dataset · Zenodo (CERN European Organization for Nuclear Research)
A dedicated reference dataset has been compiled to document surface soil moisture across irrigated agricultural lands in central-western Morocco. The collection contains 1,204 georeferenced in situ measurements obtained between December 2024 and March 2026, aligned with overpasses from the Sentinel-1, Sentinel-2, and Landsat 8/9 satellites. Field observations cover both drip and flood irrigation schemes and incorporate volumetric soil moisture, temperature, and electrical conductivity alongside field photos and soil texture attributes. Sensor readings were calibrated against gravimetric reference standards across specific soil classes, yielding post-calibration root mean square errors of 2.40 percent volume for loam and sandy clay loam, and 3.37 percent volume for clay loam. The dataset integrates comprehensive quality control metrics, including checks on physical measurement ranges, completeness, and within-pixel consistency, with over 99 percent of records meeting verification standards.
Accurate satellite monitoring of agricultural water requires dependable ground data. By precisely matching ground-level soil moisture, temperature, and texture to satellite overpasses, this dataset offers verified reference benchmarks. This helps scientists and Earth observation specialists test, calibrate, and enhance satellite-derived soil moisture algorithms over varied irrigation systems in semi-arid environments.
The dataset serves as foundational calibration and validation data for developers of satellite-based Earth observation analytics and agricultural water monitoring tools. Because the abstract details a validated reference dataset rather than a software platform or commercial service, it is early-stage research data that could inform applied irrigation and precision agriculture solutions.
AI-generated from the published abstract. Always read the original work before citing.
This dataset provides 1,204 georeferenced in situ surface soil moisture measurements collected across irrigated agricultural areas in central-western Morocco. Measurements were acquired using the Delta-T Devices WET150 sensor under two irrigation systems: 470 observations from drip irrigated fields and 734 observations from flood irrigated fields. Field campaigns were coordinated with Sentinel-1, Sentinel-2, and Landsat 8/9 satellite overpasses across 25 acquisition dates between December 2024 and March 2026. The dataset contains 581 observations associated with Sentinel-1, 645 with Sentinel-2, and 446 with Landsat 8/9. Some field campaigns correspond to more than one satellite platform. Each observation includes volumetric surface soil moisture, soil temperature, pore-water electrical conductivity (ECp), geographic coordinates, sampling date and time, irrigation type, land-cover information, field photographs, and soil-texture attributes. Soil texture was characterized using SoilGrids 2.0 sand, silt, and clay fractions for the 0–5 cm depth interval. The WET150 soil-moisture measurements were calibrated against gravimetric reference measurements using soil-specific calibration relationships. Calibration A was developed for loam and sandy clay loam soils using 38 paired samples, while Calibration B was developed for clay loam soil using 19 paired samples. Post-calibration RMSE was 2.40 %vol for loam and sandy clay loam soils and 3.37 %vol for clay loam soil. The following QC and diagnostic columns are included: record_qc_flag: Indicates whether all required information and expected WET150 replicate measurements are available for the observation. record_qc_reason: Provides the reason when a record fails the completeness check. Overall, 1,197 records (99.4%) passed, while 7 records (0.6%) contained one or more missing required measurements. sm_physical_flag: Physical-range QC result for soil moisture. Values below 0 %vol or above 100 %vol were considered invalid, while values above 60 %vol were flagged as suspect. temp_physical_flag: Indicates whether the recorded soil temperature falls within the accepted physical range. ecp_physical_flag: Indicates whether pore-water electrical conductivity (ECp) falls within the accepted physical range. physical_qc_flag: Combined physical-range QC result for the observation. Overall, 1,203 records (99.9%) passed the physical-range checks and one record (0.1%) was flagged as suspect. sm_range: Available for flood-irrigated observations. Represents the difference between the maximum and minimum of the three WET150 soil-moisture replicate measurements collected within the target pixel. flood_consistency_flag: Indicates whether within-pixel variability for flood-irrigated observations exceeds the empirical consistency threshold of 9.0 %vol. sm_diff_under: For drip-irrigated observations, represents the absolute difference between the two soil-moisture measurements collected under the drip lines. sm_diff_between: Represents the absolute difference between the two soil-moisture measurements collected between the drip lines. under_consistency_flag: Indicates whether sm_diff_under exceeds the 7.2 %vol consistency threshold. between_consistency_flag: Indicates whether sm_diff_between exceeds the 9.4 %vol consistency threshold. within_pixel_qc_flag: Provides the overall within-pixel consistency status. For drip irrigation, an observation is flagged as suspect when either the under-drip or between-drip difference exceeds its corresponding threshold. calibration_qc_flag: Indicates whether the WET150 soil-moisture measurement lies within the empirical range represented by the corresponding soil-specific calibration dataset or requires extrapolation beyond that range.
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DOI: 10.5281/zenodo.21997814
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