Regional flood frequency analysis using support vector regression in arid and semi-arid regions of Iran

Regional flood frequency analysis (RFFA) was carried out on data for 55 hydrometric stations in Namak Lake basin, Iran, for the period 1992–2012. Flood discharge of specific return periods was computed based on the log Pearson Type III distribution, selected as the best regional distribution. Independent variables, including physiographic, meteorological, geological and land-use variables, were derived and, using three strategies – gamma test (GT), GT plus classification and expert opinion – the best input combination was selected. To select the best technique for regionalization, support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and nonlinear regression (NLR) techniques were applied to predict peak flood discharge for 2-, 5-, 10-, 25-, 50- and 100-year return periods. The GT + ANFIS and GT + SVR models gave better performance than the ANN and NLR models in the RFFA. The results of the input variable selection showed that the GT technique improved the model performance.     

Geology,geochemistry, fluid inclusions and O–H stable isotope constraints on genesis of the Lake Siah Fe-oxide ± apatite deposit,NE Bafq,Central Iran

Acta Geochimica - The Lake Siah iron ± apatite deposit is situated in the Bafq Mining District (BMD), Central Iran. The iron ± apatite orebodies are hosted by a...     

Explicit data-driven models for prediction of pressure fluctuations occur during turbulent flows on sloping channels

Stochastic Environmental Research and Risk Assessment - Pressure fluctuations are among the favorite topics for hydraulic engineers due to their critical role in the design and safe operation of...     

Least-Squares Wavelet Analysis of Unequally Spaced and Non-stationary Time Series and Its Applications

Least-squares spectral analysis, an alternative to the classical Fourier transform, is a method of analyzing unequally spaced and non-stationary time series in their first and second statistical moments. However, when a time series has components with low or high amplitude and frequency variability over time, it is not appropriate to use either the least-squares spectral analysis or Fourier transform. On the other hand, the classical short-time Fourier transform and the continuous wavelet transform do not consider the covariance matrix associated with a time series nor do they consider trends or datum shifts. Moreover, they are not defined for unequally spaced time series. A new method of analyzing time series, namely, the least-squares wavelet analysis is introduced, which is a natural extension of the least-squares spectral analysis. This method decomposes a time series to the time–frequency domain and obtains its spectrogram. In addition, the probability distribution function of the spectrogram is derived that identifies statistically significant peaks. The least-squares wavelet analysis can analyze any non-stationary and unequally spaced time series with components of low or high amplitude and frequency variability, including datum shifts, trends, and constituents of known forms, by taking into account the covariance matrix associated with the time series. The outstanding performance of the proposed method on synthetic time series and a very long baseline interferometry series is demonstrated, and the results are compared with the weighted wavelet Z-transform.     

Landslide susceptibility assessment of South Pars Special Zone,southwest Iran

This study assesses the landslide susceptibility of the South Pars Special Zone (SPSZ) region that is located in southwest Iran. For this purpose, a combinatorial method containing multi-criteria decision-making, likelihood ratio and fuzzy logic was applied in two levels (regional and local) at three critical zones (northwest, middle and southeast of the project area). The analysis parameters were categorised in seven main triggering factors such as climatology, geomorphology, geology, geo-structure, seismic activity, landslide prone areas and man-made activities which have different classes with multi-agent partnership correlations. Landslide susceptibility maps were prepared for these levels and zones after purified and enriched fuzzy trending runs were performed. According to the results of the risk-ability assessment of the landslide occurrences for SPSZ, the north part of the study area which includes the south edge of the Assalouyeh anticline and the southern part of the Kangan anticline were estimated as high-risk potential areas that were used in landslide hazard mitigation assessment and in land-use planning.     

A probabilistic framework for floodplain mapping using hydrological modeling and unsteady hydraulic modeling

ABSTRACT

Prediction of design hydrographs is key in floodplain mapping using hydraulic models, which are either steady state or unsteady. The former, which require only an input peak, substantially overestimate the volume of water entering the floodplain compared to the more realistic dynamic case simulated by the unsteady models that require the full hydrograph. Past efforts to account for the uncertainty of boundary conditions using unsteady hydraulic modeling have been based largely on a joint flood frequency–shape analysis, with only a very limited number of studies using hydrological modeling to produce the design hydrographs. This study therefore presents a generic probabilistic framework that couples a hydrological model with an unsteady hydraulic model to estimate the uncertainty of flood characteristics. The framework is demonstrated on the Swannanoa River watershed in North Carolina, USA. Given its flexibility, the framework can be applied to study other sources of uncertainty in other hydrological models and watersheds.     

Self-expanded piles: A new approach to unconventional piles development

Abstract

In onshore and offshore fields of ocean engineering, piles are used as foundation systems for various structures. Piles are classified into different types depending on their materials, geometries, and particularly, installation methods, which have advantages or limitations. Companies and engineers have developed a new group of piles, because of necessity to improve their performance in terms of increasing the bearing capacity, reducing impacts of traditional installation procedures, implementing by low- torque power equipment, and utilizing them in widely different ground conditions, including in a marine environment. In the present study, three different models of a new pile with an expander body are introduced to increase the shaft and pile-toe diameters and its self-expansion in the embedment depth under the titles of the Bubble pile (BP), Self-Expanded pile (SEP) and Wing pile (WP). The main subject of this research is to achieve increased bearing capacity, reduced installation effects, and decreased required installation torque. The frustum-confining vessel of Amirkabir University of Technology (FCV-AUT) was employed for this purpose. Up to 14 axial compressive and tensile load tests were carried out on different model piles on sand collected from Anzali shore located on the northern coast of Caspian Sea in Iran, with relative densities of 45% to 50% within FCV-AUT. Comparing the performance of introduced pile with traditional pile corresponding to the same characteristics, the results indicated a significant increase in the axial bearing capacity and reduced disturbance effect of the pile. Also, a lower installation torque of the SE pile was required compared to the helical pile. The test results also demonstrated that the new pile could resist considerable compressive and uplift loads, and could be a possible alternative to traditional piles in the onshore sector.