Maggioni, V. and C. Massari (Eds.), Extreme Hydroclimatic Events and Multivariate Hazards in a Changing Environment - A remote Sensing Approach, Elsevier, June 2019, Order here:

Book Chapters

  1. Maggioni, V., C. Massari, and C. Kidd. Errors and uncertainties associated with quasiglobal satellite precipitation products. In Michaelides (Ed.), Precipitation Science. Measurement, Remote Sensing, Microphysics and Modeling, Elsevier, November 2021.
  2. Massari, C. and V. Maggioni. Error and uncertainty characterization. In Levizzani, Kidd, Kirschbaum, Kummerow, Nakamura, Turk (Eds.), Satellite Precipitation Measurement, Springer, 2020.
  3. Kidd, C., S. Shige, D. Vila, E. Tarnavsky, M. Yamamoto, V. Maggioni, B. Maseko. The IPWG satellite precipitation validation effort. In Levizzani, Kidd, Kirschbaum, Kummerow, Nakamura, Turk (Eds.), Satellite Precipitation Measurement, Springer, 2020.
  4. Emelianenko M. and V. Maggioni. Mathematical Challenges in Measuring Variability Patterns For Precipitation Analysis. In Kaper and Fred (Eds.), Mathematics of Planet Earth: Protecting Our Planet, Learning from the Past, Safeguarding for the Future, Springer, 2019.
  5. Maggioni, V. and P.R. Houser. Soil Moisture Data Assimilation. In Park, Seon Ki, Xu, Liang (Eds.), Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III), Springer International Publishing Switzerland 2017; doi: 10.1006/978-3-319-43415-5_9.

Articles in Peer Refereed Journals

(undergraduate/graduate students and postdoctoral research fellows supervised by Dr. Maggioni are underlined)

  1. Kandasamy, J., Y. Xue, P. Houser, and V. Maggioni; 2023: Performance of Different Crop Models in Simulating Soil Temperature. Sensors, 23(6), p.2891.
  2. Li, Z., D. Wright, S. Hartke, D. Kirschbaum, V. Maggioni, P. Kirstetter, S. Khan, 2022: Toward A Globally-Applicable Uncertainty Quantification Framework for Satellite Multi-sensor Precipitation Products based on GPM DPR, IEEE Transactions on Geoscience and Remote Sensing (TGRS), 10.1109/TGRS.2023.3235270.
  3. Dollan, I., V. Maggioni, J. Johnston, G. de Almeida Coelho, J. Kinter, 2022: Seasonal Variability of Future Extreme Precipitation and Associated Trends across the Contiguous U.S., Frontiers in Climate, p. 195.
  4. Maina, F. Z., S. V. Kumar, I. J. Dollan, V. Maggioni Development and evaluation of ensemble consensus precipitation estimates over High Mountain Asia, 2022: Journal of Hydrometeorology, 10.1175/JHM-D-21-0196.1.
  5. Hartke, S., D. Wright, Z. Li, V. Maggioni, D. Kirschbaum, S. Khan, 2022: Ensemble Representation of Satellite Precipitation Uncertainty using an Uncalibrated, Nonstationary, Anisotropic Autocorrelation Model, Water Resources Research, e2021WR031650.
  6. de Almeida Coelho, G., C. Ferreira, J. Johnston, J. Kinter, I. Dollan, V. Maggioni, 2022: Potential Impacts of Future Extreme Precipitation Changes on Flood Engineering Design across the Contiguous United States, Water Resources Research, p.e2021WR031432.
  7. Xue, Y., P. Houser, V. Maggioni, Y. Mei, S. Kumar, Y. Yoon, 2022: Evaluation of High Mountain Asia - Land Data Assimilation System (version 1) from 2003 to 2016, Part II: The Impact of Assimilating Satellite-Based Snow Cover and Freeze/Thaw Observations into a Land Surface Model, Journal of Geophysical Research – Atmospheres, p.e2021JD035992.
  8. Sharif, R.B., P.R Houser, V. Aquila, and V. Maggioni, 2022: Investigating Rainfall Patterns in the Hubei Province, China and Northern Italy during the Covid-19 Lockdowns. Frontiers in Climate, p.193.
  9. Rahman, A., V. Maggioni, X. Zhang, P. Houser, T. Sauer, and, D. Mocko, 2022: The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model, Remote Sensing, 14, 437.
  10. Rahman, A., X. Zhang, P. Houser, T. Sauer, and V. Maggioni, 2021: Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model, Frontiers in Water – Water and Hydrocomplexity, p.200.
