Latest additions to the knowledge base

This paper explores the use of machine learning (ML) techniques to map flood hazards based on readily available geo-environmental variables.

Over the past 15 years, mentions of FCV have been few and far between at previous Africa Regional Platform for Disaster Risk Reduction meetings. It was a marked change to hear the opening remarks by the head of UNDRR, Mr Kamal Kishore.

The GEOGLAM Crop Monitor for Early Warning (CM4EW) is an international and transparent multi-source, consensus assessment of the crop growing conditions, status, and agro-climatic conditions that are likely to impact global production.

Using climate-smart agriculture, IWMI researchers are combating low crop yields in the Global South.

This sNAPshot explores Namibia’s approach to developing a monitoring, evaluation, and learning (MEL) system for adaptation in the agriculture sector as part of the national adaptation plan (NAP) process.

Smallholder farmers across the globe produce over a third of the world’s food supply, yet they receive a disproportionately small share of global climate finance.

This study offers insights on the potential for GloFAS to complement existing forecasting and FldEWS across the region, operated by national and the regional forecasting agencies

The study aims to clarify how climate shocks influence migration decisions among farm households facing climate risks by examining diverse mobility outcomes.