Eswatini’s development is at risk by natural drought hazards. Persistent drought is exacerbating the country’s existing challenges of food security and the ability to attain sustainable development. Therefore, FutureWater, Hydrologic, and Emanti Management joined forces to bring together technologies and complementary expertise to implement the GLOW service which includes: short-term and seasonal forecasts of water availability and demand, an alerting service when forecasted water demand is higher than water availability, and water distribution advisories to reduce impact and maximise water security for all water users.

The GLOW service will be piloted in the Maputo River and Mbuluzi River Basins where three-quarters of the population of Eswatini lives, which includes the Hawane dam that supplies water to Mbabane (Capital City of Eswatini) and which is the major water supply source for Maputo, a Delta city (1 million inhabitants) which suffers from water shortages. The main beneficiaries of this project are the Joint River Basin Authority (JBRAS-PB) and the 5 River Basin authorities, AraSul (Mozambique) and the Department of Water and Sanitation (South Africa).

The innovation of GLOW is bringing together proven and award-winning technologies of advanced earth observation, open data, high-performance computing, data-driven modelling, data science, machine learning, operations research, and stakeholder interaction. These technologies require minimum ground truth information, which makes them very scalable and applicable in poorly monitored environments throughout the world. The coherent combination of the technologies into one decision support service ensures the optimum division of water, basically distributing every drop of water to meet the demands of all interests present in large river catchments.

Currently, farmers rely on weather forecasts and advisories that are either general for a given, often wide, region of interest, or highly customized to the farmers’ needs (e.g. by combining large scale atmospheric variables into synthetic parameters of interest). In both cases, such forecasts and advisories often don’t rely at all on observations collected at or around the target cultivated areas, or they are limited to traditional observations provided only by weather stations, without exploiting the full extent of measurements and observations available through European space-based assets (e.g. Galileo GNSS, Copernicus Sentinels) and ground-based radar data.

MAGDA objectives go beyond the state-of-the-art by aiming at developing a modular system that can be deployed by owners of large farms directly at their premises, continuously feeding observations to dedicated and tailored weather forecast and hydrological models, with results displayed by a dashboard and/or within a Farm Management System.

FutureWater is leading the irrigation advisory service of MAGDA, making use of hydrological modelling using SPHY (Spatial Processes in Hydrology). The output expected consists of an operational irrigation service to provide advice on when and how much to irrigate at certain moments during the cropping season, using as input data improved weather forecasts.

During this task, the SPHY water balance model will be setup for three selected demonstrator farms in Romania, France and Italy. Finally, the irrigation advisory will be validated using performance indicators (e.g., water productivity, crop yield analysis, water use efficiency) using ground truth data (e.g., weather stations, moisture probes, crop biomass measurements)