In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. 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 the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) 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 land use is available for 76ĝ€% of the experimental sites with agricultural land use as the dominant type (∼40%). We are convinced that the SWIG database will allow for a better parameterization 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 public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.
Bibliographical noteFunding Information:
The support of the Slovak Research and Development Agency through project no. APVV-15-0160 is acknowledged.
First author thanks the International and Scientific Cooperation Office of the University of Maragheh, Iran, as well as the research committee and board members of the university for their assistance in conducting the current work. The financial support received from the Forschungszentrum Jülich GmbH is gratefully acknowledged by the first author. Authors gratefully thank the International Soil Modeling Consortium (ISMC) and the International Soil Tillage Research Organization (ISTRO) for their help in distributing our call for data among researchers throughout the world. Parts of data were gathered from the work that was supported by the UK-China Virtual Joint Centre for Improved Nitrogen Agronomy (CINAg, BB/N013468/1), which is jointly supported by the Newton Fund, via UK BBSRC and NERC. The French Claduègne and Yzeron datasets were acquired during the ANR projects FloodScale (ANR-2011-BS56-027) and AVuUR (ANR-07-VULN-01), respectively. Parts of the database were made available through research work carried out in the framework of LIFEC projects funded by the EC. The support of the Spanish Ministry of Economy through project CGL2014-53017-C2-1-R is acknowledged. The support of the Czech Science Foundation through project no. 16-05665S is acknowledged. The support of the Slovak Research and Development Agency through project no. APVV-15-0160 is acknowledged. Authors are grateful to Atilla Nemes, Jan W. Hopmans, and Marnik Vanclooster for their time and attention in reviewing and commenting on this article.
Parts of the database were made available through research work carried out in the framework of LIFE+ projects funded by the EC.
The financial support received from the Forschungszentrum Jülich GmbH is gratefully acknowledged by the first author.
The support of the Czech Science Foundation through project no. 16-05665S is acknowledged.
© Author(s) 2018.