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[Adopted from a paper recently published by Dr. T. Drought analysis under El Nino Southern Oscillation]
One of the major focus areas : Precipitation Estimation and Analysis. Link to publications: click here
Ramesh S. V. Teegavarapu, Rahul Kumar, Priyank Sharma, Tibebe Dessalegne, Operational Condition Indices for Coastal Hydraulic Structures with Discharge Capabilities. Journal of Hydrologic Engineering, 30(1), 2024. https://doi.org/10.1061/JHYEFF.HEENG-6302
Ramesh S. V. Teegavarapu, Chandra Pathak, David Curtis, Sanjaya Kumar Yadav, Anant Patel, Ayushi Panchal. Role of Ensemble-based Forecasting Methods in Reservoir Operations: Issues and Implementation Challenges. Journal of Hydrologic Engineering, 2025. In Print.
Anant Patel, Sanjay M. Yadav, Ramesh S.V. Teegavarapu. Enhancing Real-time Flood Forecasting and Warning System by Integrating Ensemble Technique and Hydrologic Model Simulations. Journal of Water and Climate Change, 24(2): 397-415. https://doi.org/10.2166/wcc.2024.052
Sandipan Paul, Priyank J. Sharma, Ramesh S.V. Teegavarapu. Spatial Assessment of The Reproducibility of Indian Summer Monsoon Rainfall Regimes in Multiple Gridded Rainfall Products. Scientific Reports, 14, 29269, 2024. https://doi.org/10.1038/s41598-024-75320-5
Sandipan Paul, Priyank J. Sharma, Ramesh S.V. Teegavarapu. Rain Event Detection and Magnitude Estimation during Indian Summer Monsoon: Comprehensive Assessment of Gridded Precipitation Datasets Across Hydroclimatically Diverse Regions. Atmospheric Research, 313, https://doi.org/10.1016/j.atmosres.2024.107761
Sandipan Paul, Priyank J. Sharma, Ramesh S.V. Teegavarapu. Indian Summer Monsoon Rainfall Characteristics Derived from Multiple Gridded Datasets: A Comparative Assessment. International Journal of Climatology, 45(2), e8708, 2024. [Impact Factor: 3.61]. https://doi.org/10.1002/joc.8708
Achala Singh, Priyank, J. Sharma, Ramesh S. V. Teegavarapu. Understanding Non-Stationarity Patterns in Basin-Scale Hydroclimatic Extremes, International Journal of Climatology, 44(11), 3867-3887. 2024. [Impact Factor: 3.61]. https://doi.org/10.1002/joc.8557
Hao Chen, Yuxue Guo, Saihua Huang, Yue-Ping Xu, Ramesh S. V. Teegavarapu, Assessing the implications of climate variability for global baseflow and streamflow components. Nature Water. Under review. 2024.
Hao Chen, Bingjiao Xu, He Qiu, Saihua Huang, Ramesh S. V.Teegavarapu, Yue-Ping Xu, Yuxue Guo, Hui Nie, Huawei Xie. Adaptive Assessment of Reservoir Scheduling To Hydrometeorological Comprehensive Dry And Wet Evolution In A Multi-Reservoir Region of Southeastern China. Journal of Hydrology. 648, 2024. [Impact Factor: 5.9]. https://doi.org/10.1016/j.jhydrol.2024.132392
Hao Chen, Saihua Huang, Yue-Ping Xu, Ramesh S. V. Teegavarapu, Yuxue Guo, Hui Nie, Huaxwei Xie, Using Baseflow Ensembles for Hydrologic Hysteresis Characterization in Humid Basins in Southeastern China. Water Resources Research, 2024. [Impact Factor: 5.4]. https://doi.org/10.1029/2023WR036195
Mahdi Zarei; Reza Ghazavi; Khodayar Abdollahi; Roberto Ranzi; Ramesh S.V. Teegavarapu; Stefano Barontini. Spatiotemporal Variation of Water Balance Components In Mashhad Catchment, Iran: Investigating The Impact Of Changes In Climatic Data And Land Use. Water Supply.24(2):397–415, 2024, https://doi.org/10.2166/ws.2024.018
Tucker Hindle, Frederick Bloetscher, Anthony Abbate, Jeffery Huber, Weibo Liu, Daniel E. Meeroff, Diana Mitsova, S. Nagarajan, Colin Polsky, Hongbo Su, Ramesh S. V. Teegavarapu, Zhixiao Xie, Yan Yong, and Caiyun Zhang.Scalability of CASCADE 2001: GIS-Based Flood Risk Screening Tool to Support Watershed Master Planning. Applied Research Periodicals, 2024, 2(8), 26-41. https://doi.org/10.63002/asrp.28.562
Stephanya S. Lotero, Frederick Bloetscher, other authors, Ramesh S. V. Teegavarapu, Incorporating Flood Inundation to Flood Risk Modeling. European Journal of Applied Sciences, 12 No. 4 (2024). 241–259. https://doi.org/10.14738/aivp.124.17312
Hao Chen, Saihua Huang, Yue-Ping Xu, Ramesh S. V. Teegavarapu, Yuxue Guo, Hui Nie, Huawei Xie, Luqi Zhang. River Ecological Flow Early Warning Forecasting Using Baseflow Separation and Machine Learning in The Jiaojiang River Basin, Southeast China. Science of Total Environment, 882,163571,2023. [Impact Factor: 8.2]. https://doi.org/10.1016/j.scitotenv.2023.163571
Ramesh S. V. Teegavarapu and Priyank J. Sharma, Prem Lal Patel, Frequency-based Performance Measure for Hydrologic Model Evaluation, Journal of Hydrology, 608, 2022. [Impact Factor: 5.9]. https://doi.org/10.1016/j.jhydrol.2022.127583
Ramesh S. V. Teegavarapu and Priyank J. Sharma, Non-Overlapping Block Stratified Random Sampling Approach for Assessment of Stationarity, Journal of Hydrologic Engineering, ASCE, 2021.Selected for Editor’s Choice recognition (https://ascelibrary.org/topic/badge/ed-choice). https://doi.org/10.1061/(ASCE)HE.1943-5584.0002098
Ramesh S. V. Teegavarapu and Priyank J. Sharma, Response to the discussion on Non-Overlapping Block Stratified Random Sampling Approach for Assessment of Stationarity, Journal of Hydrologic Engineering, ASCE, 26(7) 2022. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002098
Monica Rajkumar, Sudhagar Nagarajan, Ramesh S. V. Teegavarapu, Peter DeWitt, Shoreline and Coastline Extraction using Multi-Spectral UAS Imagery, Surveying and Land Information Science Journal, AAGS, 81(2), 127-143 (17), 2022. https://www.ingentaconnect.com/contentone/aags/salis/2022/00000081/00000002/art00005
