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Item Prioritisation of watersheds using TOPSIS and VIKOR method(SPIE spie@spie.org, 2019) Makhdumi, W.; Dwarakish, G.S.Watershed management has become a necessity for the optimum use and sustainability of natural resources. Prioritisation is done to identify and rank the different watersheds in a catchment based on multiple parameters which play a role in the land and water degradation, using various multi-attribute decision-making methods (MADM). In the present study two MADM methods namely, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and VIsekriterijumsko KOmpromisno Rangiranje (VIKOR), which are based on the measure of 'closeness to ideal' were used for the prioritisation of Netravati catchment, Karnataka, India. The catchment is having an area of 3415 sq. km., and was divided into six watersheds (NET01, NET02, NET03, NET04, NET05 and NET07), using Survey of India (SOI) toposheets (1:50000) and ALOS PALSAR DEM (12.5m). Morphometric analysis was carried for each watershed. Twelve parameters related to linear, aerial and relief aspects, were considered for ranking of the watershed using the TOPSIS and the VIKOR method individually. Watersheds NET04, NET05 and NET02 were assigned ranks 1, 2 and 3 from the TOPSIS method with closeness to ideal solution values 0.6476, 0.5983 and 0.5805 respectively. Similarly, based on the VIKOR method, watersheds NET03, NET04 and NET05 were ranked 1, 2 and 3 with Q values 1, 0.9632 and 0.8176 respectively. Watershed NET07, which is on the downstream of the catchment attained the least rank from both the methods. Also, the watersheds were further characterised in three categories, based on risk erodibility using the Jenks natural breaks GIS-Classification. The watersheds with a higher risk of erodibility should be given preference for the implementation of soil and water conservation methods in the study area, and thus watersheds were prioritised accordingly. © 2019 SPIE. Downloading of the abstract is permitted for personal use only.Item Erosion and Accretion in the Netravati River Stretch: Spatiotemporal Analysis Using Geospatial Approach(Springer Science and Business Media Deutschland GmbH, 2024) Makhdumi, W.; Shwetha, H.R.; Dwarakish, G.S.Understanding erosion and accretion, which are critical geomorphic processes, is essential for effective river management and conservation. Erosion by removing soil and rock changes the river's shape, depth, and course. Accretion, conversely, involves the deposition and accumulation of sediment, shaping features like riverbanks and floodplains. Focused on a 30 km stretch of the Netravati River, in the southwestern region of India, this study used Survey of India toposheets and Landsat images to track changes over time (1973, 1998, 2022). The Normalised Difference Water Index (NDWI) and image classification were employed for the analysis which revealed notable spatiotemporal variations in these processes. From 1973 to 2022, the analysis estimated a total erosion of 510.43 hectares and an accretion of 317.71 hectares. The years 1973–1998 witnessed more accretion (417.6 hectares) than erosion (229.08 hectares). And, from 1998 to 2022, erosion dominated at 438.37 hectares, with only 56.97 hectares of accretion. These variations can be attributed to both natural processes and human interventions. Notably, the construction of a vented dam in 1993 at Thumbe, followed by the subsequent dam in 2016, 50 m downstream of the old dam, influenced the sediment dynamics and flow patterns in the Netravati River, potentially impacting erosion and accretion processes. This research adds to our understanding of erosion and sediment changes in the Netravati River over time. The dams and hydraulic structure upstream along with geospatial techniques offer researchers and river managers a unique opportunity to examine river shape impacts and thus develop sustainable strategies for river preservation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item Comparative Analysis of Topographic Factor (LS Factor) Estimation Methods for Soil Erosion Risk Assessment in the Netravati Watershed, India(Springer Science and Business Media Deutschland GmbH, 2024) Makhdumi, W.; Shwetha, H.R.; Dwarakish, G.S.Soil erosion models are crucial for soil conservation planning and environmental assessments globally. The Universal Soil Loss Equation (USLE)-based models are most popular empirical models for estimating soil erosion. The topographic factor (LS factor), which combines slope length and slope steepness, significantly affects soil loss among the input parameters. This study aimed to estimate the LS factor for the Netravati watershed in Karnataka, India, which has a high elevation variation (0–1719 m) and diverse terrain, posing soil erosion and local landslide risks that require conservation planning. Three different methods were employed for dimensionless LS factor estimation: Wischmeier and Smith equation (Method I), Moore and Burch equation (Method II), and Desmet and Govers equation (Method III) along with Geographic Information System (GIS) techniques and a high-resolution (12.5 m) ALOS-PALSAR Digital Elevation Model (DEM). The LS factor values ranged from 0.06 to 1549.39 for Method I, 0 to 191.72 for Method II, and 0.03 to 149.09 for Method III. The results showed that Method III produced values that were evenly distributed throughout the spatial domain, with a mean value of 3.31 and a standard deviation of 4.87. Method I generated very high LS factor values along the flow path and almost uniform values for the rest of the study area. The mean LS factor values for Method I and Method II were 8.31 and 7.41, respectively, with standard deviations of 18.74 and 9.88. The findings of this research suggest that Method III is preferable approach for estimating LS factor values in a spatial domain due to its even distribution of values and low standard deviation. This study demonstrates that estimating the LS factor is impacted by the availability and accuracy of topographic data and the technique used. The findings can be used to support sustainable land management practices in the study area. