Faculty Publications
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Item Morphological and thermal properties of maize fiber composites(Korean Fiber Society, 2012) Saravana Bavan, D.; Mohan Kumar, G.C.Maize stalk has become one of the major sources of fibers from the agricultural residues. Use of these fibers as a reinforcement in the polymer is described in this paper. The present work is focused on establishing the properties such as physical, chemical, morphological structure and thermal properties of maize stalk fiber using different characterization techniques. Simple hand layup method was followed for processing the composite material. Chemical treatments of fibers were carried out to study the interaction of fibers with the matrix. The results revealed that maize fibers can also be used as a traditional fiber as reinforcement in a natural fiber reinforced composite materials. © 2012 The Korean Fiber Society and Springer Science+Business Media Dordrecht.Item Streamflow response to land use-land cover change over the Nethravathi River Basin, India(American Society of Civil Engineers (ASCE), 2015) Babar, S.; Ramesh, H.Land use-land cover change (LULC) has considerable impacts on hydrologic response at the watershed level. Quantitative assessment of LULC impacts on runoff generations is vital for water resources development. The soil and water assessment tool (SWAT) model was used to study the effect of LULC change on streamflows. In addition to this, the present study proposed a newly developed flow-routing model called runoff coefficient routing model (RCRM). This new model is simple and requires limited data, such as precipitation, LULC and streamflows as compared to other models, which require meteorological and many more input data. The Nethravathi River basin was selected for testing the RCRM model with the SWAT model to study land use-land cover change on streamflows. The SWAT model and RCRM model have been calibrated for 2001-2005 and validated for 2006-2009 daily data. Results have shown that the simulated streams are well correlated with observed streamflows with a coefficient of correlation (R2) equal to 0.82 in calibration and 0.68 in validation period. Whereas, the RCRM model results have shown R2 of 0.81 and 0.66 in the calibration and validation period. Finally, the SWAT and RCRM results were compared. It is observed that the results of the RCRM model have shown a good agreement with SWAT model results of R2 equal to 0.99 and 0.98, respectively, in the calibration and validation period. The sensitivity analysis was also carried out based on Latin hypercube one factor-at-a-time (LH-OAT) method using the SWAT model and found 11 sensitive parameters out of 28 parameters. Model performance was carried out using the Nash-Sutcliffe model efficiency coefficient (NSE) and found 0.81 for calibration and 0.62 for the validation period in the SWAT model. RCRM has NSE of 0.79 and 0.63. The response of the streamflows for the year 2013 was simulated from the calibrated model. The results showed that the observed streamflows have shown good correlation with simulated streamflows with R2 values of 0.86 and NSE of 0.81. From the results, it is concluded that the runoff shows early response in the year 2013 compared to the year 2003. This is mainly due to changes in LULC, which shows the conversion of forest to agricultural area and increase in built-up area from 2003 to 2013. The effect of LULC change on the hydrological model parameters were calculated and observed a decrease in evapotranspiration (ET) of about 4.5%, an increase in runoff of about 0.9%, and an increase in groundwater of about 1.12%. In conclusion, the proposed RCRM in the present study simulates streamflows at par with the SWAT model with only few input data. Hence, the newly developed RCRM model would be used to study streamflows responses to LULC changes. © 2015 American Society of Civil Engineers.Item GeoDesic-VPC: Spatial partitioning for multi-robot coverage problem(Acta Press journals@actapress.com, 2020) Nair, V.G.; Guruprasad, K.R.In this paper, we address a problem of area coverage using multiple cooperating robots using a “partition and cover" approach, where the area of interest is decomposed into as many cells as the robots, and each robot is assigned the task of covering a cell. While the most partitioning approaches used in the literature in the context of a robotic coverage problem may result in topologically disconnected cells in the presence of obstacles leading to incomplete coverage, we propose to use geodesic distance-based generalization of the Voronoi partition, ensuring that each cell that is allotted for a robot for coverage is a topologically connected region, and hence, achieving a complete coverage. The proposed multi-robot coverage strategy is demonstrated with simulation in MATLAB and V-rep simulator, using two single-robot coverage algorithms reported in the literature, namely boustrophedon decomposition-based coverage and spanning tree-based coverage algorithms. © 2020 SAE International. All rights reserved.Item Design and Development of Single & Dual Resonant Frequency Antennas for Moisture Content Measurement(Springer, 2020) Kumar, P.; Chaturvedi, A.The microstrip antenna is designed for the measurement of soil moisture content for agriculture applications. In this paper, the single and dual-band microstrip antennas are designed, simulated and fabricated. The simulated results are compared and analysed with measured results for both designed for different types of feeds. It is found that the simulated and measured results are similar and better. Therefore, the fabricated antennas can be used for the soil moisture content measurement for agriculture applications. The dual resonant frequency antennas results are better than the single band antenna, it covers wide band thus, and it can be applied for wide applications. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.Item Evaluation of satellite precipitation products in simulating streamflow in a humid tropical catchment of india using a semi-distributed hydrological model(MDPI, 2020) Sharannya, T.M.; Al-Ansari, N.; Deb Barma, S.; Mahesha, M.Precipitation obtained from rain gauges is an essential input for hydrological modelling. It is often sparse in highly topographically varying terrain, exhibiting a certain amount of uncertainty in hydrological modelling. Hence, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. In this study, an attempt was made to evaluate the Tropical Rainfall Measuring Mission (TRMM) and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), employing a semi-distributed hydrological model, i.e., Soil and Water Assessment Tool (SWAT), for simulating streamflow and validating them against the flows generated by the India Meteorological Department (IMD) rainfall dataset in the Gurupura river catchment of India. Distinct testing scenarios for simulating streamflow were made to check the suitability of these satellite precipitation data. The TRMM was able to better estimate rainfall than CHIRPS after performing categorical and continuous statistical results with respect to IMD rainfall data. While comparing the performance of model simulations, the IMD rainfall-driven streamflow emerged as the best followed by the TRMM, CHIRPS-0.05, and CHIRPS-0.25. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) were in the range 0.63 to 0.86, 0.62 to 0.86, and ?14.98 to 0.87, respectively. Further, an attempt was made to examine the spatial distribution of key hydrological signature, i.e., flow duration curve (FDC) in the 30–95 percentile range of non-exceedance probability. It was observed that TRMM underestimated the flow for agricultural water availability corresponding to 30 percent, even though it showed a good performance compared to the other satellite rainfall-driven model outputs. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.Item Optimization modeling for conjunctive use planning in Upper Damodar River basin, India(Elsevier Ltd, 2020) Jha, M.K.; Singh, L.K.; Nayak, G.K.; Chowdary, V.M.Canal irrigated regions often suffer from twin problems of waterlogging and salinity as well as water scarcity in the absence of proper irrigation planning, particularly in developing nations. There is an urgent need to adopt the concept of ‘Conjunctive Use’ in practice for the sustainable management of land and water resources in canal commands. Considering real-world conditions, this study demonstrates a framework for conjunctive use planning using optimization modeling through a case study in the Upper Damodar River basin of Eastern India. A resource optimization model was developed taking into account spatial, seasonal and climatic variability of water supply, crop irrigation requirements and Dynamic Groundwater Reserve (DGWR) as well as considering DGWR as the available groundwater resource, which are unique in this study. The optimization model was solved for ‘Normal’ and ‘Dry’ climatic conditions considering four scenarios that represent optimal conjunctive use plans for four realistic situations. The results of optimization modeling indicated that it is possible to obtain the net annual benefits of Rs. 24818.00 million during ‘Normal’ years and Rs. 14679.00 million during ‘Dry’ years due to the efficient allocation of land and existing water supplies to current cropping patterns. If the available DGWR is fully utilized for irrigation along with the existing surface water supply, these net benefits can be increased by 197% during ‘Normal’ years and 267% during ‘Dry’ years. Thus, the developed optimal conjunctive use plans are promising and reasonable for significantly increasing farmers’ returns even during ‘Dry’ climatic condition. Based on the findings of this study, efficient management strategies could be formulated by the concerned planners/decision makers and practicing engineers to ensure sustainable management of land and water resources in the study area, which in turn can guarantee sustainable agricultural production and water security on a long-term basis. © 2020 Elsevier LtdItem 'RS' and 'GIS' based air quality atlas with integrated land use and land cover change analysis in India(ICE Publishing, 2021) Navalgund, N.; Joshi, K.; Srinikethan, S.; Shet, V.B.; Hosamane, S.N.In this paper, the effect of land use and land cover and the impact of urbanisation on respirable particulate matter (RSPM), sulfur oxide (SO x ) and nitrogen oxide (NO x ) of the Hubli-Dharwad, a Tier II city in India, are correlated based on the trends in air quality observed from 2006 to 2013, population from 1990 to 2010, the number of vehicles between the periods of 2004 and 2013 and urbanisation between the periods of 1975 and 2009. It has been found that urbanisation has increased threefold from 92 km2 in 1975 to 271 km2 in 2009 and the corresponding decrease in agricultural area was from 368.22 to 123.43 km2. The RSPM in the study region is increasing at a rate of 8.9% per year. The study shows that vehicular pollutants