Faculty Publications
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Item AN Integrated Analysis and Forecasting of Wildfires in the Nallamala Hills, India(Institute of Electrical and Electronics Engineers Inc., 2023) Kundapura, S.; Vishnu Vardhan, M.; Apoorva, K.V.Wildfires threaten ecosystems, human lives, and infrastructure, necessitating effective detection and prediction methods. In this study, an in-depth analysis of wildfire detection and forecasting is carried out over the Nallamala hills, which stretch across the states of Telangana and Andhra Pradesh. Our approach comprises three significant steps: Active fire analysis, pre-fire analysis, and post-fire analysis. Pre-fire maps were created using the Normalised Difference Vegetation Index (NDVI) during the pre-fire analysis, which involved time series analysis of significant components. For active fire analysis, the first dataset is created by using satellite imagery and its derived products. A dataset is used to train the five different machine-learning models for prediction. Among these models, the Random Forest classifier outperformed the remaining four models (Support vector Classifier, Gradient Boosting Classifier, Logistic Regression, and K-means algorithms) in accurately detecting and predicting active fires. This step enabled real-Time monitoring and prioritisation of firefighting efforts. The burnt area calculation uses the Normalised Burn Ratio (NBR) in the post-fire analysis. The analysis implemented post-fire rehabilitation and restoration efforts, giving essential information on the scope and severity of fire damage. The comprehensive study of all wildfires will provide a detailed picture of what occurred in the past (Timeseries), present (Prediction models), and future (Pre-fire maps), allowing people and government agencies to take precautions against future wildfires. © 2023 IEEE.Item Estimation of Seismicity Parameters for Andhra Pradesh and Telangana(Springer Science and Business Media Deutschland GmbH, 2024) Ashrith, M.S.; Bakale, M.S.; Kolathayar, S.The present study attempts to estimate the seismicity parameters for the states of Andhra Pradesh and Telangana (12°–19° N and 77°–89° E) using the latest earthquake data. The updated seismic catalogue was developed by using the dataset from Kolathayar et al. (J Earth Syst Sci 121:1351–1364, 2012) [1] and updating it to the present day. The catalogue was homogenized and then declustered using Gardner and Knopoff (Bull Seismol Soc Am 64:1363–1367, 1974) [2]. The period of completeness for various magnitude intervals was estimated using Stepp (Proceedings of the 1st international conference on microzonazion, vol 2(1), pp. 897–910, 1972) [3], and seismicity parameters for the study area were determined using least square fit. The Gutenberg and Richter (Bull Seismol Soc Am 34:185–188, 1944) [4] relationship was used to calculate a and b, which were 3.64 and 0.72, respectively. These values are vital in performing seismic hazard assessment for the area later. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item Natural and anthropogenic factors controlling the dissolved organic carbon concentrations and fluxes in a large tropical river, India(2006) Balakrishna, K.; Kumar, I.A.; Srinikethan, G.; Mugeraya, G.Carbon studies in tropical rivers have gained significance since it was realized that a significant chunk of anthropogenic CO2 emitted into the atmosphere returns to the biosphere, that is eventually transported by the river and locked up in coastal sediments for a few thousand years. Carbon studies are also significant because dissolved organic carbon (DOC) is known to complex the toxic trace metals in the river and carry them in the dissolved form. For the first time, this work has made an attempt to study the variations in DOC concentrations in space and time for a period of 19 months, and estimate their fluxes in the largest peninsular Indian river, the Godavari at Rajahmundry. Anthropogenic influence on DOC concentrations possibly from the number of bathing ghats along the banks and domestic sewage discharge into the river are evident during the pre-monsoon of 2004 and 2005. The rise in DOC concentrations at the onset of monsoon could be due to the contributions from flood plains and soils from the river catchment. Spatial variations highlighted that the DOC concentrations in the river are affected more by the anthropogenic discharges in the downstream than in the upstream. The discharge weighted DOC concentrations in the Godavari river is 3-12 times lower than Ganga-Brahmaputra, Indus and major Chinese rivers. The total carbon fluxes from the Godavari into the Bay of Bengal is insignificant (0.5%) compared to the total carbon discharges by major rivers of the world