Abstract:Observed rainfall and flow data from the Dongjiang River basin in humid southern China were used to investigate runoff changes during low-flow and flooding periods and in annual flows over the past 45 years. We first applied the non-parametric Mann-Kendall rank statistic method to analyze the change trend in precipitation, surface runoff and pan evaporation in those three periods. Findings showed that only the surface runoff in the low-flow period increased significantly, which was due to a combination of increased precipitation and decreased pan evaporation. The Pettitt-Mann-Whitney statistical test results showed that 1973 and 1978 were the change points for the low-flow period runoff in the Boluo sub-catchment and in the Qilinzui sub-catchment, respectively. Most importantly, we have developed a framework to separate the effects of climate change and human activities on the changes in surface runoff based on the back-propagation artificial neural network (BP-ANN) method from this research. Analyses from this study indicated that climate variabilities such as changes in precipitation and evaporation, and human activities such as reservoir operations, each accounted for about 50% of the runoff change in the low-flow period in the study basin.

This paper follows previous research that identified 15 hyperspectral wavebands that were suitable to estimate paddy rice leaf area index (LAI). The objectives of the study were to: (1) test the efficiency of the wavebands selected in the previous study, (2) to evaluate the potential of least squares support vector machines (LS-SVM) to estimate paddy rice LAI from canopy hyperspectral reflectance and (3) to compare multiple linear regression-MLR, partial least squares-PLS regression and LS-SVM to determine paddy rice LAI using the selected wavebands. In the study, measurements of hyperspectral reflectance (350-2500 nm) and corresponding LAI were made for a paddy rice canopy throughout the growing seasons. On the basis of the wavebands selected previously, models based on MLR, PLS and LS-SVM to estimate rice LAI were compared using the data from 123 observations, which were split randomly for model calibration (2/3) and validation (1/3). Root mean square errors (RMSEs) and the correlation coefficients (r) between measured and predicted LAI values from model calibration and validation were calculated to evaluate the quality of the models. The results showed that the LS-SVM model using the 15 selected wavebands produced more accurate estimates of paddy rice LAI than the PLS and MLR models. We concluded that the LS-SVM approach may provide a useful exploratory and predictive tool for estimating paddy rice LAI when applied to reflectance data using the 15 selected wavebands.

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This paper presents a model for the optimal allocation of water resources in saltwater intrusion areas. The model is comprised of four modules: a joint operation of river and reservoirs module (JORRM), a saltwater intrusion analysis module (SIAM), an economic analysis and in-stream ecology demand module (EAIEDM) and a water allocation module (WAM). Considering the social, economic and environmental aspects, the model has three objectives: the maximization of economic interest (OF 1 ), maximization of social satisfaction (OF 2 ) and the minimization of the amounts of polluted water (OF 3 ). A genetic algorithm is also employed to optimize the module. The model has then been applied to a case study of optimization of water resources for the Pearl River Delta in China. The results indicate that there is water shortage in Pearl River Delta and engineering projects are needed to satisfy water demand during the dry season when saltwater intrusion happens. The model provides a useful tool for the operation of reservoirs and freshwater allocation in saltwater intrusion area.

To investigate the performance of landfill composite liner system, a one-dimensional model was developed for solute transport through composite liners containing geomembrane defects. An analytical solution to the model was obtained by the method of Laplace transformation. The results obtained by the presented solution agree well with those obtained by the numerical method. Results show that leachate head and construction quality of geomembrane (GM) have significant influences on the performance of the composite liners for heavy metal ions. The breakthrough time of lead decreases from 50 a to 19 a when the leachate head increases from 0.3 m to 10 m. It is also indicated that the contaminant mass flux of volatile organic compounds (VOCs) induced by leakage can not be neglected in case of poor construction quality of the landfill barrier system. It is shown that diffusion coefficient and partition coefficient of GM have great influences on solute transport through composite liners for VOCs. The breakthrough time of heavy metal ions will be greatly overestimated if the effects of diffusion and adsorption of clay and geosynthetic clay liner (GCL) are neglected. The composite liner consisting of a geomembrane and a GCL provides a poor barrier for VOCs. The presented analytical solution is relatively simple to apply and can be used for preliminary design of composite liners, evaluating experimental results, and verifying more complex numerical models. defect, composite liner, contaminant transport, analytical solution, leachate head, landfill, groundwater contamination Citation:Xie H J, Chen Y M, Lou Z H. An analytical solution to contaminant transport through composite liners with geomembrane defects.

Abstract:Groundwater remediation by nanoparticles has received increasing interest in recent years. This report presents a thorough evaluation of hexavalent chromium removal in aqueous solutions using iron (Fe 0 ) nanoparticles. Cr(VI) is a major pollutant of groundwater. Zero-valent iron, an important natural reductant of Cr(VI), is an option in the remediation of contaminated sites, transforming Cr(VI) to essentially nontoxic Cr(III). At a dose of 0.4 g/L, 100% of Cr(VI) (20 mg/L) was degraded. The Cr(VI) removal efficiency decreased significantly with increasing initial pH. Different Fe 0 type was compared in the same conditions. The reactivity was in the order starch-stabilized Fe 0 nanoparticles>Fe 0 nanoparticles>Fe 0 powder>Fe 0 filings. Electrochemical analysis of the reaction process led to the conclusion that Cr(OH) 3 should be the final product of Cr(VI). Iron nanoparticles are good choice for the remediation of heavy metals in groundwater.

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