Development of an ecologically sustainable wastewater treatment system

The present study aimed mainly for the development of a wastewater treatment system incorporating enhanced primary treatment, anaerobic digestion of coagulated organics, biofilm aerobic process for the removal of soluble organics and disinfection of treated water. An attempt was also made to study the reuse potential of treated water for irrigation and use of digested sludge as soil conditioner by growing marigold plants. Ferric chloride dose of 30 mg/l was found to be the optimum dose for enhanced primary treatment with removals of COD and BOD to the extent of 60% and 77%, respectively. Efficient anaerobic digestion of ferric coagulated sludge was performed at 7 days hydraulic retention time (HRT). Upflow aerobic fixed film reactor (UAFFR) was very efficient in removals of COD/BOD in the organic loading rate (OLR) range of 0.25 to 3 kg COD/m(3)/day with COD and BOD removals in the range 65-90 and 82-96, respectively. Photo-oxidation followed by disinfection saved 50% of chlorine dose required for disinfection of treated effluent and treated water was found to be suitable for irrigation. The result also indicated that anaerobically digested sludge may be an excellent soil conditioner. From the results of this study, it is possible to conclude that the developed wastewater treatment system is an attractive ecologically sustainable alternative for sewage treatment from institutional/industrial/residential campuses.     

Improving Ann‐Based Short‐Term and Long‐Term Seasonal River Flow Forecasting with Signal Processing Techniques

One of the key elements in achieving sustainable water resources and environmental management is forecasting the future condition of the surface water resources. In this study, the performance of a river flow forecasting model is improved when different input combinations and signal processing techniques are applied on multi‐layer backpropagation neural networks. Haar, Coiflet and Daubechies wavelet analysis are coupled with backpropagation neural networks model to develop hybrid wavelet neural networks models. Different models with different input selections and structures are developed for daily, weekly and monthly river flow forecasting in Ellen Brook River, Western Australia. Comparison of the performance of the hybrid approach with that of the original neural networks indicates that the hybrid models produce significantly better results. The improvement is more substantial for peak values and longer‐term forecasting, in which the Nash–Sutcliffe coefficient of efficiency for monthly river flow forecasting is improved from 0.63 to 0.89 in this study. Copyright © 2014 John Wiley & Sons, Ltd.     

Predicting Monsoon Floods in Rivers Embedding Wavelet Transform,Genetic Algorithm and Neural Network

Monsoon floods are recurring hazards in most countries of South-East Asia. In this paper, a wavelet transform-genetic algorithm-neural network model (WAGANN) is proposed for forecasting 1-day-ahead monsoon river flows which are difficult to model as they are characterized by irregularly spaced spiky large events and sustained flows of varying duration. Discrete wavelet transform (DWT) is employed for preprocessing the time series and genetic algorithm (GA) for optimizing the initial parameters of an artificial neural network (ANN) prior to the network training. Depending on different inputs, four WAGANN models are developed and evaluated for predicting flows in two Indian Rivers, the Kosi and the Gandak. These rivers are infamous for carrying large flows during monsoon (June to Sept), making the entire North Bihar of India unsafe for habitation or cultivation. When compared, WAGANN models are found to be better than autoregression models (ARs) and GA-optimized ANN models (GANNs) which use original flow time series (OFTS) for inputs, in simulating river flows during monsoon. In addition, WAGANN models predicted relatively reasonable estimates for the extreme flows, showing little bias for underprediction or overprediction.     

Effect of Utilization of Discrete Wavelet Components on Flood Forecasting Performance of Wavelet Based ANFIS Models

Wavelet based flood forecasting models are known to perform better than conventional models, yet the effect of the way wavelet components are combined to develop a model on the forecasting performance, is inadequately investigated. To demonstrate this, two types of wavelet- adaptive neuro-fuzzy inference system (WANFIS), i.e. WANFIS-split data model (WANFIS-SD) and WANFIS-modified time series model (WANFIS-MS) are developed to forecast river water levels with 1-day lead time. To develop these models, first the original level time series (OLTS) is decomposed into discrete wavelet components (DWCs) by discrete wavelet transform (DWT) upto three resolution levels. In WANFIS-SD, all wavelet components are used as inputs while WANFIS-MS ignores the noise wavelet components and utilizes only the effective wavelet components. The effectiveness of the developed models are evaluated through application to two Indian rivers, Kamla and Kosi, which vary significantly in their catchment area and flow patterns. The proposed models are found to forecast river water levels accurately. On comparison, the WANFIS-SD is found to perform better than WANFIS-MS for high flood levels.     

