Browsing by Author "Ramesh, H."

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A novel mathematical morphology based algorithm for shoreline extraction from satellite images
(Taylor and Francis Ltd., 2017) Rishikeshan, C.A.; Ramesh, H.
Shoreline extraction is fundamental and inevitable for several studies. Ascertaining the precise spatial location of the shoreline is crucial. Recently, the need for using remote sensing data to accomplish the complex task of automatic extraction of features, such as shoreline, has considerably increased. Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating. Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps. Here, we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries. The salient features of this work are the preservation of actual size and shape of the shorelines, run-time structuring element definition, semi-automation, faster processing, and single band adaptability. The proposed approach is tested with various sensor-driven images with low to high resolutions. Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach. The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments. © 2017 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group.
A numerical modeling approach for study of mudbank impact on coastline
(Institute of Electrical and Electronics Engineers Inc., 2015) Parvathy, K.G.; Ramesh, H.; Noujas, V.; Thomas, K.V.
Coastal zone is the triple interface of land, ocean and atmosphere. Any developmental activity along the coastal zone requires a clear understanding of the dynamic processes controlling its very existence. When most of the processes, which are common to all coastlines are quite well known, there are some localized, but important processes requiring further research for developmental planning. Mudbanks are such an inquisitive coastal phenomenon which occurs only at a few locations in the nearshore waters of the world ocean. Mudbanks, its occurrence, nature, properties and characteristics are interesting subjects from engineering point of view. The objective of the study is to provide an insight of mudbank impact on coastal morphology through a numerical modeling approach. For a better understanding of the influence of mudbanks on coastal morphology, Munambam to Chettuwa sector of Thrissur coast which is a part of Southwest coast of India is considered. In the present study the description of coastline evolution due to impact of mudbank is calculated using LITLINE module of LITPACK software package. It is observed that the occurrence, non-occurrence and migration of mudbanks influence the coastal dynamics significantly along mudbank influenced coastal stretch of Kerala. Â© 2014 IEEE.
Advances of Submarine Groundwater Discharge in the Coastal Aquifers of India: A Review
(Technoscience Publications, 2025) Sunilkumar, P.S.; Ramesh, H.; Wadde, S.
Groundwater is a crucial freshwater source for coastal communities. However, population growth, urbanization, industrial activities, and the discharge of polluted sewage water have led to the contamination of coastal groundwater with nutrients, metals, and organic compounds. This contaminated groundwater and terrestrial groundwater discharges into the ocean through a process known as Submarine Groundwater Discharge (SGD). This study aims to review (i) the driving forces behind SGD across coastal barriers, (ii) methods for identifying and quantifying SGD sites, and (iii) the status of SGD in Indian coastal aquifers and groundwater resource availability. The study indicates that groundwater discharge is higher on the east coast of India than on the west coast. Data on groundwater resources in India’s coastal states show an increase in annual groundwater extractions for irrigation, industry, and domestic use, with a decreasing trend in net groundwater availability for future use between 2011, 2013, and 2017. Despite this, there is limited evidence on the quantity of SGD flux along the Indian coastline. However, preliminary studies by the Mission SGD project have made some progress in understanding this phenomenon. This research aims to improve the estimation of water resources in India and highlight the volume of SGD entering the ocean. A comprehensive understanding of hydrogeological settings, computational methods, coastal aquifer geometries, and other factors is essential for accurately estimating SGD along the Indian coastline. © 2025 by the authors Licensee: Technoscience Publications.
An ANN supported mathematical morphology based algorithm for lakes extraction from satellite images
(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2018) Rishikeshan, C.A.; Ramesh, H.
