Self-organizing map of soil properties in the context of hydrological modeling

David Rivas-Tabares*, Ángel de Miguel, Bárbara Willaarts, Ana M. Tarquis

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)


One of the most relevant inputs for hydrological modeling is the soil map. The soil sources and scales for the soil properties are diverse, and the quality of soil mapping is increasing, but soil surveying is time-consuming and large area campaigns are expensive. The taxonomic unit approach for soil mapping is common and limited to one layer of data. This limitation causes errors in simulated water fluxes through the soil when taxonomic units approach is implemented during hydrological modeling analysis. Some strategies using geostatistics and machine learning algorithms such as Kriging and Self-Organizing maps (SOM) are improving the taxonomic units’ approach and could serve as an alternative for soil mapping for hydrological purposes. The aim of this work is to study the influence of different soil maps and resolutions on the main hydrological components of a sub-arid watershed in central Spain. For this, the Soil Water and Assessment Tool (SWAT) was parameterized with three different soil maps. A first one was based on Harmonized World Soil database from FAO, at scale 1:1,000,000 (HWSD). The other two were based on a Kriging interpolation at 100 × 100 m from soil samples. To obtain soil properties map from it, two strategies were applied: one was to average the soil properties following the official taxonomic soil units at 1:400,000 scale (Agricultural Technological Institute of Castilla and Leon - ITACyL) and the other was to applied Self-organizing map (SOM) to create the soil units (SOMM). The results suggest that scale and soil properties mapping influence HRU definition, which in turn affects water flow through the soils. Statistical metrics of model performance were improved from R2 =0.62 and NSE=0.46 with HWSD soil map to R2 =0.86 and NSE=0.84 with SOM and similar values were achieved during validation. Thus, the SOM is presented as an innovative algorithm applied for hydrological modeling with SWAT, significantly increasing the level of model accuracy to stream flow in sub-arid watersheds.

Original languageEnglish
Pages (from-to)175-189
JournalApplied mathematical modelling
Publication statusPublished - Dec 2020


  • Hydrological modeling
  • Self-organizing Maps
  • Soil properties
  • Soils spatial patterns
  • SOM
  • SWAT


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