are the major cause of air pollution, followed by industries, with the highest RSPM value of 128 ?g/m3 at traffic junctions in the Hubli-Dharwad region in 2013. Based on the trend analysis, the air quality atlas predicted for 2030 shows that the RSPM level in the air will reach 150 ?g/m3, well above the national ambient air quality standards, and will have serious consequences on human health if proper strategies are not undertaken. Owing to the unique geographical setting of Hubli-Dharwad, its future urbanisation will be in a narrow area, which may lead to a severe air pollution problem that needs immediate attention to provide a safe environment. © 2021 ICE Publishing: All rights reserved.Item Assessment of surface soil moisture from ALOS PALSAR-2 in small-scale maize fields using polarimetric decomposition technique(Springer Science and Business Media Deutschland GmbH, 2021) Gururaj, P.; Umesh, P.; Shetty, A.Surface soil moisture knowledge is important, especially in agriculture and irrigation management. Properties of microwave remote sensing like penetration power and longer wavelength facilitate retrieval of surface soil moisture. ALOS PALSAR-2, quad polarized data are used to retrieve surface soil moisture using polarization decomposition techniques in a marginal farmer small-scale maize field. The focus of the study is to explore the utility of ALOS PALSAR-2 in retrieving surface soil moisture using the polarization decomposition technique. The demonstration of the study is carried out in Malavalli village, southern India, an agricultural predominant area. The study involves field soil moisture sampling in synchronous with satellite pass, measuring soil properties, preprocessing of SAR data, polarization decomposition, proportional analysis, regression analysis, model calibration and validation. Van Zyl decomposition gave the highest surface scattering component (43%) and reduced volumetric scattering component compared to Yamaguchi and Freeman–Durden decomposition. Surface scattering component of Yamaguchi decomposition gave a good coefficient of determination (R2 = 0.8029) with field-measured surface soil moisture. The semi-empirical model (SEM) was developed using surface scattering component and depolarization ratio with adjusted R2 = 0.75 at 95% confidence interval. On its comparison with existing soil moisture models, it is observed that the developed model is performing well with RMSE and AEmax of 1.81 and 2.88, respectively. Implying the applicability of ALOS PALSAR-2 in soil moisture retrieval in marginal farmer small-scale maize fields gave satisfactory results of accuracy. © 2021, Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences.Item CPC Algorithm: Exact Area Coverage by a Mobile Robot Using Approximate Cellular Decomposition(Cambridge University Press, 2021) Guruprasad, K.R.; Ranjitha, T.D.A new coverage path planning (CPP) algorithm, namely cell permeability-based coverage (CPC) algorithm, is proposed in this paper. Unlike the most CPP algorithms using approximate cellular decomposition, the proposed algorithm achieves exact coverage with lower coverage overlap compared to that with the existing algorithms. Apart from a formal analysis of the algorithm, the performance of the proposed algorithm is compared with two representative approximate cellular decomposition-based coverage algorithms reported in the literature. Results of demonstrative experiments on a TurtleBot mobile robot within the robot operating system/Gazebo environment and on a Fire Bird V robot are also provided. © 2021 Cambridge University Press. All rights reserved.Item Spatiotemporal Analysis of Compound Agrometeorological Drought and Hot Events in India Using a Standardized Index(American Society of Civil Engineers (ASCE), 2021) Muthuvel, D.; Mahesha, A.Meteorological droughts abetted by hot events could instigate an agricultural drought that eventually affects crop yield. Different types of droughts may coexist or occur in succession. A single index based on one particular variable may not be sufficient to quantify such compound drought events. Therefore, this study embedded drought indexes ofstandardized precipitation index (SPI), standardized soil-moisture index (SSI), and standardized temperature index (STI) with Gaussian copula functions to study compound agrometeorological drought and hot events in India from 1948 to 2014. By standardizing the joint probability of the SPI, SSI, and STI time series, the standardized compound drought and hot index (SCDHI) was developed. The SCDHI values in the monsoon months of different climatic zones have a strong correlation of about 0.95 with other well-established indexes such as the standardized compound event indicator (SCEI), which incorporates SPI and STI, and the multivariate standardized drought index (MSDI), which incorporates SPI and SSI. Based on the areal extent, 1965-1966, 1972, 1987, and 2002 were identified as significant compound drought years in India. The index also identified three successive compound events of the 2012-2014 northest monsoon in the southern peninsular region. A notable increase in the frequency of compound drought and hot events was found post-2000. The case studies of the major drought events and the dependent pattern of SCDHI on its constituent indexes indicate that SCDHI performs well as an indicator of compound agrometeorological and hot events across different climatic regions and in both southwest and northeast monsoons. © 2021 American Society of Civil Engineers.