With advances in remote sensing (RS) technology and platforms, more and more high-quality and fine spatial resolution satellite images are available. Manual method of feature extraction from remote sensing imagery is a tedious and time-consuming process. Thus automated and replicable technique plays vital role in updating lake database to evaluate the spatial and temporal evolution of lakes and ponds especially for vastly growing urban areas. This research work presents an artificial neural network (ANN) computed threshold value-based mathematical morphology (MM)-driven approach for extraction of lakes from satellite imageries with better accuracy. Accuracy of developed methodology has been assessed with the ground truths of the study area revealing better performance with different data-sets compared to existing methods. On an average scale for all data-sets used, the proposed algorithm is able to extract lakes with 99.47% accuracy and 0.9397 correlation coefficient (MCC). The existing classification method exhibited an accuracy of 98.75% and correlation coefficient of 0.89049. Similarly, the existing threshold-driven method has 99.31% accuracy and 0.90374 correlation coefficient. Maintenance of actual size and shape of the lakes, run-time control over structuring elements, semi-automation, faster processing, and single band adaptability are features of this work. © 2017 Indian Society for Hydraulics.
An automated mathematical morphology driven algorithm for water body extraction from remotely sensed images
(Elsevier B.V., 2018) Rishikeshan, C.A.; Ramesh, H.
The detection and extraction of water bodies from satellite imagery is very important and useful for several planning and developmental activities such as shoreline identification, mapping riverbank erosion, watershed extraction and water resource management. Popular techniques for water body extraction like those based on the normalized difference water index (NDWI) require reflectance information in the green and near-infrared (NIR) bands of the light spectrum. Moreover, some commonly used approaches may perform differently according to the spatial resolution of the images. In this regard, mathematical morphological (MM) techniques for image processing have been employed for spatial feature extraction as they preserve edges and shapes. This study proposes a flexible MM driven approach which is very effective for the extraction of water bodies from several satellite images with different spatial resolution. MM provides effective tools for processing image objects based on size and shape and is particularly adapted for water bodies that have typically specific spatial characteristics. In greater details, the proposed extraction algorithm preserves the actual size and shape of the water bodies since it is based on morphological operators based on geodesic reconstruction. Moreover, the choice of the filter size (called structural element (SE) in MM) in the proposed algorithm is done dynamically allowing one to retain the most precise results from different set of inputs images of different spatial resolution and swath. The availability of more than one spectral band of satellite imagery is not necessary for the proposed algorithm as it utilizes only a single band for its computation. This makes it convenient to apply in single band imageries obtained from satellites such as Cartosat thereby making the proposed approach effective over commonly used methods. The accuracy assessment was carried out and compared with the maximum likelihood (ML) classifier and methods based on spectral indices. In all the five test datasets, extraction accuracy of the proposed MM approach was significantly higher than that of spectral indices and ML methods. The results drawn from visual and qualitative assessments indicated its capability and efficiency in water body extraction from different satellite images. © 2018 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)
Analysis of climate trend and effect of land use land cover change on Harangi streamflow, South India: a case study
(Springer Science and Business Media Deutschland GmbH, 2017) Anil, A.P.; Ramesh, H.
Land use land cover (LULC) and climate change are considered to be driving factors contributing to the alteration of the hydrological regime. Therefore, an attempt has been made to study climate trend and the effect of LULC on streamflow in a basin covered predominantly by forest. The Harangi river basin is one of such basins located in the western ghats of South India. The LULC trend was carried out by considering temporal multispectral data for the years 1990, 2002 and 2008 obtained from Landsat-5TM and IRS 1C (Indian Remote Sensing Satellites). Climate parameters such as rainfall and temperatures were considered for the trend analysis in this study. The rainfall trend was studied using Man-Kendall and Sen’s slope method to understand the spatio-temporal variability. Rainfall shows the decrease trend at Suntikoppa rain gauge station in January and June months. Harangi and Madapura rain gauge stations also show a decrease of rainfall trend for only January month. Temperature trend show increase in maximum temperature for the month of April, May and November whereas increase in minimum temperature was observed in the month of November and December. Spatial extent of LULC found that 52.4% (220.014 km2) of the study area was covered with forest in 1990 which has considerably decreased to 43.9% (184.53 km2) in 2008. There was a rise in total area of plantation crops from 106.27 km2 (25.32%) to 138.20 km2 (32.9%) during this period. Soil and Water Assessment Tool (SWAT) was used to study the effect of LULC on streamflow. SWAT model was calibrated and validated using observed daily streamflow data. The coefficient of correlation (r2) was found to be 0.87 and 0.86 for calibration and validation, respectively. The results found the annual streamflow to increase by 0.77% from 1990 to 2008 whereas the mean monthly streamflow has increased by 9.46% during this period. This was mainly due to the reduction in forest area observed in LULC maps. © 2017, Springer International Publishing Switzerland.