  11. Dollan, I., V. Maggioni, and J. Johnston, 2021: Investigating Temporal and Spatial Precipitation Patterns in the Southern Mid-Atlantic United States, Frontiers in Climate – Climate Services, 3: 799055.
  12. Zhang, X., V. Maggioni, P. Houser, Y. Xue, 2021: The Impact of Weather Condition on COVID-19 Transmission in the United States, Journal of Environmental Management, Vol. 302, 114085.
  13. Rouf, T., M. Girotto, P. Houser, and V. Maggioni, 2021: Assimilating Satellite-Based Soil Moisture Observations in a Land Surface Model: The Effect of Spatial Resolution, Journal of Hydrology X, 13, p. 100105.
  14. Mishra, S., S. Rupper, S. Kapnick, K. Casey, H. G. Chan, E. Ciraci, U. Haritashya, J. Hayse, J. Kargel, R. Kayastha, N. Krakauer, S. Kumar, R. Lammers, V. Maggioni, S. Margulis, M. Olson, B. Osmanoglu, Y. Qian, S. McLarty, K. Rittger, D. Rounce, D. Shean, I. Velicogna, T. Veselka, A. Arendt, 2021: Grand Challenges of Hydrologic Modeling for Food-Energy-Water Nexus Security in High Mountain Asia, Frontiers in Water – Water and Hydrocomplexity, p.123.
  15. Johnston, J., P. Houser, V. Maggioni, R. Sung Kim, and C. Vuyovich, 2021: Informing Improvements in Freeze/Thaw State Classification using sub-pixel Temperature, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2021.3099292.
  16. Nanding, N., H. Wu, N. Zhou, M. Huang, J. Tao, H. Beck, Z. Huang, V. Maggioni, 2021: Assessment of Precipitation Error Propagation in Discharge Simulations over the Contiguous United States, Journal of Hydrometeorology, accepted.
  17. Kidd, C., G. Huffman, V. Maggioni, P. Chambon, R. Oki, 2021: The Global Satellite Precipitation Constellation: current status and future requirements, Bulletin of the American Meteorological Society (BAMS), pp. 1–47.
  18. Falck, A., J. Tomasella, F. Diniz, V. Maggioni, 2021: Applying a precipitation error model to numerical weather predictions for probabilistic flood forecasts, Journal of Hydrology, 598, p.126374.
  19. Xue, Y., P. Houser, V. Maggioni, Y. Mei, S. Kumar, Y. Yoon, 2021: Evaluation of High Mountain Asia - Land Data Assimilation System (version 1) from 2003 to 2016, Part I: A hyper-resolution terrestrial modeling system, Journal of Geophysical Research – Atmospheres, 126 (8).
  20. Girotto, M., R. Reichle, M. Rodell, V. Maggioni, 2021: Data Assimilation of Terrestrial Water Storage Observations to Estimate Precipitation Fluxes: A Synthetic Experiment, Remote Sensing, 13, 1223.
  21. Zavareh, M., V. Maggioni, V. Sokolov, 2021: Investigating Water Quality Data Using Principal Component Analysis and Granger Causality, Water, 13(3), p.343.
  22. Rouf, T., V. Maggioni, Y. Mei, and P. Houser, 2021: Towards Hyper‐Resolution Land‐Surface Modeling of Surface and Root Zone Soil Moisture. Journal of Hydrology, 594, p.125945.
  23. Solakian, J., V. Maggioni, A. Godrej, 2020: On the Performance of Satellite-based Precipitation Products in Simulating Streamflow and Water Quality during Hydrometeorological Extremes, Frontiers in Environmental Science, 8:585451.
  24. Mei, Y., V. Maggioni, P. Houser, Y. Xue, and T. Rouf, 2020: A Nonparametric Statistical Technique for Spatial Downscaling of Precipitation over High Mountain Asia, Water Resources Research, 56, 11.
  25. Solakian, J., V. Maggioni, A. Godrej, A. Lodhi, 2020: Investigating the Error Propagation from Satellite-based Input Precipitation to Output Water Quality Indicators Simulated by a Hydrologic Model, Remote Sensing, 12, 3728.
  26. Maggioni, V., M. Girotto, E. Habib, M.A. Gallagher, 2020: Building an Online Learning Module for Satellite Remote Sensing Applications in Hydrologic Science, Remote Sensing – Special Issue on “Teaching and Learning in Remote Sensing”, 12, 3009.
  27. Rahman, A., X. Zhang, Y. Xue, P. Houser, T. Sauer, S. Kumar, D. Mocko, and V. Maggioni, 2020: A Synthetic Experiment to Investigate the Potential of Assimilating LAI through Direct Insertion in a Land Surface Model, Journal of Hydrology X, 9, p.100063.
