Investigation of hydraulics transport time scales within the Arvand River estuary,Iran

Transport time scales are key parameters for understanding the hydrodynamic and biochemical processes within estuaries. In this study, the flushing and residence times within the Arvand River estuary have been estimated using a two‐dimensional hydrodynamic model called CE‐QUAL‐W2. The model has been calibrated and verified by two different sets of field data and using the k‐ε vertical eddy diffusivity scheme. Flushing time has been estimated using different methods such as the tidal prism and fraction of freshwater methods. Moreover, residence times have been investigated using pulse residence time, estuarine residence time and remnant function approaches. The results have shown that different methods yield different time scales, and freshwater inflow has the greatest impact upon estimation of residence time, whereas tidal circulation hardly contributes to residence time at all. It has also been shown that the neap‐spring circulation and start phase of simulations have negligible effects on the Arvand's time scales. The investigation of bathymetry showed that two sills of the estuary tend to significantly increase residence time. Understanding the applicability of these time scales and their estimation approaches helps us to evaluate the water quality management of estuaries. Copyright © 2013 John Wiley & Sons, Ltd.     

Capabilities of satellite precipitation datasets to estimate heavy precipitation rates at different temporal accumulations

The importance of satellite datasets as alternative sources of precipitation information has been argued in numerous studies. Future developments in satellite precipitation algorithms as well as utilization of satellite data in operational applications rely on a more in‐depth understanding of satellite errors and biases across different spatial and temporal scales. This paper investigates the capability of satellite precipitation data sets with respect to detecting heavy precipitation rates over different temporal accumulations. In this study, the performance of Tropical Rainfall Measuring Mission real time (TRMM‐RT), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks and CPC MORPHing (CMORPH) is compared against radar‐based gauge‐adjusted Stage IV data. The results show that none of the high temporal resolution (3‐h) datasets are ideal for detecting heavy precipitation rates. In fact, the detection skill of all products drops as the precipitation thresholds (i.e. 75 and 90 percentiles) increase. At higher temporal accumulations (6, 12 and 24 h), the detection skill improves for all precipitation products, with CMORPH showing a better detection skill compared to all other products. On the other hand, all precipitation products exhibit high false alarm ratios above the heavy precipitation thresholds, although TRMM‐RT lead to a relatively smaller level of false alarms. These results indicate that further efforts are necessary to improve the precipitation algorithms so that they can capture heavy precipitation rates more reliably. Copyright © 2013 John Wiley & Sons, Ltd.     

An investigation into the fault patterns in the Chadegan region, west Iran: Evidence for dextral brittle transpressional tectonics in the Sanandaj-Sirjan Zone

The NW-SE trending Sanandaj-Sirjan Zone (SSZ) is the internal part of the Zagros continental collision zone, which mainly consists of metamorphic rocks deformed in a dextral transpressional zone. This dextral transpression is attributed to brittle deformation related to late Cenozoic Arabia-Eurasia oblique continental collision. Major NW-trending faults, including the Dalan, Garmdareh, Yasechah, Sheida, and Ben faults, are reverse faults with a dextral strike-slip component. These faults were displaced by NW-trending synthetic and NE-trending antithetic faults. There are also E-trending thrusts and N-trending normal faults developing in directions that are, respectively, almost normal and parallel to the major shortening direction. The NW-trending Ben, Yasechah, and Sheida faults are NE-dipping faults, and the Dalan and Garmdareh faults are SW-dipping faults. These faults indicate the presence of a transpressive flower structure zone that probably led to the exhumation of Jurassic high-grade metamorphic rocks, such as eclogite, in the central part of the study area.     

Robust attenuation relations for peak time-domain parameters of strong ground motions

This study presents new attenuation models for the estimation of peak ground acceleration (PGA), peak ground velocity (PGV), and peak ground displacement (PGD) using a hybrid method coupling genetic programming and simulated annealing, called GP/SA. The PGA, PGV, and PGD were formulated in terms of earthquake magnitude, earthquake source to site distance, average shear-wave velocity, and faulting mechanisms. A worldwide database of strong ground motions released by Pacific Earthquake Engineering Research Center (PEER) was employed to establish the models. A traditional genetic programming analysis was performed to benchmark the proposed models. For more validity verification, the GP/SA models were employed to predict the ground-motion parameters of the Iranian plateau earthquakes. Sensitivity and parametric analyses were carried out and discussed. The results show that the GP/SA attenuation models can offer precise and efficient solutions for the prediction of estimates of the peak time-domain characteristics of strong ground motions. The performance of the proposed models is better than or comparable with the attenuation relationships found in the literature.     

An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia

Flooding is one of the most destructive natural hazards that cause damage to both life and property every year, and therefore the development of flood model to determine inundation area in watersheds is important for decision makers. In recent years, data mining approaches such as artificial neural network (ANN) techniques are being increasingly used for flood modeling. Previously, this ANN method was frequently used for hydrological and flood modeling by taking rainfall as input and runoff data as output, usually without taking into consideration of other flood causative factors. The specific objective of this study is to develop a flood model using various flood causative factors using ANN techniques and geographic information system (GIS) to modeling and simulate flood-prone areas in the southern part of Peninsular Malaysia. The ANN model for this study was developed in MATLAB using seven flood causative factors. Relevant thematic layers (including rainfall, slope, elevation, flow accumulation, soil, land use, and geology) are generated using GIS, remote sensing data, and field surveys. In the context of objective weight assignments, the ANN is used to directly produce water levels and then the flood map is constructed in GIS. To measure the performance of the model, four criteria performances, including a coefficient of determination (R ²), the sum squared error, the mean square error, and the root mean square error are used. The verification results showed satisfactory agreement between the predicted and the real hydrological records. The results of this study could be used to help local and national government plan for the future and develop appropriate (to the local environmental conditions) new infrastructure to protect the lives and property of the people of Johor.     

A mixture spatial point pattern model for the quasar luminosity function

Consider the problem of estimating the Quasar Luminosity Function (QLF). In a 2007 Ph.D. dissertation, Hugeback considers the QLF as a nonhomogeneous poisson process and estimates the intensity function under SDSS DR3 data (The University of Chicago, AAT 3273021). The present study follows Hugeback’s approach but introduces a mixture component which improves Hugeback’s model in several respects. Namely, the database is partitioned into two groups according to redshift: z < 2.75 and z ? 2.75. Next, a mixture model for the QLF was derived using the concept of pseudolikelihood, the addition of a K function to allow for inter-point interaction, and evaluation of residuals diagnostic plots. This mixture model (i) improves the deviance of Hugeback’s model, and (ii) satisfies residual assumptions that are violated under Hugeback’s model. Moreover, this study confirms Hugeback’s finding of inhomogeneity in the QLF, and provides stronger evidence for the existence of an interaction between redshift and absolute magnitude.