Environmental productivity and Kuznets curve in India

As a result of India's extremely rapid economic growth, the scale and seriousness of environmental problems are no longer in doubt. Whether pollution abatement technologies are utilized more efficiently is crucial in the analysis of environmental management because it influences the cost of alternative production and pollution abatement technologies. In this study, we use state-level industry data of sulfur dioxide, nitrogen dioxide, and suspended particular matter over the period 1991-2003. Employing recently developed productivity measurement technique, we show that overall environmental productivities decrease over time in India. Furthermore, we analyze the determinants of environmental productivities and find environmental Kuznets curve type relationship existences between environmental productivity and income. Panel analysis results show that the scale effect dominates over the technique effect. Therefore, a combined effect of income on environmental productivity is negative.     

An Empirical Investigation of Twin Deficits Hypothesis: Evidence from India

Journal of Quantitative Economics - The paper empirically examines the relationship between fiscal deficit and current account deficit in India for the period from 1970–1971 to...     

Skilled–unskilled wage inequality,nontraded good and endogenous supply of skilled labour: A theoretical analysis

The paper develops a static four sector competitive general equilibrium model of a small open economy in which skilled labour is endogenously produced by the education sector and is mobile between a traded good sector and a nontraded good sector. Capital is also perfectly mobile among the education sector, skilled labour using traded good sector and the nontraded good sector. However, land and unskilled labour are specific to another traded good sector. We analyse the effects of change in different factor endowments and reduction in tariff rate on skilled–unskilled wage inequality. We find that the effect of a change in different parameters on wage inequality depends on the factor intensity ranking between two skilled labour using sectors and on the relative strength of the marginal effects on demand for and supply of nontraded final good. We also analyse the effects of changes in different parameters on the supply of skilled labour.     

A comparative analysis of proxies for an optimal leverage ratio

Previous studies that test the tradeoff theory commonly use one of the following debt ratio measures to proxy for a firm's hypothesized optimal ratio: firm's time-series mean leverage, moving average leverage based on a firm's historical debt ratios, industry median leverage, and predicted leverage ratio based on cross-sectional regressions. We find that these alternative proxies yield results that are significantly different from each other. Further, regression results of models that use the optimum target leverage and the conclusions drawn from the findings are sensitive to the model's proxy. Of the proxies that are commonly used in the literature, the moving average debt measure exhibits characteristics that are most consistent with the theoretical optimal leverage ratio.     

Multi-dimensional deprivation in the awakening giants: A comparison of China and India on micro data

This paper compares multidimensional deprivation in India and China during the 1990s and beyond. The analysis is based on unit record data. The paper disaggregates the overall deprivation by categories, and compares the deprivation distribution between the two countries. The study reports that the high growth rates did not translate into an unambiguous improvement in living standards in either country. Deprivation is still unacceptably high in some categories. While rural deprivation is much higher in India than in China, they face similar levels of urban deprivation. China outperforms India on both child and maternal health.     

Exact solutions for bond and option prices with systematic jump risk

A variety of realistic economic considerations make jump-diffusion models of interest rate dynamics an appealing modeling choice to price interest-rate contingent claims. However, exact closed-form solutions for bond prices when interest rates follow a mixed jump-diffusion process have proved very hard to derive. This paper puts forward two new models of interest-rate dynamics that combine infrequent, discrete changes in the interest-rate level, modeled as a jump process, with short-lived, mean reverting shocks, modeled as a diffusion process. The two models differ in the way jumps affect the central tendency of interest rates; in one case shocks are temporary, in the other shocks are permanent. We derive exact closed-form solutions for the price of a discount bond and computationally tractable schemes to price bond options.