A multivariate statistical approach for the evaluation of spatial and temporal dynamics of surface water quality from the small reservoir located in the drought-prone area of South-West India: a case study of Tiru reservoir (India).

With the use of different multivariate statistical analysis methods, spatio-temporal fluctuations in the water parameters of Tiru reservoir located at the Marathwada drought-prone area of Maharashtra, India, have been analysed and reported in this case study. Tiru reservoir, situated on the tributary of the Godavari River, was regularly monitored at five different sites from August 2017 to January 2019 for the estimation of 20 water quality parameters. Various multivariate methods such as pattern reorganisation using cluster analysis (CA), factor analysis/principal component analysis (FA/PCA), and discriminant analysis (DA) were used for handling complex datasets. CA extracted three different clusters from five sampling sites with similar water quality characteristics. FA/PCA extracted thirteen factors (65% of 20 measured) required to explain 74% of the data variability and identified the factors accountable for variation in water quality and also evaluated the prevalence of each cluster on the overall dissimilarity at five different sampling sites. Discriminant analysis extracted a total of 16 parameters with 97.7% right assignations. Varifactors (VFs) acquired by factor analysis recommended that the water quality parameters accounted for variation were linked to two groups. The first group included water quality parameters like T, DO, SDD, turbidity, TDS, PA, and MA, whereas the second group covered most of the nutrients Cl-, silicates, PP, TP, NO3-N, NO2-N, and NH3-N; hardness; and CHL-a and mainly entered the reservoir during surface runoff from agriculture fields and the surrounding area containing domestic as well as animal waste. Thus, the present work showed the efficiency of multivariate methods for the assessment of spatial as well as a temporal variation in the water quality of a small reservoir.

Establishment of taxonomic status of Macrobrachium indicum Jayachandran amp; Joseph (Decapoda : Palaemonidae) through molecular characterization with a note on related species.

Macrobrachium indicum, a south Indian freshwater prawn described from Vellayani lake, Kerala is closely related to Koua river prawn, M. australe which in turn resembles M. ustulatum. Morphologically the three species pose difficulties in identification. A comparison of morphological characters of M. indicum, M. australe and M. ustulatum has been made in the paper. The COI sequence data for the species has been generated and made comparison with the existing COI barcode sequences for M. australe and showed clear difference between the species, thereby established the taxonomic validity of the species. Alignment of the present study sequences with reported sequences of M. australe revealed homologous region of 434 bp. Out of 434 nucleotides, the number of conserved and variable nucleotides were 313 and 121, respectively. Based on the P value (0.002) of Mann-Whitney U test, it was observed that the GC content at codon third base position between M. indicum and M. australe is significantly different. Because of the complexity of the species group a type material is highly necessary for confirmation in future studies and since holotype is irrecoverably lost, a neotype has been selected from the present collection and deposited in the CMFRI Museum at Kochi, Kerala with accession number: ED.2.2.1.8.

Trophic state modeling for shallow freshwater reservoir: a new approach.

Lakes and reservoirs around the world are facing a substantial water quality degradation problem that poses significant environmental, social, and economic impacts. Reservoir productivity is influenced primarily by the climatic, morphometric, and hydro-edaphic features. High nutrient loadings in the reservoir from agriculture runoff often provide ideal conditions for algal blooms, leading to eutrophication. Reservoir and lake management to prevent or reduce eutrophication, therefore, has become the need of the hour. The traditional approach of trophic state monitoring by rigorous field surveys and eutrophication modeling has been revised in the present study by developing a new trophic state index (TSI)-based model for tropical shallow freshwater reservoirs. The new model has been constructed based on Carlson's Limnology and Oceanography, 22, 361-369, (1977) guidelines by establishing an empirical relationship between trophic parameters including total phosphorus (TP), Secchi disk depth (SDD), and chlorophyll (Chl-a). After comparing the new model with various earlier models for its applicability and validation with actual field conditions, it was found to be most precise over previous TSI models. Temporal and spatial fluctuations in the water quality of the Tiru reservoir were primarily attributed to the changing climatic conditions during the study period. Seasonal monsoon with less frequency, heavy nutrient loading from agriculture runoff, and increased turbidity due to a high level of sediment inflow during monsoon raised the TSI (SDD) values of the Tiru reservoir to place it in the hyper-eutrophic class. Average TSI values during winter for SDD, Chl-a, and TP were indicative of the meso-eutrophic to eutrophic state. Saturation of nutrients due to low water level during summer season caused the poly-eutrophic condition for TSI (SDD)- and TSI (TP)-based estimates and eutrophic condition as per TSI (Chl-a) estimates. However, seasonal deviations of the TSI values based on the relationship between TSI (Chl-a) and TSI (SD) indicated a predominance of smaller particles (non-algal turbidity) during all seasons. Even though TP present in the Tiru reservoir is controlling the algal production, it is also affected by low-light conditions due to non-algal turbidity. The recommendation from this study is that the TSI method for estimating the health of the water bodies is the efficient, cost-effective, and time-saving approach. The model developed during the study would help managers and policy makers to take necessary steps to reduce eutrophication levels in the reservoir and would be helpful for researchers in developing new concepts and protocols, mainly focusing on shallow freshwater reservoirs.