Smoothed minima baseflow separation tool for perennial and intermittent streams

The United Kingdom Institute of Hydrology (UKIH) smoothed minima baseflow separation method originally developed for the daily flow data of perennial streams and adopted for intermittent streams is presented. The adopted method (AdUKIH) is the generalized version of the UKIH and hence applicable not only to intermittent streams but also to perennial streams. The AdUKIH method is applied on three daily streamflow gauging stations from the European part of Turkey, the Thrace region. The AdUKIH enables one to change the parameter 0·9 in the UKIH method and also introduces different block sizes, which is limited to five days in the original UKIH method. The AdUKIH method is considered a useful tool in helping practitioners and researchers to separate continuous baseflow from the daily flow in perennial and intermittent streams. Copyright © 2008 John Wiley & Sons, Ltd.     

The effect of opium poppy oil diesel fuel mixture on engine performance and emissions

Recently, decreasing of fossil fuel reserves and their negative effect on environment have increased the interest in alternative energy sources. One of the alternative energy sources is vegetable oils. In this study, blends of 50 % opium poppy oil — 50 % diesel fuel mixture are tested as alternative fuel on a single cylinder, 4-stroke, air cooled, pre-combustion chamber diesel engine at different speeds and its effects on engine performance and emissions are investigated. When compared to the diesel fuel as average, engine torque and power decrease at 4 % and 5.73 %, respectively. Specific fuel consumption increases by using of 50% opium poppy oil — 50 % diesel fuel mixture. When compared to the diesel fuel as average, carbon monoxide and nitrogen oxides emissions of 50 % opium poppy oil — 50 % diesel fuel mixture decrease to 15.5 % and 5.9 %, respectively. Diesel fuel-opium poppy oil mixture has been found notably successful and environment friendly as an alternative fuel for diesel engines.     

Variation in time-to-compliance for pump-and-treat remediation of mass transfer-limited aquifers with hydraulic conductivity heterogeneity

In this study, the impact of correlation length (λ) of hydraulic conductivity (K) heterogeneity on pump-and-treat (P&T) remediation period (time-to-compliance) for a mass transfer-limited aquifer is evaluated. Additionally, impacts of variance (σ ²), different distributions of high and low K zones and different initial contaminant masses are explored. Two different P&T policies including different number of wells pumping at different rates are employed for the investigation. Simulation–optimization approach in which a genetic algorithm (GA) is linked with a groundwater flow and contaminant transport model is used. Results show that K heterogeneity, in terms of λ _ln K , s_ln K² \sigma_{\ln \,K}^{2} and respective locations of low and high K zones, significantly impacts the time-to-compliance. Contaminant presence at low K zones can increase the time required to clean up the aquifer. Lower variation is observed in time-to-compliance for the remediation design utilizing higher number of wells pumping at slower rates compared to the design with a single well pumping at a higher rate. Higher number of wells increases the robustness of P&T remediation system when aquifer is heterogeneous in K.     

Trace metal levels in edible wild fungi

Metal levels (cadmium, cobalt, chromium, copper, iron, nickel, lead and zinc) of seventeen different edible wild fungi species (Agaricus campestris, Calocybe gambosa, Coprinus comatus, Hericium coralloides, Hydnum repandum, H. repandum var. rufescens, Lactarius deliciosus, L. salminocolor, Macrolepiota procera, Pleurotus ostreatus, P. ostreatus var. columbinus, Ramaria aurea, R. stricta, Rhizopogon luteolus, Sparassis crispa, Suillus bovinus, Tricholoma terreum) growing in Bolu-Turkey were measured by inductively coupled plasma optical emission spectrocopy. The obtained data were analyzed with “statistical package for the social sciences” statistics program. In addition, relation between metal concentrations in both soil and fungi samples were investigated. The highest metal concentrations in Bolu District, Turkey were measured in A. campestris (cadmium 0.270, chromium 2.735 and zinc 7.683), C. comatus (iron 160.12), M. procera (copper 15.990, cobalt 0.352 and nickel 3.645), R. luteolus (Pb 4.756) mg/kg dw (dry weight). As a result of the measurements, it was observed that metal uptake is related with the species of fungi and is also affected by pH and organic contents of the soil.     

