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In this paper, the coarse-scale (~28 km) European Space Agency (ESA) Climate ChangeClimate change Initiative (CCI)Climate Change Initiative (CCI) soil moistureSoil moisture product was downscaled to a high-resolution dataset (i.e., 1 km, 250 m, and 100 m) using high-resolution Sentinel-1 SARSensor Allow Researchers (SAR) data and the SMAP baseline downscaling approach. A comparison was made between the automatic weather station (AWS)Automatic Weather Stations (AWS) observed and downscaledDownscale soilSoil moistureSoil moisture results in ubRMSE (correlation coefficient (r)) of 0.090 m3/m3 (0.51), 0.100 m3/m3 (0.57), and 0.090 m3/m3 (0.61) at 1 km, 250 m, and 100 m resolutions, respectively. The comparison with field-observed dataset yields ubRMSE (r) values of 0.022 m3/m3 (0.57) and 0.032 m3/m3 (0.22) for soilSoil moisture estimates downscaled to 250 m and 100 m resolution, respectively. The downscaledDownscale soil moistureSoil moisture estimates are in good agreement with the in situ measurement and AWSAutomatic Weather Stations (AWS) observed soilSoil moisture. Thus, the result obtained in this study is quite promising and indicates the potential of the Sentinel-1 SARSensor Allow Researchers (SAR) data and the downscaling algorithm to disaggregate the coarse-resolution soil moistureSoil moisture to finer scales in the Abbay River BasinAbbay River Basin in EthiopiaEthiopia.

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Downscaling ESA CCI Soil Moisture Using Sentinel-1 SAR Data: A Case Study in the Abbay River Basin in Ethiopia

  • 章节

  • 发表日期：

    2025年

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  • Getachew Tesfaye Ayehu,
  • Wuletawu Abera,
  • Degefie Tibebe,
  • Yonas Getaneh,
  • Lulseged Tamene

摘要

In this paper, the coarse-scale (~28 km) European Space Agency (ESA) Climate ChangeClimate change Initiative (CCI)Climate Change Initiative (CCI) soil moistureSoil moisture product was downscaled to a high-resolution dataset (i.e., 1 km, 250 m, and 100 m) using high-resolution Sentinel-1 SARSensor Allow Researchers (SAR) data and the SMAP baseline downscaling approach. A comparison was made between the automatic weather station (AWS)Automatic Weather Stations (AWS) observed and downscaledDownscale soilSoil moistureSoil moisture results in ubRMSE (correlation coefficient (r)) of 0.090 m3/m3 (0.51), 0.100 m3/m3 (0.57), and 0.090 m3/m3 (0.61) at 1 km, 250 m, and 100 m resolutions, respectively. The comparison with field-observed dataset yields ubRMSE (r) values of 0.022 m3/m3 (0.57) and 0.032 m3/m3 (0.22) for soilSoil moisture estimates downscaled to 250 m and 100 m resolution, respectively. The downscaledDownscale soil moistureSoil moisture estimates are in good agreement with the in situ measurement and AWSAutomatic Weather Stations (AWS) observed soilSoil moisture. Thus, the result obtained in this study is quite promising and indicates the potential of the Sentinel-1 SARSensor Allow Researchers (SAR) data and the downscaling algorithm to disaggregate the coarse-resolution soil moistureSoil moisture to finer scales in the Abbay River BasinAbbay River Basin in EthiopiaEthiopia.