Journals & Peer Reviewed Publications

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  • SPI[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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  1. 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.
  2. Ramesh S. V. Teegavarapu, Objective and Optimal Spatial Interpolation Approaches for Imputing Missing Precipitation Records. European Geophysical Union (EGU) General Assembly, April 2025. Accepted.
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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.
  8. 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
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. Ramesh S. V. Teegavarapu, Low Flow Variability, and Coupled Oceanic-Atmospheric Oscillations, American Geophysical Union (AGU) Fall Meeting, December 2014.  2014AGUFM.H23N1086T
  15. 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
  16. 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
  17. 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.
  18. Chandra Pathak, Ramesh S. V. Teegavarapu, Uncertainty Analysis Approaches in Hydrologic Modeling, ASCE-EWRI World Environmental and Water Congress, 2014.
  19. Ramesh S. V. Teegavarapu, Climate Change-Sensitive Hydrologic Design under Uncertain Future Precipitation Extremes, ASCE-EWRI World Environmental and Water Congress, 2014.
  20. Ramesh S. V. Teegavarapu and Milla Pierce, Precipitation Regime Changes under Decadal and Multi-Decadal Oscillations, ASCE-EWRI World Environmental and Water Congress, 2014.
  21. 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.
  22. 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.
  23. Ramesh S. V. Teegavarapu,  Uncertainty Assessments of Spatially Interpolated Missing Precipitation Data Estimates, American Geophysical Union (AGU) Fall Meeting, 2013. 2013AGUFM.H33B1343T
  24. 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
  25. Aneesh Goly,  Ramesh S. V. Teegavarapu, Comparative Assessment of Statistical Downscaling Methods for Precipitation in Florida, American Geophysical Union (AGU) Fall Meeting, 2012. 2012AGUFMGC41B0966G
  26. 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
  27. 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
  28. 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
  29. 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
  30. 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.
  31. 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.
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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
  38. 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
  39. 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
  40. 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
  41. 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.
  42. 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.
  43. 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
  44. 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
  45. 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
  46. 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
  47. 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.
  48. 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
  49. 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.
  50. 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.
  51. 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.
  52. 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.
  53. 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.

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