  28. Zhang, X., V. Maggioni, A. Rahman, P. Houser, Y. Xue, T. Sauer, S. Kumar, and D. Mocko, 2020: The Influence of Assimilating Leaf Area Index in a Land Surface Model on Global Water Fluxes and Storages, Hydrology and Earth System Sciences, Vol. 24 (3775–3788).
  29. Johnston, J., V. Maggioni, and P. Houser, 2020: Comparing Global Passive Microwave Freeze/Thaw Records: Investigating Differences between Ka- and L-Band Products, Remote Sensing of the Environment, Vol. 247 (111936).
  30. Massari C., L. Brocca, T. Pellarin, G. Abramowitz, P. Filippucci, L. Ciabatta, V. Maggioni, Y. Kerr, and D. Fernandez Prieto, 2020: A daily/25 km short-latency rainfall product for data scarce regions based on the integration of the GPM IMERG Early Run with multiple satellite soil moisture products, Hydrology and Earth System Sciences, 24, pp 2687-2710.
  31. Khan, S. and V. Maggioni, 2020: Evaluating the Applicability of the PUSH Framework to Quasi-Global Infrared Precipitation Retrievals at 0.5°/Daily Spatial/Temporal Resolution, Asia-Pacific Journal of Atmospheric Sciences, 10.1007/s13143-020-00185-3.
  32. Di, Z., V. Maggioni, Y. Mei, M. Vazquez, P. Houser, M. Emelianenko, 2020: Centroidal Voronoi Tessellation Based Methods for Optimal Rain Gauge Location Prediction, Journal of Hydrology, accepted.
  33. Rouf, T., Y. Mei, V. Maggioni, P. Houser, M. Noonan, 2020: A physically-based atmospheric variables downscaling technique, Journal of Hydrometeorology, 21, 93–108.
  34. Solakian, J., V. Maggioni, A. Godrej, A. Lodhi, 2019: Investigating the Use of Satellite-based Precipitation Products for Monitoring Water Quality in the Occoquan Watershed, Journal of Hydrology: Regional Studies, 26, p.100630, doi: 10.1016/j.ejrh.2019.100630.
  35. Johnston, J., V. Maggioni, and P. Houser, 2019: Investigating the Relationship Between Satellite-Based Freeze/Thaw Products and Land Surface Temperature, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), doi: 10.1109/JSTARS.2019.2926942.
  36. Porcacchia, L., P.-E. Kirstetter, V. Maggioni, and S. Tanelli, 2019: Investigating the GPM Dual-Frequency Precipitation Radar Signatures of Low-Level Precipitation Enhancement, Quarterly Journal of the Royal Meteorological Society, 1-14, doi: 10.1002/qj.3611.
  37. Yoon, Y., S. Kumar, B. Forman, B. Zaitchik, Y. Kwon, Y. Qian, S. Rupper, V. Maggioni, P. Houser, D. Kirschbaum, A. Richey, A. Arendt, D. Mocko, J. Jacob, S. Bhanja, A. Mukherjee, 2019: Evaluating the uncertainty of terrestrial water budget components over High Mountain Asia, Frontiers in Earth Science, 7, p. 120, doi: 10.3389/feart.2019.00120.
  38. Xue, Y., P. Houser, V. Maggioni, Y. Mei, S. Kumar, Y. Yoon , 2019: Assimilation of Satellite-based Snow Cover and Freeze/Thaw Observations over High Mountain Asia, Frontiers in Earth Science – Cryospheric Sciences, doi: 10.3389/feart.2019.00115.
  39. Massari, C., V. Maggioni, S. Barbetta, L. Brocca, L. Ciabatta, S. Camici, T. Moramarco, G. Coccia, E. Todini, 2019: Complementing near-real time satellite rainfall products with satellite soil moisture-derived rainfall through a Bayesian inversion approach, Journal of Hydrology, 573 341-351.
  40. Khan, S., and V. Maggioni, 2019: Assessment of Level-3 gridded Global Precipitation Mission products over Oceans, Remote Sensing – Special Issue on "Remote Sensing of Precipitation”, 11(3), 255.
  41. Hazra, A., V. Maggioni, P. Houser, H. Antil, M. Noonan, 2019: A Monte Carlo-based multi-objective optimization approach to merge different precipitation estimates for land surface modeling, Journal of Hydrology, 570 454-462.
  42. Zavareh, M. and V. Maggioni, 2018: Application of Rough Set Theory to Water Quality Analysis: a Case Study, Data – Special Issue on "Overcoming Data Scarcity in Earth Science", 3(4), p.50.