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item Geospatial Techniques for Soil Erosion-Based Watershed Prioritisation: A Review(Springer Science and Business Media Deutschland GmbH, 2025) Makhdumi, W.; Suragamallika, R.; Shwetha, H.R.; Dwarakish, G.S.The degradation of the environment caused by anthropogenic has raised significant concerns about the sustainability of land, water, and energy resources. It is crucial to acknowledge the unique characteristics of each watershed and the variability in the impact of human and natural activities across regions. Soil erosion emerges as a major threat, which leads to degraded soil, reduced agricultural productivity, and water pollution. Effective watershed management is essential for preventing soil erosion and ensuring the sustainability of resources. A fundamental step in effective watershed management involves evaluating and identifying the most severely impacted sub-watersheds. This study focuses on soil erosion-based prioritisation studies in India, examining their main findings, models, and methodologies. Geospatial techniques, which include Remote Sensing (RS) and Geographic Information System (GIS), have proven effective for mapping and assessing soil erosion at different scales. These methods identify erosion-causing factors, including land use, slope, rainfall intensity, and soil characteristics. By integrating geospatial data, accurate assessments of soil erosion vulnerability can be made, supporting informed decision-making. Multi-Criteria Decision Analysis (MCDA) helps in prioritisation by evaluating multiple soil erosion criteria and assigning weights based on their relative importance. Geospatial tools facilitate comprehensive assessments of soil erosion vulnerability, aiding decision-making processes. The review offers insights for researchers to conduct reliable assessments and generate data on soil erosion. Integrating Land Use Land Cover Changes (LULCC) and socio-economic conditions in prioritisation studies is recommended. This paper can assist researchers generate reliable data on soil erosion, enabling policymakers to make informed decisions regarding adaptation and mitigation strategies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.Item Soil erosion in diverse agroecological regions of India: a comprehensive review of USLE-based modelling(Springer Science and Business Media Deutschland GmbH, 2023) Makhdumi, W.; Shwetha, H.R.; Dwarakish, G.S.Soil erosion caused by water refers to the removal of topsoil by rainfall and runoff. Proper selection of an assessment method is crucial for quantifying the spatial variance of soil erosion. The Universal Soil Loss Equation (USLE) and its revised version (RUSLE) are widely used for modelling soil erosion. This study aimed to evaluate the effectiveness of the USLE-based soil erosion modelling in different agroecological regions of India, identify potential issues, and provide suggestions for future applications. The review revealed that little attention has been given to estimate soil erosion in high-priority land degradation regions of India. Additionally, many studies failed to thoroughly verify the authenticity of stated soil loss rates in their research regions either by overestimating or underestimating at least one of the five soil loss parameters. Furthermore, flaws in the application of methods to calculate these parameters leading to erroneous values were identified and suggestions for improvement were made. The USLE-based soil erosion modelling is an effective tool for quantifying soil erosion risk, but researchers should put emphasis on thoroughly verifying the methodologies adopted, unit conversions, and data availability for the estimation of soil loss parameters to improve the accuracy of their final results. This paper provides valuable insights to assist researchers in implementing USLE-based erosion models in diverse agroecological regions in India and elsewhere. However, for effective soil conservation and sustainable agriculture, further research is necessary to develop efficient techniques for using USLE-based soil erosion modelling to achieve a comprehensive understanding of erosion risk across different agroecological regions. