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,  Performance Indices for Operational Considerations of Coastal Hydraulic Structures. Journal of Hydrologic Engineering, 2024. Published.
  • 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, 2024. Published.
  • Singh, A. Sharma, P. J., Ramesh S. V. Teegavarapu, Understanding nonstationarity patterns in basin-scale hydroclimatic extremes. International Journal of Climatology.  Published, 2024.
  • 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, Published, 2024.
  • Sandipan Paul, Priyank J. Sharma, Ramesh S.V. Teegavarapu. Indian Summer Monsoon Rainfall (ISMR) Characteristics Derived from Multiple Gridded Precipitation Datasets: A Comparative Assessment. International Journal of Climatology, Published. 2024.
  • Anant Patel, Sanjay M. Yadav, Ramesh S.V. Teegavarapu. Enhancing Real-time Flood Forecasting and Warning System by Integrating Ensemble Technique and Hydrologic Model Simulation. Journal of Water and Climate, Published, 2024.
  • Hao Chen, Ramesh S. V. Teegavarapu, multiple co-authors, Using Baseflow Ensembles for Hydrologic Hysteresis Characterization in Humid Basins. Water Resources Research, accepted, Published. 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. 2024. In print.
  • Mahdi Zarei; Reza Ghazavi; Khodayar Abdollahi; Roberto Ranzi; Ramesh S.V. Teegavarapu; Stefano Barontini Assessment of water resources availability using a distributed monthly water balance model (WetSpass-M) in an arid environment, Water Supply. 2024 https://doi.org/10.2166/ws.2024.018 
  • Scalability of CASCADE 2001: Gis-Based Flood Risk Screening Tool to Support Watershed Master Planning. 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. Applied Research Periodicals, 2024, Vol. 2, No. 8 pp. 26-41.
  • Ramesh S. V. Teegavarapu and multiple co-authors, River ecological flow early warning forecasting using baseflow separation and machine learning in the Jiaojiang River Basin, Southeast China. Science of Total Environment, 2023.
  • Ramesh S. V. Teegavarapu, Priyank J. Sharma, Non-overlapping Block Stratified Random Sampling Approach for Assessment of Stationarity, Closure for discussion,  Journal of Hydrologic Engineering, ASCE, 2022.  Published. https://ascelibrary.org/doi/10.1061/%28ASCE%29HE.1943-5584.0002193
  • Ramesh S. V. Teegavarapu, Priyank J. Sharma, Prem Lal Patel. Frequency-based Performance Measure for Hydrologic Model Evaluation.  Journal of Hydrology,  2022. Published. 
  • Ramesh S. V. Teegavarapu, Mean Areal Precipitation Estimation: Methods and Issues, 44 pages, Chapter 8, in Rainfall: Modeling, Measurement and Applications (ed. R. Morbidelli). 2022. Published.
  • 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, 2022. In print.
  • 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, Published,
  • Ramesh S. V. Teegavarapu, Priyank J. Sharma, Non-overlapping Block Stratified Random Sampling Approach for Assessment of Stationarity, Journal of Hydrologic Engineering, ASCE, 2021. Published.  http:/doi.org/10.1061/ 061/(ASCE)HE.1943-5584.0002098.  Received the Editor’s Choice Paper recognition.
  • Ramesh S. V. Teegavarapu and Priyank J. Sharma, Influences of Climate Variability on Regional Precipitation and Temperature Associations, Hydrological Sciences Journal, 2021. Published.
  • Priyank J. Sharma and S. V. Teegavarapu, Influences of Local Hydroclimatology and Teleconnections on Florida’s Precipitation and Temperature Variability, Published.  Hydrological Processes, 2021.  
  • Hao Chen, Ramesh S. V. Teegavarapu, Yue-Ping Xu, Oceanic-Atmospheric Variability Influences on Baseflows in the Continental United States, Water Resources Management, 2021. Published.
  • 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, 2021. Published.
  • Ramesh S. V. Teegavarapu, Precipitation Imputation using Probability Space-based Spatial Interpolation, Journal of Hydrology, 2020. Published.
    https://doi.org/10.1016/j.jhydrol.2019.124447.
  • 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, Authors in alphabetical order. Journal of Infrastructure, Policy, and Development, 5(1), 2021. DOI: 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, 2021, 9, 180-205.
  • 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, 2020. Published.
  • Fahad K. Khadim, Ramesh S. V. Teegavarapu, Optimal Interventions for Flood Control, Drainage, and Irrigation Project Improvements, Hydrological Sciences Journal, 2020. Published.
  • 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, 2020. Published. 