  43. Falck, A., V. Maggioni, J. Tomasella, F. Diniz, Y. Mei, C. Beneti, D. Herdies, D. R. Neundorf, R. Caram, D. Rodriguez, 2018: Improving the use of ground-based radar rainfall data for monitoring and predicting floods in the Iguaçu river basin, Journal of Hydrology, 567 626–636.
  44. Khan S., V. Maggioni, P.-E. Kirstetter, 2018: Investigating the potential of using satellite-based precipitation radars as reference for evaluating multi-satellite merged products, Journal of Geophysical Research – Atmospheres, 123, 8646–8660.
  45. Oliveira R., V. Maggioni, D. Vila, L. Porcacchia, 2018: Using satellite error modeling to improve GPM-Level 3 rainfall, Remote SensingSpecial Issue onRemote Sensing Precipitation Measurement, Validation, and Applications”, 10(2), p.336.
  46. Porcacchia L., P.-E. Kirstetter, J. Gourley, V. Maggioni, B. Cheong, M. Anagnostou, 2018: Toward a polarimetric radar classification scheme for coalescence dominant precipitation: Application to complex terrain, Journal of Hydrometeorology, 18(12), pp.3199-3215.
  47. Maggioni, V. and C. Massari, 2018: On the performance of satellite precipitation products in riverine flood modeling: A review, Journal of Hydrology, 558, pp.214–224.
  48. Nikolopoulos, N., E. Destro, V. Maggioni, F. Marra, M. Borga, 2017: Satellite-rainfall estimates for debris flow prediction: An evaluation based on rainfall depth-duration thresholds, Journal of Hydrometeorology, 18(8), pp.2207-2214.
  49. Maggioni V., E. Nikolopoulos, E. Anagnostou, M. Borga, 2017: Modeling satellite precipitation errors over mountainous terrain: The influence of gauge density, seasonality, and temporal resolution, IEEE Transactions on Geoscience and Remote Sensing, 55(7), pp.4130-4140.
  50. Mousam A., V. Maggioni, P. Delamater, A. Quispe, 2017: Using remote sensing and modeling techniques to investigate the annual parasite incidence of malaria in Loreto, Peru, Advances in Water Resources, Special Issue on “Hydrology, water resources and the epidemiology of water-related diseases”, 108, pp.423-438.
  51. Tadesse, H., J. Qu, A. Aguirre, M. Komba, and V. Maggioni, 2017: Land use classification and analysis using radar data mining in Ethiopia. International Journal of Advanced Remote Sensing and GIS, 6(1), pp.2006-2022.
  52. Oliveira R., V. Maggioni, D. Vila, C. Morales, 2016: Characteristics and diurnal cycle of GPM rainfall estimates over the Central Amazon Region, Remote SensingSpecial Issue onUncertainties in Remote Sensing”, 8(7), p.544.
  53. Maggioni V., P. Meyers, M. Robinson, 2016: A review of merged high resolution satellite precipitation product accuracy during the Tropical Rainfall Measuring Mission (TRMM) – Era, Journal of Hydrometeorology – International Precipitation Working Group 7 Special Collection, 17(4), pp.1101-1117.
  54. Maggioni V., M. Sapiano, R. Adler, 2016: Estimating uncertainties in high-resolution satellite precipitation products: systematic or random error?, Journal of Hydrometeorology, 17(4), pp.1119-1129.
  55. Falck A., D. Vila, J. Tomasella, V. Maggioni, 2016: Evaluation of a multidimensional stochastic error model applied to satellite rainfall estimates, Brazilian Journal of Meteorology (Revista Brasileira de Meteorologia), 31(1), pp.52-63.
  56. Falck A., V. Maggioni, J. Tomasella, D. Vila, F. Diniz, 2015: Propagation of satellite precipitation uncertainties through a distributed hydrologic model: a case study in the Tocantins-Araguaia basin in Brazil, Journal of Hydrology, 527, pp.943–957.
  57. Maggioni V., M. Sapiano, R. Adler, Y. Tian, G.J. Huffman, 2014: An error model for uncertainty quantification in high-time resolution precipitation products, Journal of Hydrometeorology, 15(3), pp.1274–1292.
  58. Seyyedi H., E. Anagnostou, P.-E. Kirstetter, V. Maggioni, Y. Hong, J. Gourley, 2014: Incorporating surface soil moisture information in error modeling of TRMM passive microwave rainfall, IEEE Transactions on Geoscience and Remote Sensing, 52(10), pp.6226-6240.
