Predicting groundwater level of wells in the Diyala River Basin in eastern Iraq using artificial neural network

Al-Mansourieh zone is a part of Al-Khalis City within the province of Diyala and located in the Diyala River Basin in eastern Iraq with a total area about 830 km2.Groundwater is the main water source for agriculture in this zone.Random well drilling without geological and hydraulic information has led the most of these wells to dry up quickly.Therefore,it is necessary to estimate the levels of groundwater in wells through observed data.In this study,Alyuda NeroIntelligance 2.1 software was applied to predict the groundwater levels in 244 wells using sets of measured data.These data included the coordinates of wells(x,y),elevations,well depth,discharge and groundwater levels.Three ANN structures(5-3-3-1,5-10-10-1 and 5-11-11-1)were used to predict the groundwater levels and to acquire the best matching between the measured and ANN predicted values.The coefficient of correlation,coefficient determination(R2)and sum-square error(SSE)were used to evaluate the performance of the ANN models.According to the ANN results,the model with the three structures has a good predictability and proves more effective for determining groundwater level in wells.The best predictor was achieved in the structure 5-3-3-1,with R2 about 0.92,0.89,0.84 and 0.91 in training,validation,testing and all processes respectively.The minimum average error in the best predictor is achieved in validation and testing processes at about 0.130 and 0.171 respectively.On the other hand,the results indicated that the model has the potential to determine the appropriate places for drilling the wells to obtain the highest level of groundwater.     

Early Cretaceous sedimentary provenance and structural evolution of the central Sanandaj–Sirjan Zone,Iran: implications for palaeogeographic reconstructions of the northern Neo-Tethyan margin

ABSTRACT

The Early Cretaceous was an important epoch in the evolution of the Earth system in which major tectonic episodes occurred, especially along the Alpine–Himalayan belt. The paucity of reliable palaeogeographic data from the central segment of this geological puzzle, however, hampers the reconstruction of a panoramic view of its Early Cretaceous palaeogeography and geodynamic setting. Here we present multidisciplinary provenance data from Lower Cretaceous strata of the overriding plate of the Neo-Tethyan subduction zone (the Sanandaj–Sirjan Zone; SSZ, of central Iran), including structural, basin-fill evolution, petrographic and geochemical analyses. Sandstone provenance analysis of Lower Cretaceous red beds suggests the occurrence of sub-mature litho-quartzose sandstones attributed to an active continental arc margin in convergent setting predominantly derived from plutonic, quartzose sedimentary and metamorphic rocks exposed in the central SSZ. Weathering indices indicate moderate chemical weathering in the source area which may be related to close source-to-sink relationships or arid climate. Our palaeogeographic reconstructions and original geological mapping indicate that the erosion of uplifted basement rocks exposed in horst blocks provided the sediment sources for the syn-extensional deposition of uppermost Jurassic–lowermost Cretaceous conglomerates and Lower Cretaceous siliciclastic red beds within a continental retro-arc basin during initiation of the ‘Neo-Tethys 2?. The polyphase tectonic reactivation along the principal fault of the study area controlled the syn- and post-extensional tectonostratigraphic evolution that reflect the corresponding mechanical decoupling/coupling along the northern Neo-Tethyan plate margin.     

Makran ophiolitic basalts (SE Iran) record Late Cretaceous Neotethys plume-ridge interaction

ABSTRACT

The Makran complex in southeast Iran provides a spectacular subduction-related accretionary complex to understand the mechanism of oceanic accretion and the evolution of subduction zones. In this paper, we present new major and trace element data as well as isotopic compositions of mafic volcanic blocks from the Makran ophiolitic mélange complex (OMC). Our aim is to assess the genesis of these rocks and discuss their implications on the evolution of Neotethys Ocean. These volcanic blocks are composed mainly of basalts with minor trachytes. The Makran lavas are occasionally interlayered with tuff layers. Zircons from these tuffs give U-Pb ages of 95 Ma, which is well in accordance with the reposted microfossil data for the interlayered pelagic limestones with pillow lavas. Makran basalts can be geochemically subdivided into four groups; normal to transitional MORB, enriched-MORB, Plume-type MORB and alkaline (-OIB-like) basalts. The OIB-like pillow lavas are represented by high values of Th/Tb (6.3–7.4) which are higher than other basalts (group 1 = 0.3–0.8; groups 2 = 0.7–1.6; group 3 = 1.58–1.36).¹⁴³Nd/¹⁴⁴Nd_(t) ratios for basalts ranges from 0.51247 to 0.51292, whereas ⁸⁷Sr/⁸⁶Sr_(t) isotopic composition of the OMC lavas varies from 0.704433 to 0.709466. The Pb isotopic composition of the lavas are quite high, ranging from 15.49–15.66 for ²⁰⁷Pb/²⁰⁴Pb_(t), 18.09–19.12 for ²⁰⁶Pb/²⁰⁴Pb_(t) and 37.80–39.23 for ²⁰⁸Pb/²⁰⁴Pb_(t). The chemistry of these rocks suggests that they were formed most likely in an oceanic setting with clear plume-ridge interaction. These rocks can form from partial melting of a highly heterogeneous mantle source, which is extensively metasomatized with deep mantle OIB-type components. We suggest these rocks have been generated in an oceanic ridge with plume-ridge interaction, similar to the Iceland-Reykjanes Ridge, before being fragmented and accreted into the Makran accretionary complex.     