  • Hao Chen, S. V. Teegavarapu, Spatial and Temporal Variability in Baseflow Characteristics across the Continental United States, Journal of Theoretical and Applied Climatology, 2020. Published.
  • 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, under review, Water, 2020. Published.
  • 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.  2020, Published.
  • 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, 2019. Published.
  • 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. Published.
  • Ramesh S. V. Teegavarapu, Singaiah Chintalapudi, Incorporating Influences of Shallow Groundwater Conditions in Curve Number-based Runoff Estimation Methods, Water Resources Management, 2018. (DOI: 10.1007/s11269-018-2053-y)
  • Ramesh S. V. Teegavarapu, Exploring Geometrical Patterns in Streamflow Timeseries: Utility for Forecasting? Hydrology Research, 2018, in print (Doi: 10.2166/nh2018.127).
  • Hao Chen, S. V. Teegavarapu, Comparative Analysis of Four Baseflow Separation Methods in the South Atlantic-Gulf Region of the U.S., Water, 2019. Published.
  •  Carlos Galvão, Young-Oh Kim, Elpida Kolokytha, Arpita Mondal, Pradeep Mujumdar, Daisuke Nohara, Satoru Oishi, Roberto Ranzi, Ramesh S V. Teegavarapu, The Contribution of IAHR’s Communities of Water Management and Climate Change Towards The Sustainable Development Goals, Special Issue of Hydrolink, 3, 2017. Equal contribution from all authors. Authors names arranged in Alphabetical order.
  • Ramesh S. V. Teegavarapu, Spatial and Temporal Estimation and Analysis of Precipitation, Handbook of Applied Hydrology, 2017, McGraw Hill, Published.
  • Ramesh S. V. Teegavarapu, A . Goly, Optimal Selection of Predictor Variables in Statistical Downscaling Models of Precipitation, Water Resources Management, 2017. Published.
  • 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. 2018.
  • Ramesh S. V. Teegavarapu, Ala Aly, Chandra S. Pathak, Jon Ahlquist, Henry Fuelberg, Improvised Spatial Interpolation Methods for Infilling Missing Precipitation Records, 2017.  International Journal of Climatology. Published.
  • 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. Published.
  • 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. Published.
  • 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. 2018. In print.  https://doi.org/10.1007/s11270-018-4053-1
  • 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, 2017, Published.
  • Chandra S. Pathak, Ramesh. S. V. Teegavarapu, D. Curtis and C. Collier, Special Issue on Radar Rainfall and Operation Hydrology, Journal of Hydrologic Engineering, ASCE., 2016  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, IAHR, 3, 93-95, 2015. Peer reviewed publication.
  • Ramesh S. V. Teegavarapu, Aneesh Goly, Qinglong Wu, A Comprehensive  Framework for Assessment of bias in radar-based precipitation estimates, Journal of Hydrologic Engineering, ASCE , 2015. Published.
  • Chandra S. Pathak, Ramesh S. V. Teegavarapu, Chris Olson, Abhishek Singh, Wasantha Lal, Ceyda Polatel, Vahid Zahraeifard, and Sharika Senarath, Issues and Proposed Resolutions on Use of Uncertainty Analyses in Hydrologic/Hydraulic Modeling, Journal of Hydrologic Engineering, ASCE, 2015.  Published.
  • 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. 2015. Published.
  • 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, 2013. DOI:10.1080/02626667.2013.862334. Published. 
  • Ramesh S. V. Teegavarapu, Climate Change-Sensitive Hydrologic Design under Uncertain Future Precipitation Extremes, Water Resources Research, 49(11), 7804-7814, 2013. Published.
  • Ramesh S. V. Teegavarapu, Statistical Corrections of Spatially Interpolated Precipitation Estimates, Hydrological processes, 28(11), 3789–3808, 2014. DOI: 10.1002/hyp.9906. Published. 
  • 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. Published.
  • Ramesh S. V. Teegavarapu and S. P. Simonovic; Dynamics of Hydropower System Operations, Water Resources Management. Springer Publications. DOI 10.1007/s11269-014-0586-2. 2014. 28:1937–1958. Published.  
  • 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,  doi:10.1002/2013WR014540.. Published.
  • Pradeep Behera and Ramesh S. V. Teegavarapu, Optimization of a Regional Stormwater Quality Management Pond System, Water Resources Management. 2014. DOI 10.1007/s11269-014-0862-1. Published.
  • 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, 1–14, doi:10.1002/wrcr.20224, 2013. Published
  • Aneesh Goly, Ramesh S. V. Teegavarapu, Arpitha Mondal, Evaluation of Statistical Downscaling Models for Monthly Precipitation in Florida, Earth Interactions, 2014.  Published.
  • 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. Published
  • 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. Published.
