Details
| Original language | English |
|---|---|
| Pages (from-to) | 1237-1263 |
| Number of pages | 27 |
| Journal | Earth system science data |
| Volume | 10 |
| Issue number | 3 |
| Publication status | Published - 10 Jul 2018 |
| Externally published | Yes |
Abstract
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.
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)
- General Earth and Planetary Sciences
Sustainable Development Goals
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In: Earth system science data, Vol. 10, No. 3, 10.07.2018, p. 1237-1263.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Development and analysis of the Soil Water Infiltration Global database
AU - Rahmati, Mehdi
AU - Weihermueller, Lutz
AU - Vanderborght, Jan
AU - Pachepsky, Yakov A.
AU - Mao, Lili
AU - Sadeghi, Seyed Hamidreza
AU - Moosavi, Niloofar
AU - Kheirfam, Hossein
AU - Montzka, Carsten
AU - Van Looy, Kris
AU - Toth, Brigitta
AU - Hazbavi, Zeinab
AU - Al Yamani, Wafa
AU - Albalasmeh, Ammar A.
AU - Alghzawi, Ma'in Z.
AU - Angulo-Jaramillo, Rafael
AU - Dantas Antonino, Antonio Celso
AU - Arampatzis, George
AU - Armindo, Robson Andre
AU - Asadi, Hossein
AU - Bamutaze, Yazidhi
AU - Batlle-Aguilar, Jordi
AU - Bechet, Beatrice
AU - Becker, Fabian
AU - Blöschl, Günter
AU - Bohne, Klaus
AU - Braud, Isabelle
AU - Castellano, Clara
AU - Cerda, Artemi
AU - Chalhoub, Maha
AU - Cichota, Rogerio
AU - Cislerova, Milena
AU - Clothier, Brent
AU - Coquet, Yves
AU - Cornelis, Wim
AU - Corradini, Corrado
AU - Coutinho, Artur Paiva
AU - de Oliveira, Muriel Bastista
AU - de Macedo, Jose Ronaldo
AU - Duraes, Matheus Fonseca
AU - Emami, Hojat
AU - Eskandari, Iraj
AU - Farajnia, Asghar
AU - Flammini, Alessia
AU - Fodor, Nandor
AU - Gharaibeh, Mamoun
AU - Ghavimipanah, Mohamad Hossein
AU - Ghezzehei, Teamrat A.
AU - Giertz, Simone
AU - Hatzigiannakis, Evangelos G.
AU - Horn, Rainer
AU - Jimenez, Juan Jose
AU - Jacques, Diederik
AU - Keesstra, Saskia Deborah
AU - Kelishadi, Hamid
AU - Kiani-Harchegani, Mahboobeh
AU - Kouselou, Mehdi
AU - Jha, Madan Kumar
AU - Lassabatere, Laurent
AU - Li, Xiaoyan
AU - Liebig, Mark A.
AU - Lichner, Lubomir
AU - Victoria Lopez, Maria
AU - Machiwal, Deepesh
AU - Mallants, Dirk
AU - Mallmann, Micael Stolben
AU - de Oliveira Marques, Jean Dalmo
AU - Marshall, Miles R.
AU - Mertens, Jan
AU - Meunier, Felicien
AU - Mohammadi, Mohammad Hossein
AU - Mohanty, Binayak P.
AU - Pulido-Moncada, Mansonia
AU - Montenegro, Suzana
AU - Morbidelli, Renato
AU - Moret-Fernandez, David
AU - Moosavi, Ali Akbar
AU - Mosaddeghi, Mohammad Reza
AU - Mousavi, Seyed Bahman
AU - Mozaffari, Hasan
AU - Nabiollahi, Kamal
AU - Neyshabouri, Mohammad Reza
AU - Ottoni, Marta Vasconcelos
AU - Ottoni Filho, Theophilo Benedicto
AU - Pahlavan-Rad, Mohammad Reza
AU - Panagopoulos, Andreas
AU - Peth, Stephan
AU - Peyneau, Pierre-Emmanuel
AU - Picciafuoco, Tommaso
AU - Poesen, Jean
AU - Pulido, Manuel
AU - Reinert, Dalvan Jose
AU - Reinsch, Sabine
AU - Rezaei, Meisam
AU - Roberts, Francis Parry
AU - Robinson, David
AU - Rodrigo-Comino, Jesus
AU - Filho, Otto Correa Rotunno
AU - Saito, Tadaomi
AU - Suganuma, Hideki
AU - Saltalippi, Carla
AU - Sandor, Renata
AU - Schütt, Brigitta
AU - Seeger, Manuel
AU - Sepehrnia, Nasrollah
AU - Moghaddam, Ehsan Sharifi
AU - Shukla, Manoj
AU - Shutaro, Shiraki
AU - Sorando, Ricardo
AU - Stanley, Ajayi Asishana
AU - Strauss, Peter
AU - Su, Zhongbo
AU - Taghizadeh-Mehrjardi, Ruhollah
AU - Taguas, Encarnacion
AU - Teixeira, Wenceslau Geraldes
AU - Vaezi, Ali Reza
AU - Vafakhah, Mehdi
AU - Vogel, Tomas
AU - Vogeler, Iris
AU - Votrubova, Jana
AU - Werner, Steffen
AU - Winarski, Thierry
AU - Yilmaz, Deniz
AU - Young, Michael H.
AU - Zacharias, Steffen
AU - Zeng, Yijian
AU - Zhao, Ying
AU - Zhao, Hong
AU - Vereecken, Harry
N1 - Funding 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.
PY - 2018/7/10
Y1 - 2018/7/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85049846331&partnerID=8YFLogxK
U2 - 10.5194/essd-10-1237-2018
DO - 10.5194/essd-10-1237-2018
M3 - Article
VL - 10
SP - 1237
EP - 1263
JO - Earth system science data
JF - Earth system science data
SN - 1866-3508
IS - 3
ER -