Effect of changing spatio-temporal precipitation patterns on river network dynamics

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Armaghan Abed-Elmdoust, University of Central Florida, Department of Civil Environmental and Construction Engineering, Orlando, FL, United States and Arvind Singh, University of Central Florida, Orlando, FL, United States
Quantifying the impacts of climate change on landscape evolution has been a subject of intense research for past many years. Among the various impacts of climate change in landscapes is the influence of changing precipitation patterns on the re-organization of river network across the basin. Here, we investigate the effect of non-uniform spatio-temporal patterns of precipitations on the evolution of river networks. For this, we simulate river networks dynamics based on optimal channel network approach, on a prescribed two-dimensional lattice, under constant and varying spatial and temporal patterns of precipitation. For a given precipitation rate, the steady state river network (the optimal channel network) is obtained by finding a drainage pattern that minimizes the total energy of the network. This steady state river network is further perturbed with non-uniform rainfall patterns and its dynamics are recorded. We show that under non-uniform rainfall conditions, river networks significantly re-organize themselves towards new steady states with different total energies. Although the reorganized river networks statistically follow similar bifurcation rules (Horton’s laws), they exhibit different geomorphological signatures. In particular, the re-organization on the landscape is mainly seen in the form of order based channel migration, basin capture and formation of new channels and basins. Based on an empirical slope-area relationship coupled with optimal channel network, we generate three-dimensional digital elevation models of the evolved landscape for further exploring the hillslope-channels interactions. Our results show the potential use of optimal channel networks as a simple and yet versatile method for exploring the effects of climate change on river networks.