Hao Chen, Saihua Huang, Yue-Ping Xu, Ramesh S. V. Teegavarapu, Yuxue Guo, Jingkai Xie, Nie Hui. Quantitative Assessment of Impact of Climate Change And Human Activities on Streamflow Changes Using An Improved Three-Parameter Monthly Water Balance Model, Remote Sensing, 14(17), 4411, 2022. [Impact Factor: 4.20]. https://doi.org/10.3390/rs14174411
Ramesh S. V. Teegavarapu and Priyank J. Sharma, Influences of Climate Variability on Regional Precipitation and Temperature Associations, Hydrological Sciences Journal, 66(16), 2395–2414, 2021. https://doi.org/10.1080/02626667.2021.1994976
Hao Chen, Yue-Ping Xu, Ramesh S. V. Teegavarapu, Yuxue Guo, Jingkai Xie. Assessing Different Roles of Baseflow and Surface Runoff for Long-Term Streamflow Forecasting In Southeastern China, Hydrological Sciences Journal, 66(16), 2312–2329, 2021. https://doi.org/10.1080/02626667.2021.1988612
Priyank J. Sharma and S. V. Teegavarapu, Influences of Local Hydroclimatology and Teleconnections on Florida’s Precipitation and Temperature Variability, In print. Hydrological Processes, 35(9), 2021. https://doi.org/10.1002/hyp.14347
Hao Chen, Ramesh S. V. Teegavarapu, Yue-Ping Xu, Oceanic-Atmospheric Variability Influences on Baseflows in the Continental United States, Water Resources Management, 3005–3022, [Impact Factor: 3.9]. https://doi.org/10.1007/s11269-021-02884-6
Caiyun Zhang, Hongbo Su, Tiantian Li, Gerardo Rojas, Tucker Hindle, Weibo Liu, Diana Mitsova, Sudhagar Nagarajan, Zhixiao Xie, Ramesh S. V. Teegavarapu, Daniel Meeroff , Fred Bloetscher, Yan Yong, Modeling and Mapping High Groundwater Table for a Coastal Region in Florida using Lidar DEM Data. Groundwater. 59(2), 190-198, 2021, (Top cited article in 2021 and 2022) https://doi.org/10.1111/gwat.13041
Frederick Bloetscher, Anthony Abbate, Jeffery Huber, Wiebo Liu, Daniel E. Meeroff, Diana Mitsova, S. Nagarajan, Colin Polsky, Hongbo Su, Ramesh S. V. Teegavarapu, Zhixiao Xie, Yan Yong, Caiyun Zhang, Richard Jones, Glen Oglesby, Eva Suarez, Jared Weaver, Mushfiqul Hoque, and Tucker Hindle. Establishing a framework of a watershed-wide screening tool to support the development of watershed-based flood protection plans for low-lying coastal communities, Journal of Infrastructure, Policy, and Development, 1273, 5(1), 2021. https://doi.org/10.24294/jipd.v5i1.1273
Frederick Bloetscher, Gerardo Rojas, Anthony Abbate, Tucker Hindle, Jeffery Huber, Richard Jones, Weibo Liu, Daniel Eduardo Meeroff, Diana Mitsova, Sudhagar Nagarajan, Glen Oglesby, Colin Polsky, Hongbo Su, Eva Suarez, Ramesh S. V. Teegavarapu, Jared Weaver, Zhixiao Xie, Yan Yong, Caiyun Zhang. A Framework for a Subwatershed-Scale Screening Tool to Support Development of Resiliency Solutions and Flood Protection Priority Areas in a Low-Lying Coastal Community. Journal of Geoscience and Environment Protection, 9(10), 2021. https://www.scirp.org/journal/paperinformation?paperid=112831
Ramesh S. V. Teegavarapu, Precipitation Imputation using Probability Space-based Weighting Methods. Journal of Hydrology, 2020. https://doi.org/10.1016/j.jhydrol.2019.124447 [Impact Factor: 5.9].
Aneesh Goly, Ramesh S. V. Teegavarapu, Optimization, and Variants of Quantile Mapping -based Methods for Bias Corrections of Downscaled Precipitation Data. Journal of Hydrologic Engineering, ASCE, 25(7), 2020. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001926
Subash Yeggina, S. V. Teegavarapu, Sekhar M., and Satya Prakash. Evaluation and Bias Corrections of Gridded Precipitation Data for Hydrologic Modeling Support in Kabini River Basin, India, Journal of Theoretical and Applied Climatology,140,1495–1513, 2020. https://doi.org/10.1007/s00704-020-03175-7
Hao Chen, S. V. Teegavarapu, Spatial and Temporal Variability in Baseflow Characteristics across the Continental United States, Journal of Theoretical and Applied Climatology, 143, 1615–1629, 2020. https://doi.org/10.1007/s00704-020-03481-0
Marco Arrieta-Castro, Adriana Donado-Rodríguez, Fausto Canales, Guillermo J. Acuña, Ramesh S. V. Teegavarapu, Analysis of Streamflow Variability and Trends in the Meta River, Colombia, Water, 12(5), 1451, 2020. https://doi.org/10.3390/w12051451
Evengalos I. Kaisar, Ramesh S. V. Teegavarapu, Elizabeth Gunderson, Data Envelopment Analysis Model for Assessment of Safety and Security of Intermodal Transportation Facilities, Journal of Traffic and Transportation Engineering, 2019. 7, 191-205. DOI:10.17265/2328-2142/2019.05.001
Subash Yeggina, Ramesh S. V. Teegavarapu, Sekhar Muddu, A Conceptually Superior Variant of Shepard’s Method with Modified Neighborhood Selection for Precipitation Interpolation, International Journal of Climatology, 39(12), 4627-4647, 2019. https://doi.org/10.1002/joc.6091
Hao Chen, S. V. Teegavarapu, Comparative Analysis of Four Baseflow Separation Methods in the South Atlantic-Gulf Region of the U.S., Water, 12(1), 120, 2019. https://doi.org/10.3390/w12010120
Ramesh S. V. Teegavarapu, Exploring Geometric Patterns in Streamflow Time Series: Utility for Forecasting? Hydrology Research, 49(6),1724-1739, 201 https://doi.org/10.2166/nh.2018.127
Ramesh S. V. Teegavarapu, Singaiah Chintalapudi, Ricardo Brown, Chandra Pathak, Optimal Spatial Interpolation and Data-Driven Methods for Filling Missing Rain Gauge Records using Radar-based Precipitation Estimates, Journal of Environmental Informatics, 2019. Tentatively accepted.
Fahad K. Khadim, Ramesh S. V. Teegavarapu, Optimal Interventions for Flood Control, Drainage, and Irrigation Project Improvements, Hydrological Sciences Journal, 65(3), 427–441, https://doi.org/10.1080/02626667.2019.1701191.
