A spatio-temporal three-dimensional conceptualization and simulation of Dera Ismail Khan alluvial aquifer in visual MODFLOW: a case study from Pakistan

Dera Ismail Khan (DIK) is situated in the Lower Indus Basin of Pakistan. The land use has been changed in the canal command area due to irrigation activities near the Indus River. To check the current status and predict the groundwater levels in the area, the unconfined aquifer has been simulated in Visual MODFLOW for a period of 35 years, i.e., from 1985 to 2020. The 2900-km² area has been modeled with a grid of 500 by 500 m and the depth set to 100 m. The aquifer in the study area has been divided vertically and laterally into three and ten zones, respectively, for the characterization. Water wells and streams were used as the sinks and hydrologic boundaries, respectively. The model was successfully calibrated in steady and the non-steady state. The simulation revealed that the whole simulation can be divided into two phases, i.e., before and after the construction of the Chashma Right Bank Canal (CRBC), whereas the results were summarized in the form of water table depth maps and groundwater budget calculations. To determine the groundwater sustainability, a conjunctive use scenario has been employed to simulate the aquifer dynamics till 2020. The simulation revealed incremental drawdowns till the end.     

Climatic prediction of the terrestrial and coastal areas of Iraq

Climatic data from four meteorological stations in Iraq (Mosul, Baghdad, Basra, and Rutba) were obtained. The recorded temperature data since 1960 till 2007 and rainfall and evaporation data since 1960 till 2008 and 1970 till 2008, respectively, were used and interpreted. This study showed an increase in temperature of about 5°C/47?years and an increase in evaporation rate with a decrease in the rainfall rate. Carbon dioxide in the atmosphere appears to be a factor controlling climate change. Basra climate, due to its location which is nearest to the Arabian Gulf, is expressed as a coastal climate and has a different behavior from Mosul, Baghdad, and Rutba, which are considered as terrestrial climates.     

An operational multiscale system for hazards prediction, mapping, and response

By definition, a crisis is a situation that requires assistance to be managed. Hence, response to a crisis involves the merging of local and non-local emergency response personnel. In this situation, it is critical that each participant: (1) know the roles and responsibilities of each of the other participants; (2) know the capabilities of each of the participants; and (3) have a common basis for action. For many types of natural disasters, this entails having a common operational picture of the unfolding events, including detailed information on the weather, both current and forecasted, that may impact on either the emergency itself or on response activities. The Consequences Assessment Tool Set (CATS) is a comprehensive package of hazard prediction models and casualty and damage assessment tools that provides a linkage between a modeled or observed effect and the attendant consequences for populations, infrastructure, and resources, and, hence, provides the common operational picture for emergency response. The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is an atmospheric simulation system that links the latest methods in computational fluid dynamics and high-resolution gridding technologies with numerical weather prediction to provide specific weather analysis and forecast capability that can be merged into the geographic information system framework of CATS. This paper documents the problem of emergency response as an end-to-end system and presents the integrated CATS–OMEGA system as a prototype of such a system that has been used successfully in a number of different situations.     

Chemical Characteristics of Stream Draining fromDudu Glacier: An Alpine Meltwater Stream inGanga Headwater, Garhwal Himalaya

I-DtjcrONAlpine environment enjoys a distinct set of physicochemical conditions asl compared to other aqueous systems. Thehydrochemical characteristics of meltwater draining from thisenvironment are different from the other aqueous ecosystemsdue to their mountainous nature and extreme cold climatic conditions. The high concentration of various chemical constitu.ents in meltwater shows the intensive chemical weathering inthe basin. The rapid physical weathering due tO grinding actionof the gl…     

Eco-friendly smart hydrogels for soil conditioning and sustain release fertilizer

In the agricultural industry, biomass waste generated along with the production of food, is transformed into value-added products. Also, the demand for the slow or control release fertilizer is increasing to reduce the cost of maintaining the agricultural land. These issues are tackled by converting biomass waste to a slow fertilizer release vehicle and biodegradable water retention material that could reduce the cost for fertilizer application and simultaneously preserved the soil from dryness. A series of carboxymethyl sago pulp (CMSP) hydrogels were prepared by electron beam irradiation. Slow release systems were evaluated by loading potassium nitrate (KNO₃) and ammonium nitrate (NH₄NO₃) into the CMSP hydrogels. These CMSP hydrogels endow slow release property, biodegradability and a soil moisture preservation property that could find greener application in agricultural industries. The results indicate that CMSP hydrogels have a great potential as an agent for slow release of fertilizers.     

