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Item Strengthening of brick masonry with welded wire mesh(Science Publishing Corporation Inc, 2018-07-20) Umamaheswari, V; Kanchidurai, S; Krishnan, P.A.; Baskar, KUnreinforced brickwork (URM) is the most established development method. URM being weak can't withstand the parallel burdens amid a seismic region. Consequently, it is important to locate an appropriate low-cost technique to fortify existing brickwork structures. In this paper flexural bond strength test was conducted on the rectangular brick masonry prisms with two types of welded wire meshes (epoxy coated mesh with the spacing of 12mm and galvanized iron wire mesh with the spacing of 15mm). Masonry prisms were cast and tested as per the guidelines are given in ASTM E518 /E518-15 standards. The results of the flexural bond strength embedded masonry prism show greater when comparing the prisms with no mesh embedmentItem An assessment of brick masonry strengthening practice by special methods(Blue Eyes Intelligence Engineering and Sciences Publication, 2019-09-03) Kanchidurai, S; Krishnan, P.A.; Baskar, KThis study aims to identify the best suitable method to enhance strength and the structural performance of masonry. There are different techniques available to strengthen the existing and new masonry structures. This paper deals the metal/mesh embedment in the masonry wall, strengthening by added different polymers and textile strips, masonry grout, engineered cementitious materials (ECC) and interlocking masonry method. The comparison of different unique masonry strengthening methods helps us to provide a better suggestion for construction issues. In contrast to the conventional method, welded wire mesh gives better results than all other ways. Also, embedment of TRM, ECC, FRP, GFRP, CFRP, and interlocking holds an excellent performance in some other aspects. © BEIESP.Item GIS-based multi-criteria analysis for identification of potential groundwater recharge zones - a case study from Ponnaniyaru watershed, Tamil Nadu, India(KeAi Communications Co., 2020-02-21) Abijith, Devanantham; Saravanan, Subbarayan; Singh, Leelambar; Jennifer, Jesudasan Jacinth; Saranya, Parthasarathy K.S.S.Groundwater is one of the most vital natural resources; spatially varying in quality and quantity. Increased urbanisation and population creates tremendous pressure on the quality and quantity of the groundwater resources. In this study, Ponnaniyaru watershed of Cauvery basin was considered for this research. Geographical information system (GIS) and remote sensing (RS) plays a vital role in preparing various thematic layers for targeting the groundwater potential zones (GWPZ). This study adopts the Analytical Hierarchy Process (AHP) and Multi influence factor (MIF), multi-criteria decision-making approaches to determine the weights for the influencing factors. Weighted linear overlay analysis was carried out to determine the GWPZ. Further, the resultant GWPZ map has been reclassified into five different classes, namely Very good, Good, Moderate, Poor and Very poor. The results were validated with observed well-yield data, and the predictive precision for AHP and MIF was found to be 75%, and 71% respectively. © 2020 The AuthorsItem Kinetics and equilibrium studies for the removal of heavy metals in both single and binary systems using hydroxyapatite(Springer Verlag, 2012-03-21) Ramesh S.T.; Rameshbabu, N; Gandhimathi, R; Nidheesh, P.V.; Srikanth Kumar, MRemoval of heavy metals is very important with respect to environmental considerations. This study investigated the sorption of copper (Cu) and zinc (Zn) in single and binary aqueous systems onto laboratory prepared hydroxyapatite (HA) surfaces. Batch experiments were carried out using synthetic HA at 30 °C. Parameters that influence the adsorption such as contact time, adsorbent dosage and pH of solution were investigated. The maximum adsorption was found at contact time of 12 and 9 h, HA dosage of 0. 4 and 0. 7 g/l and pH of 6 and 8 for Cu and Zn, respectively, in single system. Adsorption kinetics data were analyzed using the pseudofirst-, pseudosecond-order and intraparticle diffusion models. The results indicated that the adsorption kinetic data were best described by pseudosecond-order model. Langmuir and Freundlich isotherm models were applied to analyze adsorption data, and Langmuir isotherm was found to be applicable to this adsorption system, in terms of relatively high regression values. The removal capacity of HA was found to be 125 mg of Cu/g, 30. 3 mg of Zn/g in single system and 50 mg of Cu/g, 15. 