Solidification of Tank Bottom Sludge

Tank bottom oily sludge (S) is collected from tank bottoms during cleaning operations and contaminated soil is collected after spills and leakages. Disposal of tank sludge is a significant item of tank maintenance for producers, refiners and transporters of petroleum materials. The objective of this paper is to investigate the use of various additives in the solidification of tank bottom sludge. The sludge was solidified using various combinations of additives including ordinary Portland cement (OPC), cement by-pass dust (CBPD) and quarry fines (QF). Geotechnical and leachability properties of the mixtures were determined. The use of OPC alone as a solidifying agent yielded the best results. This was followed by blends S:OPC:QF of 1:0.5:1.5 and S:CBPD of 1:2. Economically, the latter two mixtures would be considered more cost-effective in solidifying the sludge as the additives are waste by-product materials. The Toxicity Characteristic Leaching Procedure (TCLP) results indicated that no extracts exceeded the threshold TCLP limits established by U.S. Environmental Protection Agency (USEPA). The solidified material can be used in construction of roads, embankments and landfill layers.     

Groundwater level simulation using gene expression programming and M5 model tree combined with wavelet transform

ABSTRACT

In order to understand and adequately manage hydrological stress, it is necessary to simulate groundwater levels accurately. In this research, gene expression programming (GEP) and M5 model tree (M5) are used to simulate monthly groundwater levels. The models are combined with wavelet transform to produce two hybrid models: wavelet gene expression programming (WGEP) and wavelet M5 model tree (WM5). For the simulation, groundwater level, temperature and precipitation values from three observation wells and one meteorological station, located in Iran, are used. The results indicate that the hybrid models, WGEP and WM5, lead to a better performance than the simple models, GEP and M5. The performance of the two hybrid models is similar. It is also observed that selecting a suitable time lag for inputs plays an important role in the accuracy of the simple models. The selection of a suitable decomposition level strongly affects the accuracy of hybrid models.     

Use of Systematic, Palaeoflood and Historical Data for the Improvement of Flood Risk Estimation. Review of Scientific Methods

The catastrophic floods recently occurring in Europe warn of the critical need forhydrologic data on floods over long-time scales. Palaeoflood techniques provideinformation on hydrologic variability and extreme floods over long-time intervals(100 to 10,000 yr) and may be used in combination with historical flood data (last1,000 yr) and the gauge record (last 30–50 yr). In this paper, advantages anduncertainties related to the reconstruction of palaeofloods in different geomorphologicalsettings and historical floods using different documentary sources are described.Systematic and non-systematic data can be combined in the flood frequency analysisusing different methods for the adjustment of distribution functions. Technical toolsintegrating multidisciplinary approaches (geologic, historical, hydraulic and statistical)on extreme flood risk assessment are discussed. A discussion on the potential theoreticalbases for solving the problem of dealing with non-systematic and non-stationary data ispresented. This methodology is being developed using new methodological approachesapplied to European countries as a part of a European Commission funded project (SPHERE).     

Bentonite as a Natural Adsorbent for the Sorption of Iron from the Ground Water Exploited from Aswan Area, Egypt

Sorption of dissolved Fe²⁺ on bentonite was studied using a batch technique. The distribution coefficient, K_d , was evaluated for a bentonite-iron system as a function of contact time, pH, sorbent and sorbate concentrations, and temperature. Sorption results were interpreted in terms of Freundlich's and Langmuir's equations. Thermodynamic parameters for the sorption system were determined at three temperatures: 298°, 308°, and 318°K. The values of ΔH°(-4.0 kjmol⁻¹) and ΔG°(-2.46 Kjmol⁻¹) at 298°K (25°C) suggest that sorption of iron on bentonite is an exothermic and a spontaneous process. The ΔG° value became less negative at higher temperatures and, therefore, less iron was sorbed at higher temperatures. The desorption studies with 0.01 M CaCl₂ and deionized water at iron loading on bentonite showed that more than 90 wt% of the iron is irreversibly sorbed, probably due to the fixation of the iron by isomorphous replacement in the crystal lattice of the sorbent.     