  • 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. DOI: 10.1007/s11269-011-9940-9. Published.
  • 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. Doi:10.1016./j.cageo2011.07.004. Published.
  • Ramesh S. V. Teegavarapu, Modeling Climate Change Uncertainties in Water Resources Management Models, Environmental Modeling and Software, Volume 25, Issue 10, October 2010, Pages 1261-1265. Published.
  • Ramesh S. V. Teegavarapu, Estimation of Missing Precipitation Records Integrating Surface Interpolation Techniques and Spatio-Temporal Association Rules , Journal of HydroInformatics Vol, 11 No 2 pp 133–146, 2009. Published.
  • 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.
  • 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.
  • 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.
  • 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, 2006.
  • 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.
  • 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.
  • Ramesh S. V. Teegavarapu and Amin Elshorbagy, Fuzzy Set-Based Error Measure for Hydrologic Model Evaluation,  Journal of Hydroinformatics, 7,  199-208, 2005.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • P. P. Mujumdar and Ramesh S. V. Teegavarapu; A Short Term Reservoir Operation Model for Multicrop Irrigation; Hydrological Sciences Journal, 43(3), pp 479 – 494, June, 1998.
  • P.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.
  • 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.
  • Ramesh S. V. Teegavarapu, Training Neural Networks to Perform Rainfall Disaggregation,  Journal of Hydrologic Engineering, Vol 4, July/August, 342, ASCE, 2002.

Book Chapters

  • 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 Co-author. Climate Change and Stationarity, Monograph/book: Water Engineering Design Guidance in a Changing Climate, IAHR to be published in 2024.
  • Ramesh S. V. Teegavarapu and Co-authors. Hydroclimatic Variability, Monograph/book: Water Engineering Design Guidance in a Changing Climate, IAHR to be published in 2024.
  • Ramesh S. V. Teegavarapu Stationary: Basics,  in Stationarity: A Gentle Introduction. World Scientific Press (WSP), to be published in 2024.
  • Ramesh S. V. Teegavarapu Statistical Hypothesis-based Parametric Assessments, in Stationarity: A Gentle Introduction. World Scientific Press (WSP), to be published in 2024.
  • Ramesh S. V. Teegavarapu Statistical Hypothesis-based Non-parametric Assessments, in Stationarity: A Gentle Introduction. World Scientific Press (WSP), to be published in 2024.
  • Ramesh S. V. Teegavarapu Introduction to Missing data, In Methods for Imputation of Missing Hydrometeorological Data, Springer. Publsihed 2024.
  • Ramesh S. V. Teegavarapu Methods for Imputation of Missing Data, In Methods for Imputation of Missing Hydrometeorological Data, Springer, Published 2024.
  • Ramesh S. V. Teegavarapu Temporal Interpolation Methods, In Methods for Imputation of Missing Hydrometeorological Data, Springer,  Published 2024.
  • Ramesh S. V. Teegavarapu Spatial Interpolation Methods, In Methods for Imputation of Missing Hydrometeorological Data, Springer,Published 2024.
  • Ramesh S. V. Teegavarapu Data-driven Models for Imputation, In Methods for Imputation of Missing Hydrometeorological Data, Springer, Published 2024.
  • Ramesh S. V. Teegavarapu Multiple Imputation Methods, In Methods for Imputation of Missing Hydrometeorological Data, Springer, Published 2024.
  • Ramesh S. V. Teegavarapu Evaluation of Methods and Imputed Data, In Methods for Imputation of Missing Hydrometeorological Data, Springer, Published 2024.
  • Ramesh S. V. Teegavarapu Case Studies and Applications: Imputation of Missing Hydrometeorological Data, In Methods for Imputation of Missing Hydrometeorological Data, Springer, Published 2024.
  • 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. Published.
  • 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. Published.
  • 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. Published 2020.
  • Ramesh S. V. Teegavarapu, Simulation Models and Systems Thinking, Dynamic Simulation and Virtual Reality Approaches for Hydrologic Modeling and Water Resources Management. Published. 2021.
  • Ramesh S. V. Teegavarapu, Building Models using System Dynamics Principles, Dynamic Simulation and Virtual Reality Approaches for Hydrologic Modeling and Water Resources Management. Published. 2021.
  • Ramesh S. V. Teegavarapu, System Dynamics Models and Applications, Dynamic Simulation and Virtual Reality Approaches for Hydrologic Modeling and Water Resources Management. Published.
  • Ramesh S. V. Teegavarapu, Simulation with Animation. Dynamic Simulation and Virtual Reality Approaches for Hydrologic Modeling and Water Resources Management 2021.
