Thamirabarani River Research Articles

Flood risk zone mapping and future projections for the Thamirabarani river basin, Southern India: insights from decadal rainfall trends and GIS-based analytical hierarchy process technique

Flood risk zone mapping and future projections for the Thamirabarani river basin, Southern India: insights from decadal rainfall trends and GIS-based analytical hierarchy process technique

Evaluating Water Quality through Macroinvertebrate Diversity and Physicochemical Parameters in the Thamirabarani River Basin

<p style="margin-top:13px; text-align:justify"><span style="font-size:11pt"><span style="line-height:115%"><span style="font-family:Arial,"sans-serif""><span lang="EN" style="font-size:12.0pt"><span style="line-height:115%"><span style="font-family:"Times New Roman","serif"">Aquatic ecosystems in the Thamirabarani River Basin, Tamil Nadu, India, are facing increasingly complex challenges due to climate change, particularly concerning water temperature and dissolved oxygen levels. This study delves into the intricate relationship between these variables and their profound implications for freshwater biodiversity. The rising temperatures and declining dissolved oxygen levels pose escalating threats to the health of aquatic organisms and the stability of ecosystems. To tackle this issue, a hybrid methodology that integrates remote sensing and field data is proposed to calculate the Water Quality Index (WQI) and comprehensively assess ecosystem health. Remote sensing data offer valuable spatial insights, while field measurements ensure accuracy, resulting in robust findings. The study uncovers a significant negative correlation between water temperature and dissolved oxygen levels, highlighting the adverse effects of warming waters on aquatic habitats. Moreover, habitat fragmentation exacerbates climate stressors, adding further challenges to freshwater biodiversity conservation. The findings underscore the urgent need for conservation and adaptive management strategies, including temperature regulation, riparian vegetation enhancement, nutrient pollution management, and habitat connectivity preservation. By implementing these measures, biodiversity loss in freshwater ecosystems can be minimized, ensuring their resilience in the face of ongoing climate change. </span></span></span></span></span></span></p>

Character-based Identification System (CBIS) for Authentication and Conservation of Fishes from the Thamirabarani River, Western Ghats of India

Character-based Identification System (CBIS) for Authentication and Conservation of Fishes from the Thamirabarani River, Western Ghats of India

Exploring of Bacterial Pigments from Thamirabarani River Alluvial Soil: Harnessing their Versatility in Dye and Paint Manufacturing

Color is a fundamental aspect of human life, playing a vital role in culture and industry. The paints and coatings industry, a significant sector within global manufacturing, has seen increased scrutiny due to its environmental and health impacts. Conventional paints contain harmful chemicals like volatile organic compounds (VOCs) and solvents, which pose risks to both workers and the environment. Recent shifts towards natural and bio-based pigments, particularly those derived from microorganisms, offer a promising alternative. Microbial pigments, such as those produced by chromogenic bacteria, provide eco-friendly, non-toxic colorants with additional benefits like antioxidant and antimicrobial properties. This review highlights the potential of bacterial pigments in various applications, particularly in the textile industry as natural dyes, and discusses their role in reducing the environmental footprint of synthetic pigments. The study also emphasizes the importance of further research into improving the production and stability of these bio- pigments for broader commercial use in industries such as food, cosmetics, and pharmaceuticals.

Assessment of depositional environmental factors in quaternary sediments: a case study of Thamirabarani River basin, Srivaikundam region of southern India

This study uses a thorough grain size analysis approach to the depositional environment in the Thamirabarani River basin, specifically in the Srivaikundam district of Tamil Nadu, India. There is a significant lack of research on the depositional settings and sediment features unique to the Thamirabarani River basin, even though there have been numerous sediments studies conducted in other river basins. Consequently, the purpose of this study is to investigate the depositional habitats and sediment characteristics of this area. The majority of the 18 sediment samples were determined to be medium- to fine-grained and poorly sort-able after extensive analysis using granulometric research and sieve methods. The low-energy formation process took place in a largely fine-grained or very fine-grained sandy soil, as indicated by the sediments platykurtic and mesokurtic morphologies. The depositional habitats within the region can be better understood by classifying the soil based on ternary plots of clay, silt, and sand, such as particle distribution curve. Furthermore, comparison with a unified soil classification chart aids in further categorizing the soil types. Soils can be classified and the depositional settings of different landscapes, such as rivers, estuaries, beaches, and aeolian terrains, can be better understood with the use of this comprehensive grain size study. Another interesting aspect of the Thamirabarani River basin sediment movement and deposition is the slow breakdown of rocks, especially feldspar and quartz, as they move through rivers and streams.

