Understanding how streamflow and its components, baseflow and quickflow, vary spatially according to climate and landscape characteristics is fundamental for dealing with different water-related issues. Analytical formulations have been proposed to investigate their long-term behavior and additional influencing factors, suggesting that they are mainly controlled by the aridity index ( Φ). Nevertheless, these studies assume the catchment as a closed water balance system, neglecting inter-catchment groundwater flow (IGF). This simplification makes the analysis of the long-term streamflow components and their main control mechanisms challenging, given that many catchments cannot be considered as closed hydraulic entities. Here, we assessed the controls of the mean-annual streamflow components and their behavior under an open water balance assumption, using observed data of 731 Brazilian catchments with diverse hydroclimatic conditions. Our results indicate that indeed streamflow components are primarily controlled by at the mean annual timescale. The consideration of an open water-balance significantly improved the performance of the functional forms to describe streamflow components while also elucidating the assessment of other influencing factors on the streamflow behavior. Land cover, groundwater, climate seasonality and topographic attributes appeared as the main control mechanisms beyond aridity. Overall, our study provides new insights of the main control mechanism of the streamflow behavior at the mean-annual scale, while shedding light on the importance of the open water-balance assumption for model development and water resources management.

Understanding transit times (TT) and residence times (RT) distributions of water in catchments has recently received a great deal of attention in hydrologic research since it can inform about important processes relevant to the quality of water delivered by streams and landscape resilience to anthropogenic inputs. The theory of transit time distributions (TTD) is a practical framework for understanding TT of water in natural landscapes but, due to its lumped nature, it can only hint at the possible internal processes taking place in the subsurface. While allowing for the direct observation of water movement, Electrical Resistivity Imaging (ERI) can be leveraged to better understand the internal variability of water ages within the subsurface, thus enabling the investigation of the physical processes controlling the time-variability of TTD. We estimated time variable TTD through the storage selection (SAS) framework following a traditional lumped-systems approach, based on sampling of output tracer concentrations, as well as through an ERI SAS approach based on spatially distributed images of water ages. We compared the ERI-based SAS results with the output-based estimates to discuss the viability of ERI at laboratory experiments for understanding TTD. The ERI-derived images of the internal evolution of water ages were able to elucidate the internal mechanisms driving the time-variability of ages of water being discharged by the system, which was characterized by a delayed discharge of younger water starting at the highest storage level and continuing throughout the water table recession.

The direct observation of water movement via Electrical Resistivity Imaging (ERI) can leverage the understanding of the processes that lead to the occurrence of variable residence times (RT) within the Critical Zone (CZ). While hydrological processes at natural landscapes are often space and time-variable, quantitatively estimating solute transport with ERI under transient conditions is challenging due to necessary considerations of moisture states and electrical properties of the medium. Here, we introduce the use of Periodic Steady State (PSS) theory applied to electrical resistivity of soils to provide a simple solution to the problems and report a laboratory experiment to test the proposed method. We used a 1 m3 sloping lysimeter to represent the hydrological functioning of natural hillslopes, equipped with electrodes to provide cross-borehole images of bulk soil electrical conductivity and performed a 28-days experiment in which a periodic irrigation was applied. A saline tracer was added to the lysimeter in two irrigation pulses and subsequent pulses were applied until the tracer was flushed out. ERT-surveys and estimates of background soil-water conductivity were used to quantitatively estimate solute breakthrough throughout the different cross-sections. Integrated lysimeter-scale images were superimposed with the water table progression throughout the experiment to leverage the understanding of flow and transport processes responsible for the tracer mobilization. Our study introduces a novel method for laboratory experimentation at mesocosm scales using ERT and provides valuable insight into the role of water table dynamics in mediating the occurrence of variable flow pathways within hillslopes.

This study investigates the impacts of climate seasonality, i.e., the seasonal cycle of precipitation (P) relative to that of potential evaporation (PET), on surface water supply and the long-term water partitioning and proposes an augmented aridity index considering climate seasonality in addition to climatic mean. Evaporation tends to be favored over streamflow at long-term timescales when both cycles occur in tandem (in-phase seasonality), while the opposite occurs (less evaporation, more streamflow) when the two cycles are out-of-phase. This study proposes a straightforward approach to incorporating the seasonality effects on the mean annual water balance into the Budyko framework, by revising the water availability (A) in the formulation of the aridity index (Φ). We hypothesize the Budyko curve represents catchments with uniform monthly values of P, leading to a mathematical formulation of A that better represents the coupled, land-atmosphere nature of the water availability. Our results also provide a simple mathematical framework for incorporating the seasonality into the aridity index, thus reducing the dimensionality of the long-term water balance problem through an aridity-seasonality index (Φ’). The formulation used here was able to improve the explanatory power of the Budyko framework for 328 catchments within the continental US, being proved as a useful strategy for the incorporating climate variations into its formulation in addition to climatic mean.

Direct-runoff and baseflow are the two primary components of total streamflow and their accurate estimation is indispensable for a variety of hydrologic applications. While direct runoff is the quick response stemming from surface and shallow subsurface flow paths, and is often associated with floods, baseflow represents the groundwater contribution to streams and is crucial for environmental flow regulations, groundwater recharge, and water supply, among others. L’vovich (1979) proposed a two-step water balance where precipitation is divided into direct runoff and catchment wetting followed by the disaggregation of the latter into baseflow and evapotranspiration. Although arguably a better approach than the traditional Budyko framework, the physical controls of direct runoff and baseflow are still not fully understood. Here, we investigate the role of the aridity index (ratio between mean annual potential evapotranspiration and precipitation) in controlling the long-term (mean-annual) fluxes of direct runoff and baseflow. We present an analytical solution beginning with similar assumptions as proposed by Budyko (1974), leading to two complementary expressions for the two fluxes. The aridity index explained 83% and 91% of variability in direct runoff and baseflow from 499 catchments within the continental US, and our formulations were able to reproduce the patterns of water balance proposed by L’vovich (1979) at the mean annual timescale. Our approach allows for the prediction of baseflow and direct runoff at ungauged basins and can be used to further understand how climate and landscape controls the terrestrial water balance at mean annual timescales.

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors (e.g., food and energy production and urban supply). However, the drivers of decreased streamflow, particularly the potential role of groundwater withdrawals, have not been yet investigated. Here, we assess long-term trends in baseflow, quickflow, and streamflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that over 82% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend (< -20 m3 s-1 y-1) along the SFR with spatial agreement between decreased baseflow, increased ET, and irrigated agricultural land. We also found a decrease in TWS across the SFB with trends exceeding -20 mm y-1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) are the primary cause of the observed reduction in total SFR flow. A lack of significant climate trends indicates that climate variability likely has not caused the observed baseflow reduction, mainly in the Middle and Sub-middle SFB, and therefore groundwater and surface withdrawals may be the most likely driver of water scarcity over the SFB. We call for increased attention on groundwater’s key role for the SFB and integrated regional management of surface and groundwater.