DROP app: A hydroclimate information service to deliver scientific rainfall, local rainfall, and soil moisture forecasts for agricultural decision-making.

ABSTRACT: Weather and Climate Information Services developed for agriculture often only provide scientific weather and climate forecasts on various timescales. Yet, local forecasts derived from indigenous knowledge and soil moisture information are still missing. In this study, we evaluate the implementation of the DROP app, a hydroclimate information service, offering both local (LF) and scientific rainfall forecasts (SF) and soil moisture forecasts, that was designed with and for smallholder farmers working on rainfed agriculture in northern Ghana. Results of the forecast assessment show that the LF generates a high probability of rain detection (POD), with a minimum value of 0.7. The hybrid forecast (HF) that integrates the SF and LF yields the highest POD value of 0.9 compared to others. However

SUBMITTER: Sutanto SJ 

PROVIDER: S-EPMC11883362 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature