A scalable open-source web-analytic framework to improve satellite-based operational water management in developing countries

Two software development hurdles to advancing real-world operationalization of satellite datasets for water management are addressed in this study. First, a simple, easy-to-build and open-source web portal connecting to a back-end complex model is developed for resource-constrained developing nations. Second, to enhance the skill of satellite-based predictions, an innovative and dynamic web analytics-based correction system is developed to reduce the uncertainty of satellite estimates. The correction system comprises dynamic precipitation bias correction and streamflow correction. Dynamically web crawled in-situ hydrologic data pertaining to the region are used to estimate satellite estimation bias. These corrected datasets are finally shared through the web portal. On average, these dynamic correction techniques reduced root mean squared error in streamflow by 80–90% for the case of South Asian river basins. The take-home message is that it is now possible to build cost-effective operational web portals based on satellite data and non-proprietary software.