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Item Hydrological responses to land use/land cover change in Tikur Wuha Watershed in Southern Ethiopia(Springer Science and Business Media Deutschland GmbH, 2022) Ketema, A.; Dwarakish, G.S.; Makhdumi, W.Due to its diverse environmental impacts, change in land use/ land cover (LU/LC) has become a global concern. LU/LC change is a critical factor that directly impacts watershed hydrology. The study intends to assess the LU/LC dynamics and their impacts on the streamflow of the Tikur Wuha watershed (TWW) in Ethiopia. LU/LC change was assessed using Landsat images. Each image is classified using a maximum likelihood algorithm of the supervised classification method. The Soil and Water Assessment Tools (SWAT) model were used to examine the impact of LU/LC change on streamflow. The overall accuracy of the LU/LC maps ranged from 77.50 to 87.33%. The findings demonstrated an increase in built-up and cultivated areas and a decrease in shrubland, grassland, swampy areas, and water bodies. The calibration and validation results showed a reasonable performance rate of the SWAT model. The LU/LC changes, which occurred between 1978 and 2017, had increased the average annual streamflow by 8.12%, 9.78%, and 14.77% between 1978 and1988, 1978 and 1998, 1978 and 2017. The Kiremt season flow increased by 9.80% during the first half of the study period (1978–1998) and by 5.41% in the second half (1998–2017). It is risen by 15.74% in 2017 compared to in 1978. The observed changes in the streamflow have resulted from LU/LC changes in the TWW. The study suggests that quick action is required to manage the LU/LC shift and execute land use planning to ensure water availability in the watershed. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Item Addressing Spatial Variability in Estimating Cover Management Factor of Soil Erosion Models using Geoinformatics: A Case Study of Netravati Catchment, Karnataka, India(SAGE Publications Ltd, 2025) Makhdumi, W.; R, S.H.; Dwarakish, G.S.; Pai, J.Soil erosion is a significant threat to both agricultural productivity and natural resources. The most commonly applied soil erosion models are the Universal Soil Loss Equation (USLE) and its revised version (RUSLE), which rely heavily on the Cover Management factor (C factor) as a critical input parameter. This study aims to improve the accuracy of C factor estimates for the Netravati catchment present in the Western Ghats and Coastal Plains of India by using the Random Forest Algorithm and Sentinel 2 satellite data. The research examined five commonly used Normalized Difference Vegetation Index (NDVI) based C factor estimating equations and found that they inadequately represented local vegetation dynamics in the study area. To address this, a high-resolution Land Use Land Cover (LULC) map was generated using the Random Forest algorithm and in situ C factor values were assigned to LULC classes. A regression analysis between Sentinel 2-derived NDVI and the actual C factor yielded a novel equation. The proposed equation estimated C factor values ranging from 0.056 to 0.99, which closely align with actual observations and outperforming existing methods. The model’s performance was evaluated using statistical metrics, including a correlation coefficient of 0.984, mean absolute error of 0.048, root mean square error of 0.058, and Kling-Gupta efficiency of 0.921, indicating superior accuracy compared to existing methods. This study presents a region-specific approach for estimating the C factor, serving as a reliable tool for improving soil erosion predictions in the Western Ghats and Coastal Plains of India. Apart from highlighting the need for local parameterisation, the results have important implications for soil conservation planning, erosion risk management, and sustainable land use practices in the region. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).Item Coastal vulnerability assessment of the Kasaragod Coast in Kerala, West Coast of India(Springer Nature, 2025) N A, A.; Makhdumi, W.; G S, D.; Pai, J.Coastal zones are transition zones between the land and sea, characterised by unique coastal ecosystems and natural resources, making them the focal point of human activities. Vulnerability assessments have been carried out along several coastal zones across the world. These assessments help coastal scientists, engineers, and policymakers prepare plans and devise mitigation measures to safeguard the environment and coastal population against climate change and coastal hazard impacts. The present study evaluates the vulnerability of the Kasaragod coast in Kerala, the west coast of India, due to sea-level rise. Eleven variables, viz. relative sea-level change, mean significant wave height, tidal range, geomorphology, shoreline change rate, regional elevation, coastal slope, population, road/railway networks, tourist sites and land use/land cover are considered in the estimation of the Coastal Vulnerability Index (CVI). The resulting CVI values were categorized into low, moderate, high and very high vulnerability classes. Based on this classification, 41.33% of the Kasaragod sub-district and 13.26% of the Hosdurg sub-district fall under the ‘very high’ vulnerability category. A significant decrease in vulnerability was observed along the Kasaragod sub-district when socioeconomic variables were excluded from the CVI calculation. However, in the Hosdurg sub-district exclusion of the socioeconomic variables led to increased vulnerability along the coast. The vulnerability maps developed in this study provide a crucial tool for identifying highly vulnerable coastal stretches and guiding effective strategies to safeguard the Kasaragod coast and its communities. © The Author(s) 2025.