Sina Borzooei, G. Miranda, Ramesh S. V. Teegavarapu, G. Scibilia, L. Meucci, C. Zanetti, Assessment of Weather-based Influent Scenarios for a Water Resource Recovery Facility: Application of Pattern Recognition Technique, Journal of Environmental Management. 2019. 242, 450-456. [Impact Factor: 8.0]. https://doi.org/10.1016/j.jenvman.2019.04.083
Sina Borzooei, Ramesh S. V. Teegavarapu, Soroush Abolfathi, Eugenio Lorenzi, Maria Chiara Zanetti, Data Mining Application in Assessment of Weather-based Influent Scenarios for a WWTP: Getting the Most out of plant Historical Data. Water, Air and Soil Pollution, 230, 5, https://doi.org/10.1007/s11270-018-4053-1
Ramesh S. V. Teegavarapu, Aneesh Goly. Optimal Selection of Predictor Variables in Statistical Downscaling Models of Precipitation, Water Resources Management, 32(6), 1969-1992, 2018. [Impact Factor: 3.9]. https://doi.org/10.1007/s11269-017-1887-z
Ramesh S. V. Teegavarapu and Singaiah Chintalapudi, Incorporating Influences of Shallow Groundwater Conditions in Curve Number-based Runoff Estimation Methods, Water Resources Management, 32, 4313–4327, [Impact Factor: 3.9]. https://doi.org/10.1007/s11269-018-2053-y
Ramesh S. V. Teegavarapu, Ala Aly, Chandra S. Pathak, Jon Ahlquist, Henry Fuelberg, J Hood, Infilling Missing Precipitation Records using Variants of Spatial Interpolation and Data-Driven Methods: Use of Optimal Weighting Parameters and Nearest Neighbor-based Corrections, 2017. International Journal of Climatology. 38(2), 776-793. [Impact Factor: 3.61]. https://doi.org/10.1002/joc.5209
Carlos Galvão, Young-Oh Kim, Elpida Kolokytha, Arpita Mondal, Pradeep P. Mujumdar, Daisuke Nohara, Satoru Oishi, Roberto Ranzi, Ramesh S V. Teegavarapu, The Contribution of IAHR’s (International Association for Hydro-Environment Engineering and Research) Communities of Water Management and Climate Change Towards the Sustainable Development Goals, Special Issue of Hydrolink, 3, 77-79, 2017. Equal contribution from all authors. Authors’ names arranged in alphabetical order. https://hdl.handle.net/20.500.11970/109373
Ramesh S. V. Teegavarapu and Anurag Nayak. Evaluation of Long-term Trends in Extreme Precipitation: Implications of Infilled Historical Data and Temporal-Window based Analysis, Journal of Hydrology, 2017. 550, 614-634. [Impact Factor: 5.9] https://doi.org/10.1016/j.jhydrol.2017.05.030
Tigstu, Dullo, A. Kalyanapu and Ramesh S. V. Teegavarapu, Evaluation of Changing Characteristics of Temporal Rainfall Distribution within 24-hour Duration Storms and their Influences on Peak Discharges: A Case Study of Asheville, North Carolina, ASCE Journal of Hydrologic Engineering, 22(11), 2017. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001575
Chandra S. Pathak, S. V. Teegavarapu, D. Curtis and C. Collier, Special Issue on Radar Rainfall and Operation Hydrology, Journal of Hydrologic Engineering, ASCE., 22(5), 2017 https://doi.org/10.1061/(ASCE)HE.1943-5584.0001533
Ranzi R., G. Nalder, A.A. Abdalla, J. Ball, G.S. De Costa, C. Galvão, Y.Jia,Y.O. Kim, E. Kolokytha, S.I. Lee, E. Nakakita, V.T.V. Nguyen, A. Paquier, P.L. Patel, M.A. Peviani, Ramesh Teegavarapu, Summary of Recommendations for Policymakers on Adaption to Climate Change In Water Engineering. Hydrolink, ISSN: 1388-3445, International Association for Hydro-Environment Engineering and Research (IAHR), 3, 93-95, 2015. Equal contribution from all authors. Authors’ names are arranged in alphabetical order.
Ramesh S. V. Teegavarapu, Aneesh Goly and Qinglong Wu, Comprehensive Framework for Assessment of Radar-based Precipitation Data Estimates, Journal of Hydrologic Engineering, ASCE, 22(5), 2015, E4015002. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001277
Chandra S. Pathak, Ramesh S. V. Teegavarapu, Chris Olson, Abhishek Singh, Wasantha Lal, Ceyda Polatel, Vahid Zahraeifard, and Sharika Senarath, Uncertainty Issues and Proposed Resolutions on Use of Uncertainty Analyses in Hydrologic/Hydraulic Modeling, Journal of Hydrologic Engineering, ASCE, 2015, 20(10), 02515003. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001231
Ramesh S. V. Teegavarapu, Chandra S. Pathak, John R. Mecikalski, and Jayanthi Srikishen, Optimal Solar Radiation Sensor Network Design using Spatial and Geostatistical Analyses, Journal of Spatial Science. 61(1), 69–97, https://doi.org/10.1080/14498596.2015.1051147
Pradeep Behera and Ramesh S. V. Teegavarapu, Optimization of a Regional Stormwater Quality Management Pond System, Water Resources Management. 29, 1083–1095, 2015. [Impact Factor: 3.9] https://doi.org/10.1007/s11269-014-0862-1
Ramesh S. V. Teegavarapu and S. P. Simonovic; Simulation of Multiple Hydropower Reservoir Operations Using System Dynamics Approach, Water Resources Management. Springer Publications. 2014. 28:1937–1958. [Impact Factor: 3.9] https://doi.org/10.1007/s11269-014-0586-2
Ramesh S. V. Teegavarapu, Statistical Corrections of Spatially Interpolated Precipitation Estimates, Hydrological Processes, 28(11), 3789–3808, https://doi.org/10.1002/hyp.9906
Aneesh Goly and Ramesh S. V. Teegavarapu, Individual and coupled Influences of AMO and ENSO on Regional Precipitation Characteristics and Extremes, Water Resources Research, 2014. 50. 50(6), 4686-4709, [Impact Factor: 4.6] https://doi.org/10.1002/2013WR014540
Aneesh Goly, Ramesh S. V. Teegavarapu, Arpitha Mondal, Evaluation of Statistical Downscaling Models for Monthly Precipitation in Florida, Earth Interactions, 2014. [Impact Factor: 1.6] DOI: 10.1175/EI-D-14-0024.1
Ramesh S. V. Teegavarapu, Missing Precipitation Data Estimation Using Optimal Proximity Metric-based Imputation, Nearest Neighbor Classification and Cluster-based Interpolation Methods, Hydrological Sciences Journal, 59(11), 2009–2026, 2013. [Impact Factor: 2.8]. https://doi.org/10.1080/02626667.2013.862334
Ramesh S. V. Teegavarapu, Climate Change-Sensitive Hydrologic Design under Uncertain Future Precipitation Extremes, Water Resources Research, 49(11), 7804-7814, 2013. [Impact Factor: 4.6] https://doi.org/10.1002/2013WR013490
Ramesh S. V. Teegavarapu, Aneesh Goly, and Jayantha Obeysekera, Influences of Atlantic Multi-Decadal Oscillation on Regional Precipitation Extremes, Journal of Hydrology, 495, 2013, 74–93.[Impact Factor: 5.9] https://doi.org/10.1016/j.jhydrol.2013.05.003
Ramesh S. V. Teegavarapu, Andre Ferreira, and S. P. Simonovic, Fuzzy Multi-Objective Models for Optimal Operation of a Hydropower System, Water Resources Research, 49(6), 3180-3193, 2013, [Impact Factor: 4.6] https://doi.org/10.1002/wrcr.20224
