Published February 19, 2020 | Version v1
Dataset Open

Data for "Function Space Optimization: A symbolic regression method for estimating parameter transfer functions for hydrological models"

  • 1. Institute for Hydrology and Water Management, University of Natural Resources and Life Sciences, Vienna, Austria
  • 2. LIT AI Lab & Institute for Machine Learning, Johannes Kepler University Linz, Linz, Austria

Description

This repository contains all geo-physical catchment properties used in the publication "Function Space Optimization: A symbolic regression method for estimating parameter transfer functions for hydrological models".

Files

Files (37.9 MB)

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md5:0a8e0c973c3bf11db9132cd913c18c0b
4.5 MB Download
md5:35c7c52358748c6365d46cf31887023d
5.5 MB Download
md5:010ae95c62532ef8192dbede6e5174bf
2.7 MB Download
md5:3f6d00361f707ae3e060835bca46a88b
6.1 MB Download
md5:28fa49e5791c835436b6b54e18722f79
1.9 MB Download
md5:48a0625212c879d67b51b40883fc956d
6.2 MB Download
md5:48491c3c58d6203ac993be0ad492f888
5.5 MB Download
md5:fd8f746ee9af1e7180943e7d172d8f3f
5.5 MB Download