文章基本信息

标题：EstSoil-EH: a high-resolution eco-hydrological modelling parameters dataset for Estonia
本地全文：下载
作者：Alexander Kmoch ; Arno Kanal ; Alar Astover 等
期刊名称：Earth System Science Data Discussions
电子版ISSN：1866-3591
出版年度：2021
卷号：13
期号：1
页码：83-97
DOI：10.5194/essd-13-83-2021
语种：English
出版社：Copernicus Publications
摘要：To understand, model, and predict landscape evolution, ecosystem services, and hydrological processes, the availability of detailed observation-based soil data is extremely valuable. For the EstSoil-EH dataset, we synthesized more than 20 eco-hydrological variables on soil, topography, and land use for Estonia (https://doi.org/10.5281/zenodo.3473289, Kmoch et al., 2019a) as numerical and categorical values from the original Soil Map of Estonia, the Estonian 5 m lidar DEM, Estonian Topographic Database, and EUSoilHydroGrids layers. The Soil Map of Estonia maps more than 750 000 soil units throughout Estonia at a scale of 1 : 10 000 and forms the basis for EstSoil-EH. It is the most detailed and information-rich dataset for soils in Estonia, with 75 % of mapped units smaller than 4.0 ha, based on Soviet-era field mapping. For each soil unit, it describes the soil type (i.e. soil reference group), soil texture, and layer information with a composite text code, which comprises not only the actual texture class, but also classifiers for rock content, peat soils, distinct compositional layers, and their depths. To use these as eco-hydrological process properties in modelling applications we translated the text codes into numbers. The derived parameters include soil layering, soil texture (clay, silt, and sand contents), coarse fragments, and rock content of the soil layers within the soil profiles. In addition, we aggregated and predicted physical variables related to water and carbon cycles (bulk density, hydraulic conductivity, organic carbon content, available water capacity). The methodology and dataset developed will be an important resource for the Baltic region, but possibly also for all other regions where detailed field-based soil mapping data are available. Countries like Lithuania and Latvia have similar historical soil records from the Soviet era that could be turned into value-added datasets such as the one we developed for Estonia.