Economics of Paddy Cultivation in Thamirabarani River Basin of Tamil Nadu, India

Economics of Paddy Cultivation in Thamirabarani River Basin of Tamil Nadu, India

Seasonal assessment of water quality for irrigation using multiple indices in Thamirabarani river, Kanyakumari district, India

The Hydrochemical analysis and evaluation of the irrigation water quality of the Thamirabarani river system has great significance for maintaining the livelihoods of people and ecological stability in the area. Thamirabarani river is a significant river in kanyakumari district and the people of this district use the water largely without enough and unbelievable information about the water qualities and levels of contamination. The study is the prime source of water for irrigation and domestic uses in the above district. The water samples were collected from ten locations, Pechiparai dam to Thengapattanam estuary in pre-monsoon, monsoon and post-monsoon seasons respectively. The hydrochemistry in the river water was established by twelve parameters such as (pH, EC, TDS, NO3-, SO42-, Cl-,CO32-, HCO3-, Ca2+, Mg2+, Na+, K+) and also characterized by Box plot. Furthermore the potential effects of irrigation water qualities were evolved on sodicity hazard, magnesium hazard, sodium permeability hazard, and permeability hazards were assessed by using derived parameters including sodium adsorption ratio, Soluble Sodium Percentage, Permeability index and Kelly’s ratio. The correlation study reveals that there is a strong positive correlation among the indices. The Wilcox diagram describes that the upstream stations in the river water is used for irrigation the downstream stations especially station 9 and station 10 were unsuitable for irrigation because of sea water intrusion discharge of domestic wastes and agricultural activity contaminates the quality of the river water. Therefore the study need special attention to maintain the quality of the river.

Diatoms and water quality indices in Thamirabarani river help environmental impact assessment of stretch between Naranammalpuram and Punnakayal, Tamil Nadu, India

The present study reports the occurrence of diatom taxa, their distribution and ecology in Thamirabarani River between the study areas Naranammalpuram and Punnakayal, covering the districts of Tirunelveli and Thoothukudiin Tamil Nadu, India. The study employs diatoms collected from 10 different locations in the Thamirabarani River to monitor its quality. A total of 40 diatom taxa belonging to 20 genera were recorded in the study area. The dominant presence of diatom taxa, such as Aulacoseira ambigua, Cocconeis placentula, Cyclotella meneghiniana, Cymbella tropica, Discostella stelligera, Gyrosigma acuminatum, Navicula cryptonella, Nitzschia amphibia, Planothidium lanceolatum, Staurosirella pinnata, and the water quality index values (29–48) recorded at sites 1 to 7 indicate oligotrophic due to good flow of water. The abundant of diatom taxa, such as Diadesmis confervacea, Gomphonema parvulum, Nitzschia palea and Pinnularia gibba, were recorded at sites 8–10, and the water quality indices (100–110) indicate eutrophication attributable to less flow of water, high dispersion of cremation ashes (the casting ceremony) and anthropogenic activities. Particularly, locations around Punnakayal are most polluted due to the dumping of fish wastes as well as stagnant water.

Assessment of water quality changes and HFE-D studies in Thamirabarani River, Thoothukudi district, Southern India

Assessment of water quality changes and HFE-D studies in Thamirabarani River, Thoothukudi district, Southern India

Water Quality Prediction Based on Hybrid Deep Learning Algorithm

Pollution from many different sources severely affects the quality of our water supply. Over the past few years, a large number of online water quality monitoring stations have been used to gather time series data on water quality monitoring. These numbers are the foundation for deep learning techniques for forecasting water quality. In particular, typical deep learning approaches struggle to accurately estimate water quality in the presence of net promoter system (NPS) contamination. To overcome this shortcoming, a new deep learning model called long short-term memory (LSTM)–gray wolf optimization (GWO)–fish swarm optimization (FSO) was developed to enhance the precision of water quality prediction with NPS pollution. The well-established model may remedy the mechanism models’ inability to foretell changes in water quality on a minute-by-minute basis. Thamirabarani river watershed was used for the model’s application. Based on experimental data, the suggested model outperformed the mechanism model and the LSTM model in predicting extreme values. Maximum relative errors in anticipated against observed dissolved oxygen, chemical oxygen demand, and NH3─N values were 7.58%, 18.45%, and 22.25%, respectively. In comparison to the artificial neural network (ANN), back propagation neural network (BPNN), and recurrent neural network (RNN) models, the created LSTM–GWO–FSO model was shown to have greater computational performance (RNN). LSTM–GWO–FSO outperformed ANN, BPNN, and RNN regarding R2 of 3.1%–38.4% improvements. The suggested approach may provide a fresh perspective when predicting water quality in the presence of NPS contamination.