Analysis of extreme rainfall events over Nethravathi basin
(Taylor and Francis Ltd., 2014) Babar, S.; Ramesh, H.
India gets three fourths of its annual rainfall during the south-west monsoon season (June-September). The study of extreme events is significant in the stochastic behaviour of rainfall pattern. The aim of the present work is to compare different methods; and find a suitable method to study extreme rainfall trend analysis. In this study, frequency distribution method, generalized extreme value (GEV) distribution, Mann-Kendall and Sens slope estimator are used for rainfall trend analysis over the Nethravathi basin located in the southern part of India. The rainfall data during the monsoon months (June-September) were analysed for a period of 1971-2010. The comparison of all the methods had been carried out and it has been observed that there is an increasing trend of frequency in class-1 and decreasing trend in class-2 and class-3, respectively. The interpretation of the results is carried by using the GEV distribution and non-parametric trend analysis (Mann-Kendall and Sens slope estimator test). It turns out the best results to identify the extreme rainfall trend are obtained by the statistical techniques - Block Maxima (GEV) distribution, Mann-Kendall and Sens slope estimator test as compared to frequency-based method. The above results which help to study climate change will contribute towards sustainable development of the Nethravathi River basin. © 2013 © 2013 Indian Society for Hydraulics.
Assessment of hydropower potential in Nethravathi river basin using SWAT model
(CAFET INNOVA Technical Society cafetinnova@gmail.com 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2015) Babar, S.; Shobhita, M.P.; Ramesh, H.
Hydropower plants have the advantage of producing renewable and clean power, the renewable and reliable energy source that serves national environmental and energy policy objectives. Therefore, the development of hydropower plant and improvements of water management have essential in contributing to sustainable growth and energy production in developing countries like India. The present study is concerned with the development of methodology and assessment of hydropower potential in the Nethravathi River basin with the help of Remote Sensing and GIS. The drainage area covers about 3190 km2 at Bantwal gauging point, and most of the land cover of the basin is dominated by forest. The basin was divided into six sub-basins based on hydrology and topography using GIS tools. The climate over the basin is coastal humid tropical and receives an average annual rainfall of about 4000 mm. sub-basin discharges were estimated using the Soil Conservation Services (SCS) curve number method. To ensure the total discharge from six sub-basins computed from SCS curve number method, the flows were routed and simulated at the gauging location using Soil and Water Assessment Tool (SWAT). SWAT model was calibrated for monthly time steps from 1998–2001, and validated for 2002–2003. Flow-duration curves (FDC) were generated for each sub-basin to assess the dependable yield. The results have shown a good agreement between observed and the simulated flows. The available discharge at 75%, 80% and 90% of time for each sub-basin were extracted from the FDC. This result were used to calculate the hydropower potential in all the six sub-basins at Q75, Q80 and Q90, by integrating thematic layers using ArcSWAT. © 2015 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.
Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin
(Elsevier B.V., 2016) Ganasri, B.P.; Ramesh, H.
Soil erosion is a serious problem arising from agricultural intensification, land degradation and other anthropogenic activities. Assessment of soil erosion is useful in planning and conservation works in a watershed or basin. Modelling can provide a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions. In the present study, the soil loss model, Revised Universal Soil Loss Equation (RUSLE) integrated with GIS has been used to estimate soil loss in the Nethravathi Basin located in the southwestern part of India. The Nethravathi Basin is a tropical coastal humid area having a drainage area of 3128 km2 up to the gauging station. The parameters of RUSLE model were estimated using remote sensing data and the erosion probability zones were determined using GIS. The estimated rainfall erosivity, soil erodibility, topographic and crop management factors range from 2948.16 to 4711.4 MJ/mm·ha? 1hr? 1/year, 0.10 to 0.44 t ha? 1·MJ? 1·mm? 1, 0 to 92,774 and 0 to 0.63 respectively. The results indicate that the estimated total annual potential soil loss of about 473,339 t/yr is comparable with the measured sediment of 441,870 t/yr during the water year 2002–2003. The predicted soil erosion rate due to increase in agricultural area is about 14,673.5 t/yr. The probability zone map has been derived by the weighted overlay index method indicate that the major portion of the study area comes under low probability zone and only a small portion comes under high and very high probability zone. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Nethravathi Basin. © 2015 China University of Geosciences (Beijing) and Peking University
Assessment of Soil Loss in Wet Tropical Region: A Case Study in Kumaradhara Basin, Western Ghats, India
(Springer Nature, 2024) Roopa, N.; Ramesh, H.; Dhanush, B.M.; Meghana, C.S.
