EGU22-10457
https://doi.org/10.5194/egusphere-egu22-10457
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

A Statistical Downscaling Approach of Soil Moisture Estimations by Synergistically using Optical Remote Sensing and Ground Soil Moisture Measurements at the Valencia Anchor Station

Abdolreza Ansari Amoli1,2, Ali Mahmoodi3, and Ernesto Lopez-Baeza2,4
Abdolreza Ansari Amoli et al.
  • 1Remote Sensing & GIS Department, Iranian Space Agency, Tehran, Islamic Republic of Iran (abdolreza.ansari@gmail.com)
  • 2Environmental Remote Sensing Group (Climatology from Satellites), Earth Physics & Thermodynamics Department, Faculty of Physics, University of Valencia, Valencia, Spain (anab@alumni.uv.es), (Ernesto.Lopez@uv.es)
  • 3Centre d’Etudes Spatiales de la Biosphere (CNRS, IRD, CNES, Université de Toulouse), Toulouse, France (mahmoodi.ca@gmail.com)
  • 4Albavalor S.L.U. University of Valencia Science Park, Paterna, Valencia, Spain (elopezbaeza@albavalor.es)

A multifractal technique has been used to downscale 1 km optical remote sensing MODIS derived soil moisture index (SMI) to the scale of interpolated soil moisture map produced by ground measurements at the Valencia Anchor Station (VAS) during the SMOS Validation Rehearsal Campaign (2008) with the spatial resolution of 32 meters. Scale invariance assessment shows a constant behavior of soil moisture variability at all scales of aggregation. This result proves the homogeneity of the VAS region from a mathematical point of view and exempts or allows us from using ancillary data such as topography, soil texture and vegetation characteristics in our downscaling model. Our predicted soil moisture values compared to the observed ground data show RMSE ranges from 0.026 to 0.039 for 2008/05/02, indicating accurate predictions for this date. However, there are high RMSE values in the range of 0.761 to 0.784 for 2008/04/24, due to rainfall events (30 mm accumulated) occurring in the region a few days prior to the measurements, which influenced the result of the downscaling model. At the same time, the strong correlation (77%) between the predicted and the observed data is promising and warrants further application of the model to other homogeneous areas with or without rainfall events.

How to cite: Ansari Amoli, A., Mahmoodi, A., and Lopez-Baeza, E.: A Statistical Downscaling Approach of Soil Moisture Estimations by Synergistically using Optical Remote Sensing and Ground Soil Moisture Measurements at the Valencia Anchor Station, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10457, https://doi.org/10.5194/egusphere-egu22-10457, 2022.

Displays

Display link