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Hydrological functions of river basins are summarized as collection, storageand discharge, which can be characterized by the dynamics of hydrologicalvariables including precipitation, evaporation, storage and runoff. Thetemporal patterns of each variable can be indicators of the functionality ofa basin. In this paper we introduce a measure to quantify the degree ofsimilarity in intra-annual variations at monthly scale at different years forthe four main variables. We introduce this measure under the term ofrecurrence and define it as the degree to which a monthly hydrologicalvariable returns to the same state in subsequent years. The degree ofrecurrence in runoff is important not only for the management of waterresources but also for the understanding of hydrologic processes, especiallyin terms of how the other three variables determine the recurrence in runoff.The main objective of this paper is to propose a simple hydrologicclassification framework applicable to large basins at global scale based onthe combinations of recurrence in the four variables using a monthly scaletime series. We evaluate it with lagged autocorrelation (AC), fast Fouriertransforms (FFT) and Colwell's indices of variables obtained from theEU-WATCH data set, which is composed of eight global hydrologic model(GHM) and land surface model (LSM) outputs. By setting a threshold to define highor low recurrence in the four variables, we classify each river basin into 16possible classes.  The overview of recurrence patterns at global scale suggested thatprecipitation is recurrent mainly in the humid tropics, Asian monsoon areaand part of higher latitudes with an oceanic influence. Recurrence inevaporation was mainly dependent on the seasonality of energy availability,typically high in the tropics, temperate and sub-arctic regions. Recurrencein storage at higher latitudes depends on energy/water balances and snow,while that in runoff is mostly affected by the different combinations ofthese three variables. According to the river basin classification, 10 out ofthe 16 possible classes were present in the 35 largest river basins in theworld. In the humid tropic region, the basins belong to a class with highrecurrence in all the variables, while in the subtropical region many of theriver basins have low recurrence. In the temperate region, the energy limited orwater limited in summer characterizes the recurrence in storage, but runoffexhibits generally low recurrence due to the low recurrence inprecipitation. In the sub-arctic and arctic regions, the amount of snow alsoinfluences the classes; more snow yields higher recurrence in storage andrunoff. Our proposed framework follows a simple methodology that can aid ingrouping river basins with similar characteristics of water, energy andstorage cycles. The framework is applicable at different scales withdifferent data sets to provide useful insights into the understanding ofhydrologic regimes based on the classification

Hydrological recurrence as a measure for large river basin classification and process understanding