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Analysis of daily streamflow variability in space and time is important forwater resources planning, development, and management. The natural variabilityof streamflow is being complicated by anthropogenic influences and climatechange, which may introduce additional complexity into the phenomenologicalrecords. To address this question for daily discharge data recorded during theperiod 1989-2016 at twelve gauging stations on Brazos River in Texas (USA), weuse a set of novel quantitative tools: Kolmogorov complexity (KC) with itsderivative associated measures to assess complexity, and Lyapunov time (LT) toassess predictability. We find that all daily discharge series exhibit longmemory with an increasing downflow tendency, while the randomness of the seriesat individual sites cannot be definitively concluded. All Kolmogorov complexitymeasures have relatively small values with the exception of the USGS (UnitedStates Geological Survey) 08088610 station at Graford, Texas, which exhibitsthe highest values of these complexity measures. This finding may be attributedto the elevated effect of human activities at Graford, and proportionallylesser effect at other stations. In addition, complexity tends to decreasedownflow, meaning that larger catchments are generally less influenced byanthropogenic activity. The correction on randomness of Lyapunov time(quantifying predictability) is found to be inversely proportional to theKolmogorov complexity, which strengthens our conclusion regarding the effect ofanthropogenic activities, considering that KC and LT are distinct measures,based on rather different techniques.

Analysis of Daily Streamflow Complexity by Kolmogorov Measures and Lyapunov Exponent