Articles | Volume 13, issue 1
Earth Syst. Sci. Data, 13, 83–97, 2021
https://doi.org/10.5194/essd-13-83-2021

Special issue: Linking landscape organisation and hydrological functioning:...

Earth Syst. Sci. Data, 13, 83–97, 2021
https://doi.org/10.5194/essd-13-83-2021
Data description paper
20 Jan 2021
Data description paper | 20 Jan 2021

EstSoil-EH: a high-resolution eco-hydrological modelling parameters dataset for Estonia

Alexander Kmoch et al.

Related authors

Teaching geoinformatics: challenges and opportunities
Evelyn Uuemaa and Alexander Kmoch
AGILE GIScience Ser., 3, 65, https://doi.org/10.5194/agile-giss-3-65-2022,https://doi.org/10.5194/agile-giss-3-65-2022, 2022
ML-based water quality modeling at national level in a data-scarce region
Holger Virro, Alexander Kmoch, Marko Vainu, and Evelyn Uuemaa
AGILE GIScience Ser., 3, 66, https://doi.org/10.5194/agile-giss-3-66-2022,https://doi.org/10.5194/agile-giss-3-66-2022, 2022
Applied open-source Discrete Global Grid Systems
Alexander Kmoch, Oleksandr Matsibora, Ivan Vasilyev, and Evelyn Uuemaa
AGILE GIScience Ser., 3, 41, https://doi.org/10.5194/agile-giss-3-41-2022,https://doi.org/10.5194/agile-giss-3-41-2022, 2022
GRQA: Global River Water Quality Archive
Holger Virro, Giuseppe Amatulli, Alexander Kmoch, Longzhu Shen, and Evelyn Uuemaa
Earth Syst. Sci. Data, 13, 5483–5507, https://doi.org/10.5194/essd-13-5483-2021,https://doi.org/10.5194/essd-13-5483-2021, 2021
Short summary

Related subject area

Pedology
A high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region based on circumpolar land cover upscaling
Juri Palmtag, Jaroslav Obu, Peter Kuhry, Andreas Richter, Matthias B. Siewert, Niels Weiss, Sebastian Westermann, and Gustaf Hugelius
Earth Syst. Sci. Data, 14, 4095–4110, https://doi.org/10.5194/essd-14-4095-2022,https://doi.org/10.5194/essd-14-4095-2022, 2022
Short summary
A repository of measured soil freezing characteristic curves: 1921 to 2021
Élise G. Devoie, Stephan Gruber, and Jeffrey M. McKenzie
Earth Syst. Sci. Data, 14, 3365–3377, https://doi.org/10.5194/essd-14-3365-2022,https://doi.org/10.5194/essd-14-3365-2022, 2022
Short summary
A compiled soil respiration dataset at different time scales for forest ecosystems across China from 2000 to 2018
Hongru Sun, Zhenzhu Xu, and Bingrui Jia
Earth Syst. Sci. Data, 14, 2951–2961, https://doi.org/10.5194/essd-14-2951-2022,https://doi.org/10.5194/essd-14-2951-2022, 2022
Short summary
New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau
Yueli Chen, Xingwu Duan, Minghu Ding, Wei Qi, Ting Wei, Jianduo Li, and Yun Xie
Earth Syst. Sci. Data, 14, 2681–2695, https://doi.org/10.5194/essd-14-2681-2022,https://doi.org/10.5194/essd-14-2681-2022, 2022
Short summary
SGD-SM 2.0: An Improved Seamless Global Daily Soil Moisture Long-term Dataset From 2002 to 2022
Qiang Zhang, Qiangqiang Yuan, Taoyong Jin, Meiping Song, and Fujun Sun
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-80,https://doi.org/10.5194/essd-2022-80, 2022
Revised manuscript accepted for ESSD
Short summary

Cited articles

Abbaspour, K. C., Vaghefi, S. A., Yang, H. and Srinivasan, R.: Global soil, landuse, evapotranspiration, historical and future weather databases for SWAT Applications, Sci. Data, 6, 263, https://doi.org/10.1038/s41597-019-0282-4, 2019. 
Abdelbaki, A. M.: Evaluation of pedotransfer functions for predicting soil bulk density for U.S. soils, Ain Shams Eng. J., 9, 1611–1619, https://doi.org/10.1016/j.asej.2016.12.002, 2018. 
Adams, W. A.: The Effect of Organic Matter on the bulk and true Densities of some Uncultivated Podzolic Soils, J. Soil Sci., 24, 10–17, https://doi.org/10.1111/j.1365-2389.1973.tb00737.x, 1973. 
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing area model of basin hydrology, Hydrol. Sci. B., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979. 
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001. 
Download
Short summary
The Soil Map of Estonia is the most detailed and information-rich dataset for soils in Estonia. But its information is not immediately usable for analyses or modelling. We derived parameters including soil layering, soil texture (clay, silt, and sand content), coarse fragments, and rock content and aggregated and predicted physical variables related to water and carbon cycles (bulk density, hydraulic conductivity, organic carbon content, available water capacity).