Ramesh S. V. Teegavarapu, Spatial Interpolation using Non-linear Mathematical Programming Models for Estimation of Missing Precipitation Records, Hydrological Sciences Journal, 57(3), 383-406, 2012. https://doi.org/10.1080/02626667.2012.665994
Andre Ferreira and Ramesh S. V. Teegavarapu, Partial Constraint Satisfaction Approaches for Optimal Operation of a Hydropower System, Engineering Optimization, 44(9), 1073-1093, 2012. https://doi.org/10.1080/0305215X.2011.632007
Andre Ferreira and Ramesh S. V. Teegavarapu, Optimal and Adaptive Operation of a Hydropower System with Unit Commitment and Water Quality Constraints, Water Resources Management, 26:707–732, 2012. [Impact Factor: 3.9] https://doi.org/10.1007/s11269-011-9940-9
Ramesh S. V. Teegavarapu, Tadesse Meskele and Chandra Pathak, Geo-Spatial Grid-based Transformation of Multi-Sensor Precipitation using Spatial Interpolation Methods, Computers and Geosciences, 40, 28-39, 2012. [Impact Factor: 4.2] https://doi.org/10.1016/j.cageo.2011.07.004
Ramesh S. V. Teegavarapu, Modeling Climate Change Uncertainties in Water Resources Management Models, Environmental Modeling and Software, 25(10), 1261-1265, 2010. [Impact Factor: 5.22]. https://doi.org/10.1016/j.envsoft.2010.03.025
Ramesh S. V. Teegavarapu, Estimation of Missing Precipitation Records Integrating Surface Interpolation Techniques and Spatio-Temporal Association Rules, Journal of HydroInformatics, 11(2), 133–146, 2009. https://doi.org/10.2166/hydro.2009.009
Mohammad Tufail, Lindell Ormsbee, Ramesh S. V. Teegavarapu, Artificial Intelligence-Based Inductive Models for Prediction and Classification of Fecal Coliform in Surface Waters, Journal of Environmental Engineering, ASCE, 2008, 789-799. https://doi.org/10.1061/(ASCE)0733-9372(2008)134:9(789)
Ramesh S. V. Teegavarapu, Use of Universal Function Approximation in Variance-dependent Interpolation Technique: An Application in Hydrology, 332, 16-29, Journal of Hydrology, 2007. [Impact Factor: 5.9] https://doi.org/10.1016/j.jhydrol.2006.06.017
Ramesh S. V. Teegavarapu, Mohammad Tufail and Lindell Ormsbee, Optimal Functional Forms for Estimation of Missing Precipitation Records, Journal of Hydrology, 2009, 374 (2009) 106–115. [Impact Factor: 5.9] https://doi.org/10.1016/j.jhydrol.2009.06.014 In the GP Bibliography database:http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/RameshSVTeegavarapu.html
Amin Elshorbagy, Ramesh S. V. Teegavarapu, and Lindell Ormsbee, Assessment of Pathogen Pollution in Watersheds using Object-Oriented Modeling and Probabilistic Analysis, Journal of Hydroinformatics, 7, 51-63, https://doi.org/10.2166/jh.2006.012
Ramesh S. V. Teegavarapu and V. Chandramouli, Improved Weighting Methods, Deterministic and Stochastic Data-driven Models for Estimation of Missing Precipitation Records, Journal of Hydrology, 191-206, 312, 2005. https://doi.org/10.1016/j.jhydrol.2005.02.015
The original methods developed in this study are used in several studies worldwide. More than 500 citations of this work.1
Ramesh S. V. Teegavarapu, Anil Tangirala and Lindell Ormsbee, Development of Water Quality Management Alternatives for a Nutrient Impaired Stream using System Dynamics Simulation, Journal of Environmental Informatics, 5(2), 73-81, 2005. [Impact Factor: 10.22] https://api.semanticscholar.org/CorpusID:110478964
Ramesh S. V. Teegavarapu and Amin Elshorbagy, Fuzzy Set-Based Error Measure for Hydrologic Model Evaluation, Journal of Hydroinformatics, 7, 199-208, 2005. https://doi.org/10.2166/hydro.2005.0017
Amin Elshorbagy, Ramesh S.V. Teegavarapu and Lindell Ormsbee, Total Daily Maximum Load (TMDL) Approach to Water Quality Management: Concepts, Issues and Applications Canadian Journal of Civil Engineering (CJCE), 32(2), 442-448, 2005. https://doi.org/10.1139/l04-107
Amin Elshorbagy, Ramesh S.V. Teegavarapu and Lindell Ormsbee, Framework for Assessment of Relative Pollutant Loads with Limited Data, Journal of IWRA, Water International, 30(3), 350-355, 2005. [Impact Factor: 2.6] https://doi.org/10.1080/02508060508691892
Ramesh S. V. Teegavarapu and S. P. Simonovic; Optimal Operation of Water Resource Systems Using Simulated Annealing, Water Resources Management, Journal, Vol 16, pp 401 – 428, 2003. [Impact Factor: 3.9] https://doi.org/10.1023/A:1021993222371
Ramesh S. V. Teegavarapu, Training Neural Networks to Perform Rainfall Disaggregation, Journal of Hydrologic Engineering, Vol 4, July/August, 342, ASCE, 2002. https://doi.org/10.1061/(ASCE)1084-0699(2002)7:4(342)
Ramesh S. V. Teegavarapu+ and S. P. Simonovic; Short-term Operation Model for Coupled Hydropower Reservoirs, Journal of Water Resources Planning and Management, ASCE, Vol. 126, No.2, pp 98 – 106, 2000. [Impact Factor: 3.0] https://doi.org/10.1061/(ASCE)0733-9496(2000)126:2(98)
Ramesh S. V. Teegavarapu and S. P. Simonovic; Modeling Uncertainty in Reservoir Loss Functions using Fuzzy Sets, Water Resources Research, Vol 35, No.9, pp 2815 – 2823, 1999. [Impact Factor: 4.6] https://doi.org/10.1029/1999wr900165
P. Mujumdar and Ramesh S. V. Teegavarapu; A Short-Term Reservoir Operation Model for Multi-crop Irrigation; Hydrological Sciences Journal, 43(3), pp 479 – 494, June 1998. https://doi.org/10.1080/02626669809492139
P. Mujumdar and Ramesh S. V. Teegavarapu; Real-time Reservoir Operation for Irrigation; Water Resources Research, Vol. 33, No.5, pp 1157 – 1164, May 1997. [Impact Factor: 4.6] https://doi.org/10.1029/96WR03907
Ramesh S. V. Teegavarapu and P. P. Mujumdar; Stochastic Models for Reservoir Planning and Operation, Hydrology Review, Vol. 8, No.1, pp 20 – 28, June 1993.
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Book Mini Chapters/Articles
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Sina Borzooei, Ramesh S. V. Teegavarapu, Soroush Abolfathi, Youri Amerlinck, Ingmar Nopens, Maria Ch. Zanetti, Impact Evaluation of Wet-Weather Events on Influent Flow and Loadings of a Water Resource Recovery Facility. UDM: International Conference on Urban Drainage Modeling, UDM 2018, in New Trends in Urban Drainage Modeling, Ed. Giorgio Mannina, (part of Green Energy and Technology book Series), Springer, 2018. 706-711.https://link.springer.com/chapter/10.1007/978-3-319-99867-1_122 https://doi.org/10.1007/978-3-319-99867-1_122
Ramesh S.V. Teegavarapu and Chandra Pathak, Development of Optimal Z-R Relationships, Weather Radar, and Hydrology, International Association of Hydrological Sciences (IAHS) Red Book, United Kingdom, 351, 75-80. 2012. ISBN 978-1-907161-26-1, 672.