A GIS based Morphometric Analysis of Thamirabarani River Basin, Tuticorin district, Tamilnadu, India, using CARTOSAT-1 DEM Data and ArcGIS

Due to its use in numerous geological and biological contexts, morphometric analysis has drawn more attention in recent years. It offers perception into process-associated modifications together with catchment assessment, runoff, infiltration, watershed development, natural and structural frameworks. Study of the Thamirabarani river is composed of Achaean crystalline rocks in the west and tertiary and quaternary sedimentary rocks on the east coast. In the current work, a morphometric analysis of the Thamirabarani river was performed to describe the various surface processes that cut the watershed into the river topography. Catchments were defined using Cartosat data and Arc GIS 10.4.1. This study shows that the stream varied from 1 to 5 (I-357, II-89, III-21, IV-9 and V-3) orders. According to the mean bifurcation ratio, the stream is topographical and complex regulated in its shallower parts. The analyzed basin's high permeability is explained by the studied basin's low current frequency values. Plate erosion rather than channel erosion can be seen in overland flow lengths (>0.14) and rough textures can be seen in drainage patterns. Asymmetric and extended basins with neotectonic activity are indicated by analysis of measured parameters using morphometry. Therefore, various interpretations are produced based on morphometric test of the Thamirabarani stream system to help provide information pertinent to social benefits.

A biological diatom indices based preliminary assessment of water quality of Thamirabarani river, Southern India

ABSTRACT Diatoms have long been used as bio-indicators for the assessment of surface water quality. This study investigates the biological diatom index (BDI) and water quality index (WQI) for evaluating the water quality impact in the Thamirabarani River, Southern India. Diatom and water samples were taken for the present investigation from ten different locations along the river. The samples were enumerated and the morphometrics valve was documented by light microscopy. In the study area, a total of 70 diatom taxa belonging to 28 genera were recorded. The diatom indices implemented in OMNIDIA software version 6.1 was used to infer the river water quality status. The results showed that based on the BDI and WQI analysis values varied from 6.7 to 17.4 and 48 to 71 were observed. According to the BDI and WQI analysis result during the study period in the river revealed the water quality varied between good (Oligo-mesotrophic) to bad (Eutrophic) ecological conditions. The biological diatom index and water quality index results indicate the respective locations (Site 2, Site 3, Site 7, Site 8, Site 9 and Site 10) represent bad water quality. The result indicated moderate water quality at Sites 4 and Site 6. The diatom indices and water quality index results show the locations Site 1, and Site 5 indicate good water quality. The biological diatom index results from diatom assemblages show more information about the water quality and environmental impact on the river. For the national assessment of water quality better to use diatoms along with physico-chemical parameters variables. Based on the analysis result reveal that the major component of water quality degradation was due to anthropogenic activities, domestic waste and industrial effluents in the study area.

Study on Drainage Network Pattern and Morphometric Analysis by Using Hydrology Support Algorithm

Abstract The degree of accuracy in the extraction of the drainage network and morphometric analysis of the basin plays a vital role in assessing geomorphological characteristics and hydrological processes. The extraction of the exact flow network from SRTM-DEM quantifies the drainage network, and morphometric parameters, which is the main objective of this study. The Thamirabarani river basin in Tamil Nadu, India is taken as the study area. The stream order threshold algorithm is used for stream rasterization to get the pattern of the basin’s drainage network. The hydrology-based algorithm uses a different range of threshold values to determine the stream pattern, which is comparable to the stream vectors of the toposheet. The drainage network distribution with a threshold value of 10000 gives many minor streams which imply dissimilarities with the stream network of toposheet, whereas the threshold value of 20000 shows remarkable similarity to an existing river system. The model with threshold 20000 provides a Stranhler-based drainage network with a basin area of 5664.52 km2. The basin is the fifth-order stream network with many lower-order streams. The drainage pattern is resulted in dendritic and sub-dendritic. The morphometric parameters of the basin are evaluated with the help of an aspect, slope, and contour. The slope of the study area is flat in the east and steeper in the west, along the area of Western Ghats. A bifurcation ratio ranges from 1.05 to 2.42, indicating that the drainage network is not influenced by structural disturbances in that area. The comprehensive evaluation of flow patterns along with morphometric properties obtained from this study provides data support for estimation of the volume of water in the basin, reservoir operation, and construction of hydrological structures. Also, this result can be used to compute watershed attributes normally used in hydrologic and water resources studies. The hydrology-based algorithm can be employed in other river basins to extract drainage network patterns.