  59. Vergara H.J., Y. Hong, J.J. Gourley, E.N. Anagnostou, V. Maggioni, D. Stampoulis and P.E. Kirstetter, 2013: Effects of resolution of satellite-based rainfall estimates on hydrologic modeling skill at different scales, Journal of Hydrometeorology, 15(2), pp.593-613.
  60. Maggioni V., H. Vergara, E. Anagnostou, J. Gourley, Y. Hong, and D. Stampoulis, 2013: Investigating the applicability of error correction ensembles of satellite rainfall products in river flow simulations, Journal of Hydrometeorology, 14(4), pp.1194-1211.
  61. Tian, Y., G. Huffman, R. Adler, L. Tang, M. Sapiano, V. Maggioni, and H. Wu, 2013: Modeling errors in daily precipitation measurements: additive or multiplicative?, Geophysical Research Letters, 40(10), pp.2060-2065.
  62. Maggioni, V., R. Reichle, and E. Anagnostou, 2012: The efficiency of assimilating satellite soil moisture retrievals in a land data assimilation system using different rainfall error models, Expedited Contributions - Journal of Hydrometeorology, 14(1), pp.368-374.
  63. Maggioni, V., E. Anagnostou, and R. Reichle, 2012: The impact of land model structural, parameter, and forcing errors on the characterization of soil moisture uncertainty, Hydrology and Earth System Sciences, 16, pp.3499-3515.
  64. Maggioni, V., R. Reichle, and E. Anagnostou, 2012: The impact of rainfall error characterization on the estimation of soil moisture fields in a land data assimilation system, Journal of Hydrometeorology, 13(3), pp.1107-1118.
  65. Maggioni, V., R. Reichle, and E. Anagnostou, 2011: The effect of satellite-rainfall error modeling on soil moisture prediction uncertainty, Journal of Hydrometeorology, 12(3), pp.413-428.
  66. Anagnostou, E., V. Maggioni, E. Nikolopoulos, T. Meskele, and F. Hossain, 2010: Benchmarking high-resolution global satellite rain products to radar and rain gauge rainfall estimates, IEEE Transactions on Geosciences and Remote Sensing, 48(4), pp.1667-1683.
  67. Serpetzoglou, E., E. Anagnostou, A. Papadopoulos, E. Nikolopoulos, and V. Maggioni, 2010: Error propagation of remote sensing rainfall estimates in soil moisture prediction from land surface model, Journal of Hydrometeorology, 11(3), pp.705–720.

Articles in Peer Refereed Conference Proceedings

  1. Zhang, X., V. Maggioni, A. Rahman, 2020: Investigating the assimilation of leaf area index products at different temporal resolutions in a land surface model, International Geoscience and Remote Sensing Symposium (IGARSS), IEEE Xplore, pp.3931-3934.
  2. Reagle C., V. Maggioni, M. Boicu, M. Albanese, M. Joshi, D. Sklarew, N. Peixoto, 2017: From idea to prototype: introducing students to entrepreneurship, IEEE Integrated STEM Education Conference (ISEC), pp. 71-75, IEEE.
  3. Khan S., V. Maggioni, L. Porcacchia, 2016: Uncertainties associated with the IMERG multi-satellite precipitation product, Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International, pp. 2127-2130, IEEE.
  4. Maggioni, V., R. Panciera, J.P. Walker, M. Rinaldi and V. Paruscio, 2006: A multi-sensor approach for high resolution airborne soil moisture mapping, 30th Hydrology and Water Resources Symposium [CD-ROM]. The Institute of Engineers Australia, Launceston, Australia, 4-8 December 2006, 6pp.


  1. Maggioni V., S. Upadhyaya, V. Petkovic and G. Mascaro, 2022: Editorial: A quest to fully understand precipitation: Novel methods to characterize, model, and detect precipitation processes, Frontiers in Climate, 4:992356.
  2. Roca, R, Z. Haddad, F. Akimoto, L. Alexander, A. Behrangi, G.Huffman, S. Kato, C. Kidd, P.-E. Kirstetter, T. Kubota, C. Kummerow, T. L’Ecuyer, V. Levizzani, V. Maggioni, C. Massari, H. Masunaga, M. Schröder, F. Tapiador, F. Turk, N. Utsumi, 2021: The Joint IPWG/GEWEX Precipitation Assessment, World Climate Research Program,
  3. Chambon, P. and V. Maggioni (coordinators, 20 authors), 2021: A review of the different operational applications of spaceborne precipitation radars within the International Precipitation Working Group (IPWG) community.
  4. Osmanoglu, B., D. Kirschbaum, V. Maggioni, S. Nicholls, 2018: NASA High Mountain Asia Team Precipitation Workshop Summary, The Earth Observer, vol. 30, no. 2, 27–30.