Degradation of land resources and soil erosion are major issues affecting the productivity of the land. To design appropriate regional land management approaches using field data, an evaluation is a requirement to ascertain the extent and severity of soil degradation. Western Ghats of India is one of 34 global biodiversity hotspots, and habitat degradation has been causing havoc in this area for decades. The Kumaradhara River is a dominant part of wet tropical forested land on the Western side of the Western Ghats. The Hongadahalla and Kadumanehalla Rivers are tributaries of the Kumaradhara River. Mookanamane, Bidahalli, and Marenahalli are sub-catchments covering parts of the rivers Hongadahalla, and Kadumanehalla, having catchment areas of 41Â km2, 33Â km2, and 64Â km2, respectively. The primary goal of the current study is to use the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information Systems (GIS) to estimate annual erosion rates and develop a soil loss map for the year 2021 for the mountainous watershed of Kumaradhara. The geo-environmental data were collected from Indian Meteorological Department, Earth Explorer, and the National Bureau of Soil Survey and Land Use Planning. The impacts of rainfall erosivity, soil erodability, slope length and steepness, cover management, and conservation practice variables on mean annual soil loss in the study were calculated using GIS data layers. The quantitative results and analysis of soil erosion estimated by the RUSLE model ranged from 29.56 to 7992.89 t haâˆ’1Â yearâˆ’1 in Mookanamane, 25.6 to 20,494.12 t haâˆ’1Â yearâˆ’1 in Marenahalli, and 21.6 to 15,265.25 t haâˆ’1Â yearâˆ’1 in Bidahalli. It has been observed that the risk of soil erosion in forests is low in the study area, whereas the risk of soil erosion on barren land is moderate. The study results shall create terrain management and planning strategies in environmentally sensitive mountainous areas. Â© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Comparison of Different Pan Sharpening Techniques using Landsat 8 Imagery
(Institute of Electrical and Electronics Engineers Inc., 2019) Govind, N.R.; Rishikeshan, C.A.; Ramesh, H.
Pan sharpening technique is a widely used image processing technique which combines the data available from various sensors and exploits its varied capabilities. In this study, the efficiency of four diverse pan sharpening methods namely High Pass filter, Modified Intensity Hue Saturation, Ehlers fusion and Hyperspectral Colour Sharpening was evaluated. The pan sharpening approaches are applied to Landsat 8 imagery of an urban area. The spatial and spectral quality of the fused images is assessed using different indices like Bias, RMSE, Correlation Coefficient and ERGAS. The fused images obtained have improved spatial resolution and visual appearance compared to the original MS image. The fused images have a spatial resolution comparable to that of the PAN image. According to visual analysis, Modified IHS method yielded a fused image with better visual interpretability. The statistical analysis shows that the high pass filter is the most suitable pan sharpening method for this dataset. On testing for Bias, RMSE, ERGAS and CC, the high pass filter method performed best followed by Modified Intensity Hue saturation, Ehlers fusion and Hyperspectral Colour Sharpening while Ehlers fusion showed a higher correlation, compared to Modified IHS. Â© 2019 IEEE.
Conjunctive use in India's Varada River Basin
(American Water Works Association cs-journals@wiley.com, 2009) Ramesh, H.; Mahesha, A.
