An iterative runoff propagation approach to identify priority locations for land cover change minimizing downstream river flood hazard

Abstract

Local infiltration and surface runoff generation depends on local land use, soil type, antecedent soil water content and slope, while runoff accumulation downstream is furthermore determined by re-infiltration along the flow paths. Hence, land use changes can both mitigate and exacerbate runoff accumulation and flood hazard, providing an opportunity to identify optimal locations for land use changes. An optimization method is presented, encompassing the iterative application of a spatially explicit rainfall-runoff model. This method ranks eligible locations (pixels) according to their modelled contribution to accumulated runoff downstream for a given land use change and given rainfall events, thereby guaranteeing maximal or minimal impact. This method was tested for two medium-sized catchments, located in Flanders, Belgium. Three land use changes were considered: afforestation, sealing and practicing winter cover crops. Results show the considerable impact of these land use changes and their locations on runoff accumulation at the outlet: afforestation of all eligible pixels reduces runoff volumes with 67% to 84 %, cover crops reduce runoff volumes in winter with 42% to 37%, while sealing triples runoff. The priority pixels have a larger impact on downstream runoff volume: afforesting or sealing the 20% highest or lowest ranked pixels leads to a reduction of 71% to 54%, resp. an increase of 102% to 115%. These priority pixels are characterized by high flow accumulation, highlighting the importance of enhancing the infiltration capacity in river valleys. The presented procedure allows spatial planners to consider the impact of local land use interventions to flood resistance downstream.