into oceans. © Springer Science+Business Media, Inc. 2006.Item Spatial and temporal variations in water quality, major ions and trace metals(2007) Deepa, V.J.; Balakrishna, K.; Mugeraya, G.; Srinkethan, G.; Krishnakumar, P.K.Godavari river at Rajahmundry is monitored for a period of seven months at five stations along its course for the physicochemical parameters, major ions and trace metals. This study is made to obtain a baseline data of the existing pollutants in this 'hotspot', which is set to become the industrial hub of Andhra Pradesh. Results indicate that A P Paper Mills may not be polluting the river at this period, contrary to what was expected. Clear picture will emerge, once the data for the rainy season is available. Local pollution from detergents and soap in the river is seen in the downstream (station VIP) as lot of bathing and washing activity is done on the banks. There is no pollution of Cu, Ni, Pb, As and Co in the Godavari river at Rajahmundry. In general the pollutant levels in all the stations analysed is within the prescribed limits set by BIS and WHO standards. Copyright © Enviromedia.Item A note on the occurrence of landslides in Araku valley and its environs, Visakhapatnam district, Andhra Pradesh, India(2010) Balaji, P.; Pavanaguru, R.; Venkat Reddy, D.The occurrence of landslides in Araku valley and its environs of Visakhapatnam district of Andhra Pradesh have been studied. The slides occurred in a rugged hilly terrain which is a part of Eastern Ghats Mobile Belt. The slides are predominantly debris slides of varying dimensions and occurred in khondalitic country having slopes of the order of 30°. The debris are composed mostly of scree, soil, boulders and weathered rock. The significant causative factor of triggering slides was manifested through heavy rainfall associated with cyclonic storm. The causes of the slope failure include toe erosion, debris accumulation that resulted in blockade, overtopping and changes in the stream courses. The present paper is aimed to identify damage assessment, magnitude of slides and causes of slides with an attempt to suggest some long term corrective and control measures in the area. © 2010 Cafet-Innova Technical Society.Item Identification of Artificial recharge sites in hard rock terrain using RS and GIS in Chintapally Mandal, Nalgonda District, Andhra Pradesh, India(2010) Raju, A.; Reddy, A.G.S.; Venkat Reddy, D.A study has been undertaken to identify the favorable areas for artificial recharge in Chintapally mandal in Nalgonda district, Andhra Pradesh. Geographical Information System (GIS) and Remote Sensing technology contributes an efficient and effective result oriented methods for studying the occurrence and movement of groundwater resources. Integration of various thematic layers such as geomorphology, slope, soil types, lineament density, and drainage density have been used to identify the suitable zones for the artificial recharge in the study area. For identifying the suitable zones, weightage and ranking scores were assigned to each thematic layer then using ARC/INFO GIS software, the above themes have been integrated and the areas suitable for artificial recharge have been identified using spatial analysis tools from GIS environment. The favorable areas for artificial recharge have been categorized into Very Good, Good, Moderate to Good, Moderate, Poor to Moderate and poor for recharge in the study area. © 2010 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.Item Assessment of Environmental Impact of Aquaculture Ponds in the Western Delta Region of Andhra Pradesh(MDPI, 2022) Thotakura, T.V.; Malegole, S.B.; Chaudhary, B.; Gobinath, G.Aquaculture is persistent and well-established in the delta region of Andhra Pradesh. In recent years, the expansion of aquaculture has conferred positive economic growth in the newly formed state. However, the enormous development of aqua ponds increases the effluents from aquaculture which contain various chemical compounds that can cause negative impacts when released into the environment. This paper presents the effect of unengineered aquaculture on the environment in the delta region of Andhra Pradesh. The expansion rate of aquaculture practice in the delta region has been carried out using remote sensing and a geospatial information system. An experimental investigation was carried out on soil and water samples collected from the aquaculture ponds to evaluate the water quality parameters and soil characterization. Analysis of the geotechnical properties and microstructure was carried out to determine the interaction between the soil and the aquaculture contaminants. Based on the geospatial data and field survey, the aquaculture practice in the delta region of Andhra Pradesh was