16 mg of Zn/g in binary system. The results indicated that the HA used in this work proved to be effective material for removing Cu and Zn from aqueous solutions. © 2012 The Author(s).Item Adsorptive removal of Pb(II) from aqueous solution using nano-sized hydroxyapatite(Springer Verlag, 2012-10-11) Ramesh, S.T.; Rameshbabu, N; Gandhimathi, R; Srikanth Kumar, M; Nidheesh P.V.This study investigated the sorption of Pb(II) in aqueous solution onto hydroxyapatite (HA) surfaces. Batch experiments were carried out using synthetic HA. The effect of contact time, HA dosage, and initial pH on removal efficiency were also investigated. The adsorption equilibrium and kinetics of Pb(II) on this adsorbent were then examined at 25 °C. Kinetic data were analyzed by pseudo first, second, and intra-particle diffusion models. The sorption data were then correlated with the Langmuir, Freundlich, Halsey, and Harkins-Jura adsorption isotherm models. The optimum dose of HA for Pb(II) removal is found to be 0. 12 g/l with the removal efficiency of 97. 3 % at an equilibrium contact time of 1 h. It is found that the adsorption kinetics of the Pb(II) on HA follow the pseudo second-order reaction. All the isotherms fitted well for experimental data. Capacity of HA is found as 357. 14 mg Pb(II)/g of HA. The Pb(II) immobilization mechanism was studied. The results indicated that HA can be used as an effective adsorbent for removal of Pb(II) from aqueous solution. © 2012 The Author(s).Item Effects of Climate Change on Streamflow in the Godavari Basin Simulated Using a Conceptual Model including CMIP6 Dataset(MDPI, 2023-04-27) Reddy, Nagireddy Masthan; Saravanan, Subbarayan; Almohamad, Hussein; Al Dughairi, Ahmed Abdullah; Abdo, Hazem GhassanHydrological reaction to climate change anticipates water cycle alterations. To ensure long-term water availability and accessibility, it is essential to develop sustainable water management strategies and better hydrological models that can simulate peak flow. These efforts will aid in water resource planning, management, and climate change mitigation. This study develops and compares Sacramento, Australian Water Balance Model (AWBM), TANK, and SIMHYD conceptual models to simulate daily streamflow at Rajegaon station of the Pranhita subbasin in the Godavari basin of India. The study uses daily Indian Meteorological Department (IMD) gridded rainfall and temperature datasets. For 1987–2019, 70% of the models were calibrated and 30% validated. Pearson correlation (CC), Nash Sutcliffe efficiency (NSE), Root mean square error (RMSE), and coefficient of determination (CD) between the observed and simulated streamflow to evaluate model efficacy. The best conceptual (Sacramento) model selected to forecast future streamflow for the SSP126, SSP245, SSP370, and SSP585 scenarios for the near (2021–2040), middle (2041–2070), and far future (2071–2100) using EC-Earth3 data was resampled and bias-corrected using distribution mapping. In the far future, the SSP585 scenario had the most significant relative rainfall change (55.02%) and absolute rise in the annual mean temperature (3.29 °C). In the middle and far future, the 95th percentile of monthly streamflow in the wettest July is anticipated to rise 40.09% to 127.06% and 73.90% to 215.13%. SSP370 and SSP585 scenarios predicted the largest streamflow increases in all three time periods. In the near, middle, and far future, the SSP585 scenario projects yearly relative streamflow changes of 72.49%, 93.80%, and 150.76%. Overall, the findings emphasize the importance of considering the potential impacts of future scenarios on water resources to develop effective and sustainable water management practices.Item Streamflow simulation using conceptual and neural network models in the Hemavathi sub-watershed, India(Elsevier B.V., 2022-11-21) Reddy, Nagireddy Masthan; Saravanan, Subbarayan; Abijith, DevananthamWater is one of the most valuable natural resources and a major element of a state's and country's socioeconomic growth. The world's water resources and India are under huge pressure because of rising demand and a limited supply. Proper water management is the only solution for ensuring a close gap between demand and supply. Hydrological modeling offers an answer to this issue by establishing relationships between different hydrological processes. Several models have been developed in the past decade to simulate the rainfall and runoff relations. Some models are simple conceptual models based on spatially distributed event-based or continuous and artificial intelligence (AI) models. This study aims to compare two conceptual daily-based models and one AI model developed for the Hemavathi sub-watershed in the Cauvery Basin (India). Two daily runoff models are implemented using conceptual models, i.e., Sacramento and the Australian water