Rahmati, Mehdi; Weihermüller, Lutz; Vereecken, Harry (2018): Soil Water Infiltration Global (SWIG) Database [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.885492,

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Supplement to: Rahmati, M et al. (2018): Development and Analysis of Soil Water Infiltration Global Database. Earth System Science Data

In this database we present and analyze a global database of soil infiltration measurements, Soil Water Infiltration Global (SWIG) database, for the first time. In total, 5023 infiltration curves were collected across all continents. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and USA. In addition to its global spatial coverage, the collected infiltration curves cover a time span of research from 1976 to late 2017. In addition to infiltration data, basic information of the measurement location, the measurement method, soil properties, and land use were collected, which makes the database valuable for the development of pedo-transfer functions for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (~76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on the land use is available for 76 % of experimental sites with agricultural land use as the dominant type (~40%). We are convinced that the SWIG database will allow for a better parametrization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for use by public domain only and can be copied freely by referencing it. Data quality assessment is strongly advised prior to any use of this database. New data are welcomed to extend/update SWIG.