Application of the analytical hierarchy process (AHP) for flood susceptibility mapping using GIS techniques in Thamirabarani river basin, Srivaikundam region, Southern India

Application of the analytical hierarchy process (AHP) for flood susceptibility mapping using GIS techniques in Thamirabarani river basin, Srivaikundam region, Southern India

Distribution of the Diatoms and Water Quality Assessment of the Thamirabarani River, Tamil Nadu, South India


 
 
 
 
 
 The diatoms are one of the most significant organisms beneficial for biomonitoring investigations. The present study deals with the diatom and water samples collected from 10 different localities in the Thamirabarani River, Southern India. Diatom samples were collected by scraping stones with a toothbrush and squeezing macrophytes. Study of diatom valve morphology and measurements of diatoms were carried out using an optical miccroscope. The present study recorded 58 diatom taxa belonging to 25 genera. Among the diatoms, the taxonomical characters of 20 abundant diatom taxa viz. Aulacoseira granulata, Discostella stelligera, Navicula cryptocephala, Encyonema minutum, Gomphonema gandhii, Eunotia asterionelloides, Gomphonema parvulum, Brachysira neglectissima, Aulacoseira ambigua, Diadesmis confervacea, Nitzschia palea, Nitzschia amphibia, Sellaphora Americana, Staurosirella pinnata, Gomphonema affine, Fragilaria pararumpens, Eunotia incisa, Navicula erifuga, Navicula cryptotenella and Navicula rostellata are described and illustrated. In the present study abundant diatom genera were observed such as Aulacoseira, Discostella, Navicula, Encyonema, Gomphonema, Brachysira, Nitzschia, Sellaphora, Staurosirella, Fragilaria and Euno- tia. In abundant diatom taxa such as Aulacoseira granulate, Discostella stelligera, Gomphonema gandhii, Fragilaria pararumpens, Navicula cryptocephala, Navicula rostellata, Staurosirella pinnata water quality index values between 21-42 were recorded at Sites 1-9, which indicates unpolluted water. The abundant diatom taxa Diadesmis confervacea, Nitzschia palea, and Gomphonema parvulum were present at Site 10 and a water quality index value of 101 was recorded, indicating water polluted due to anthropogenic activity. The diatom assemblage of the present study was compared with various river systems to understand the environmental condition assessment. The water samples were analysed for assessment of the water quality.
 
 
 
 
 
 
 

Environmental Impact Assessment Using Diatoms in Thamirabarani River, Tirunelveli District, Tamil Nadu, India

The present study provides a detailed report on the occurrence and record of diatom taxa from the Thamirabarani River. A total number of 55 diatom taxa belonging to 25 genera were identified. The result shows the abundance of diatom genera viz. Amphora, Aulacoseira, Cyclotella, Cymbella, Eunotia, Gomphonema, Melosira and Ulnaria in the study area indicated varying pollution levels and pristine conditions. The diversity of diatom taxa in Site 1 and Site 3-7 indicate that the river water is not polluted in these locations. Domestic waste input in the river at Site 2 area may responsible for the dominant occurrence of moderate pollution tolerant diatoms taxa. The abundance of pollution tolerant diatom taxa in Site 8, Site 9 and Site 10 areas of the river indicates high pollution. The Canonical Correspondence Analysis (CCA) results also show that the concentration of diatom taxa and physico-chemical parameters suggest the release of industrial effluents and anthropogenic activity. The proper waste water treatment methods need to be implemented along the catchment areas of the river to ratify pollution levels. Keywords: Diatoms, Thamirabarani River, Pollution, Water Quality, Anthropogenic Impact

Studies on Estuary of Thamirabarani River, Tamilnadu, India

The state of Tamilnadu is located along the south west of Indian peninsula. The state has nearly 40 river basin and most of them are seasonal. The river Thamirabarani is one of the perennial rivers covering 3 districts namely Tenkasi, Tirunelveli and Tuticorin. The river originates from the eastern side of the west coast and confluences with Bay of Bengal at a village called Punnakayal in Tuticorin district. The Thamirabarani river is known for its irrigation potential in the upper reaches. By the time it reaches the lower end, the flow is very low. The east coast is well known for its littoral drift which is dominantly towards the north direction. The village is famous for its fishing potential. The study area of Punnakayal is influenced by two monsoons namely south west and north east. Due to absence of high flow in the non-monsoon period, the estuaries are highly blocked by sand bar formation. Because of this sand bar formation, the fisherman find it difficult to go in to deep sea during low tide time. Hence studies were made and remedial measures were suggested and completed. The details of hydrologic analyses, hydraulic modelling, hydrodynamic studies, assessment of littoral drift remedial measures and post project performance are detailed in the paper.

