A proposed methodological framework to estimate the utility of EO-based information in data scarce contexts: challenges and recommendations

Abstract The growing imperative for resilience to extreme events has elevated the role of Earth Observation (EO) technologies in supporting global water resources management and disaster preparedness. Building on a growing body of work to assess the value of EO information in different contexts, we propose a methodological framework to maximize the expected utility of streamflow information in data scarce environments. GEOGLOWS, an EO-based hydrological forecasting initiative, has successfully demonstrated its use in Ecuador through partnerships with local institutions. Its Hydroviewer provides crucial streamflow predictions with sufficient lead time, enabling early action to mitigate flood and drought risks. To complement qualitative information, economic models can be designed to quantify the expected value to individuals, provinces, or other unit-areas, however systemic data limitations may challenge efforts to fully estimate such utility. This perspective paper proposes a detailed framework to apply a standard economic impact evaluation framework, and it uses the application of GEOGLOWS in Ecuador as a case study. This approach highlights the need for targeted data collection strategies, specifically, on damages, averted losses, and system usage metrics, alongside frequently updated socioeconomic information. Such data are crucial to enable robust economic impact assessments and to inform future investments in EO-driven water management solutions, especially in resource-constrained environments.