balance model (AWBM) using Rainfall-Runoff Library (RRL) tool and Feed forward Backpropagation neural network (FFBPNN) model. The models were calibrated for daily streamflow values from 1990 to 2006 and then validated from 2007 to 2015. The effectiveness of model runoff predictions is evaluated using statistical parameters such as Nash-Sutcliffe efficiency (NSE) and Correlation coefficient (CC) values. The NSE values for the FFBPNN is 0.88 (calibration) and 0.74 (validation), Sacramento model is 0.66 (calibration) and 0.48 (validation), and 0.63 (calibration) and 0.44 (validation) for the AWBM model. From the obtained results, the FFBPNN model performs well in terms of NSE and CC compared to Sacramento and AWBM models. © 2022Item Multi-Criterion Analysis of Cyclone Risk along the Coast of Tamil Nadu, India—A Geospatial Approach(Multidisciplinary Digital Publishing Institute (MDPI), 2023-08-16) Saravanan, Subbarayan; Abijith, Devanantham; Kulithalai Shiyam Sundar, Parthasarathy; Reddy, Nagireddy Masthan; Almohamad, Hussein; Al Dughairi, Ahmed Abdullah; Al-Mutiry, Motrih; Abdo, Hazem GhassanA tropical cyclone is a significant natural phenomenon that results in substantial socio-economic and environmental damage. These catastrophes impact millions of people every year, with those who live close to coastal areas being particularly affected. With a few coastal cities with large population densities, Tamil Nadu’s coast is the third-most cyclone-prone state in India. This study involves the generation of a cyclone risk map by utilizing four distinct components: hazards, exposure, vulnerability, and mitigation. The study employed a Geographical Information System (GIS) and an Analytical Hierarchical Process (AHP) technique to compute an integrated risk index considering 16 spatial variables. The study was validated by the devastating cyclone GAJA in 2018. The resulting risk assessment shows the cyclone risk is higher in zones 1 and 2 in the study area and emphasizes the variations in mitigation impact on cyclone risk in zones 4 and 5. The risk maps demonstrate that low-lying areas near the coast, comprising about 3%, are perceived as having the adaptive capacity for disaster mitigation and are at heightened risk from cyclones regarding population and assets. The present study can offer valuable guidance for enhancing natural hazard preparedness and mitigation measures in the coastal region of Tamil Nadu.Item Machine Learning Approaches for Streamflow Modeling in the Godavari Basin with CMIP6 Dataset(Multidisciplinary Digital Publishing Institute (MDPI), 2023-08-11) Saravanan, Subbarayan; Reddy, Nagireddy Masthan; Pham, Quoc Bao; Alodah, Abdullah; Abdo, Hazem Ghassan; Almohamad, Hussein; Al Dughairi, Ahmed AbdullahAccurate streamflow modeling is crucial for effective water resource management. This study used five machine learning models (support vector regressor (SVR), random forest (RF), M5-pruned model (M5P), multilayer perceptron (MLP), and linear regression (LR)) to simulate one-day-ahead streamflow in the Pranhita subbasin (Godavari basin), India, from 1993 to 2014. Input parameters were selected using correlation and pairwise correlation attribution evaluation methods, incorporating a two-day lag of streamflow, maximum and minimum temperatures, and various precipitation datasets (including Indian Meteorological Department (IMD), EC-Earth3, EC-Earth3-Veg, MIROC6, MRI-ESM2-0, and GFDL-ESM4). Bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets were utilized in the modeling process. Model performance was evaluated using Pearson correlation (R), Nash–Sutcliffe efficiency (NSE), root mean square error (RMSE), and coefficient of determination (R2). IMD outperformed all CMIP6 datasets in streamflow modeling, while RF demonstrated the best performance among the developed models for both CMIP6 and IMD datasets. During the training phase, RF exhibited NSE, R, R2, and RMSE values of 0.95, 0.979, 0.937, and 30.805 m3/s, respectively, using IMD gridded precipitation as input. In the testing phase, the corresponding values were 0.681, 0.91, 0.828, and 41.237 m3/s. The results highlight the significance of advanced machine learning models in streamflow modeling applications, providing valuable insights for water resource management and decision making.Item Assessing the impact of climate and land use change on flood vulnerability: a machine learning approach in coastal region of Tamil Nadu, India(Springer Science and Business Media Deutschland GmbH, 2025-01-27) Abijith, Devanantham; Saravanan, Subbarayan; Parthasarathy K.S.S.; Reddy, Nagireddy Masthan; Niraimathi, Janardhanam; Bindajam, Ahmed Ali; Mallick, Javed; Alharbi, Maged Muteb; Abdo, Hazem GhassanFlooding and other natural disasters threaten human life and property worldwide. They can cause significant damage to infrastructure and disrupt economies. Tamil Nadu coast is severely prone to flooding due to land use and climate changes. This research applies geospatial tools and machine learning to improve flood susceptibility mapping across the Tamil Nadu coast in India, using projections of Land Use and Land Cover (LULC) changes under current and future climate change scenarios. To identify flooded areas, the study utilised Google Earth Engine (GEE), Sentinel-1 data, and 12 geospatial datasets from multiple sources. A random forest algorithm was used for LULC change and flood susceptibility mapping. The LULC data are classified for the years 2000, 2010, and 2020, and from the classified data, the LULC for years 2030, 2040, and 2050 are projected for the study. Four future climate scenarios (SSP 126, 245, 370, and 585) were used for the average annual precipitation from the Coupled Model Intercomparison Project 6 (CMIP6). The results showed that the random forest model performed better in classifying LULC and identifying flood-prone areas. From the results, it has been depicted that the risk of flooding will increase across all scenarios over the period of 2000–2100, with some decadal fluctuations. A significant outcome indicates that the percentage of the area transitioning to moderate and very high flood risk consistently rises across all future projections. This study presents a viable method for flood susceptibility mapping based on different climate change scenarios and yields estimates of flood risk, which can provide valuable insights for managing flood risks. © The Author(s) 2025.Item Behavior of pile due to combined loading with lateral soil movement(Springer, 2016-05-20) Jegatheeswaran, B; Muthukkumaran, KPiles are commonly used to transfer vertical forces, arising primarily from super structure. Lateral loads, however, are just as important as vertical loads in designing pile foundations and are often more complicated. More powerful lateral loads occur as a result of unpredicted events such as heavy wind, earthquakes, slope failure, and lateral spread induced by liquefaction. But in actual case combined action of vertical and horizontal ground loads can occur in many situations for a pile. So the study of combined load behaviour of soil is important. But these all are suitable only in horizontal ground only. If the pile is in sloped ground then the behaviour of a pile is not only depend on the combined loading but also depends on the lateral soil movement due to the effect of slope. So in this paper by using finite element software, the behaviour of a pile due to the combined loading is studied along with and without the influence of lateral soil movement is made. The effect of the lateral soil movement is depends on the slope angle, so for this study varying slope angles (1:1, 1:1.5 and 1:2) were also considered. © 2016, Jegatheeswaran and Muthukkumaran.Item Non-linear performance analysis of free headed piles in consolidating soil subjected to lateral loads(Elsevier B.V., 2020-10-15) Sivaraman, S; Muthukkumaran, KasinathanThe analysis of laterally loaded pile is complex due to its site specific behaviour. Whereas most of the analytical methods provides only a generalized solution to it. Behaviour of piles in clay depends on site specific factors like subsoil condition, type of super-structure and the load transfer from it, construction duration and ground improvement process. The present study deals with the assessment of lateral load behaviour of pile based on the results of conventional and instrumented field load tests. The pile was designed based on the results of laboratory and field geotechnical investigations. The diameter and depth of bored cast in-situ pile were fixed as 600 mm and 16 m from the natural ground level respectively. The deflection profile obtained using inclinometer for various lateral loads on piles tested during different phases of site development were analyzed. The pile bending moment, shear force and soil reaction profile were established from the inclinometer data. The results obtained from the experimental data were found to be comparable with that of analytical method. The non-linear lateral load-displacement curves obtained from the load test conducted at different period of consolidation induced by site development process were analyzed. The curves thus obtained were transferred into a non-dimensional kh/khmax versus shear strain curve for the formation of equation explicit to the specific site. A site specific equation was proposed for the estimation of lateral load-displacement curve with respect to degree of consolidation of the surrounding soil subjected to surcharge load induced by the site development process.Item Estimation of lateral capacity of rock socketed piles in layered soil-rock profile(Springer, 2021-04-20) Prakash, A.R.; Muthukkumaran, KasinathanLarge diameter rock socketed piles were preferred for the purpose of transmission of a huge volume of both vertical and lateral load from superstructure to a deeper depth safely without any structural defects. A series of experimental program was conducted on model pile for studying the behaviour of the rock socketed pile under static lateral load in a soil-rock layered profile system. The model piles were instrumented with displacement and force transducers for measuring the magnitude of the pile movement and load transferred by the pile. The experimental results showed that the rock socketed pile lateral capacity has significantly affected by the depth of embedment of the pile in soil and depth of rock socket. There was a considerable increase in the lateral capacity of the pile when the depth of socketing is three times the diameter of the pile into rock with a minimum embedment. In the 3D socketed piles, the lateral capacity of the pile is almost 18 times higher than the non-socketed piles. From the experimental study, it is also observed that when the piles socketed more in to the hard strata (rock), the depth of fixity increases and the lateral displacement reduces substantially. © 2021, The Author(s).Item Assessment of innovative dented sheet liner on the improvement of hydraulic properties of pervious concrete pile(Elsevier B.V., 2021-05-14) Umanath, U; Muthukkumaran, KasinathanThe Pervious Concrete Pile (PCP) is a technique that has emerged as an innovative method to improve radial consolidation and the bearing capacity of soft soils. The PCP, a stiffer vertical column (pile), has voids on the surface that accelerate the radial consolidation and eventually improve soft soils' bearing capacity. Since the PCP is stiffer material, the performance does not depend on the confined soil, unlike other drains. As the rate of radial consolidation hinges on the drain's hydraulic conductivity, ensuring the permeability of PCP along its total length is essential. An innovative method of dented sheet liner has been introduced in this study to improve the hydraulic conductivity of PCP. This method was introduced to create surface roughness and regular voids along the length of PCP. Malleable material like aluminium has been dented with specified patterns as a liner on the inner surface and introduced along with conventional formwork, which shall be removed after the concrete's final setting time. A series of laboratory experiments such as compressive strength, split tensile strength, porosity, and falling head permeability tests were performed on PCP cast using dented sheet liners. The results were compared with the conventional PCP properties to establish the efficiency of dented sheet liner in improving the hydraulic conductivity of pervious concrete. The results show that using dented sheet liners, the hydraulic properties porosity and permeability of PCP have been increased up to 22.5% and 79%, respectively, with minimum reduction in the strength parameters.Item Rainfall-Induced Slope Instability in Tropical Regions Under Climate Change Scenarios(Multidisciplinary Digital Publishing Institute (MDPI), 2025-05-06) Kumar, Rajendra P.; Muthukkumaran, Kasinathan; Sharma, Chetan; Shukla, Anoop Kumar; Sharma, Surendra KumarThe reduction in the stability of rock slopes due to rainfall is a significant issue in tropical regions. Unsaturated soil, commonly found on hill slopes, provides higher shear strength compared to saturated soil due to matric suction. Soil moisture plays a crucial role in determining slope stability during rainfall events, yet it is often overlooked in geotechnical engineering projects. This study integrates both steady-state and transient analyses to examine how rainfall intensity affects the stability of a rock slope near a tunnel portal. Transient seepage analysis was conducted using SEEP/W to simulate changes in pore water pressure (PWP) resulting from rainfall infiltration under historical and future precipitation conditions. The analysis considers medium (SSP245) and worst-case (SSP585) climate change scenarios as per Coupled Model Intercomparison Project Phase 6 (CMIP6). The findings underscore the significant impact of rainfall-induced infiltration on slope stability and highlight the importance of incorporating soil moisture dynamics in slope stability assessments. The safety factor, initially 1.54 before accounting for rainfall effects, decreases to 1.34 when the effects of rainfall are included. © 2025 by the authors.Item