Drainage network dynamics in an agricultural headwater sub-basin

Headwaters provide many ecosystems services. Currently, these vulnerable systems are subject to threats related to human activities. This work aims to analyse the spatial pattern changes (expansion/contraction) in the drainage network (DN) of a headwater sub-basin under agriculture between 1966 and 2019 in the Argentine Pampas Region. We study and discuss the hydrometeorological and land use context to understand the spatial and temporal dynamics of the DN, and propose a conceptual model that synthesizes the complex interactions between the factors involved in that dynamics. A broad (1950-2019, at the Del Azul Creek basin) and a short (1996-2019, at the sub-basin of the Videla Creek -SVC-) temporal and spatial scale analysis of data were carried out. We studied rainfall, evapotranspiration, water table depth, streamflow and land use. Temporal and spatial changes in the DN of the SVC were analysed by aerial photos and historical satellite images. Four wet and three dry periods were identified, and close surface-subsurface water interactions typical of plains, were found. The area under agriculture showed a first gradual increase (1975-2012), which turned sharp from 2012 (30,908 ha year^-1), with a leading role of soybeans' sown area. The area of the DN increased 1.4699*10⁵ m² between 1966 and 2010, both under dry conditions, which evidenced its expansion. The study of the flatlands' particular hydrology within the current land use and management trends provided key elements to understand DN area's changes. Complex interactions between processes associated with climatic forcing and the system's sensitivity (its state to receive and process the inputs), are involved in the spatial and temporal dynamics of the DN. Our work improves the understanding of the functioning of these vulnerable systems within agricultural areas, nowadays under productive pressures associated with increasing global food demand, and threats to changes in the hydrological dynamics by global change.