The use of groundwater in conjunction with surface water resources has gained prominence in regions experiencing scarce or uneven distribution of water. In the Varada River Basin in Karnataka, India, for example, an optimization model was developed for the conjunctive use of surface water and groundwater resources because of the increasing demand on agricultural and domestic sectors of this area's water supply. Monsoon rains, which occur only six months a year, predominantly control the basin's agricultural activities. However, the area has an immense need for efficient use of available water resources during the rest of the year. The model, based on linear programming, optimizes the allocation of groundwater and surface water subject to hydraulic and stream flow constraints. The model incorporates policy scenarios that add to the sustainability of the system. The developed conjunctive-use model is simple but effective in computing the optimal use of the Varada basin's water resources.
Effectiveness of contrast limited adaptive histogram equalization technique on multispectral satellite imagery
(2017) Ganesh, V.R.; Ramesh, H.
Contrast Limited Adaptive Histogram Equalization technique (CLAHE) is a widely used form of contrast enhancement, used predominantly in enhancing medical imagery like X-rays and to enhance features in ordinary photographs. This paper aimed to understand the effectiveness of using this technique in multispectral satellite imagery and to study its effectiveness in different regions of the electromagnetic spectrum. This study also aimed at analyzing variations of spatial and spectral resolutions of a sensor affect the performance of the CLAHE technique by means of comparing quantitative parameters of the enhanced images between the sensors. A general idea of the feature that can be enhanced in each spectral region was also studied. The results showed that a comparative study between the CLAHE technique and the conventional global histogram equalization technique resulted in the former technique emerging superior of the two and thereby reconstructed images of better quality. � 2017 Association for Computing Machinery.
Effectiveness of contrast limited adaptive histogram equalization technique on multispectral satellite imagery
(Association for Computing Machinery acmhelp@acm.org, 2017) Ganesh, V.R.; Ramesh, H.
Contrast Limited Adaptive Histogram Equalization technique (CLAHE) is a widely used form of contrast enhancement, used predominantly in enhancing medical imagery like X-rays and to enhance features in ordinary photographs. This paper aimed to understand the effectiveness of using this technique in multispectral satellite imagery and to study its effectiveness in different regions of the electromagnetic spectrum. This study also aimed at analyzing variations of spatial and spectral resolutions of a sensor affect the performance of the CLAHE technique by means of comparing quantitative parameters of the enhanced images between the sensors. A general idea of the feature that can be enhanced in each spectral region was also studied. The results showed that a comparative study between the CLAHE technique and the conventional global histogram equalization technique resulted in the former technique emerging superior of the two and thereby reconstructed images of better quality. Â© 2017 Association for Computing Machinery.
Estimation of Reservoir Storage Using Artificial Neural Network (ANN)
(Springer Nature, 2018) Satish, P.; Ramesh, H.
The rapid growth in population increases water demand thus resulting in scarcity of water which is due to improper management rather than lack of resources. Reservoir is the most important source for surface water. So, reservoir storage plays a crucial role in efficient reservoir management. Artificial neural network (ANN) is capable of simulating reservoir storage capacity. So, in the present work five different feed forward back propagation ANN models by varying number of hidden layer neurons were developed for estimation of Harangi reservoir storage, Karnataka, India. The first 2 years (2010–12) data was used for supervised training and remaining data (2013–14) was used in prediction. The predictive accuracy using the statistical parameters like correlation coefficient (R) and mean absolute percentage error (MAPE) were found within the acceptable limit. Result shows that, ANN model with five hidden neurons (i.e., network architecture of 6-5-1) is performing well compared to all other models for prediction of reservoir storage estimation. © Springer Nature Singapore Pte Ltd. 2019.
Evaluating the effects of forest fire on water balance using fire susceptibility maps
(Elsevier B.V., 2020) Venkatesh, K.; Konkathi, K.; Ramesh, H.
Sudden and long term changes in the landscape can be attributed to periodic wildfires which, is a cyclic occurrence at Kudremukh national forest in Western Ghats of India. These land-use changes influence the hydrology of landscape, causing disintegration of soil, loss of biodiversity, changes in stream and flooding. To understand and account for these land-use changes, a new approach was implemented by developing fire susceptibility map from topographic, climatic and human-induced factors and validating it with MODIS (Moderate-resolution Imaging Spectro-radiometer) fire points for discretising accuracy. The fire susceptibility map can be used for studying the long-term (year or more) effects of fire on water balance systems. The fire susceptibility map generated for the years 2005 and 2017 was overlaid with MODIS LULC (Land Use Land Cover) for establishing the post-fire scenario whereas MODIS LULC MCD12Q1 (2005 and 2017) was considered as the no-fire scenario to analyse the intensity of the fire and its effect on streamflow and infiltration. These maps along with historical satellite hydro-climatic datasets, were used to assess the effect of forest fire on hydrological parameters using the SWAT (Soil and Water Assessment Tool) model. No-fire and post-fire conditions were established by modifying SCS-CN (Soil Conservation Service-Curve Number) based on previous works of literature to represent the catchment as unburnt and burnt area. The SWAT model was calibrated (2002–2008) and validated (2009–2012) for establishing a baseline scenario. The sensitive parameters obtained from SUFI-2 (Sequential Uncertainty Fitting) algorithm in SWAT-CUP (Calibration and Uncertainty Programs) were used to simulate stream flows till 2017 due to lack of observed streamflow data for the year 2017. It was inferred that the effect of wildfire on flows in recent years (2017) had increased radically when compared to the flows before a decade (2005), diminishing the rate of infiltration and causing the deficit in groundwater to energise. The methodology can further be executed in any forest area for distinguishing fire hazard zones and implementing prior actions in those areas for mitigation of forest fires and maintaining sustainable water balance. © 2019 Elsevier Ltd
Evaluating the Performance of Secondary Precipitation Products through Statistical and Hydrological Modeling in a Mountainous Tropical Basin of India
(Hindawi Limited, 2020) Venkatesh, K.; Krakauer, N.Y.; Sharifi, E.; Ramesh, H.
This paper investigates the performance of gridded rainfall datasets for precipitation detection and streamflow simulations in Indias Tungabhadra river basin. Sixteen precipitation datasets categorized under gauge-based, satellite-only, reanalysis, and gauge-adjusted datasets were compared statistically against the gridded Indian Meteorological Dataset (IMD) employing two categorical and three continuous statistical metrics. Further, the precipitation datasets' performance in simulating streamflow was assessed by using the Soil and Water Assessment Tool (SWAT) hydrological model. Based on the statistical metrics, Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) furnished very good results in terms of detecting rainfall, followed by Climate Hazards Group Infrared Precipitation (CHIRP), National Centres for Environmental Prediction-Climate Forecast System Reanalysis (NCEP CFSR), Tropical Rainfall Measurement Mission (TRMM) 3B42 v7, Global Satellite Mapping of Precipitation Gauge Reanalysis v6 (GSMaP_Gauge_RNL), and Multisource Weighted Ensemble Precipitation (MSWEP) datasets which had good-to-moderate performances at a monthly time step. From the hydrological simulations, TRMM 3B42 v7, CHIRP, CHIRPS 0.05°, and GSMaP_Gauge_RNL v6 produced very good results with a high degree of correlation to observed streamflow, while Soil Moisture 2 Rain-Climate Change Initiative (SM2RAIN-CCI) dataset exhibited poor performance. From the extreme flow event analysis, it was observed that CHIRP, TRMM 3B42 v7, Global Precipitation Climatology Centre v7 (GPCC), and APHRODITE datasets captured more peak flow events and hence can be further implemented for extreme event analysis. Overall, we found that TRMM 3B42 v7, CHIRP, and CHIRPS 0.05° datasets performed better than other datasets and can be used for hydrological modeling and climate change studies in similar topographic and climatic watersheds in India. © 2020 Kolluru Venkatesh et al.
Evaluating the reliability of open-source hydrodynamic models in flood inundation mapping: an exhaustive approach over a sensitive coastal catchment
(Elsevier, 2024) Thakur, D.A.; Suryawanshi, V.; Ramesh, H.; Prakash Mohanty, M.P.
