Forecasting river discharge using machine learning methods: with application to the Geul and Rur river

The objective of this study is find out whether maximum daily discharge of the Geul and Rur catchments can be forecast using machine learning (ML) methods, and if so, to what extent. In addition, these ML models are compared to a conceptual model to see which performs better. A second objective is to test whether soil moisture content (SMC) and...

Improving water efficiency and crop yield on a sugarcane plantation in Xinavane, Mozambique: An analysis of irrigation practices, yield variability and the potential of a decision support system

This report contains the findings of a multidisciplinary project in Mozambique which ran from mid-November 2018 to mid-January 2019. This study is part of the IWACA-TECH project, which is an abbreviation for “Improved Water efficiency Control based on remote sensing TECHnologies. The goal is to increase water efficiency and crop yield without...