Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion

Soil erosion due to surface water is a standout among the serious threat land degradation problem and an hazard environmental destruction. The first stage for every kind of soil conservation planning is recognition of soil erosion status. In this research, the usability of two new techniques remote sensing and geographical information system was assessed to estimate the average annual specific sediments production and the intensity erosion map at two sub-basins of DEZ watershed, southwest of Lorestan Province, Iran, namely Absorkh and Keshvar sub-basins with 19,920 ha, using Modified Pacific Southwest Inter-Agency Committee (MPSIAC) soil erosion model. At the stage of imagery data processing of IRS-P6 satellite, the result showed that an overall accuracy and kappa coefficient were 90.3% and 0.901, respectively, which were considered acceptable or good for imagery data. According to our investigation, the study area can be categorized into three level of severity of erosion: moderate, high, and very high erosion zones. The amount of specific sediments and soil erosion predicted by MPSIAC model was 1374.656 and 2396.574 m³ km^?2 year^?1, respectively. The areas situated at the center and south parts of the watershed were subjected to significant erosion because of the geology formation and ground cover, while the area at the north parts was relatively less eroded due to intensive land cover. Based on effective of nine factors, the driving factors from high to low impact included: Topography > Land use > Upland erosion > Channel erosion > Climate > Ground cover > Soil > Runoff > Surface geology. The measured sediment yield of the watershed in the hydrometric station (Keshvar station) was approximately 2223.178 m³ km^?2 year^?1 and comparison of the amount of total sediment yield predicted by model with the measured sediment yield indicated that the MPSIAC model 38% underestimated the observed value of the watershed.     

An integrated data-mining and multi-criteria decision-making approach for hazard-based object ranking with a focus on landslides and floods

This study is aimed at conducting a hazard-based sustainability gap analysis considering spatial threats driven by floods and landslides, that is, a multi-hazard-based prioritization of the most important cities in Gorganrood Basin, Iran. Two data-mining models were used to assess the spatial probability of flood inundation and landslide occurrence, namely, support vector machine with the radial basis function kernel (SVM-RBF) and maximum entropy (ME). As inputs, a total of 124 flooded locations and 346 landslides with ten flood/landslide predisposing factors were mapped using geoinformatics and organizational data. The random selection method was used to split the flood and landslide inventories into two sets of train and test data. Tolerance index was used to test the multicollinearity among predictors. Validation of the models was carried out using the area under the receiver operating characteristic (ROC) curve (AUC). Finally, TOPSIS was used, as a multi-criteria decision-making model, to make an internal sustainability gap analysis to prioritize the threatened and safe cities. For flood inundation, the AUC values obtained from the test set revealed that the SVM-RBF outperformed ME in terms of predictive power and generalization capacity with the respective areas of 0.831 and 0.796 under the curve. For landslide susceptibility assessment, SVM-RBF again excelled ME in predictive power with the respective values of 0.887 and 0.84. Therefore, the susceptibility maps derived from SVM-RBF, as the premier model, were used for the next stage. Extracting the flood and landslide spatial probability values to 14 city points, the TOPSIS-Solver software made a prioritization using the similarity function to the ideal solution. Accordingly, Aliabad, Minoodasht, and Azadshahr cities, with having the smallest similarity coefficients, were found to be the top three spatially threatened cities in Gorganrood Basin, while Aq Qala, Gomishan, and Gonbad-e Kavus cities were placed at the bottom as the safest cities. This study can be a pivotal point in regional risk-based planning, implementation of further pragmatic measures, and allocation of resources for improving sustainable development most wisely.     

Biomarker analysis of the upper Jurassic Naokelekan and Barsarin formations in the Miran Well-2, Miran oil field,Kurdistan region,Iraq

The Miran oilfield is one of the new oil fields in Kurdistan region, northern Iraq, located in the Sulaimani Governorate. Twelve Cuttings samples from the Upper Jurassic Naokelekan and Barsarin formations in well Miran-2 were selected for detailed organic geochemical investigations. All the samples were subjected to bitumen extraction in order to study any biomarkers present using gas chromatography-mass spectrometry. The dominance of low-molecular-weight n-alkanes and other calculated parameters indicate a marine source for the organic matter derived from planktonic algal and bacterial precursors deposited under anoxic conditions. The isoprenoids/n-alkanes ratios indicate type II and mixed II/III kerogen for both formations. The type II/III kerogen is characteristic of transitional environment under anoxic to dysoxic conditions as also indicated by the homohopane index for studied samples. More argillaceous carbonate rocks were deposited when reducing conditions were prevalent. Medium to high gammacerane index values in the rock extracts probably indicate a stratified water column during deposition of both formations. The studied samples from both formations have entered peak oil window maturity as reflected from the biomarker ratios from both aliphatic and aromatic fractions of the extracts.     

Application of GAINS model for assessing selected air pollutants in Khyber Pakhtunkhwa and Balochistan,Pakistan

Pakistan is a developing country existing geographically at a pivoted location between two of the world’s largest pollution emitting countries (China and India) which adds to the severity of environmental issues faced by the country. These concerns include air pollution, climate change, and extreme weather situations prevailing in Pakistan. This increasing air pollution is deteriorating the health, threatening the food security and adding up its share to the already existing global warming. The initial step in devising a wide ranging, multifaceted, economically feasible, and sustainable solution to deal with the severity of this issue is the quantification of the air pollution and greenhouse gas emission in Pakistan. The GAINS model is one of the most comprehensive tools, dealing with the air pollutants and greenhouse gases covered by the Kyoto Protocol. This study has utilized this model to analyze the source-based anthropogenic emissions of air pollutants (NH₃ and SO₂), volatile organic compounds (VOCs), and greenhouse gases (CH₄ and CO₂), their impacts and abatement cost, for the duration of 1990–2030, in the Khyber Pakhtunkhwa and Balochistan regions of Pakistan. An overall increasing trend was observed during 1990–2030 for (a) air pollutants: NH₃ (223.52–568.87kT/Y); SO₂ (50.52–332.95kT/Y), (b) VOCs (121.76–246.81kT/Y), and (c) greenhouse gases: CO₂ (7.83–62.45MT/Y) and CH₄ (1120-2314kT/Y). The emission inventories created for all greenhouse gases together estimated the increase of 42.37 to 138.57 MTCO₂eq. for greenhouse gases over the time duration of 1990–2030.     

