Detrended Fluctuation Studies Of Long-Term Persistence And Multifractality Of Precipitation And River Runoff Records

We studied and compared the autocorrelation behaviour and the temporal multifractal properties of long daily river discharge and precipitation records from 42 hydrological stations and 99 meteorological stations around the globe To determine the scaling behaviour in the presence of trends, we applied detrended fluctuation analysis (DFA) and multifractal DFA We found that the daily runoffs are characterised by a power-law decay of the autocorrelation function above some crossover time that usually is several weeks The corresponding correlation exponent varies from river to river in a wide range Below the crossovers pronounced short-term correlations occur In contrast, most of the precipitation series show scaling behaviour corresponding to a rapid decay of the autocorrelation function For the multifractal characterisation of the data we determined the generalised Hurst exponents and applied three operational models We found that the universal multifractal model fits well the scaling behaviour of the positive moments in nearly all runoff and precipitation records, while positive as well as negative moments are consistent with two-parameter fits from an extended version of the multiplicative cascade model for all runoff records and most of the precipitation records Some weakly multifractal precipitation records, however, are better characterised by a simple bifractal model