Improvement of liquefaction resistance and cyclic response of sandy soil by air injection method(Chinese Academy of Sciences, 2026-04-21) Das, Rima; Muthukkumaran, KasinathanInducing partial saturation within the soil matrix has emerged as an effective approach to enhancing liquefaction resistance in fully saturated sands. Conventional methods for mitigating liquefaction susceptibility often involve substantial costs, complex implementation procedures, and potential environmental implications. This study investigates the enhancement of cyclic liquefaction resistance in sandy soils through induced partial saturation by air injection. Undrained cyclic triaxial tests under stress control were carried out on specimens in fully saturated, air-injected, and partially saturated states, considering a range of relative densities and loading configurations. The effect of air injection pressure and desaturation on the cyclic response was systematically examined. Liquefaction resistance curves and safety factors against liquefaction were evaluated for different earthquake records. Furthermore, a comparative analysis of the dynamic characteristics of fully saturated and partially saturated sand specimens was conducted to investigate the effect of saturation levels on their cyclic response. The experimental results validated the increased liquefaction resistance achieved through the induction of partial saturation. Moreover, the results demonstrated a notable decline in generated excess pore water pressure corresponding to a reduction in the degree of saturation to 95%. The liquefaction resistance ratio (CRR) increased significantly with a saturation level of 75%, irrespective of relative density. Furthermore, the target degree of saturation (Srtarget) was determined for loose to medium-dense relative density. © 2026 Institute of Rock and Soil Mechanics, Chinese Academy of SciencesItem Advancing Agricultural Land Suitability in Urbanized Semi-Arid Environments: Insights from Geospatial and Machine Learning Approaches(Multidisciplinary Digital Publishing Institute (MDPI), 2024-12-03) Sathiyamurthi, Subbarayan; Subbarayan, Saravanan; Ramya, Madhappan; Sivasakthi, Murugan; Gobi, Rengasamy; Qaysi, Saleh; Praveen Kumar, Sivakumar; Lee, Jinwook; Alarifi, Nassir; Wahba, Mohamed; M. Youssef, YoussefRising food demands are increasingly threatened by declining crop yields in urbanizing riverine regions of Southern Asia, exacerbated by erratic weather patterns. Optimizing agricultural land suitability (AgLS) offers a viable solution for sustainable agricultural productivity in such challenging environments. This study integrates remote sensing and field-based geospatial data with five machine learning (ML) algorithms—Naïve Bayes (NB), extra trees classifier (ETC), random forest (RF), K-nearest neighbors (KNN), and support vector machines (SVM)—alongside land-use/land-cover (LULC) considerations in the food-insecure Dharmapuri district, India. A grid searches optimized hyperparameters using factors such as slope, rainfall, temperature, texture, pH, electrical conductivity, organic carbon, available nitrogen, phosphorus, potassium, and calcium carbonate. The tuned ETC model showed the lowest root mean squared error (RMSE = 0.15), outperforming RF (RMSE = 0.18), NB (RMSE = 0.20), SVM (RMSE = 0.22), and KNN (RMSE = 0.23). The AgLS-ETC map identified 29.09% of the area as highly suitable (S1), 19.06% as moderately suitable (S2), 16.11% as marginally suitable (S3), 15.93% as currently unsuitable (N1), and 19.21% as permanently unsuitable (N2). By incorporating Landsat-8 derived LULC data to exclude forests, water bodies, and settlements, these suitability estimates were adjusted to 19.08% (S1), 14.45% (S2), 11.40% (S3), 10.48% (N1), and 9.58% (N2). Focusing on the ETC model, followed by land-use analysis, provides a robust framework for optimizing sustainable agricultural planning, ensuring the protection of ecological and social factors in developing countries. © 2024 by the authors.Item Soil and Water Assessment Tool-Based Prediction of Runoff Under Scenarios of Land Use/Land Cover and Climate Change Across Indian Agro-Climatic Zones: Implications for Sustainable Development Goals(Multidisciplinary Digital Publishing Institute (MDPI), 2025-02-06) Subbarayan, Saravanan; Youssef, Youssef M.; Singh, Leelambar; Dąbrowska, Dominika; Alarifi, Nassir; Ramsankaran, RAAJ.; Visweshwaran, R; Saqr, Ahmed M.Assessing runoff under changing land use/land cover (LULC) and climatic conditions is crucial for achieving effective and sustainable water resource management on a global scale. In this study, the focus was on runoff predictions across three diverse Indian watersheds—Wunna, Bharathapuzha, and