Browsing by Author "Venkatesh, K."

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Effects of land use and climate change on water scarcity in rivers of the Western Ghats of India
(Springer Science and Business Media Deutschland GmbH, 2021) Sharannya, T.M.; Venkatesh, K.; Mudbhatkal, A.; Muthuvel, M.; Mahesha, A.
This paper assesses the long-term combined effects of land use (LU) and climate change on river hydrology and water scarcity of two rivers of the Western Ghats of India. The historical LU changes were studied for four decades (1988–2016) using the maximum likelihood algorithm and the long-term LU (2016–2075) was estimated using the Dyna-CLUE prediction model. Five General Circulation Models (GCMs) were utilized to assess the effects of climate change (CC) and the Soil and Water Assessment Tool (SWAT) model was used for hydrological modeling of the two river catchments. To characterize granular effects of LU and CC on regional hydrology, a scenario approach was adopted and three scenarios depicting near-future (2006–2040), mid-future (2041–2070), and far-future (2071–2100) based on climate were established. The present rate of LU change indicated a reduction in forest cover by 20% and an increase in urbanized areas by 9.5% between 1988 and 2016. It was estimated that forest cover in the catchments may be expected to halve compared to the present-day LU (55% in 2016 to 23% in 2075), along with large-scale conversion to agricultural lands (13.5% in 2016 to 49.5% in 2075). As a result of changes to LU and forecasted climate, it was found that rivers in the Western Ghats of India might face scarcity of fresh water in the next two decades until the year 2040. However, because of large-scale LU conversion toward the year 2050, streamflow in rivers might increase as high as 70.94% at certain times of the year. Although an increase in streamflow is perceived favorable, the streamflow changes during summer and winter may be expected to affect the cropping calendar and crop yield. The changes to streamflow were also linked to a 4.2% increase in ecologically sensitive wetlands of the Aghanashini river catchment. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
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.
Impact of land use land cover change on run off generation in tungabhadra river basin
(2018) Venkatesh, K.; Ramesh, H.
Streamflow can be affected by a number of aspects related to land use and can vary promptly as those factors change. Urbanization, deforestation, mining, agricultural practices and economic growth are some of the factors related to these land use changes which alter the stream flow. In the present study, the impact of land use land cover change (LULC) on stream flow is studied by using SWAT model for Tungabhadra river basin, located in the state of Karnataka, India. Tungabhadra river originates in the Western Ghats of Karnataka and flows towards north-east and joins the river Krishna. The land use maps of 1993, 2003 and 2018 are used for assessing the stream flow changes with respect to LULC. Calibration and validation of the model for streamflow was carried out using the SUFI-2 algorithm in SWAT-CUP for the years 1983-1993 and 1994-2000 respectively. Statistical parameters namely Coefficient of Determination (R2) & Nash-Sutcliffe (N-S) were used to assess the efficiency and performance of the SWAT model. It was found that the observed and simulated streamflow values are closely matching, which in turn projects that the model results are acceptable. The calibrated model was used for simulation of future dynamic land use scenario to assess the impact on streamflow. The results can be used for conservation of water and soil management. � 2018 Authors.
Impact of land use land cover change on run off generation in tungabhadra river basin
(Copernicus GmbH info@copernicus.org, 2018) Venkatesh, K.; Ramesh, H.
Streamflow can be affected by a number of aspects related to land use and can vary promptly as those factors change. Urbanization, deforestation, mining, agricultural practices and economic growth are some of the factors related to these land use changes which alter the stream flow. In the present study, the impact of land use land cover change (LULC) on stream flow is studied by using SWAT model for Tungabhadra river basin, located in the state of Karnataka, India. Tungabhadra river originates in the Western Ghats of Karnataka and flows towards north-east and joins the river Krishna. The land use maps of 1993, 2003 and 2018 are used for assessing the stream flow changes with respect to LULC. Calibration and validation of the model for streamflow was carried out using the SUFI-2 algorithm in SWAT-CUP for the years 1983-1993 and 1994-2000 respectively. Statistical parameters namely Coefficient of Determination (R2) & Nash-Sutcliffe (N-S) were used to assess the efficiency and performance of the SWAT model. It was found that the observed and simulated streamflow values are closely matching, which in turn projects that the model results are acceptable. The calibrated model was used for simulation of future dynamic land use scenario to assess the impact on streamflow. The results can be used for conservation of water and soil management. Â© 2018 Authors.
Modelling stream flow and soil erosion response considering varied land practices in a cascading river basin
(Academic Press, 2020) Venkatesh, K.; Ramesh, H.; Das, P.
[No abstract available]
Performance evaluation of OCR on poor resolution text document images using different pre processing steps
(2015) Naganjaneyulu, G.V.S.S.K.R.; Narasimhadhan, A.V.; Venkatesh, K.
The performance of optical character recognition (OCR) algorithm is poor on low resolution scanned text images. The conventional low pass filters in L2 space can slightly improve the performance. The method of enhancement of poor resolution text images using a low pass signal filtering algorithm in the weighted Sobolev space results in high pass correction similar to un sharp masking. This can further improve the performance of OCR on low resolution text images. In this paper, the performance of a typical OCR system on low resolution scanned text images, is studied without using any preprocessing step, with low pass filtering in L2 space, and compared with low pass filtering in weighted Sobolev space as pre processing steps. � 2014 IEEE.
Performance evaluation of OCR on poor resolution text document images using different pre processing steps
(Institute of Electrical and Electronics Engineers Inc., 2015) Naganjaneyulu, G.V.S.S.K.R.; Narasimhadhan, A.V.; Venkatesh, K.
The performance of optical character recognition (OCR) algorithm is poor on low resolution scanned text images. The conventional low pass filters in L2 space can slightly improve the performance. The method of enhancement of poor resolution text images using a low pass signal filtering algorithm in the weighted Sobolev space results in high pass correction similar to un sharp masking. This can further improve the performance of OCR on low resolution text images. In this paper, the performance of a typical OCR system on low resolution scanned text images, is studied without using any preprocessing step, with low pass filtering in L2 space, and compared with low pass filtering in weighted Sobolev space as pre processing steps. Â© 2014 IEEE.