Development of a minimalist conceptual numerical model for flood forecasting and management under GIS environment

Abstract The floods that Algeria has experienced in recent years are among the most significant natural disasters recorded by the country. These disasters, whose amplitude and frequency have tended to become increasingly irregular in space and time, in the current context of global climate change, encourage us to improve our flood management and forecasting strategies, notably through the re-evaluation of protection structure capacities, designed on the basis of hydrological data analyzed by statistical adjustment of past rainfall hazards. The objective of this study is to develop a minimalist conceptual numerical model for flood forecasting and management under GIS environment for the north-east region of Algeria. This model was developed by analyzing hydrographic data that can be adapted to climate data collected in real time, to predict short-term flood hydrographs in all segments of the hydrographic network, based on the Sokolovsky model for construction of synthetic hydrographs, combined with the Horton architecture for basin discretization. We obtained accuracy on past rainfall hazard simulations around 65.2% for peak flow amplitudes and 88.3% for surface runoff base times. This low-cost simple model opens the way to more possibilities in flood management, and can be improved through better spatialization and calibration with more field data.