Mahanadi—spanning distinct agro-climatic zones to capture varying climatic and hydrological complexities. The soil and water assessment (SWAT) tool was used to simulate future runoff influenced by LULC and climate change and to explore the related sustainability implications, including related challenges and proposing countermeasures through a sustainable action plan (SAP). The methodology integrated high-resolution satellite imagery, the cellular automata (CA)–Markov model for projecting LULC changes, and downscaled climate data under representative concentration pathways (RCPs) 4.5 and 8.5, representing moderate and extreme climate scenarios, respectively. SWAT model calibration and validation demonstrated reliable predictive accuracy, with the coefficient of determination values (R2) > 0.50 confirming the reliability of the SWAT model in simulating hydrological processes. The results indicated significant increases in surface runoff due to urbanization, reaching >1000 mm, 600 mm, and 400 mm in southern Bharathapuzha, southeastern Wunna, and northwestern Mahanadi, respectively, especially by 2040 under RCP 8.5. These findings indicate that water quality, agricultural productivity, and urban infrastructure may be threatened. The proposed SAP includes nature-based solutions, like wetland restoration, and climate-resilient strategies to mitigate adverse effects and partially achieve sustainable development goals (SDGs) related to clean water and climate action. This research provides a robust framework for sustainable watershed management in similar regions worldwide. © 2025 by the authors.Item Evaluation of hydrological responses to decadal variability of land use/land cover patterns in tropical river basin of the Western Ghats, Southern India(Taylor and Francis Ltd., 2026-07-03) Gayen, Sudeshna; Seenipandi, Kaliraj; Srinivas, Reji; Devaraj, Suresh; Subbarayan, Saravanan; Loganathan, ParthibanLULC change is increasingly altering hydrological processes in the Karamana River Basin, which faces declining vegetation cover, increasing impervious surfaces, and growing drought vulnerability. This study evaluates decadal LULC transformations and their hydrological impacts using Landsat (2000, 2015 and 2025), MODIS-derived variables, and IMD rainfall data integrated within a GIS-SVM framework. Unlike previous studies that primarily assessed individual indicators, this research provides a comprehensive evaluation linking LULC dynamics with multiple hydrological and drought indicators. Built-up areas expanded by 68.2% between 2000 and 2025, accompanied by a 2.12 °C increase in LST. NDVI maximum values declined from 1 to 0.92, NDWI decreased from 0.79 to 0.48, ET reduced from 55.88 to 38.60 mm, and SPI ranged from −1.84–0.70 to −1.47–1.13, indicating localized severe drought hotspots (SPI < −1.5). The findings highlight the need for sustainable land-use planning, urban growth regulation, watershed restoration, and climate-resilient water resource management. © 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.Item Mapping of Spatially Distributed Soil Erosion over the Tungabhadra River Sub-Basin (TRB) Using Satellite-Based Precipitation Products (SPPs) and RUSLE Modelling(Multidisciplinary Digital Publishing Institute (MDPI), 2026-06-05) Subbarayan, Saravanan; Sankriti, RamanarayanIn many developing regions, the lack of on-site weather data impedes the estimation of rainfall-driven processes, such as soil erosion. Satellite-based precipitation products (SPPs) can support hydrological modelling in gauge-sparse regions by providing continuous rainfall estimates. Accurate rainfall estimation is crucial to soil erosion modelling, particularly in data-scarce regions such as the TRB. In this study, seven satellite-based precipitation products—CHIRPS, IMERG, TRMM, ERA5, GLDAS, and PERSIANN-CDR, along with the IMD gridded dataset—were evaluated for their ability to represent rainfall patterns and support R-factor estimation in the RUSLE framework. This is the first comprehensive evaluation of multiple SPPs for RUSLE-based soil erosion modelling in the Tungabhadra river basin (TRB), providing insights for ungauged watersheds in India. CHIRPS and IMERG displayed relatively smooth and continuous patterns, while PERSIANN-CDR and TRMM exhibited fragmented rainfall zones. ERA5 and GLDAS demonstrated consistent but moderate values across the basin. IMD data served as the reference product for comparison. The findings reveal that the choice of precipitation dataset directly affects the accuracy of erosion estimation. Therefore, multi-dataset evaluation is recommended for reliable assessment of soil loss and watershed planning in ungauged or partially gauged catchments. © 2026 by the authors.