Risk minimization in water quality control problems of a river system

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte-Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga-Bhadra river system in southern India, with a steady state BOD-DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality. (c) 2005 Elsevier Ltd. All rights reserved.

MONTBLEX tower observations: Instrumentation, data acquisition and data quality

Tower platforms, with instrumentation at six levels above the surface to a height of 30 m, were used to record various atmospheric parameters in the surface layer. Sensors for measuring both mean and fluctuating quantities were used, with the majority of them indigenously built. Soil temperature sensors up to a depth of 30 cm from the surface were among the variables connected to the mean data logger. A PC-based data acquisition system built at the Centre for Atmospheric Sciences, IISc, was used to acquire the data from fast response sensors. This paper reports the various components of a typical MONTBLEX tower observatory and describes the actual experiments carried out in the surface layer at four sites over the monsoon trough region as a part of the MONTBLEX programme. It also describes and discusses several checks made on randomly selected tower data-sets acquired during the experiment. Checks made include visual inspection of time traces from various sensors, comparative plots of sensors measuring the same variable, wind and temperature profile plots calculation of roughness lengths, statistical and stability parameters, diurnal variation of stability parameters, and plots of probability density and energy spectrum for the different sensors. Results from these checks are found to be very encouraging and reveal the potential for further detailed analysis to understand more about surface layer characteristics.

Climate change induced risk in water quality control problems

A modeling framework is presented in this paper, integrating hydrologic scenarios projected from a General Circulation Model (GCM) with a water quality simulation model to quantify the future expected risk. Statistical downscaling with a Canonical Correlation Analysis (CCA) is carried out to develop the future scenarios of hydro-climate variables starting with simulations provided by a GCM. A Multiple Logistic Regression (MLR) is used to quantify the risk of Low Water Quality (LWQ) corresponding to a threshold quality level, by considering the streamflow and water temperature as explanatory variables. An Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) presented in an earlier study is then used to develop adaptive policies to address the projected water quality risks. Application of the proposed methodology is demonstrated with the case study of Tunga-Bhadra river in India. The results showed that the projected changes in the hydro-climate variables tend to diminish DO levels, thus increasing the future risk levels of LWQ. (C) 2012 Elsevier B.V. All rights reserved.