Heavy metal pollution and human health risk assessment for exposure to surface soil of mining area: a comprehensive study

Climate change projections indicate an increase in intense rainfall events with consequent river flooding, which could lead to devastating natural disaster     

Time independent seismic hazard analysis in Alborz and surrounding area

The Bayesian probability estimation seems to have efficiencies that make it suitable for calculating different parameters of seismicity. Generally this method is able to combine prior information on seismicity while at the same time including statistical uncertainty associated with the estimation of the parameters used to quantify seismicity, in addition to the probabilistic uncertainties associated with the inherent randomness of earthquake occurrence. In this article a time-independent Bayesian approach, which yields the probability that a certain cut-off magnitude will be exceeded at certain time intervals is examined for the region of Alborz, Iran, in order to consider the following consequences for the city of Tehran. This area is located within the Alpine-Himalayan active mountain belt. Many active faults affect the Alborz, most of which are parallel to the range and accommodate the present day oblique convergence across it. Tehran, the capital of Iran, with millions of inhabitants is located near the foothills of the southern Central Alborz. This region has been affected several times by historical and recent earthquakes that confirm the importance of seismic hazard assessment through it. As the first step in this study an updated earthquake catalog is compiled for the Alborz. Then, by assuming a Poisson distribution for the number of earthquakes which occur at a certain time interval, the probabilistic earthquake occurrence is computed by the Bayesian approach. The highest probabilities are found for zone AA and the lowest probabilities for zones KD and CA, meanwhile the overall probability is high.     

Investigation of Failed Slopes Based on a New Method of Back Analysis in Rock Masses: A Case Study

Geotechnical and Geological Engineering - Small variation in shear strength parameters results in remarkable changes in the safety factor (SF) of a rock slope. In this regard, rock mass strength of...     

Gold Deposits in the Sanandaj–Sirjan Zone: Orogenic Gold Deposits or Intrusion‐Related Gold Systems?

Most of the known large gold deposits in Iran are located along the Sanandaj–Sirjan Zone, western Iran, which hosts a wide range of gold deposit types. Gold deposits in the belt, hosted in upper Paleozoic to upper Mesozoic volcano‐sedimentary sequences of lower greenschist to lower amphibolite metamorphic grade, appear to represent mainly orogenic and intrusion‐related gold deposit types. The largest resource occurs at Muteh, with smaller deposits/occurrences at Zartorosht, Qolqoleh, Kervian, Qabaqloujeh, Kharapeh, and Astaneh. Although a major part of the gold deposits in the Sanandaj–Sirjan Zone are related to metamorphic devolatilization, some deposits including Muteh and Astaneh are related to short‐lived disruptions in an extensional tectonic regime and are associated with magma generation and emplacement. The age of gold ore formation in the orogenic gold deposits is Late Cretaceous to Tertiary, reflecting peak‐metamorphism during regional Cretaceous–Paleocene convergence and compression. The Oligocene to Pliocene age of most intrusion‐related gold systems is consistent with the young structural setting of the gold ore bodies; these deposits are sequestered along normal faults, correlated with Middle to Late Tertiary extensional tectonic events. This relationship is comparable to the magmatic‐metallogenetic evolution of the Urumieh‐Dokhtar magmatic arc, where the number of different types of gold‐copper deposits and the magnitude of the larger ones followed development of a magmatic arc. The appropriate explanation may be related to two different stages of gold mineralization consisting of a first compressional phase during the Late Cretaceous to Early‐Middle Tertiary, which is related to orogenic gold mineralization in the Qolqoleh, Kervian, Qabaqloujeh, Kharapeh, and Zartorosht deposits, and the extensional phase during the Eocene to Pliocene that is recognized by young intrusion‐related gold mineralization in the Muteh and Astaneh deposits.     

Optimal water and waste load allocation in reservoir–river systems: a case study

In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.