Hydrogeochemistry and Water Quality Assessment in the Thamirabarani River Stretch by Applying GIS and PCA Techniques

The primary objective of this research is to assess the hydrogeochemical features and water quality of the Thamirabarani river stretch, located in southern India. Thirty-five water samples from the Thamirabarani river stretch were obtained from the districts of Tirunelveli and Thoothukudi. Twelve water quality parameters were measured during the pre-monsoon and post-monsoon periods of 2020 and 2021. The analytical results were verified with BIS and WHO standards to evaluate the water for drinking purposes. A Geographic Information system (GIS) was applied to know the spatial variation of the hydrogeochemical properties over the research area. Moreover, the Water Quality Index was calculated and it was revealed that 15% of the water samples used are outstanding, 35% are fit for potable use, 25% are poor, 15% water are very poor, and 10% unfit for consumption. Principal Component analysis (PCA) was performed to find out the dominant factors and their variance coverage for the overall water quality. The PCA results indicate that a water sample in Zone 1 is known for its alkalinity. The water qualities in Zone 2 and Zone 3 were affected by anthropogenic factors and industry wastes. More sea water intrusion was observed in Zone 4 in the water quality of the Thamirabarani river basin.

Efficiency of convolutional neural networks (CNN) based image classification for monitoring construction related activities: A case study on aggregate mining for concrete production

Monitoring construction activities is an important task for efficiency in construction site operations thus the topic received a fair amount of attention in the literature. Optimizing construction site operations by monitoring and detecting various tasks is dependent on the size of the construction field, which determines the tools that can be used for the job. A monitoring task can be performed with high efficiency through image classification algorithms by training the algorithms to detect construction machinery. If the area of monitoring is larger, such as the task of detecting construction related operations in a large infrastructural construction, using drone images might become inefficient. We aimed to take a first step towards a cost-efficient monitoring system specifically for construction activities that cover large territories. Consequently, satellite image classification has been performed for construction machinery detection in this study. We utilized different versions of well-established convolutional neural network architectures as backbone for the transfer learning method and their performances are evaluated. Finally, the best performing models are determined as DenseNet161 and ResNet101 with 0.919 and 0.903 test accuracies, respectively. DenseNet161 model was discussed in terms of its accuracy and efficiency in a case study to detect illegal aggregate mining activity through the basin of Thamirabarani River.

An Annotated Checklist of Ichthyofaunal Diversity of the Potamon Zone of Thamirabarani River, South India

Background: Thamirabarani is a major east-flowing river originates from the Pothigai Hills of Southern Western Ghats (8°36'07.1"N 77°15'50.9"E) at an altitude of 2074 m with a catchment area of 5482 km2 and meanders through a distance of 120 km (24 km in hilly terrain and 96 km in plains) in Tirunelveli and Tuticorin districts and drains into the Bay of Bengal. Present paper provides information on abundance, distribution, human utility, Trophic level, Lm and IUCN status of the Thamirabarani River. Methods: The present study was conducted by monthly intervals on Ichythyofaunal diversity of the Potamon Zone of Thamirabarani River from November 2019 to October 2021, selecting seven sampling stations viz Cherenmahadevi, Vannarpettai, Murappanadu, Karungulam, Srivaikuntam, Eral and Authoor. Result: In the present study, a total of 57 species comprising 11 orders, 19 families and 38 genera were documented from downstream stretch of Thamirabarani River, of which three fish species namely Horadandia atukorali; Oreochromis mossambicus and Wallago attu are under vulnerable category and three fish species namely are Hypselobarbus dubius; Labeo fisheri and Dawkinsia tambraparniei endangered listed in the International Union for Conservation of Nature red list. Among the 11 orders reported, the order Cypriniformes (52%) was observed to have the highest contribution to the Ichthyofaunal diversity and the family Cyprinidae (32%) was recorded the highest contribution to the finfish diversity. The trophic level community structure of recorded fish species revealed the dominance of mid-level carnivores (48%). The human utility of recorded finfishes was found to be the highest was observed as edible (72%) and IUCN status was the highest with least concern (72%).