Intentional contamination of water distribution networks: developing indicators for sensitivity and vulnerability assessments

Performing a comprehensive risk analysis is primordial to ensure a reliable and sustainable water supply. Though the general framework of risk analysis is well established, specific adaptation seems needed for systems such as water distribution networks (WDN). Understanding of vulnerabilities of WDN against deliberate contamination and consumers’ sensitivity against contaminated water use is very vital to inform decision-maker. This paper presents an innovative step-by-step methodology for developing comprehensive indicators to perform sensitivity, vulnerability and criticality analyses in case of absence of early warning system (EWS). The assessment and the aggregation of these indicators with specific fuzzy operators allow identifying the most critical points in a WDN. Intentional intrusion of contaminants at these points can potentially harm both the consumers as well as water infrastructure. The implementation of the developed methodology has been demonstrated through a case study of a French WDN unequipped with sensors.     

Wave data assimilation using a hybrid approach in the Persian Gulf

The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches. It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN.     

Baseline metals pollution profile of tropical estuaries and coastal waters of the Straits of Malacca

The status report on metal pollution in tropical estuaries and coastal waters is important to understand potential environmental health hazards. Detailed baseline measurements were made on physicochemical parameters (pH, temperature, redox potential, electrical conductivity, salinity, dissolved oxygen, total dissolved solid), major ions (Na, Ca, Mg, K, HCO₃, Cl, SO₄ and NO₃) and metals concentrations (²⁷Al, ⁷⁵As, ¹³⁸Ba, ⁹Be, ¹¹¹Cd, ⁵⁹Co, ⁶³Cu, ⁵²Cr, ⁵⁷Fe, ⁵⁵Mn, ⁶⁰Ni, ²⁰⁸Pb, ⁸⁰Se, ⁶⁶Zn) at estuaries and coastal waters along the Straits of Malacca. Principal component analysis (PCA) was employed to reveal potential pollution sources. Seven principal components were extracted with relation to pollution contribution from minerals-related parameters, natural and anthropogenic sources. The output from this study will generate a profound understanding on the metal pollution status and pollution risk of the estuaries and coastal system.     

BIBLIOGRAPHY—BIBLIOGRAPHIE

Abstract

The Coupled Routing and Excess STorage model (CREST, jointly developed by the University of Oklahoma and NASA SERVIR) is a distributed hydrological model developed to simulate the spatial and temporal variation of land surface, and subsurface water fluxes and storages by cell-to-cell simulation. CREST's distinguishing characteristics include: (1) distributed rainfall–runoff generation and cell-to-cell routing; (2) coupled runoff generation and routing via three feedback mechanisms; and (3) representation of sub-grid cell variability of soil moisture storage capacity and sub-grid cell routing (via linear reservoirs). The coupling between the runoff generation and routing mechanisms allows detailed and realistic treatment of hydrological variables such as soil moisture. Furthermore, the representation of soil moisture variability and routing processes at the sub-grid scale enables the CREST model to be readily scalable to multi-scale modelling research. This paper presents the model development and demonstrates its applicability for a case study in the Nzoia basin located in Lake Victoria, Africa.

Citation Wang, J., Yang, H., Li, L., Gourley, J. J., Sadiq, I. K., Yilmaz, K. K., Adler, R. F., Policelli, F. S., Habib, S., Irwn, D., Limaye, A. S., Korme, T. &; Okello, L. (2011) The coupled routing and excess storage (CREST) distributed hydrological model. Hydrol. Sci. J. 56(1), 84–98.     

A Parametric Study on Stability of Open Excavations in Alluvial Soils of Lahore District, Pakistan

Rapid urbanization and expansion of metropolitans in the developing world is pressing the need of tall structures with multiple basements. In several such projects, open land is available around excavation site and unsupported deep excavations by maintaining appropriate side slopes offer economical solution. In this research, subsoil stratigraphy of Lahore district was established to be comprising of a top clay stratum 1.5–8 m thick, followed by a sand layer. Considering subsoil data from several geotechnical investigation reports, the effect of four key parameters viz., cohesion of clay layer, friction angle of sand layer, thickness of clay layer at the top and slope inclination of underlying sand layer on safety factor of open excavations was studied. Six hundred twenty-five slope stability analyses were conducted by considering different geometries and soil properties. Based on the results of these analyses, a regression model was suggested to estimate safety factor of open excavations in similar stratigraphy which would be useful in feasibility studies and preliminary design of deep excavations. It was established that the clay layer cohesion was the most dominant contributor to safety factor.     

Seismic hazard assessment for Mymensingh,Bangladesh

Mymensingh municipality lies in one of the most earthquake-prone areas of Bangladesh. The town was completely destroyed during the Great Indian Earthquake of 12 June 1897, for which the surface-wave magnitude was 8.1. In this study the 1897 Great Indian Earthquake was used as a scenario event for developing seismic microzonation maps for Mymensingh. For microzonation purposes SPT data from 87 boreholes were collected from different relevant organizations. To verify those data ten boreholes of depth up to 30 m were drilled. Intensity values obtained for different events were calibrated against attenuation laws to check applicability to the study area. Vibration characteristics at diverse points of the study area were estimated by employing the one-dimensional wave-propagation software SHAKE. SHAKE discretizes the soil profile into several layers and uses an iterative technique to represent the non-linear behavior of the soil by adjusting the material properties at each iteration step. The required input information includes depth, shear wave velocity, damping factor, and unit weight of each soil layer. The liquefaction resistance factor and the resulting liquefaction potential were estimated to quantify the severity of liquefaction. Quantification of secondary site effects and the weighting scheme for combining the various seismic hazards were heuristic, based on judgment and expert opinion.     

Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers

Abstract

The study of sediment load is important for its implications to the environment and water resources engineering. Four models were considered in the study of suspended sediment concentration prediction: artificial neural networks (ANNs), neuro-fuzzy model (NF), conjunction of wavelet analysis and neuro-fuzzy (WNF) model, and the conventional sediment rating curve (SRC) method. Using data from a US Geological Survey gauging station, the suspended sediment concentration predicted by the WNF model was in satisfactory agreement with the measured data. Also the proposed WNF model generated reasonable predictions for the extreme values. The cumulative suspended sediment load estimated by this model was much higher than that predicted by the other models, and is close to the observed data. However, in the current modelling, the ANN, NF and SRC models underestimated sediment load. The WNF model was successful in reproducing the hysteresis phenomenon, but the SRC method was not able to model this behaviour. In general, the results showed that the NF model performed better than the ANN and SRC models.

Citation Mirbagheri, S. A., Nourani, V., Rajaee, T. & Alikhani, A. (2010) Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers. Hydrol. Sci. J. 55(7), 1175–1189.