Dieses Bild zeigt Peyman Saemian

Peyman Saemian

Herr Dr.-Ing.

Akademischer Mitarbeiter
Geodätisches Institut

Kontakt

+49 711 685 83419
+49 711 685 83285

Geschwister-Scholl-Str. 24D
70174 Stuttgart
Deutschland
Raum: 5.349

  1. 2023

    1. Tourian, M. J., Saemian, P., Ferreira, V. G., Sneeuw, N., Frappart, F., & Papa, F. (2023). A copula-supported Bayesian framework for spatial downscaling of GRACE-derived terrestrial water storage flux. Remote Sensing of Environment, 295, 113685. https://doi.org/10.1016/j.rse.2023.113685
    2. Foster, J., Tourian, M. J., Saemian, P., & Deng, X. (2023). Alexander von Humboldt-Stiftung  Netzwerktagung am Geodätischen Institut der Universität Stuttgart.
    3. Yi, S., Saemian, P., Sneeuw, N., & Tourian, M. (2023). Estimating runoff from pan-Arctic drainage basins for 2002-2019 using and improved runoff-storage relationship. The 8th Youth Geoscience Forum, Wuhan, China.
    4. Yi, S., Saemian, P., Sneeuw, N., & Tourian, M. (2023). Estimating runoff from pan-Arctic drainage basins for 2002-2019 using and improved runoff-storage relationship (2). Workshop on Geodesy and Climate Change, Zhuhai, China.
    5. Yi, S., Saemian, P., Sneeuw, N., & Tourian, M. J. (2023). Estimating runoff from pan-Arctic drainage basins for 2002–2019 using an improved runoff-storage relationship. Remote Sensing of Environment, 298, 1–23. https://doi.org/10.1016/j.rse.2023.113816
    6. Yi, S., Saemian, P., Sneeuw, N., & Tourian, M. J. (2023). Estimating runoff from pan-Arctic drainage basins for 2002–2019 using an improved runoff-storage relationship. Remote Sensing of Environment, 298, 113816. https://doi.org/10.1016/j.rse.2023.113816
    7. Elmi, O., Tourian, M. J., Saemian, P., & Sneeuw, N. (2023). Extending river discharge time series of the Global Runoff Data Center (GRDC) using satellite data: A product with uncertainty estimate. Hydrospace 2023, Lisbon, Portugal.
    8. Elmi, O., Tourian, M. J., Saemian, P., Papa, F., & Sneeuw, N. (2023). Long Term Analysis of Global Surface Water Volume Change Using Remote Sensing Data. Hydrospace 2023, Lisbon, Portugal.
  2. 2022

    1. Saemian, P., Tourian, M. J., & Sneeuw, N. (2022). A least-squares collocation approach to densifying river level from multi-mission satellite altimetry; Case study Mackenzie River basin. EGU 2022, Vienna, Austria.
    2. Ghajarnia, N., Akbari, M., Saemian, P., Ehsani, M. R., Hosseini-Moghari, S.-M., Azizian, A., Kalantari, Z., Behrangi, A., Tourian, M. J., Klöve, B., & Haghighi, A. T. (2022). Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5. https://doi.org/10.31223/x5bp6p
    3. Ghajarnia, N., Akbari, M., Saemian, P., Ehsani, M. R., Hosseini-Moghari, S.-M., Azizian, A., Kalantari, Z., Behrangi, A., Tourian, M. J., Klöve, B., & Haghighi, A. T. (2022). Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5. Earth and Space Science, 9(10), Article 10. https://doi.org/10.1029/2022EA002352
    4. Saemian, P., Tourian, M. J., AghaKouchak, A., Madani, K., & Sneeuw, N. (2022). How much water did Iran lose over the last two decades? Journal of Hydrology: Regional Studies, 41, 101095. https://doi.org/10.1016/j.ejrh.2022.101095
    5. Tourian, M. J., Elmi, O., Shafaghi, Y., Behnia, S., Saemian, P., Schlesinger, R., & Sneeuw, N. (2022). HydroSat: geometric quantities of the global water cycle from geodetic satellites. Earth System Science Data. https://doi.org/10.5194/essd-14-2463-2022
    6. Douch, K., Saemian, P., & Sneeuw, N. (2022). Identification of conceptual rainfall-runoff models of large drainage basins based on GRACE and in-situ data. EGU 2022, Vienna, Austria.
    7. Douch, K., Sneeuw, N., & Saemian, P. (2022). Identification of lumped rainfall-runoff models of large drainage basins for satellite data assimilation. ESA Living Planet Symposium 2022, Bonn, Germany.
    8. Behling, R., Roessner, S., Foerster, S., Saemian, P., Tourian, M. J., Portele, T. C., & Lorenz, C. (2022). Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series. Scientific Reports, 12(1), Article 1. https://doi.org/10.1038/s41598-022-24712-6
    9. Saemian, P., Tourian, M. J., Douch, K., & Sneeuw, N. (2022). Long-term Total Water Storage Anomalies Over Land Using GRACE observations, Models, and data-driven method. Frontiers of Geodetic Science, Essen.
  3. 2021

