Mapping of a detachment fault in Kythera Island and study of the related structural shear sense indicators

Kythera Island is located on the prominent submarine horst between Crete and the Peloponnese in the southwestern part of the Aegean. The structure of Kythera is characterized by a pile of tectonic slices derived from different paleogeographic zones. The upper unmetamorphosed units comprise pelagic limestones and cherts of Pindos zone emplaced by thrusting in the Eocene on top of Tripolis zone neritic limestones. These units are separated from the lower metamorphosed unit of Phyllite-Quartzite (PQU) exposed in the northern part of Kythera by an extensional detachment fault of Late Miocene age. The lower tectonic unit of PQU was affected by high-pressure/low-temperature blueschist metamorphism during or after the middle Miocene, but the higher non-metamorphic carbonate units were affected only by local recrystallization. Both brittle and ductile structures related to the extensional detachment can be mapped near the contact of the contrasting metamorphic and non-metamorphic units. Brittle extension is expressed in the cover rocks by dominant NW-SE striking normal faults and related veins and breccias. Ductile structures in the metamorphic unit include mylonites and prominent ductile stretching fabrics which have in different places components of NW-SE and NE-SW extension. Pliocene sediments are mostly horizontal and cover the detachment unconformably. Extension was presumably related to rapid subduction rollback, as previously suggested by others. Differential movement of and vertical axis rotation in the Crete-Peloponnese ridge during this process may be linked to cross-ridge strike slip faults. Evidence of NE-SW dextral faulting is seen in northern Kythera outcrops, related to a significant fault of this type between Kythera and the Peloponnese

Extension and exhumation of the Hellenic forearc and radiation damage in zircon

Mapping and new structural observations on Kythera demonstrate the presence of a major detachment fault, which borders the domed structure of a metamorphic core complex. A three stage extensional context accompanied the exhumation of HP-rocks in Kythera. Early ductile structures near the mapped detachment fault indicate its initiation under NE-trending extension. Later ductile, ductile-brittle and some brittle structures, in the metamorphic unit near the detachment, indicate a significant NW-SE extension along-the-arc. The youngest brittle structures indicate return to NE-SW extension. Thermochronological and structural data show the intensive extension along-the-arc in the Kythera area fades out in both directions along the Cretan-Peloponnese ridge. The exhumation of HP-rocks in the Hellenic forearc ridge and arc-parallel extension in the Hellenic forearc ridge are tectonic episodes resulting from simultaneously high rates of trench rollback and slab retreat and consequent expansion of the arc of the overriding Aegean plate and simultaneously, the bending of the arc from a more rectilinear shape. Local arc-parallel extension occurred where stretching was a maximum, and occurred in a position of oblique late convergence along the arc. Determination of radiation damage (RD) in zircon using Raman spectroscopy and annealing experiments shows wavenumber shifts to correlate strongly with uranium concentration of zircon (Uz). Consequently, Raman spectroscopy of v3[SiO4] can potentially determine the Uz. There is a progressively increasing range of wavenumber shift due to Uz increase, which reflects the ratio of intact versus distorted crystallinity. The time since crystallization or last annealing of the zircon will control the amount of radiation damage and the Raman wavenumber shift for zircons with a given Uz. A longer time is required for a low-uranium zircon to reach the same amount of alpha and fission damage events of a high-uranium zircon, in order for both to show equal wavenumber shift. Time distinguishes zircons of same Uz, which show differences in the Raman wavenumber. The correlation of the Raman wavenumber range and Uz may permit the development of a new chronometer using Raman measurements only for determining U concentration

An efficient prediction model for water discharge in Schoharie Creek, NY

Flooding normally occurs during periods of excessive precipitation or thawing in the winter period (ice jam). Flooding is typically accompanied by an increase in river discharge. This paper presents a statistical model for the prediction and explanation of the water discharge time series using an example from the Schoharie Creek, New York (one of the principal tributaries of the Mohawk River). It is developed with a view to wider application in similar water basins. In this study a statistical methodology for the decomposition of the time series is used. The Kolmogorov-Zurbenko filter is used for the decomposition of the hydrological and climatic time series into the seasonal and the long and the short term component. We analyze the time series of the water discharge by using a summer and a winter model. The explanation of the water discharge has been improved up to 81%. The results show that as water discharge increases in the long term then the water table replenishes, and in the seasonal term it depletes. In the short term, the groundwater drops during the winter period, and it rises during the summer period. This methodology can be applied for the prediction of the water discharge at multiple sites

Artificial Neural Network and Multiple Linear Regression for Flood Prediction in Mohawk River, New York

This research introduces a hybrid model for forecasting river flood events with an example of the Mohawk River in New York. Time series analysis and artificial neural networks are combined for the explanation and forecasting of the daily water discharge using hydrogeological and climatic variables. A low pass filter (Kolmogorov–Zurbenko filter) is applied for the decomposition of the time series into different components (long, seasonal, and short-term components). For the prediction of the water discharge time series, each component has been described by applying the multiple linear regression models (MLR), and the artificial neural network (ANN) model. The MLR retains the advantage of the physical interpretation of the water discharge time series. We prove that time series decomposition is essential before the application of any model. Also, decomposition shows that the Mohawk River is affected by multiple time scale components that contribute to the hydrologic cycle of the included watersheds. Comparison of the models proves that the application of the ANN on the decomposed time series improves the accuracy of forecasting flood events. The hybrid model which consists of time series decomposition and artificial neural network leads to a forecasting up to 96% of the explanation for the water discharge time series