River discharge serves many different purposes and is recorded automatically in many watersheds worldwide to support water supply, use and management decisions, hydroelectric generation and water quality assessment. In hydrology, streamflow records may be used to improve our understanding of hydrologic processes (Tetzlaff

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Proper uncertainty estimation for data series with a high proportion of zero and near zero observations has been a challenge in hydrologic studies. This technical note proposes a modification to the Generalized Likelihood function that accounts for zero inflation of the error distribution (ZI‐GL). We compare the performance of the proposed ZI‐GL with the original Generalized Likelihood function using the entire data series (GL) and by simply suppressing zero observations (GLy>0). These approaches were applied to two interception modeling examples characterized by data series with a significant number of zeros. The ZI‐GL produced better uncertainty ranges than the GL as measured by the precision, reliability and volumetric bias metrics. The comparison between ZI‐GL and GLy>0 highlights the need for further improvement in the treatment of residuals from near zero simulations when a linear heteroscedastic error model is considered. Aside from the interception modeling examples illustrated herein, the proposed ZI‐GL may be useful for other hydrologic studies, such as for the modeling of the runoff generation in hillslopes and ephemeral catchments.

In this paper we synthesize the special sessions of the XXIII Brazilian Water Resources Symposium 2019 in order to understand the major advances and challenges in the water sciences in Brazil. We analyzed more than 250 papers and presentations of 16 special sessions covering topics of Climate Variability and Change, Disasters, Modeling, Large Scale Hydrology, Remote Sensing, Education, and Water Resources Management. This exercise highlighted the unique diversity of natural and human water features in Brazil, that offers a great opportunity for understanding coupled hydrological and societal systems. Most contributions were related to methods and the quantification of water phenomena, therefore, there is a clear necessity for fostering more research on phenomena comprehension. There is a vast network of co-authorship among institutions but mostly from academia and with some degree of regional fragmentation. The ABRhidro community now has the challenge to enhance its collaboration network, the culture of synthesis analysis, and to build a common agenda for water resources research. It is also time for us to be aligned with the international water science community and to use our experiences to actively contribute to the tackling of global water issues.

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Daily streamflow dynamics can be accurately simulated by conceptual models as simple as a single bucket in some catchments, while they require more complex configurations in other catchments. However, without resorting to calibration, anticipating where and why a given model structure may be appropriate remains difficult. In this work, we explored the feasibility of relating suitable model structures to the climate and streamflow characteristics of 508 catchments in Brazil. Specifically, we tested four model structures using up to three reservoirs, where each reservoir is intended to represent a catchment function: the rainfall‐runoff threshold, the fast, and the slow hydrograph response. We hypothesized a relationship between suitable model structures and hydrological signatures of aridity (IA) and baseflow index (IB). Our results show that different classes of signatures resulted in distinct patterns of model performance. Wet catchments (IA < 0.9) with low baseflow (IB < 0.4) were the easiest to model, with a single‐reservoir model presenting a relatively good performance. In the case of low baseflow, adding a rainfall‐runoff threshold reservoir resulted in better performance than adding a slow response reservoir, whereas in the case of high baseflow (IB < 0.6) the opposite occurred. In the case of low baseflow, the inclusion of a slow response reservoir helped the simulation of dry catchments (IA < 1.1), but not of wet ones, which we attributed to the impact of permeability in dry catchments. These results indicate a path toward model structure identification from streamflow signatures and potentially from landscape features.