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Updated: Aug 23, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Multiorder hydrologic Position for Europe - a Set of Features for Machine Learning and Analysis in Hydrology
Maximilian Nölscher1, Michael Mutz2, Stefan Broda3
1Federal Institute for Geosciences and Natural Resources (BGR), Berlin, 13593, Germany. max-n@posteo.de.
Abstract:
The presented dataset EU-MOHP v013.1.1 provides multiscale information on the hydrologic position (MOHP) of a geographic point within its respective river network and catchment as gridded maps. More precisely, it comprises the three measures "divide to stream distance" (DSD) as sum of the distances to the nearest stream and catchment divide, "lateral position" (LP) as a relative measure of the position between the nearest stream and divide and "stream distance" (SD) as the distance to the nearest stream. These three measures are calculated for nine hydrologic orders to reflect different spatial scales from local to continental. Its spatial extent covers major parts of the European Economic Area (EEA39) which also largely coincides with physiographical Europe. Although there are multiple potential use cases, this dataset serves predominantly as valuable static environmental descriptor or predictor variable for hydrogeological and hydrological modelling such as mapping or forecasting tasks using machine learning. The generation of this dataset uses free open source software only and therefore can be transferred to other regions or input datasets.
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