Seismic fragility functions for code compliant and non-compliant RC SMRF structures in Pakistan

Fragility functions are derived for low-rise code compliant & non-compliant special moment resisting frames (SMRFs). Non-compliant SMRFs those built in low strength concrete and lacking confining ties in joint panel zones, commonly found in developing countries. Shake table tests were performed on single-storey and two-storey 1:3 reduced scale representative frames to understand the damage mechanism and develop deformation-based damage scale. The non-compliant SMRF experienced column flexure cracking, longitudinal bar-slip in beam and observed with cover concrete spalling from the joint panels. The code compliant SMRF experienced flexure cracks in beam/column, and experienced joint cracking under extreme shaking. Numerical modeling technique is developed for inelastic modeling of reinforced concrete frame with beam bar-slip and joint damageability using SeismoStruct. Natural accelerograms were used to analyze the considered frames through incremental dynamic analyses in SeismoStruct. A probabilistic based approach was used to derive fragility functions for the considered frames. An example case study is presented for damageability evaluation of structures for earthquakes of various return periods (43, 72, 475, 2475 years).     

Numerical simulation of damage–Permeability relationship in brittle geomaterials

Finding a coupling model between a hydraulic parameter such as permeability and a mechanical parameter such as damage is the key element for several recent engineering problems. A review of the technical literature reveals that several mechanical constitutive laws exist which allow determining a damage tensor for a damageable porous material under loading. But the present work develops a method to deduce the permeability change due to the damage propagation.     

Iron-Titanium Oxide Geothermometry and Petrogenesis of Lava Flows and Dykes from Mandla Lobe of the Eastern Deccan Volcanic Province, India

Compositional studies on different forms of magnetite, ulvospinel, ilmenite and hematite mineral phases occurring in 37 lava flows and 6 dykes of the Mandla lobe are presented in this paper. Ilmenite (0001) in equilibrium with titanomanetite show high values of temperature of equilibration, ranging from 1172–974°C, for high alumina quartz normative tholeiitic lava flows of Chemical Type - A; 1129–1229°C for low alumina quartz normative tholeiitic lava flows of Chemical Type - B; 1283–1124°C for tholeiitic lava flows of Chemical Type - F and 1243°C and 99O°C for two diopside olivine normative tholeiite flows of Chemical Type D. High olivine normative flows of Chemical Type - G and H show 1095°C and 1092°C respectively. Whereas, high hypersthene normative tholeiite flow of Chemical me C shows temperature of 1187°C. Data plots disposition over iron-titanium oxide equilibration temperature vs – logfo₂, diagram for Mandla lava flows and other parts of the Deccan (Igatpuri, Mahabaleshwer, Nagpur and Sagar areas) revealed that tholeiitic (evolved) basalt of the eastern Deccan volcanic province formed at high temperatures whereas, picritic (primitive) lavas of Igatpuri and tholeiitic basalt of Mahabaleshwar areas were formed at low temperatures. Mahabaleshwer basalts follow FMQ (fayalite-magnetite-quartz) buffer curve but, plots of the Mandla basalts lie above this curve indicating higher temperatures of crystallisation of ilmenite-titanomagnetite than that of the lava flows from other parts of Deccan 'Raps. The eastern Deccan Traps are most evolved types of lava as characterised by its low Mg-number and Ni content whereas, Igatpuri lava flows are picritic (primitive), having high Mg-number and Ni contents. Temperature vs FeO + Fe₂O₃ / FeO + Fe₂O₃ + MgO ratio data plots for Mandla and other Deccan lava flows and liquidus data for Hawaiian tholeiites, indicated that Igatpuri basalts lie parallel to the liquidus line of Hawaiian tholeiite but at lower temperatures. Large data plots of Mandla lava flows lie along the liquidus line of the Hawaiian lava. The highly vesicular nature of compound lava flows having large amount of volatile is responsible for low temperature values whereas, lava flows represented by high temperatures show high modal values of glass and opaque minerals.     

3D inversion of DC data using artificial neural networks

In this paper, we investigate the applicability of artificial neural networks in inverting three-dimensional DC resistivity imaging data. The model used to produce synthetic data for training the artificial neural network (ANN) system was a homogeneous medium of resistivity 100 Ωm with an embedded anomalous body of resistivity 1000 Ωm. The different sizes for anomalous body were selected and their location was changed to different positions within the homogeneous model mesh elements. The 3D data set was generated using a finite element forward modeling code through standard 3D modeling software. We investigated different learning paradigms in the training process of the neural network. Resilient propagation was more efficient than any other paradigm. We studied the effect of the data type used on neural network inversion and found that the use of location and the apparent resistivity of data points as the input and corresponding true resistivity as the output of networks produces satisfactory results. We also investigated the effect of the training data pool volume on the inversion properties. We created several synthetic data sets to study the interpolation and extrapolation properties of the ANN. The range of 100–1000 Ωm was divided into six resistivity values as the background resistivity and different resistivity values were also used for the anomalous body. Results from numerous neural network tests indicate that the neural network possesses sufficient interpolation and extrapolation abilities with the selected volume of training data. The trained network was also applied on a real field dataset, collected by a pole-pole array using a square grid (8 ×8) with a 2-m electrode spacing. The inversion results demonstrate that the trained network was able to invert three-dimensional electrical resistivity imaging data. The interpreted results of neural network also agree with the known information about the investigation area.