Correction to: New climatic zones in Iran: a comparative study of different empirical methods and clustering technique

Theoretical and Applied Climatology -     

Proposed algorithm for optimization of directional additional exploratory drill holes and computer coding

Block model estimated based on the drill hole information gathered during exploration stage is not appropriate for short- and medium-term mine planning. Additional information prior to mining is required for various purposes, that the source of this information is drill holes. In most situations, reducing the overall uncertainty on the estimation is the major objective of additional drilling and collecting samples from them. The topic of selecting the optimum location for additional exploratory drill holes has been of interest to mining engineers and geostatisticians in the second half of last century, but all of them are not able to optimize directional drill holes because they are based on the 2D space and do not consider the 3D extension of drill holes and block model. This study introduces a methodology to optimize the dip and location of additional exploratory drill holes based on the defined objective function with considering 3D extension of ore body and drill holes. Direct search simulated annealing used that is efficient and robust method for solving the nonlinear unconstrained global optimization problems. This method is very useful in the case that drilling the drill holes with different dips has been obligated due to topography condition and ore body situation. A case study in gold resource illustrates the method.     

Biodegradation of phenol from a synthetic aqueous system using acclimatized activated sludge

Phenol is one of the aromatic hydrocarbons. Phenol and its derivatives are highly toxic. These pollutants can be observed in the effluents of many industries. This research investigates the removal of phenol by the use of activated sludge in a batch system. The effects of influencing factors on biodegradation efficiency have been evaluated. The main factors considered in this study were the volume of acclimatized activated sludge inoculation, pH, temperature, and initial concentration of phenol. The inoculation volumes of 1, 3, and 5 mL of acclimatized activated sludge were taken into account. Different pH values of 3, 5, 7, 9, and 11 were examined. The experiments were conducted for temperatures of 25, 30, 35, and 40 °C and initial phenol concentrations of 400, 800, 1,000, and 1,500 ppm. The results show that the acclimatized activated sludge has a high capacity for the removal of phenol. From a 100-mL aqueous solution was removed 1,500 ppm of phenol after 80 h. Furthermore, maximum phenol removal was observed for an inoculation volume of 5 mL for three different phenol concentrations of 100, 400, and 800 ppm. The best pH was 7 for the biodegradation process, and the optimum temperature was 30 °C. It was further found that an increase in the phenol concentration increased its removal time. Moreover, the activated sludge could effectively remove about 99.9 % of phenol from a synthetic aqueous solution in a batch system.     

Ascribing soil erosion types for sediment yield using composite fingerprinting technique

Abstract

Soil erosion and eroded sediment are serious threats to sound land management. However, less attention has been given to quantifying the importance of different soil erosion features based on appropriate control measures that could be designated. Accordingly, this research was planned to quantify the contribution of potential sediment sources, i.e. sheet, rill and gully erosion, in Idelo watershed in Zanjan Province, Iran, using composite fingerprinting. Toward this aim, 16 geochemical and organic tracers were detected in sediment sources and sediment deposited at the outlet. The results of applying the composite fingerprinting technique, with a relative error of 16%, showed that sheet, rill and gully sources contributed 56%, 44% and 0%, respectively, to sediment yield. It was also apparent from the results that the composite fingerprinting approach could be successfully utilized to assess the provenance of sediment deposited at the main outlet of the study watershed by soil erosion type.

Editor Z.W. Kundzewicz     

Analysis of recharge conceptualization in inverse groundwater modelling

ABSTRACT

This study presents a systematic illustration quantifying how misleading the calibration results of a groundwater simulation model can be when recharge rates are considered as the model parameters to be estimated by inverse modelling. Three approaches to recharge estimation are compared: autocalibration (Model 1), the empirical return coefficient method (Model 2), and distributed hydrological modelling using the Soil and Water Assessment Tool, SWAT (Model 3). The methodology was applied in the Dehloran Plain, western Iran, using the MODFLOW modular flow simulator and the PEST method for autocalibration. The results indicate that, although Model 1 performed the best in simulating water levels at observation wells in the calibration stage, it did not perform satisfactorily in real future scenarios. Model 3, with SWAT-based recharge rates, performed better than the other models in the validation stage. By not evaluating the model performance solely on calibration results, we demonstrate the relative significance of using more accurate recharge estimates when calibrating groundwater simulation models.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR M. Besbes     

A Monte Carlo adapted finite element method for dislocation simulation of faults with uncertain geometry

Dislocation modelling of an earthquake fault is of great importance due to the fact that ground surface response may be predicted by the model. However, geological features of a fault cannot be measured exactly, and therefore these features and data involve uncertainties. This paper presents a Monte Carlo based random model of faults with finite element method incorporating split node technique to impose the effects of discontinuities. Length and orientation of the fault are selected as random parameters in the domain model, and hence geometrical uncertainties are encountered. Mean and standard deviation values, as well as probability density function of ground surface responses due to the dislocation are computed. Based on analytical and numerical calculation of dislocation, two approaches of Monte Carlo simulations are proposed. Various comparisons are examined to illustrate the capability of both methods for random simulation of faults.