Scarlatos P., Kaisar E., and S. V. Teegavarapu, Modeling, and Simulation of Catastrophic Events Affecting Critical Infrastructure Systems, Mathematical Methods, and Applied Computing, MMACTEE’09: Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering. Vol. 3, 2009, pp. 334-346. ISBN:978-960-474-124-3
Ramesh S.V. Teegavarapu and S. P. Simonovic; Optimal Operation of Water Resource Systems: Trade-offs between Modeling and Practical Solutions, Integrated Water Resources Management, International Association of Hydrological Sciences (IAHS) Red Book, 272, 2002, 257 – 262, International Association of Hydrological Sciences, United Kingdom (UK). ISBN: 978-1-901502-71-8
Ramesh S. V. Teegavarapu et al.; A new Error Statistic for Performance Evaluation of Models in Hydrology, Volume 1, # 47, Developments in Water Science, Computational Methods in Water Resources, Editors: S. M. Hassanizadeh, R. J. Schotting., W. G. Gray and G. F. Pinder, pp 787 –794., 2002, 7 pages. Elsevier Science, Amsterdam. ISBN-13 : 978-0444509758 https://doi.org/10.2136/vzj2004.0731
Amin Elshorbagy, RameshV. Teegavarapu and Lindell Ormsbee; System Dynamics Approach for Water Quality Management in South Eastern Kentucky, Volume 2, # 47, Developments in Water Science, Computational Methods in Water Resources, Editors: S. M. Hassanizadeh, R. J. Schotting., W. G. Gray and G. F. Pinder, pp 1557 –1564, 2002, 7 pages Elsevier Science, Amsterdam. ISBN-13 : 978-0444509758 https://doi.org/10.2136/vzj2004.0731
Ramesh S. V. Teegavarapu; Input Structures for a Neural Network Model used for Streamflow Forecasting, Hydrology in Changing Environment, Vol (3), pp 104 – 115, 1998. International Association of Hydrological Sciences (IAHS) Publication. ISBN: 978-0-471-98686-7.
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Book Chapters [52] [38 chapters published, 14 under submission]
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Ramesh S. V. Teegavarapu, Data Cleaning and Hydroanlytics in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu, Outliers and Anomalies in Hydrometeorological Data in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu, Rule-based and Statistical Methods in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu, Machine Learning Methods in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu, Bias Assessment and Corrections in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu, Analyzing and Correcting Precipitation Data in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu, Analyzing Stage Data in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu, Analyzing Temperature and Snow Data in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu, Design of Quality Assessment Systems in book: Hydroanlytics: Methods for Detection of Outliers and Anomalies in Hydrometeorological Data. To be published in 2025.
Ramesh S. V. Teegavarapu and Roberto Ranzi. Climate Change and Stationarity, Monograph/book: Water Engineering Design Guidance in a Changing Climate, International Association for Hydro-Environment Engineering and Research (IAHR) to be published in 2025.
Roberto Ranzi and Ramesh S. V. Teegavarapu. Hydroclimatic Variability, Monograph/book: Water Engineering Design Guidance in a Changing Climate, International Association for Hydro-Environment Engineering and Research (IAHR) to be published in 2025.
Ramesh S. V. Teegavarapu Stationary: Basics, in Stationarity: A Gentle Introduction. World Scientific Publising (WSP), to be published in 2025. ISBN: 9789811255403. https://doi.org/10.1142/12810
Ramesh S. V. Teegavarapu Statistical Hypothesis-based Parametric Assessments, in Stationarity: A Gentle Introduction. World Scientific Press (WSP), to be published in 2025. ISBN: 9789811255403. https://doi.org/10.1142/12810
Ramesh S. V. Teegavarapu Statistical Hypothesis-based Non-parametric Assessments, in Stationarity: A Gentle Introduction. World Scientific Press (WSP), to be published in 2025. ISBN: 9789811255403. https://doi.org/10.1142/12810
Ramesh S. V. Teegavarapu Introduction to Missing data, In Imputation Methods for Missing Hydrometeorological Data Estimation, Springer, 2024. ISBN:978-3031609459. https://doi.org/10.1007/978-3-031-60946-6_1
Ramesh S. V. Teegavarapu Methods for Imputation of Missing Data, In Imputation Methods for Missing Hydrometeorological Data Estimation, Springer, 2024. ISBN:978-3031609459. https://doi.org/10.1007/978-3-031-60946-6_2
Ramesh S. V. Teegavarapu Temporal Interpolation Methods, In Imputation Methods for Missing Hydrometeorological Data Estimation, Springer, 2024. ISBN:978-3031609459. https://doi.org/10.1007/978-3-031-60946-6_3
Ramesh S. V. Teegavarapu Spatial Interpolation Methods, In Imputation Methods for Missing Hydrometeorological Data Estimation, 2024. ISBN:978-3031609459. https://doi.org/10.1007/978-3-031-60946-6_4
Ramesh S. V. Teegavarapu Universal Function Approximation and Data-driven Models for Imputation, In Imputation Methods for Missing Hydrometeorological Data Estimation, Springer, 2024. ISBN:978-3031609459. https://doi.org/10.1007/978-3-031-60946-6_5
Ramesh S. V. Teegavarapu Machine Learning and Multiple Imputation Methods, In Imputation Methods for Missing Hydrometeorological Data Estimation, Springer, ISBN:978-3031609459. https://doi.org/10.1007/978-3-031-60946-6_6
Ramesh S. V. Teegavarapu Evaluation of Methods and Imputed Data, In Imputation Methods for Missing Hydrometeorological Data Estimation, Springer, ISBN:978-3031609459. https://doi.org/10.1007/978-3-031-60946-6_7
Ramesh S. V. Teegavarapu Case Studies and Applications: Imputation of Missing Hydrometeorological Data, In Imputation Methods for Missing Hydrometeorological Data Estimation, Springer, ISBN:978-3031609459. https://doi.org/10.1007/978-3-031-60946-6_8
Ramesh S. V. Teegavarapu, Evolving Adaptive Hydrologic Design and Water Resources Management in a Changing Climate. 2020. In Climate-Change Sensitive Water Resources Management, Taylor and Francis. ISBN: 978-0367674144. https://doi.org/10.1201/9780429289873
Ramesh S. V. Teegavarapu, Elpida Kolokytha, Carlos Galvao Water Resources Management in a Changing Climate: Major Issues. 2020. In Climate-Change Sensitive Water Resources Management, Taylor and Francis. ISBN: 978-0367674144. https://doi.org/10.1201/9780429289873
Elpida Kolokytha, Ramesh S. V. Teegavarapu, Carlos Galvao, Adaptive Water Management, and Climate Effects. 2020. In Climate-Change Sensitive Water Resources Management, Taylor and Francis. 2020. ISBN: 978-0367674144. https://doi.org/10.1201/9780429289873
Ramesh S. V. Teegavarapu, Simulation Models and Systems Thinking, Dynamic Simulation and Virtual Reality Approaches for Hydrologic Modeling and Water Resources Management. ISBN: 9781000414271. https://doi.org/10.1201/9780429345555
Ramesh S. V. Teegavarapu, Building Models using System Dynamics Principles, Dynamic Simulation and Virtual Reality Approaches for Hydrologic Modeling and Water Resources Management. ISBN: 9781000414271. https://doi.org/10.1201/9780429345555
Ramesh S. V. Teegavarapu, System Dynamics Models and Applications, Dynamic Simulation and Virtual Reality Approaches for Hydrologic Modeling and Water Resources Management. ISBN: 9781000414271. https://doi.org/10.1201/9780429345555
Ramesh S. V. Teegavarapu, Simulation with Animation. Dynamic Simulation and Virtual Reality Approaches for Hydrologic Modeling and Water Resources Management. ISBN: 9781000414271. https://doi.org/10.1201/9780429345555
Ramesh S. V. Teegavarapu, Mean Areal Precipitation Estimation: Issues and Methods, in the book Rainfall: Modeling, Measurement and Applications, Elsevier Publication. 2022. Edited by Renato Morbidelli. 48 pages. ISBN: https://doi.org/10.1016/C2019-0-04937-0
Ramesh S. V. Teegavarapu, Spatial and Temporal Estimation and Analysis of Precipitation, , Ed. V. P. Singh, McGraw Hill, 2016, The book won the “2018 PROSE Award for Excellence” in Engineering & Technology Category. https://proseawards.com/winners/2018-award-winners/ https://www.accessengineeringlibrary.com/content/book/9780071835091/toc-chapter/chapter39/section/section1 ISBN-13: 978-0071835091
Ramesh S. V. Teegavarapu, Evaluation and Improvement of Radar Rainfall Data, Radar Rainfall Data Estimation and Use (MOP 139), 53-58. 2019, https://doi.org/10.1061/9780784415115.ch04 ISBN: 978-0784415115.