Recently, the frequency and severity of flooding events have escalated, underscoring the urgent requirement for effective flood management strategies. Comprehensive flood inundation mapping and the precise identification of flood-prone areas are indispensable tools in this endeavor. In the current research, the Hydrologic Engineering Center's River Analysis System (HEC-RAS) version 6.3 software was employed to create inundation maps and delineate areas at risk of flooding for the Netravati-Gurupura River basins. Flood flows for various years have been simulated across the river basin, with terrain characteristics derived from the 30-m spatial resolution Shuttle Radar Topography Mission digital elevation model. The simulation of flow within the model was conducted using daily discharge data, with the model being calibrated at an optimal Manning's roughness coefficient value of n = 0.032. The calibration process was carried out by performance metrics, including the coefficient of determination, Nash-Sutcliffe efficiency, and the index of agreement, to ensure precision and reliability in the model's outputs. The outcomes of the model simulation provided depth, velocity, and water surface elevation data, from which potential flood-prone zones were identified. Model performance validation was conducted for the flood events of 2007 and 2014, revealing that the results of the statistical parameters fell within the anticipated range. This study demonstrated that flood events could be effectively simulated using the HEC-RAS two-dimensional model, enabling the identification of flood-prone areas. This research underscores the pivotal role of open-source hydrodynamic modeling in enhancing our predictive capabilities and preparedness for flood events. This approach not only optimizes resource allocation for flood defense infrastructure but also informs the strategic planning of land use, minimizing potential flood damage and bolstering environmental and societal well-being. © 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.
Evaluation and Prediction of Land Use and Land Cover Changes in the Kumaradhara Basin, Western Ghats, India
(Springer Science and Business Media Deutschland GmbH, 2024) Roopa, N.; Namratha, N.; Ramesh, H.; Manjunath, K.C.
Land use land cover (LULC) is considered as the most significant and obvious indicator of changes in ecosystems. An understanding of current and potential future development opportunities is provided through analysis on the spatiotemporal shifting patterns of LULC and simulation of future scenarios. Kumaradhara river flows in the Western Ghats in southern peninsular, India. It is the major tributary of the Netravathi river, and the catchment has numerous perennial streams and is dominated by dense evergreen forests with high conservation value. In the present study, an integrated approach of remote sensing and geospatial techniques is used to assess LULC changes for the period of 2010â€“2020, and prediction of future LULC change was carried out by ANN model using MOLUSCE plugin of QGIS for the year 2025. The results have shown that the build-up land has increased considerably, and forest has decreased which is evident from the increase in cultivated land. The predicted LULC showed an increase in built-up land and a significant transformation of barren land. The results of this study indicate significant changes in the LULC pattern. Â© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Evaluation of stakeholder knowledge and practices of water use management strategy: Observations from a questionnaire survey in Southern India
(Elsevier Ltd, 2024) Chinmayi, B.Y.; Ramesh, H.
Freshwater resources remain unequally distributed in time and space around the world. Water resource frameworks should be designed, planned, and overseen in order to fully meet current and future social and economic objectives. The difficulties grow as the system gets bigger and more complex, with varying spatial distribution of water and insufficient resources, making water re-distribution more difficult. The current study fills such gaps by evaluating several factors influencing conjunctive management. In the current study, an effort has been made to compile the best data on water use, agricultural practises, socioeconomic status, and so on through field surveys in order to comprehend the reality on the ground. Additionally, investigations are being conducted into the causes and barriers that are most likely to have slowed the implementation of conjunctive use of available water resources. Two comprehensive socioeconomic surveys were conducted using the quantitative research methodology in a river basin in Southern India, and the results clearly show that stakeholders are unaware of the most effective agricultural water management techniques and the rationale behind modern irrigation systems. Over ninety-five percent of the total respondents were farmers, with only five percent having basic knowledge of watershed development and conjunctive use water management. The identified gaps and the inference made in the study are in the context of conjunctive water management of agricultural water. The current work may provide useful information on the baseline scenarios for upcoming agricultural water management plans, as well as a useful tool for achieving significant milestones in the agricultural sector. Furthermore, the prepared questionnaire and the data gathered for the study may also be helpful to decision-makers. © 2024 The Authors