Development of regional flood frequency analysis techniques using generalized additive models for Australia

Estimation of flood quantiles in ungauged catchments is a common problem in hydrology. For this, the log-linear regression model is widely adopted. However, in many cases, a simple log transformation may not be able to capture the complexity and nonlinearity in flood generation processes. This paper develops generalized additive model (GAM) to deal with nonlinearity between the dependent and predictor variables in regional flood frequency analysis (RFFA) problems. The data from 85 gauged catchments from New South Wales State in Australia is used to compare the performances of a number of alternative RFFA methods with respect to variable selection, variable transformation and delineation of regions. Four RFFA methods are compared in this study: GAM with fixed region, log-linear model, canonical correlation analysis (to form neighbourhood in the space catchment attributes) and region-of-influence approach. Based on the outcome from a leave-one-out validation approach, it has been found that the GAM method generally outperforms the other methods even without linking GAM with a neighbourhood/region-of-influence approach. The main strength of GAM is that it captures the non-linearity between the dependent and predictor variables without any restrictive assumption. The findings of this study will encourage other researchers worldwide to apply GAM in RFFA studies, allowing development of more flexible and realistic RFFA models and their wider adoption in practice.     

Assessment of regional estimation error by canonical residual kriging

Various regional flood frequency analysis procedures are used in hydrology to estimate hydrological variables at ungauged or partially gauged sites. Relatively few studies have been conducted to evaluate the accuracy of these procedures and estimate the error induced in regional flood frequency estimation models. The objective of this paper is to assess the overall error induced in the residual kriging (RK) regional flood frequency estimation model. The two main error sources in specific flood quantile estimation using RK are the error induced in the quantiles local estimation procedure and the error resulting from the regional quantile estimation process. Therefore, for an overall error assessment, the corresponding errors associated with these two steps must be quantified. Results show that the main source of error in RK is the error induced into the regional quantile estimation method. Results also indicate that the accuracy of the regional estimates increases with decreasing return periods. Copyright © 2010 John Wiley & Sons, Ltd.     

A simultaneous analysis of gradual and abrupt changes in Canadian low streamflows

In most studies, trend detection is performed under the assumption of a monotonic trend. However, natural processes and, in particular, hydro‐climatic variables may not conform to this assumption. This study performs a simultaneous evaluation of gradual and abrupt changes in Canadian low streamflows using a modified Mann–Kendall (MK) trend test and a Bayesian multiple change‐point detection model. Statistical analysis, using the whole record of observation (under a monotonic trend assumption), shows that winter and summer low flows are dominated by upward and downward trends, respectively. Overall, about 20% of low flows are characterized by significant trends, where ～80% of detected significant trends are upward (downward) for winter (summer) season. Change‐point analysis shows that over 50% of low‐flow time series experienced at least one abrupt change in mean or in direction of trend, of which ～50% occurred in 1980s with a mode in 1987. Analysis of segmented time series based on a common change‐point date indicates a reduced number of significant trends, which is attributed to first, the change in nonstationarity behaviour of low flows leading to less trend‐type changes in the last few decades; and second, the false detection of trends when the sample data are characterized by shifts in mean. Depending on whether the monotonic trend assumption holds, the on‐site and regional interpretation of results may vary (e.g. winter low flow) or even lead to contradictory conclusions (e.g. summer low flow). Trend analysis of last two decades of streamflows shows that (1) winter low flows are increasing in eastern Canada and southern British Columbia, whereas they are decreasing in western Canada; (2) summer low flows are increasing in central Canada, southern British Columbia and Newfoundland, whereas they are decreasing in Yukon and northern British Columbia and also in eastern Ontario and Quebec. Copyright © 2010 John Wiley & Sons, Ltd.     

Prediction of long-term settlement on soft clay using shear wave velocity and damping characteristics

This paper presents a method of calculating long-term settlement of a loaded pad on soft clay at Klang, Selangor, Malaysia where the soil model is treated as an anelastic material of viscoelastic property. Initially, an elastic shear modulus (G) value from shear wave velocity profiles of the seismic tests from spectral analysis of surface wave (SASW) and continuous surface wave (CSW) tests was obtained. A value of damping (D) at an equivalent elastic strain is then calculated from the hysteresis of the plate load tests corrected to equivalent strain using the Damping–Strain formula. The calculated elastic settlement and its equivalent damping are then used to calculate the long-term settlement by applying the generalised viscoelastic formula. Comparisons to traditional methods of settlement predictions were made and the viscoelastic formula has shown better agreement to the observed settlement. Further modification of the settlement formula is introduced to improve the settlement accuracy to 10%.