Ramesh S. V. Teegavarapu, Rain-Gauge Rainfall Data Augmentaion and Radar Rainfall Data Analysis, Radar Rainfall Data Estimation and Use, (MOP 139), 95-110. 2019. https://doi.org/10.1061/9780784415115.ch08 ISBN: 978-0784415115
Ramesh S. V. Teegavarapu, Framework for Bias Analysis of Radar Data, Radar Rainfall Data Estimation and Use, (MOP -139), 73-93. 2019. https://doi.org/10.1061/9780784415115.ch07 ISBN: 978-0784415115
Ramesh S. V. Teegavarapu, Design of Rainfall Monitoring Networks, Radar Rainfall Data Estimation and Use, (MOP 139), 111-120. https://doi.org/10.1061/9780784415115.ch09 ISBN: 978-0784415115
Ramesh S. V. Teegavarapu, Statistical Analysis of Precipitation Extremes, in ASCE Book on Statistical Analysis of Hydrologic Variables: Methods and Applications, Ramesh Teegavarapu and Chandra Pathak, ASCE. 2019. https://doi.org/10.1061/9780784415177.ch02 ISBN: 978-0784415177
Ramesh S. V. Teegavarapu, Jose D. Salas, Jery R. Stedinger, Introduction in ASCE Book on Statistical Analysis of Hydrologic Variables: Methods and Applications, ISBN: 978-0784415177. https://doi.org/10.1061/9780784415177.ch02
Ramesh S. V. Teegavarapu, Climate Variability and Changes in Precipitation Extremes and Characteristics, Springer, 2016. In Sustainable Water Resources Planning and Management Under Climate Change. ISBN: 978-9811020490. https://doi.org/10.1007/978-981-10-2051-3_1
Elpida Kolokytha, Carlos de Oliveira Galvao, Ramesh S. V. Teegavarapu, Climate Change Impacts in Water Resources Management and Planning, Springer, 2016. In Sustainable Water Resources Planning and Management Under Climate Change. ISBN: 978-9811020490. https://doi.org/10.1007/978-981-10-2051-3_11
Ramesh S. V. Teegavarapu, Methods for Analysis of Trends and Change Detection, Elsevier Published, 2018. In Trends and Changes in Hydroclimatic Variables: Links to Climate Variability and Change. ISBN: 978-0128109854. https://doi.org/10.1016/B978-0-12-810985-4.00001-3
Ramesh S. V. Teegavarapu, Changes and Trends in Precipitation Extremes and Characteristics: Links to Climate Variability, Elsevier (published), 2018. In Trends and Changes in Hydroclimatic Variables: Links to Climate Variability and Change. ISBN: 978-0128109854. https://doi.org/10.1016/B978-0-12-810985-4.00002-5
Ramesh S. V. Teegavarapu, Alejandra Schmidt, Variations and Trends in Global and Regional Sea Levels, Elsevier (published), 2018. In Trends and Changes in Hydroclimatic Variables: Links to Climate Variability and Change. ISBN: 978-0128109854. https://doi.org/10.1016/B978-0-12-810985-4.00007-4
Ramesh S. V. Teegavarapu Technology Enhanced Learning for Civil Engineering Education: Use of Dynamic and Virtual-Reality based Simulation, Online Data Analysis and Optimization Tools, Taylor and Francis (in print) in the book: Blended Learning in Engineering Education: Recent Developments in Curriculum, Assessment, and Practice, 2018. ISBN-10:1138056227. https://doi.org/10.1201/9781315165486
Ramesh S. V. Teegavarapu, Precipitation and Climate Change, Floods in a Changing Climate: Extreme Precipitation, Cambridge University Press, UNESCO, International Hydrology Series, 2013. & 2018. ISBN:9781107018785. https://doi.org/10.1017/CBO9781139088442
Ramesh S. V. Teegavarapu, Precipitation Measurement, Floods in a Changing Climate, Cambridge University Press: Extreme Precipitation, Cambridge University Press, International Hydrology Series, 2013 & 2018. ISBN:9781107018785. https://doi.org/10.1017/CBO9781139088442
Ramesh S. V. Teegavarapu, Spatial Analysis of Precipitation, Floods in a Changing Climate: Extreme Precipitation, Cambridge University Press, International Hydrology Series, 2013 & 2018. ISBN:9781107018785. https://doi.org/10.1017/CBO9781139088442
Ramesh S. V. Teegavarapu, Extreme Precipitation and Floods, Floods in a Changing Climate: Extreme Precipitation, Cambridge University Press, International Hydrology Series, 2013 & 2018. ISBN:9781107018785. https://doi.org/10.1017/CBO9781139088442
Ramesh S. V. Teegavarapu, Climate Change Modeling and Precipitation, Floods in a Changing Climate: Extreme Precipitation, Cambridge University Press, International Hydrology Series, 2013 & 2018. ISBN:9781107018785. https://doi.org/10.1017/CBO9781139088442
Ramesh S. V. Teegavarapu, Precipitation Variability, and Teleconnections, Floods in a Changing Climate: Extreme Precipitation, International Hydrology Series, 2013 & 2018. ISBN:9781107018785.https://doi.org/10.1017/CBO9781139088442
Ramesh S. V. Teegavarapu, Precipitation Trends, and Variability, Floods in a Changing Climate: Extreme Precipitation, Cambridge University Press, 2013. & 2018. ISBN:9781107018785. https://doi.org/10.1017/CBO9781139088442
Ramesh S. V. Teegavarapu, Hydrologic Modeling and Design, Floods in a Changing Climate: Extreme Precipitation, Cambridge University Press, 2013. & 2018. ISBN:9781107018785. https://doi.org/10.1017/CBO9781139088442
Ramesh S. V. Teegavarapu, Future Perspectives, Floods in a Changing Climate: Extreme Precipitation, Cambridge University Press, 2013. & 2018. ISBN:9781107018785. https://doi.org/10.1017/CBO9781139088442
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Peer Reviewed Abstracts
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- Achala Singh, Priyank Sharma, Ramesh S. V. Teegavarapu, A Novel Approach for Assessing Non-stationarity in Hydroclimatic Extremes. European Geophysical Union (EGU) General Assembly, April 2025. Accepted.
- Ramesh S. V. Teegavarapu, Objective and Optimal Spatial Interpolation Approaches for Imputing Missing Precipitation Records. European Geophysical Union (EGU) General Assembly, April 2025. Accepted.