    1. Douch, K., Saemian, P., & Sneeuw, N. (2021). A state-space representation of the water storage dynamics at basin scale to do hydrology backward. https://iccc.iag-aig.org/iccc-workshops/ws21
    2. Saemian, P., Hosseini-Moghari, S.-M., Fatehi, I., Shoarinezhad, V., Modiri, E., Tourian, M. J., Tang, Q., Nowak, W., Bárdossy, A., & Sneeuw, N. (2021). Comprehensive evaluation of precipitation datasets over Iran. Journal of Hydrology, 603, 1–23. https://doi.org/10.1016/j.jhydrol.2021.127054
    3. Douch, K., Saemian, P., & Sneeuw, N. (2021). Data-driven and physically informed modelling of the Terrestrial Water Storage dynamics. https://doi.org/10.5194/egusphere-egu21-15253
    4. Saemian, P., Tourian, M. J., & Sneeuw, N. (2021). Estimation of sub-monthly discharge over Arctic rivers through satellite altimetry: case study Mackenzie River. Frontiers of Geodetic Science digital 2021, Hannover.
    5. Tourian, M. J., Elmi, O., Shafaghi, Y., Behnia, S., Saemian, P., Schlesinger, R., & Sneeuw, N. (2021). HydroSat: a repository of global water cycle products from spaceborne geodetic sensors. https://doi.org/10.5194/essd-2021-174
  4. 2020

    1. Saemian, P., Elmi, O., Vishwakarma, B., Tourian, M., & Sneeuw, N. (2020). Analyzing the Lake Urmia restoration progress using ground-based and spaceborne observations. Science of The Total Environment, 139857. https://doi.org/10.1016/j.scitotenv.2020.139857
  5. 2019

    1. Saemian, P., Hashemi Farahani, H., & Sneeuw, N. (2019). A comprehensive assessment of GRACE decorrelating filters for hydrological applications.
    2. Purkhauser, A., Pail, R., Hauk, M., Visser, P., Sneeuw, N., Saemian, P., Liu, W., Engels, J., Chen, Q., Siemes, C., Haagmans, R., & Massotti, L. (2019). Comprehensive analysis of the influence of different parameters on the achievable gravity fields of NGGM: Results of the ESA-ADDCON project.
    3. Sneeuw, N., & Saemian, P. (2019). Next-Generation Gravity Missions for Drought Monitoring. https://www.gis.uni-stuttgart.de/forschung/doc/Saemian_2019.pdf
  6. 2018

    1. Purkhauser, A., Pail, R., Hauk, M., Visser, P., Sneeuw, N., Saemian, P., Liu, W., Engels, J., Chen, Q., & Siemes, C. (2018). Gravity Field Retrieval of Next Generation Gravity Missions regarding Geophysical Services: Results of the ESA-ADDCON Project.
  7. 2017

    1. Daras, I., Visser, P., Sneeuw, N., van Dam, T., Pail, R., Gruber, T., Tabibi, S., Chen, Q., Liu, W., Tourian, M. J., Engels, J., Saemian, P., Siemes, C., & Haagmans, R. (2017). Impact of Orbit Design Choices on the Gravity Field Retrieval of Next Generation Gravity Missions - Insights on the ESA-ADDCON Project.
    2. Daras, I., Visser, P., Sneeuw, N., van Dam, T., Pail, R., Gruber, T., Chen, Q., Liu, W., Tourian, M. J., Engels, J., Saemian, P., Siemes, C., & Haagmans, R. (2017). Near real-time gravity and its applications in the era of Next Generation Gravity Missions - Insights on the ESA-ADDCON project.
    3. Pail, R., Hauk, M., Purkhauser, A., Visser, P., Sneeuw, N., van Dam, T., Gruber, T., Chen, Q., Liu, W., Tourian, M. J., Engels, J., Saemian, P., Siemes, C., & Haagmans, R. (2017). Studies on next-generation gravity missions for climate-relevant applications.
    4. Saemian, P., Elmi, O., Vishwakarma, B. D., Tourian, M. J., & Sneeuw, N. (2017). The desiccating Lake Urmia is restoring: A multisensor approach to investigate natural and human-induced reasons for increase of lake volume after 2014.
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