Statistical complexity in the hydrological information from urbanizing basins

Thursday, 18 December 2014: 11:35 AM
Tijana Jovanovic1, Alfonso Mejia1, Ridwan Siddique1 and Jorge A Gironas2, (1)Pennsylvania State University Main Campus, University Park, PA, United States, (2)Pontifical Catholic University of Chile, Santiago, Chile

Urbanizing basins (i.e. basins under urban growth) typify coupled human-natural (CHN) systems, which are said to be complex. Furthermore, the level of complexity of these basins could be assumed to depend on how much the natural environment has been disturbed. In this study we attempt to characterize these systems by quantifying their statistical complexity and its linkage with the degree of urbanization. To perform this quantification, we use both multifractal detrended fluctuation analysis (MDFA) and permutation entropy (PE). MDFA is used to determine long-term dependencies, the Hurst exponent, and the level of multifractality in the hydrological records. On the other hand, PE is used to characterize short-term dependencies and determine the degree of statistical complexity in the records using a metric that depends non-trivially on entropy. The MDFA and PE analysis were applied to long-term hydrologic records (streamflow, baseflow, and rainfall) from 20 urbanizing basins located in the metropolitan areas of Baltimore, Philadelphia, and Washington DC, US. Results show that streamflow in urbanizing basins displays scaling over a wide range of temporal scales, as well as multifractal properties. More relevantly, we found that the scaling and the strength of the multifractality tend to weaken as the basins become more urbanized (i.e. streamflow records become more similar to the driving rainfall forcing with increasing urbanization). This interpretation is supported by the non-significant dependency of baseflow on the amount of urban development in the basin. The PE analysis shows that the statistical complexity of streamflow decreases for the most urbanized basins while the entropy increases, thereby suggesting that streamflow become less structured and more random with increasing urbanization. Overall, this study illustrates the potential of the analysis performed and associated metrics to characterize the hydrological impact of urbanization.