Seasonal forecast
A suit of sectoral models (watershed, groundwater, crop yield, economic and reservoir management), driven by downscaled seasonal forecasts and remote sensing data, will constitute the forecasts-based guidance of this study. Specifically, predicted streamflow from the watershed model along with reservoir management optimization tools will inform optimal water releases for hydropower and major irrigated agriculture schemes. Simulations from a sub-nested groundwater model will inform farmers and small-scale irrigated agriculture communities about the impact of different water uptake strategies on the seasonal dynamics of their local water resources (e.g. water levels at ponds, groundwater wells and small rivers and lakes).
Crop yield model simulations, driven with the watershed and groundwater model outputs, will inform government organizations and local rainfed agriculture and small irrigation scheme farmers about the impact of different crop practices on food production. Outputs from a multi-market economic model driven by BNB crop yield and hydropower generation predictions will inform stakeholder organizations in Ethiopia (MoWIE, ABA, EEPCo) through policy workshops coordinated by IFPRI and EIWR. Finally, outputs from the agent-based model (ABM) informed and validated by social scientific investigations (surveys and ethnographies) will be used in an iterative way to study the implications of stakeholder decisions (e.g. adoption/rejection rates of the hydrologic forecasts, reservoir optimization, crop choices, etc.) and facilitate uptake of the forecasts.
How does the high quality seasonal forecast information produced by the above modeling efforts reach to the local farmers and irrigation/hydropower managers? How do local farmers and communities, in turn, provide data on soil moisture, stream flow and lake water level to scientists? Development of digital apps to collect near real time meteorological data and to relay the resulting forecast information to local farmers is the answer. The Apps will be designed to exploit existing digital infrastructure and mobile networks in Ethiopia. The digital tool has capability for mobile-enabled meteorological data collection and analysis as well as near real time transmission of Mobile-enabled forecast services to local farmers. The goal is to promote community resilience to economic shock and fast recovery from agriculture related stress. Ultimately, digital agricultural information access is expected to improve crop growing decisions of framers and hence food and water security in the Blue Nile Basin.