Short- and long-term temporal variations in salinity and the oxygen, carbon and hydrogen isotopic compositions of the Hooghly Estuary water, India

The Hooghly River estuary provides a unique experimental site to understand the effect of monsoonal river discharge on freshwater and seawater mixing. Water samples collected bi-weekly for a duration of 17 months were analyzed for salinity, delta O-18,delta C-13(DIC), as well as delta D to investigate the differential mixing of freshwater and seawater. The differences in salinity and delta O-18 of samples collected during low and high tides on the same day are strongly correlated suggesting a well mixed water column at our sampling site. Low salinity and depleted delta O-18 during monsoon is consistent with increased river discharge as well as high rainfall. We identified different slopes in a delta O-18 versus salinity plot for the estuary water samples collected during monsoon and non-monsoon seasons. This is driven by composition of the freshwater source which is dominated by rainwater during monsoon and rivers during non-monsoon months. Selected delta D analyses of samples indicate that groundwater contributes significantly to the Hooghly Estuary during low rainfall times of the year. delta C-13(DIC) measured in the water recorded low values towards the end of monsoon indicating low productivity (i.e. increased organic respiration) while progressively increasing delta C-13(DIC) values from October till January as well as during some of the pre-monsoon months can be explained by increasing productivity. Very low delta C-13(DIC) (similar to-20%0) suggests involvement of carbon derived from anaerobic oxidation of organics and/or methane with potential contribution from increased anthropogenic water supply. An estimate of seawater incursion into the Hooghly Estuary at different times of the year is obtained by using salinity data in a two-component mixing model. Presence of seawater was found maximum (31-37%) during February till July and lowest (less than or equal to 6%) from September till November. We notice a temporal offset between Ganges River discharge farther upstream at Farakka and salinity variation at the Hooghly Estuary. We believe that this time lag is a result of the physical distance between Farakka and Kakdweep (our sampling location) and put constraints on the travel time of river water during early monsoon. (c) 2012 Published by Elsevier B.V.

Fish distribution dynamics in the Aghanashini estuary of Uttara Kannada, west coast of India

Fish diversity (77 species) in the Aghanashini River estuary of the Indian west coast is linked to variable salinity conditions and zones I, II and III for high, medium and low salinity respectively. Zone I, the junction between Arabian Sea and the estuary, had all species in yearly succession due to freshwater conditions in monsoon to high salinity in pre-monsoon. The medium (zone II) and low (zone III) salinity mid and upstream portions had maximum of 67 and 39 fish species respectively. Maintenance of natural salinity regimes in estuary, among other ecological factors, is critical for its fish diversity.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

Role of predictors in downscaling surface temperature to river basin in India for IPCC SRES scenarios using support vector machine

In this paper, downscaling models are developed using a support vector machine (SVM) for obtaining projections of monthly mean maximum and minimum temperatures (T-max and T-min) to river-basin scale. The effectiveness of the model is demonstrated through application to downscale the predictands for the catchment of the Malaprabha reservoir in India, which is considered to be a climatically sensitive region. The probable predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1978-2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 1978-2100. The predictor variables are classified into three groups, namely A, B and C. Large-scale atmospheric variables Such as air temperature, zonal and meridional wind velocities at 925 nib which are often used for downscaling temperature are considered as predictors in Group A. Surface flux variables such as latent heat (LH), sensible heat, shortwave radiation and longwave radiation fluxes, which control temperature of the Earth's surface are tried as plausible predictors in Group B. Group C comprises of all the predictor variables in both the Groups A and B. The scatter plots and cross-correlations are used for verifying the reliability of the simulation of the predictor variables by the CGCM3 and to Study the predictor-predictand relationships. The impact of trend in predictor variables on downscaled temperature was studied. The predictor, air temperature at 925 mb showed an increasing trend, while the rest of the predictors showed no trend. The performance of the SVM models that are developed, one for each combination of predictor group, predictand, calibration period and location-based stratification (land, land and ocean) of climate variables, was evaluated. In general, the models which use predictor variables pertaining to land surface improved the performance of SVM models for downscaling T-max and T-min

Cloning and development of pathotype-specific SCAR marker associated with Sclerospora graminicola isolates from pearl millet

Downy mildew pathogen of pearl millet in India is associated with the spread of the highly virulent Sclerospora graminicola pathotype-1. Twenty-seven S. graminicola isolates were screened using 20 intersimple sequence repeats (ISSR). Dinucleotide repeat primer [17898A-(CA)(6) AC] amplified a similar to 600 bp fragment specific to five isolates of pathotype-1 (Sg 048, Sg 153, Sg 212, DM-11 and DM-90). The ISSR fragment linked with pathotype-1 was cloned successfully and sequenced. To convert ISSR fragments into pathotype-specific sequence characterised amplified region (SCAR) markers, PCR primers were designed using a sequence of the cloned DNA fragment. PCR amplification using SCAR primer pair (UOM3-Sg-Path1-F/R) amplified a single 284 bp band only in isolates of S. graminicola pathotype-1. This SCAR primer pair did not amplify the 284 bp product from the other five S. graminicola pathotypes or a negative control, which demonstrates primer specificity for pathotype-1. The SCAR primer pair (UOM3-Sg-Path1-F/R) obtained in this study will provide a valuable tool for rapid identification and specific detection of S. graminicola pathotype-1.

Multiobjective Analysis of Irrigation Planning in River Basin Development

A river basin that is extensively developed in the downstream reaches and that has a high potential for development in the upper reaches is considered for irrigation planning. A four-reservoir system is modeled on a monthly basis by using a mathematical programing (LP) formulation to find optimum cropping patterns, subject to land, water, and downstream release constraints. The model is applied to a fiver basin in India. Two objectives, maximizing net economic benefits and maximizing irrigated cropped area, considered in the model are analyzed in the context of multiobjective planning, and the tradeoffs are discussed.

Optimal irrigation planning in river basin development: The case of the Upper Cauvery river basin

The study deals with the irrigation planning of the Cauvery river basin in peninsular India which is extensively developed in the downstream reaches and has a high potential for development in the upper reaches. A four-reservoir system is modelled on a monthly basis by using a mathematical programming (LP) formulation to find optimum cropping patterns, subject to land, water and downstream release constraints, and applied to the Cauvery basin. Two objectives, maximizing net economic benefits and maximizing irrigated cropped area, considered in the model are analysed in the context of multiobjective planning and the trade-offs discussed.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

Molecular Characterization of Sclerospora graminicola, the Incitant of Pearl Millet Downy Mildew Using ISSR Markers

The DNA polymorphism among 22 isolates of Sclerospora graminicola, the causal agent of downy mildew disease of pearl millet was assessed using 20 inter simple sequence repeats (ISSR) primers. The objective of the study was to examine the effectiveness of using ISSR markers for unravelling the extent and pattern of genetic diversity in 22 S. graminicola isolates collected from different host cultivars in different states of India. The 19 functional ISSR primers generated 410 polymorphic bands and revealed 89% polymorphism and were able to distinguish all the 22 isolates. Polymorphic bands used to construct an unweighted pair group method of averages (UPGMA) dendrogram based on Jaccard's co-efficient of similarity and principal coordinate analysis resulted in the formation of four major clusters of 22 isolates. The standardized Nei genetic distance among the 22 isolates ranged from 0.0050 to 0.0206. The UPGMA clustering using the standardized genetic distance matrix resulted in the identification of four clusters of the 22 isolates with bootstrap values ranging from 15 to 100. The 3D-scale data supported the UPGMA results, which resulted into four clusters amounting to 70% variation among each other. However, comparing the two methods show that sub clustering by dendrogram and multi dimensional scaling plot is slightly different. All the S. graminicola isolates had distinct ISSR genotypes and cluster analysis origin. The results of ISSR fingerprints revealed significant level of genetic diversity among the isolates and that ISSR markers could be a powerful tool for fingerprinting and diversity analysis in fungal pathogens.

Road kills of amphibians in different land use areas from Sharavathi river basin, central Western Ghats, India

A survey of amphibian mortality on roads was carried out in the Sharavathi river basin in the central Western Ghats. Road kills in three different land use areas: agricultural fields, water bodies and forests were recorded for four days along three 100m stretches in each type of area. One-hundred-and-forty-four individuals belonging to two orders, eight families, 11 genera and 13 species were recorded in the survey. Kills/km observed were: in forest 55, agricultural fields 38 and water bodies 27, for an overall average of 40 kills/km. Kill species compositions varied significantly between land use areas, but not overall kill rates.

Road kills of amphibians in different land use areas from Sharavathi river basin, central Western Ghats, India

A survey of amphibian mortality on roads was carried out in the Sharavathi river basin in the central Western Ghats. Road kills in three different land use areas: agricultural fields, water bodies and forests were recorded for four days along three 100m stretches in each type of area. One-hundred-and-forty-four individuals belonging to two orders, eight families, 11 genera and 13 species were recorded in the survey. Kills/km observed were: in forest 55, agricultural fields 38 and water bodies 27, for an overall average of 40 kills/km. Kill species compositions varied significantly between land use areas, but not overall kill rates.

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.

Circular dichroism and 13C nuclear magnetic resonance spectroscopy of pennisetin from pearl millet

The conformation and stability of pearl millet prolamin (pennisetin) were examined by using circular dichroism and C-13 nuclear magnetic resonance spectroscopy. The far UV spectrum of pennisetin in 70% (v/v) aqueous ethanol showed the presence of predominant alpha-helical structure and its occurrence in the alpha + beta class of protein. The far and near UV spectra of pennisetin in ethanol: trifluoroethanol also supported this observation. However pennisetin showed the presence of some helical structure in 8 M urea which is known to be a highly unordered structure forming solvent. A decrease in alpha helical content of native pennisetin was observed with rise in temperature from 5-75-degrees-C and this effect of temperature was found to be reversible. A C-13 NMR spectrum of pennisetin in 70% ethanol suggested a high degree of molecular mobility in ethanol. Comparison of the cross polarization spectrum with the single pulse excitation spectrum suggested pennisetin to be a heterogeneous protein.