  • Ramesh S. V. Teegavarapu, Mean Areal Precipitation Estimation: Issues and Methods, in the book: Rainfall: Modeling, Measurement and Applications, Elsevier Publication. Published 2022. Edited by Renato Morbidelli. 48 pages.
  • Ramesh S. V. Teegavarapu, Spatial and Temporal Estimation and Analysis of Precipitation, Handbook of Applied Hydrology, McGraw Hill, 2016, ISBN-13: 978-0071835091. The book won the “2018 PROSE Award for Excellence” in Engineering & Technology Category.
  • Ramesh S. V. Teegavarapu, Climate variability and changes in precipitation extremes and characteristics, Springer, 2016. Published.
  • Ramesh S. V. Teegavarapu, Evaluation and Improvement of Radar-based Rainfall and Design of Monitoring Networks, Radar Rainfall Data Estimation and Use, Published.
  • Ramesh S. V. Teegavarapu, Precipitation Data Augmentation, and Analysis of Radar-based Rainfall Data, Radar Rainfall Data Estimation and Use, 2019. Published.
  • Ramesh S. V. Teegavarapu, Framework for Bias Analysis of Radar Data, Radar Rainfall Data Estimation and Use, 2019. Published.
  • Ramesh S. V. Teegavarapu, Design of Rainfall Monitoring Network, Radar Rainfall Data Estimation and Use, 2019. Completed. Published.
  • Ramesh S. V. Teegavarapu, Statistical Analysis of Precipitation Extremes, Chapter in ASCE Book on Statistical Analysis of Hydrologic Variables: Methods and Applications, Ramesh Teegavarapu and Chandra Pathak, ASCE. 2019.
  • Ramesh S. V. Teegavarapu, Jose D. Salas, Jery R. Stedinger, Introduction chapter, in ASCE Book on Statistical Analysis of Hydrologic Variables: Methods and Applications, 2019.
  • Elpida Kolokytha, Carlos Galvao, Ramesh S. V. Teegavarapu, Climate Change Impacts in Water Resources Management and Planning, Springer, Published, December 2016.
  • Ramesh S. V. Teegavarapu, Methods for Analysis of Trends and Change Detection, Elsevier (published), 2018.
  • Ramesh S. V. Teegavarapu, Analyzing Changes and Trends in Precipitation Extremes and Characteristics: Links to Climate Variability, Elsevier (published), 2018.
  • Ramesh S. V. Teegavarapu, Alejandra Schmidt, Trends and Variations in Global and Regional Sea Levels, Elsevier (published), 2018.
  • 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. Published.
  • Ramesh S. V. Teegavarapu, Precipitation and Climate Change, Floods in a Changing Climate, Cambridge University Press, UNESCO, International Hydrology Series, 2013. & 2018.
  • Ramesh S. V. Teegavarapu, Precipitation Measurement, Floods in a Changing Climate, Cambridge University Press, International Hydrology Series, 2013 & 2018.
  • Ramesh S. V. Teegavarapu, Spatial Analysis of Precipitation, Floods in a Changing Climate, Cambridge University Press, International Hydrology Series, 2013 & 2018.
  • Ramesh S. V. Teegavarapu, Extreme Precipitation and Floods, Floods in a Changing Climate, Cambridge University Press, International Hydrology Series, 2013 & 2018.
  • Ramesh S. V. Teegavarapu, Climate Change Modeling and Precipitation, Floods in a Changing Climate, Cambridge University Press, International Hydrology Series, 2013 & 2018.
  • Ramesh S. V. Teegavarapu, Precipitation Variability and Teleconnections, Floods in a Changing Climate, Cambridge University Press, International Hydrology Series, 2013 & 2018.
  • Ramesh S. V. Teegavarapu, Precipitation Trends, and Variability, Floods in a Changing Climate, International Hydrology Series, Cambridge University Press, 2013. & 2018.
  • Ramesh S. V. Teegavarapu and Co-authors Climate Change and Stationarity, Monograph/book “ Water Engineering Design Guidance in a Changing Climate, IAHR to be published in 2022.
  • Ramesh S. V. Teegavarapu and Co-authors Hydroclimatic Variability, Monograph/book “ Water Engineering Design Guidance in a Changing Climate, IAHR to be published in 2022.

Articles in Books

  • Ramesh S.V. Teegavarapu and Chandra Pathak, Development of Optimal Z-R Relationships, Weather Radar, and Hydrology, IAHS Red Book published by International Association of Hydrological Sciences, 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, Vol. 3, 2009, pp. 334-346.
  • 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, IAHS Red Book, 272, 2002, 257 – 262, Publication of International Association of Hydrological Sciences, United Kingdom.
  • 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.
  • 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
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