Morphometric assessment and prioritization of the South India Moyar river basin sub-watersheds using a geo-computational approach

Krishnan, Annaidasan; Ramasamy, Jaganathan

doi:10.1080/24749508.2022.2109819

Cited by 10 publications

(4 citation statements)

References 33 publications

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“…(16,17) . This method has been used to investigate the sub-watersheds vulnerability to various conditions, including runoff, peak flow, soil erosion, etc (18) . Amongst the morphometric parameters, 20 parameters have been considered depending upon their effectiveness rate on the factors as mentioned earlier.…”

Section: Prioritization Of Sub-watersheds Using Morphometric Parametersmentioning

confidence: 99%

“…https://www.indjst.org/ However, sub-watersheds with the highest values for areal parameters have been ranked lowest, suggesting a possible indirect relationship between these two factors (3,(18)(19)(20) . After assigning ranks to all the parameters individually for each sub-watershed, the ranks have been added and then divided by the 20 parameters to find the compound values (Table 4).…”

Section: Prioritization Of Sub-watersheds Using Morphometric Parametersmentioning

confidence: 99%

“…Accordingly, planning and strategies have been initiated to safeguard from excess degradation, particularly soil loss or erosion (8) . Similarly, the present study, therefore, has accomplished the task of providing the final priority by considering the compound factor values generated from morphometry and LULC (3,18) . After finding the averages from these compound values, the integrated ranking has been assigned to each sub-watershed.…”

Section: Integration Of Morphometric Parameters and Lulc Rankingmentioning

confidence: 99%

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Integrated Approach of Morphometric and LULC Parameters for Watershed Prioritization in Pachnoi River Basin, North-East India

Borah,

Bora

2023

IJST

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Objective: This study intends to prioritize the Pachnoi river basin, located in the north eastern part of India, covering an area of 504.54 km 2 . "Prioritization" indicates the arrangement or sorting of the sub-watersheds within a broad watershed depending upon their risk of environmental problems and accordingly the treatment needed to be executed at high-priority areas. Methods: The research adopted an integrated approach combining morphometry and land use/land cover (LULC) parameters. Each morphometric and LULC parameters has been ranked for individual sub-watershed, and thereafter, the averages were determined to generate compound values. Based on compound values determined from the two approaches, rankings have been assigned to each sub-watershed and accordingly, priorities were set. Findings: The Pachnoi is a sixth-order watershed with a dendritic drainage pattern and elongated morphology. Depending upon morphometric analysis, SW1, SW2, and SW3 were grouped under high-priority zones, while SW7, SW8, SW9 and SW10 were categorised as high-risk regions based on LULC assessment. Integration of both the approaches has offered significant results, with SW4, SW7, SW8 and SW10 covering an area of 300 km 2 (59.46%) within high-risk areas. It implies that these micro-watersheds are more prone to environmental risk factors such as illegal logging, soil erosion, bank erosion, drastic land use change and runoff instability that requires urgent attention. Novelty: The novelty lies in adopting an integrated approach using geospatial techniques that would certainly enhance natural resource conservation. The high-risk sub-watersheds facing severe environmental problems necessitates prompt strategy implementation to enhance policymakers and stakeholders in drafting a plan for an integrated watershed management program.

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Section: Prioritization Of Sub-watersheds Using Morphometric Parametersmentioning

confidence: 99%

Section: Prioritization Of Sub-watersheds Using Morphometric Parametersmentioning

confidence: 99%

Section: Integration Of Morphometric Parameters and Lulc Rankingmentioning

confidence: 99%

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Integrated Approach of Morphometric and LULC Parameters for Watershed Prioritization in Pachnoi River Basin, North-East India

Borah,

Bora

2023

IJST

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“…The Bhavani basin in South India documented by many researchers (Balasubramanian et al, 2017;Gobinath et al, 2020;Krishnan & Ramasamy, 2022;Prasannakumar et al, 2011;Saravanan et al, 2021). The basin has more than six reservoirs, and the major reservoir is the Bhavani Sagar dam, which is used for multipurpose, whereas the remaining reservoirs are only used for generating hydropower.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Impacts of Future Land Use Land Cover and Climate Change on the Water Balance Components and Sediment Yield of The Bhavani Watershed in India

Kamaraj,

Rangarajan

2023

Preprint

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This study aims to investigate land use/land cover (LULC) and climate change for a better understanding of the hydrological processes of the Bhavani watershed, India. The ANN-CA model, which is based on artificial neural networks and cellular automata, is utilized for the simulation and prediction of LULC. Five criteria, including DEM, slope, aspect, distance from the road, and distance from existing built-up areas, were used as exploratory data for the learning process of the ANN-CA model. The calibrated LULC maps for 2020 showed a high level of agreement, with a kappa index of 0.76 and a percentage of correctness 78.23%. The model was then used to predict LULC changes for the years 2030, 2040, and 2050 and integrated these predictions with different future climate scenarios (CMIP6 RCP4.5 and RCP8.5) to estimate changes in hydrological components using the soil and water assessment tool (SWAT). The average sediment yield ranges from 9.86 to 14.79 ton/ha/year between 2000 and 2020, which is attributed to the changes in LULC. Additionally, the combination of climate change scenarios and changes in LULC resulted in the projected increases in annual average soil losses by 23.90 and 20.18 ton/ha/year in 2030; 18.22 and 25.07 ton/ha/year in 2040 and 23.87 and 23.54 ton/ha/year in 2050. Among the 26 sub-watersheds, SW-07, SW-09, SW-21, SW-22, SW-25, and SW-26, showed high sediment yield in the watershed. The model calibration and validation values of R2, NSE, PBIAS, and RSR showed that the predicted flow and sediment yield results are in good agreement with the observed values.

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Climate Change and Cyclones: Its Associated Consequences in Tamil Nadu Coastal Cities of Chennai and Thoothukudi

Krishnan,

Ramasamy

2024

Climate Change, Vulnerabilities and Adaptation

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Morphometric assessment and prioritization of the South India Moyar river basin sub-watersheds using a geo-computational approach

Cited by 10 publications

References 33 publications

Integrated Approach of Morphometric and LULC Parameters for Watershed Prioritization in Pachnoi River Basin, North-East India

Integrated Approach of Morphometric and LULC Parameters for Watershed Prioritization in Pachnoi River Basin, North-East India

Assessing the Impacts of Future Land Use Land Cover and Climate Change on the Water Balance Components and Sediment Yield of The Bhavani Watershed in India

Climate Change and Cyclones: Its Associated Consequences in Tamil Nadu Coastal Cities of Chennai and Thoothukudi

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