Bench blasting design based on site-specific attenuation formula in a quarry

This research was performed on the quarry that will be opened to produce aggregates and rock filling material at Catalagzi region at Zonguldak province in Turkey. However, there are some structures which can be adversely affected by blasting at the quarry. These structures are a methane exploration drill hole and a house at the distances of 340 and 390 m, respectively. One of the main goals of this study is to perform a preliminary assessment of possible damage effect of ground vibrations induced by blasting on these structures by risk analysis based on ground vibration measurements. In order to propose a preliminary blast design models separately for aggregate and rock filling material production, six test shots with different maximum charge per delay were planned and fired at the quarry. In these shots, 90 events were recorded. To predict peak particle velocity (PPV), the relationship between the recorded peak particle velocities and scaled distances were investigated. During this investigation, the data pairs were statistically analyzed and a PPV prediction equation specific to this site with 95% prediction line were obtained. And also, this equation was used in the derivation of the practical blasting charts specific to this site as a practical way of predicting the peak particle velocity and maximum charge per delay for future blasting. A risk analysis was performed by using this equation. In the light of this analysis, preliminary blast design models were proposed to be used in this quarry for aggregate and rock filling material production.     

Modified dynamic programming approach for offline segmentation of long hydrometeorological time series

For the offline segmentation of long hydrometeological time series, a new algorithm which combines the dynamic programming with the recently introduced remaining cost concept of branch-and-bound approach is developed. The algorithm is called modified dynamic programming (mDP) and segments the time series based on the first-order statistical moment. Experiments are performed to test the algorithm on both real world and artificial time series comprising of hundreds or even thousands of terms. The experiments show that the mDP algorithm produces accurate segmentations in much shorter time than previously proposed segmentation algorithms.     

A Fuzzy Rule Based Remedial Priority Ranking System for Contaminated Sites

Contaminated site remediation is generally difficult, time consuming, and expensive. As a result ranking may aid in efficient allocation of resources. In order to rank the priorities of contaminated sites, input parameters relevant to contaminant fate and transport, and exposure assessment should be as accurate as possible. Yet, in most cases these parameters are vague or not precise. Most of the current remediation priority ranking methodologies overlook the vagueness in parameter values or do not go beyond assigning a contaminated site to a risk class. The main objective of this study is to develop an alternative remedial priority ranking system (RPRS) for contaminated sites in which vagueness in parameter values is considered. RPRS aims to evaluate potential human health risks due to contamination using sufficiently comprehensive and readily available parameters in describing the fate and transport of contaminants in air, soil, and groundwater. Vagueness in parameter values is considered by means of fuzzy set theory. A fuzzy expert system is proposed for the evaluation of contaminated sites and a software (ConSiteRPRS) is developed in Microsoft Office Excel 2007 platform. Rankings are employed for hypothetical and real sites. Results show that RPRS is successful in distinguishing between the higher and lower risk cases.     

Removal of chromate from wastewater using amine-based-surfactant-modified clinoptilolite

This study presents the results of chromate adsorption upon organically modified clinoptilolite obtained by the treatment of Bigadic clinoptilolite with surfactants in primary amine structure, namely 1-dodecylamine, 1-hexadecylamine and oleylamine. Natural and organo-clinoptilolites were characterized by X-ray diffraction, thermal gravimetry and Fourier transform infrared spectrometry which proved the integration of amine groups followed by the order oleylamine > 1-hexadecylamine > 1-dodecylamine. Organo-clinoptilolites were tested for their efficacy in chromate removal under base case conditions which implied 100 ppm initial concentration, pH 4.0, 10 g l^?1 adsorbent dose and at 298 K. Results showed that amine loading induced chromate removal reaching up to 90 % for oleylamine-modified clinoptilolite. Experimentation was continued to determine the effects of pH, adsorbent dosage and initial concentration on chromate adsorption. Accordingly, maximum removal of 94.0 % was attained with 14 g l^?1 of oleylamine-modified clinoptilolite, from Cr(VI) solution of 100 ppm initially at pH 3.0. Langmuir isotherm described the adsorption of chromate on oleylamine-modified clinoptilolite with 96.4 % consistency. Maximum theoretical uptake capacity was calculated as 6.72 mg g^?1. Kinetic data were consistent with pseudo-second-order model with the controlling steps being film and pore diffusions.     

Artificial neural network models for forecasting monthly precipitation in Jordan

Forecasting precipitation in arid and semi-arid regions, in Jordan in the Middle East for example, has particular importance since precipitation is the unique source of water in such regions. In this study, 1-month ahead precipitation forecasts are made using artificial neural network (ANN) models. Feed forward back propagation (FFBP), radial basis function (RBF) and generalized regression type ANNs are used and compared with a simple multiple linear regression (MLR) model. The models are tested on monthly total precipitation recorded at three meteorological stations (Baqura, Amman and Safawi) from different climatological regions in Jordan. For the three stations, it is found that the best calibrated model is FFBP with respect to all performance criteria used in the study, including determination coefficient, mean square error, mean absolute error, the slope and the intercept in the best-fit linear line of the scatter diagram. In the validation stage, FFBP is again the best model in Baqura and Amman. However, in Safawi, the driest station, not only FFBP but also RBF and MLR perform equally well depending on the performance criterion under consideration.