyolite porphyry. Detailed systematic mapping leads to the recognition of three distinct breccia bodies: volcaniclastic breccia with a dominantly clastic matrix; gray polymict breccia with a greater proportion of hydrothermal cement; and mixed monomict to polymict breccia with clay matrix. The polymictic breccias generated bulk-mineable ore, whereas the volcaniclastic breccia is relatively impermeable and largely barren. Precious metals occur with sulfide and sulfosalt minerals as disseminations, as well as in the veins and breccia cements. There is a progression from pyrite-dominated (stage 1) to pyrite-base metal sulfide and sulfosalt-dominated (stages 2 and 3) to base metal sulfide-dominated (stage 4) breccias and veins. Hydrothermal alteration and deposition of gangue minerals progressed from illite-quartz to quartz-adularia, carbonate, and finally gypsum-dominated assemblages. Free gold occurs in stages 2 and 4, principally intergrown with pyrite, quartz, chalcopyrite, galena, sphalerite, and Ag-rich tennantite–tetrahedrite, and also as inclusions in pyrite. High Rb/Sr ratios in ore-grade zones are closely related to sericite and adularia alteration. Positive correlations of Au and Ag with Cu, As, Pb, Zn, Sb, and Cd in epithermal veins and breccias suggest that all these elements are related to the same mineralization event.     

Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping

This study compares the predictive performance of GIS-based landslide susceptibility mapping (LSM) using four different kernel functions in support vector machines (SVMs). Nine possible causal criteria were considered based on earlier similar studies for an area in the eastern part of the Khuzestan province of southern Iran. Different models and the resulting landslide susceptibility maps were created using information on known landslide events from a landslide inventory dataset. The models were trained using landslide inventory dataset. A two-step accuracy assessment was implemented to validate the results and to compare the capability of each function. The radial basis function was identified as the most efficient kernel function for LSM with the resulting landslide susceptibility map showing the highest predictive accuracy, followed by the polynomial kernel function. According to the obtained results, it concluded that using SVMs can generally be considered to be an effective method for LSM while it demands careful consideration of kernel function. The results of the present research will also assist other researchers to select the best SVM kernel function to use for LSM.     

Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran

The main goal of this study was to investigate the application of the weights-of-evidence and certainty factor approaches for producing landslide susceptibility maps of a landslide-prone area (Haraz) in Iran. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. The landslide conditioning factors considered for the study area were slope gradient, slope aspect, altitude, lithology, land use, distance from streams, distance from roads, distance from faults, topographic wetness index, stream power index, stream transport index and plan curvature. For validation of the produced landslide susceptibility maps, the results of the analyses were compared with the field-verified landslide locations. Additionally, the receiver operating characteristic curves for all the landslide susceptibility models were constructed and the areas under the curves were calculated. The landslide locations were used to validate results of the landslide susceptibility maps. The verification results showed that the weights-of-evidence model (79.87%) performed better than certainty factor (72.02%) model with a standard error of 0.0663 and 0.0756, respectively. According to the results of the area under curve evaluation, the map produced by weights-of-evidence exhibits satisfactory properties.     

Event in the case of a single reservoir: the Ghèzala dam in Northern Tunisia

The paper focuses on the development of reservoir operating rules for dry and rainfall events, and their implementation in the case of the Ghézala dam located in northern Tunisia (characterized by Mediterranean climate). Rainfall events are defined in terms of depth and duration that are correlated to each other. A depth analysis per event is performed, conditioned on the event duration. The gamma distribution provides a good fit to depth per event, especially for events lasting at least 6 days. The event duration fits a geometric distribution, whereas the dry events during the rainy season fit a negative binomial distribution. The climatic cycle length is fitted to a gamma distribution. On this basis, many 50-year synthetic event series were generated. Every synthetic streamflow sequence obtained from synthetic rainfall sequences as well as the one derived from the historic rainfall events time series were optimized and optimal decisions were formulated. These decisions were assessed by means of multiple regression analysis to estimate the relation between the optimal decision to every stage (dry or rainfall event) and other system variables. Optimal rules, which have a linear form, were derived by predetermined useful storage interval and depend on storage, inflows and downstream demand at dry or rainfall event t. The range of t is 1–13 days (rainfall event) and 1–57 days (dry event). The rules were satisfactory for every predetermined useful storage interval. The simulated dam performance generated by the operation rules was compared with the deterministic optimum operation and the historical operation. Also included is the comparison of the implicit stochastic optimization-based operation policy per event during the water years 1985–2002.