- Thu Nguyen, Anika Azad, Ramesh S. V. Teegavarapu, Model Tree, and Regularization Approaches for Estimation of Missing precipitation Records. European Geophysical Union (EGU) General Assembly 2024, Vienna, April 2024. 2024EGUGA..2618097N. https://ui.adsabs.harvard.edu/link_gateway/2024EGUGA..2618097N/doi:10.5194/egusphere-egu24-18097
- Achala Singh, Priyank Sharma, Ramesh S. V. Teegavarapu, Navigating Hydroclimatic Extremes: Understanding the Interplay of Climate Change and Variability. European Geophysical Union (EGU) General Assembly 2024, Vienna, April 2024. 2024EGUGA..2614414S. https://ui.adsabs.harvard.edu/link_gateway/2024EGUGA..2614414S/doi:10.5194/egusphere-egu24-14414
- Ramesh S. V. Teegavarapu, Priyank Sharma, Diego Jara Li. Stationarity Assessment of Precipitation and Temperature Extremes in the Continental United States. European Geophysical Union (EGU) General Assembly 2023, Vienna, April 25, 2023. 2023EGUGA..2513123T. https://ui.adsabs.harvard.edu/link_gateway/2023EGUGA..2513123T/doi:10.5194/egusphere-egu23-13123
- Achala Singh, Priyank, J. Sharma, Ramesh S. V. Teegavarapu, Stationarity Assessment of Hydroclimatic Variables for a Tropical River Basin. European Geophysical Union (EGU) General Assembly, 2023, Vienna, April 25, 2023. 2023EGUGA..25..634S. https://ui.adsabs.harvard.edu/link_gateway/2023EGUGA..25..634S/doi:10.5194/egusphere-egu23-634
- Ramesh S. V. Teegavarapu,Precipitation Imputation using Optimal Probability Space-based Interpolation, European Geophysical Union (EGU) General Assembly, 2020. 2020EGUGA..2220930T.https://ui.adsabs.harvard.edu/link_gateway/2020EGUGA..2220930T/doi:10.5194/egusphere-egu2020-20930 Not presented due to COVID.
- Patel, P. L., Sharma, P., and Ramesh. S. V. Teegavarapu. Assessing the utility of climate variability information in streamflow forecasting, European Geophysical Union (EGU) General Assembly 2021, online, 19–30 Apr 2021. 2021EGUGA..2314633L. https://ui.adsabs.harvard.edu/link_gateway/2021EGUGA..2314633L/doi:10.5194/egusphere-egu21-14633
- Sina Borzooei, Ramesh S. V. Teegavarapu, Soroush Abolfathi, Youri Amerlinck, Ingmar Nopens and Maria Chiara Zanetti, Evaluation of the Impact of Wet-weather Events on Influent Flow and Loadings of a Water Resource Recovery Facility, 11th International Conference on Urban Drainage Modelling, 23-26 September 2018, Palermo, Italy. 706-707.
- C. Pathak and Ramesh S. V. Teegavarapu, Radar-based Precipitation Estimates Use in Hydrologic Modeling and Extreme Event Analysis: Emerging Issues, Applications, and Lessons Learned, ASCE-EWRI World Environmental and Water Congress, Sacramento, May 2017.
- Pradeep Behera, Ramesh S. V. Teegavarapu, C. Pathak. Variability of Storm Event Characteristics in Different Climate Zones of Continental United States: Implications for Stormwater Management and Hydrologic Design. ASCE-EWRI World Environmental and Water Congress, Sacramento, May 2017.
- Pradeep Behera, Ramesh S. V. Teegavarapu, et al. Tracking Changes and Trends in the Potomac River Stream Flow Extremes and Characteristics. ASCE-EWRI World Environmental and Water Congress, 2016 International Conference, West Palm Beach, Florida, USA.
- Ramesh S. V. Teegavarapu, C. Chandramouli, P. Behera. Evaluating between Sea Level Variations and Climate Variability for the Continental United States, ASCE-EWRI World Environmental and Water Congress, 2016 International Conference, West Palm Beach, Florida, USA.
- Ramesh S. V. Teegavarapu, Low Flow Variability, and Coupled Oceanic-Atmospheric Oscillations, American Geophysical Union (AGU) Fall Meeting, December 2014. 2014AGUFM.H23N1086T
- Aneesh Goly and Ramesh S. V. Teegavarapu, Optimal Selection of Predictor Variables in Statistical Downscaling Models of Precipitation. American Geophysical Union (AGU) Fall Meeting, December 2014. 2014AGUFM.H13F1188G
- Sudhagar Nagarajan, Yushin Ahn, Ramesh S. V. Teegavarapu, Analytical Incorporation of Velocity Parameters into Ice Sheet Elevation Change Rate Computations. American Geophysical Union (AGU) Fall Meeting, Extended Abstract: # C21C-0361. 2014AGUFM.C21C0361N
- Ramesh S. V. Teegavarapu, Hydrologic Design under Changing Regional Precipitation Extremes and Characteristics: Influences of Climate Variability and Change, KOBE-EU Symposium, October 13-15, 2014.
- Chandra Pathak, Ramesh S. V. Teegavarapu, Uncertainty Analysis Approaches in Hydrologic Modeling, ASCE-EWRI World Environmental and Water Congress, 2014.
- Ramesh S. V. Teegavarapu, Climate Change-Sensitive Hydrologic Design under Uncertain Future Precipitation Extremes, ASCE-EWRI World Environmental and Water Congress, 2014.
- Ramesh S. V. Teegavarapu and Milla Pierce, Precipitation Regime Changes under Decadal and Multi-Decadal Oscillations, ASCE-EWRI World Environmental and Water Congress, 2014.
- Ramesh S. V. Teegavarapu, Chandra Pathak, Optimizing Reflectivity-Rain Rate (Z-R) Relationship Parameters for Improved Radar-based Precipitation Estimates, Weather Radar and Hydrology (WRaH) International Symposium, April 7-9, Washington DC, 2014.
- Ramesh S. V. Teegavarapu, Aneesh Goly, Quinlong Wu, A Comprehensive Framework for Assessment of Radar Data, Weather Radar and Hydrology (WRaH) International Symposium, April 7-9, Washington DC, 2014.
- Ramesh S. V. Teegavarapu, Uncertainty Assessments of Spatially Interpolated Missing Precipitation Data Estimates, American Geophysical Union (AGU) Fall Meeting, 2013. 2013AGUFM.H33B1343T
- Aneesh Goly, Ramesh S. V. Teegavarapu, Coupled Oceanic-Atmospheric Variability at Different Temporal Scales and U.S. Precipitation Characteristics, American Geophysical Union (AGU) Fall Meeting, 2013. 2013AGUFM.H52B..05G
- Aneesh Goly, Ramesh S. V. Teegavarapu, Comparative Assessment of Statistical Downscaling Methods for Precipitation in Florida, American Geophysical Union (AGU) Fall Meeting, 2012. 2012AGUFMGC41B0966G
- Ramesh S. V. Teegavarapu,Estimation of Missing Precipitation Records using Classifier, Cluster and Proximity Metric-Based Interpolation Schemes. American Geophysical Union (AGU) Fall Meeting, 2012. 2012AGUFM.H33K1489T
- Husayn El. Sharif, Ramesh S. V. Teegavarapu, Evaluation of Fuzzy-Logic Framework for Spatial Statistics Preserving Methods for Estimation of Missing Precipitation Data. American Geophysical Union (AGU) Fall Meeting, 2012. 2012AGUFM.H33C1352E
- Husayn El. Sharif, Ramesh S. V. Teegavarapu, Spatial Statistics Preserving Interpolation Methods for Estimation of Missing Precipitation Data. American Geophysical Union (AGU) Fall Meeting, 2011. 2011AGUFM.H41G1132E
- Ramesh S. V. Teegavarapu, Viswanathan, C., Behera P.Variability of Precipitation Extremes and Climate Change: Evaluation using Descriptive Indices. American Geophysical Union (AGU) Fall Meeting, 2011. 2011AGUFM.H21D1138T
- Ramesh S. V. Teegavarapu, Anurag Nayak, Chandra Pathak, Assessment of Long-term Trends in Extreme Precipitation: Implications of In-filled Historical Data and Temporal Window-Based Analysis, American Geophysical Union (AGU) Fall Meeting, 2010. 2010AGUFM.H13E1020T.