intensive and extended towards the northeast from the southwest. Between 2016 and 2020, aquaculture practice significantly increased by 6.08%. Moreover, the water quality parameters and pond bottom soil showed a higher concentration of ammonia and nitrates. Further, aquaculture leachate may interact with the subsoil and have a negative impact on soil mineralogy and hydraulic conductivity. The extensive experimental data and field surveys reveal that adequate guidelines are needed to control the pollution load on the ecosystem. © 2022 by the authors.Item Prediction of ammonia contaminants in the aquaculture ponds using soft computing coupled with wavelet analysis(Elsevier Ltd, 2023) Thotakura, T.V.; Sunil, B.M.; Chaudhary, B.; Durga Prasad, C.D.; Gobinath, G.Intensive aquaculture practices generate highly polluted organic effluents such as biological oxygen demand (BOD), alkalinity, total ammonia, nitrates, calcium, potassium, sodium, iron, and chlorides. In recent years, Inland aquaculture ponds in the western delta region of Andhra Pradesh have been intensively expanding and are more concerned about negative environmental impact. This paper presents the water quality analysis of aquaculture waters in 64 random locations in the western delta region of Andhra Pradesh. The average water quality index (WQI) was 126, with WQI values ranging from 21 to 456. Approximately 78% of the water samples were very poor and unsafe for drinking and domestic usage. The mean ammonia content in aquaculture water was 0.15 mg/L, and 78% of the samples were above the acceptable limit set by the World Health Organization (WHO) of 0.5 mg/L. The quantity of ammonia in the water ranged from 0.05 to 2.8 mg/L. The results show that ammonia levels exceed the permissible limits and are a significant concern in aquaculture waters due to toxicity. This paper also presents an intelligent soft computing approach to predicting ammonia levels in aquaculture ponds, using two novel approaches, such as the pelican optimization algorithm (POA) and POA coupled with discrete wavelet analysis (DWT-POA). The modified and enhanced POA with DWT can converge to higher performance when compared to standard POA, with an average percentage error of 1.964 and a coefficient of determination (R2) value of 0.822. Moreover, it was found that prediction models were reliable with good accuracy and simple to execute. Furthermore, these prediction models could help stakeholders and policymakers to make a real-time prediction of ammonia levels in intensive farming inland aquaculture ponds. © 2023 Elsevier LtdItem Novel assessment tools for inland aquaculture in the western Godavari delta region of Andhra Pradesh(Springer, 2024) Thotakura, T.V.; Malegole, S.B.; Chaudhary, B.; Gobinath, G.; Chitturi, P.; Durga Prasad, D.P.The production of fisheries and shrimp has been twice every 10 years for the previous five decades, making it the most rapidly expanding food industry. This growth is due to intensive farming and the conversion of agriculture into aquaculture in many parts of South Asia. Furthermore, intensive aquaculture generates positive economic growth but leads to environmental degradation without proper monitoring. Unfortunately, technical innovation is less in aquaculture than agricultural and manufacturing industries. The advent of remote sensing and soft computing has expanded various opportunities for utilizing and integrating technological advances in civil and environmental disciplines. This paper presents the aquaculture scenario in the western Godavari delta region of Andhra Pradesh and proposes various novel assessment tools to monitor the aquaculture environment. An experimental investigation was carried out on the physicochemical characteristics of the inland aquaculture ponds to evaluate water quality in the aquaculture ponds. Furthermore, to assess the intensity of inland aquaculture, the current work concentrates on the potential application of remote sensing and soft computing approaches. Geospatial models of kriging and inverse distance weighing (IDW) show higher performance in estimating ammonia levels in the intensive aquaculture groundwaters with coefficient of determination (R2) values of 0.947 and 0.901, respectively. Teaching learning-based optimization (TLBO) and adaptive particle swarm optimization (APSO), two of the five soft computing techniques utilized in the study, perform better than the others. Additionally, it was found that remote sensing-based assessment tools and soft computing prediction models were both trustworthy, accurate, and easy to use. Furthermore, these methods could assist in the real-time evaluation of inland aquaculture waters by stakeholders and policymakers. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.