In situ surface soil water content and precipitation dataset from a preserved Caatinga area in the Brazilian semi-arid region

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Authors: Cloves Vilas Boas dos Santos, Josiclêda Domiciano Galvíncio, Rodrigo de Queiroga Miranda, Herica Fernanda de Sousa Carvalho, Alzira Gabrielle Soares Saraiva Souza, INAJÁ FRANCISCO DE SOUSA, M. S. B. de Moura
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Abstract

This dataset provides continuous time series of in-situ soil moisture and precipitation collected over a six-year period (2015–2020) in a preserved area of the Caatinga biome, located in the Brazilian semiarid region at the Embrapa Semiárido experimental field in Petrolina, Pernambuco, Brazil. The dataset contains essential hydrological observations for investigating ecohydrological processes in seasonally dry tropical ecosystems. Soil moisture was measured in situ at a depth of 5 cm, representing volumetric soil water content (m³/m³). Measurements include daily averaged values and two fixed daily observations recorded at 6:00 AM and 18:00 local time. Precipitation data correspond to daily accumulated rainfall (mm), measured using a rain gauge installed within the same experimental area to ensure spatial consistency between variables. Data are provided in a single CSV (comma separated values) file structured according to international formatting standards: comma-separated fields, decimal point, and dates in ISO 8601 format (YYYY-MM-DD). Each row represents one day of observation. Althought the dataset was primarily developed to support the validation of satellite-derived soil moisture products, its applicability extends to multiple research fields, including hydrology, remote sensing, ecology, hydrological modeling, climate change studies, and water resource management in semiarid environments. By making these measurements publicy available, this dataset contributes to reducing the scarcity of long term in situ observations from preserved Caatinga areas, a biome that remains underrepresented in global hydrological databases.

Fields of Study & Subjects

Soil Moisture and Remote Sensing Soil and Unsaturated Flow Hydrology and Watershed Management Studies

Publication details

Journal / source
Mendeley Data
Publication date
9 February 2026
Document type
Dataset