- Noemi Gonzalez, Ramesh S. V. Teegavarapu, Lin Huang, Evaluation of Spatial and Temporal Distribution of Extreme Precipitation Events and their Relation to Peak Flooding, American Geophysical Union (AGU) Fall Meeting, 2010. 2010AGUFM.H13E1021G.
- Ramesh S. V. Teegavarapu, Sharika U. Senarath, Chandra S. Pathak. Evaluation of Variants of Monte Carlo Simulation for Hydrologic Model Uncertainty Assessment, American Geophysical Union (AGU) Fall Meeting, 2009. 2009AGUFM.H41F0963T
- Andre Ferreira, Ramesh S. V. Teegavarapu, Chandra S. Pathak. Evaluation of Optimal Reflectivity-Rain Rate (Z-R) Relationships for Improved Precipitation Estimates, American Geophysical Union (AGU) Fall Meeting, 2009. 2009AGUFM.H31D0805F
- Meskele, T., Ramesh. S. V. Teegavarapu, Chandra S. Pathak. Comparative Evaluation of NEXRAD and TRMM Satellite based Precipitation Estimates and Rain Gage Measurements, American Geophysical Union (AGU) Fall Meeting, 2008. 2008AGUFM.H23E1023M
- Ramesh. S. V. Teegavarapu, Meskele, T., Chandra S. Pathak, Geo-Spatial Grid-based Transformations of Multi-Sensor Precipitation Estimates, American Geophysical Union (AGU) Fall Meeting, 2008. 2008AGUFM.H23E1022T
- Ramesh. S. V. Teegavarapu,Water Resources Management and Hydrologic Design Under Uncertain Climate Change Scenarios, American Geophysical Union (AGU) Spring Meeting, 2008. 2008AGUSM.H51B..04T
- Ramesh. S. V. Teegavarapu,Optimal Cluster-based Models for Estimation of Missing Precipitation Records, American Geophysical Union (AGU) Fall Spring Meeting, 2008. 2008AGUSM.H23A..06T
- Delroy Peters, Ramesh. S. V. Teegavarapu, Chandra S. Pathak. Characterizing Rain Gage – Radar (NEXRAD) Data Relationships Using Inductive Modeling, American Geophysical Union (AGU) Fall Meeting, 2007. 2007AGUFM.H23K..08P
- Ramesh S. V. Teegavarapu, Estimation of Missing Precipitation Data using Soft Computing based Spatial Interpolation Techniques, American Geophysical Union (AGU) Fall Meeting, 2007. 2007AGUFM.H13H1683T
- Ramesh S.V. Teegavarapu, Integration of Spatial Interpolation Techniques and Association Rules for Estimation of Missing Precipitation Data, American Geophysical Union (AGU) Fall Meeting, 2006. 2006AGUFM.H23D1544T
- Ramesh S.V. Teegavarapu, Seth Bradley and Lindell Ormsbee, Probabilistic Goal-Driven Water Quality Management, abstract published, American Geological Society (AGS) Annual Meeting, March 2006. Presented by Seth Bradley.
- Seth Bradley, Lindell Ormsbee, Ramesh S.V. Teegavarapu, Modeling the Fate and Transport of Pathogens in a Watershed using Discrete Volume Method, abstract published, American Geological Society (AGS) Annual Meeting, March 2006.
- Ramesh S. V. Teegavarapu, and Lindell Ormsbee. Sustainable and Climate Sensitive Hydrologic Design and Management of Hydrosystems. Proceedings of ASCE Conference on Impacts of Global Climate Change, Alaska. https://doi.org/10.1061/40792(173)332
- Ramesh S.V. Teegavarapu, A New Integrated Neural Network Architecture for Streamflow Forecasting, abstract, American Geophysical Union (AGU) Fall Meeting, December 2005. EOS transactions, 86(52), H54B-08. 2005AGUFM.H54B..08T
- Viswanathan C., Ramesh S. V. Teegavarapu, Lindell Ormsbee. Surface Water Assessment and Hydrologic Modeling under Karst Aquifer Conditions. American Geophysical Union (AGU) Fall Meeting, December 2005. 2005AGUFM.H21A1320V
- Ramesh S. V. Teegavarapu, and Lindell Ormsbee, Regional Assessment of Pathogen Pollution Using Kriging Approach, EOS transactions, American Geophysical Union (AGU) Fall Meeting, December 2004. H53A-1210, 85(47), 2004. 2004AGUFM.H53A1210T
- Ramesh S.V. Teegavarapu, Anil Tangirala, and Lindell Ormsbee. Assessing Hydrologic Similarity of Watersheds by Analyzing Geometric Patterns in Streamflow Time Series, Abstract in EOS Transactions 84(46), American Geophysical Union (AGU) Fall Meeting, 2003. 2003AGUFM.H12B0969T.
- Anil Tangirala, Ramesh S.V. Teegavarapu and Lindell Ormsbee. Developing Water Quality Management Strategies at Different Watershed Scales Using System Dynamics Simulation, Abstract in EOS Transactions 84(46), American Geophysical Union (AGU) Fall Meeting, 2003. 2003AGUFM.H51C1064T
- Ramesh S.V. Teegavarapu, Improving Neural Network Performance for Streamflow Prediction: Use of Geometrical Patterns in Time Series, extended abstract, AWRA Annual Conference, November 2002, p129, Welty Claire, Ed. TPS-02-4, Middleburg, Virginia.
- Ramesh S.V. Teegavarapu, Amin Elshorbagy and Lindell Ormsbee; Characterizing Pollutant Loadings in Streams using System Dynamics Simulation, extended abstract, Proceedings of AWRA Annual Conference, November 2002, p 247, Welty Claire, Ed. TPS-02-4, Middleburg, Virginia.
- Amin Elshorbagy, Ramesh S.V. Teegavarapu and Lindell Ormsbee; System Dynamics, GIS and Inductive Modeling: A Tool Kit for Water Quality Management, extended abstract, Proceedings of AWRA Annual Conference, November 2002, p 64, Welty Claire, Ed. TPS-02-4, Middleburg, Virginia.
- Ramesh S.V. Teegavarapu and Lindell Ormsbee; Modeling Environmental Systems using System Dynamics Approach and Object-Oriented Simulation Tools, extended abstract published in CD ROM proceedings of AEESP/AAEE Conference, Understanding Complex Environmental systems, pp 52, 2002.
- Ramesh S. V. Teegavarapu and Amin El-Shorbagy; Disaggregation of Streamflows Using Neural Networks, Extended Abstract published. International Conference of the American Institute of Hydrology (AIH), November 2000.