Modeling of spatiotemporal variations in runoff contribution areas and analysis of hydrologic connectivity

Abstract

AbstractTraditional delineation and modeling methods do not consider the spatial arrangement and dynamic threshold control of surface depressions. Instead, full structural hydrologic connectivity, uniform well‐connected drainage networks, and an invariant contributing area are often assumed. In reality, depressions play an important role in quantifying functional connected areas (ACs) and contributing area. This study is aimed to develop a new procedure to analyze functional hydrologic connectivity related to topography at a mesoscale, specifically in depression‐dominated areas by (a) characterizing surface topography, (b) quantifying and locating dynamic hydrologic connectivity, and (c) analyzing hydrologic connectivity and threshold‐controlled dynamics of contributing area using a set of dimensionless indicators and a new normalized connected area function. Thorough analyses for different topographic surfaces provided improved understanding of the intrinsic relationship and interaction between structural and functional hydrologic connectivity patterns. In addition, the new procedure was compared against a traditional delineation method, terrain analysis using digital elevation models (TauDEM), to determine structural and functional connectivity. It was found that spatial arrangement and scale of depressions had a direct effect on hydrologic connectivity. A stepwise trend, unique to depression‐dominated areas, highlighted the effect of threshold behaviors on contributing area and ACs. Conversely, dendritic surfaces showed an expedited surface connectivity due to the assumption of depressionless topography. Thus, precisely locating and quantifying ACs and contributing area via the new analysis procedure improve our understanding of the mechanisms of topography‐controlled overland flow and sediment transport dynamics, and hence, the findings are valuable in making informed decisions about water quantity and quality across varying topographic surfaces.