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Ethanol production in Brazil is projected to double between 2012 and 2030 in order to meet increased global demand, resulting in the expansion of sugarcane cultivation. Sugarcane expansion drives both direct and indirect land-use changes, and subsequent changes in hydrology may exacerbate problems of (local) water scarcity. This study assesses the impacts of projected ethanol-driven sugarcane expansion on agricultural and hydrological drought in Brazil. Drought due to sugarcane expansion is modelled using a spatial terrestrial hydrological model (PCR-GLOBWB) with spatiotemporally variable land-use change and climate change scenarios as input. We compare an ethanol scenario with increased ethanol demand to a reference situation in which ethanol demand does not increase. The results show that, on average, 29% of the Centre West Cerrado region is projected to experience agricultural drought between 2012 and 2030, and the drought deficit in this region is projected to be 7% higher in the ethanol scenario compared to the reference. The differences between the ethanol and the reference scenario are small when averaged over macro-regions, but can be considerable at a local scale. Differences in agricultural and hydrological drought between the ethanol and reference scenario are most notable in the Centre West Cerrado and Southeast regions. Locally, considerable changes may also occur in other regions, including the Northeast Coast and Northern Amazon region. Because the South East and Centre West Cerrado regions are responsible for a large proportion of agricultural production, increased agricultural drought may result in significant economic losses, while increased hydrological drought could exacerbate existing problems of water supply to large metropolitan areas in these regions. The identification of areas at risk of increased droughts can be important information for policy makers to take precautionary measures to avoid negative hydrological impacts of increased ethanol demand.

As human water demand is increasing worldwide, pressure on available water resources grows and their sustainable exploitation is at risk. To mimic changes in exploitation intensity and the connecting feedbacks between surface water and groundwater systems, a dynamic attribution of demand to water resources is necessary. However, current global-scale hydrological models lack the ability to do so. This study explores the dynamic attribution of water demand to simulated water availability. It accounts for essential feedbacks, such as return flows of unconsumed water and riverbed infiltration. Results show that abstractions and feedbacks strongly affect water allocation over time, particularly in irrigated areas. Also residence time of water is affected, as shown by changes in low flow magnitude, frequency, and timing. The dynamic representation of abstractions and feedbacks makes the model a suitable tool for assessing spatial and temporal impacts of changing global water demand on hydrology and water resources.

Groundwater is the world's largest accessible source of fresh water. It plays a vital role in satisfying basic needs for drinking water, agriculture and industrial activities. During times of drought groundwater sustains baseflow to rivers and wetlands, thereby supporting ecosystems. Most global-scale hydrological models (GHMs) do not include a groundwater flow component, mainly due to lack of geohydrological data at the global scale. For the simulation of lateral flow and groundwater head dynamics, a realistic physical representation of the groundwater system is needed, especially for GHMs that run at finer resolutions. In this study we present a global-scale groundwater model (run at 6' resolution) using MODFLOW to construct an equilibrium water table at its natural state as the result of long-term climatic forcing. The used aquifer schematization and properties are based on available global data sets of lithology and transmissivities combined with the estimated thickness of an upper, unconfined aquifer. This model is forced with outputs from the land-surface PCRaster Global Water Balance (PCR-GLOBWB) model, specifically net recharge and surface water levels. A sensitivity analysis, in which the model was run with various parameter settings, showed that variation in saturated conductivity has the largest impact on the groundwater levels simulated. Validation with observed groundwater heads showed that groundwater heads are reasonably well simulated for many regions of the world, especially for sediment basins (R2 = 0.95). The simulated regional-scale groundwater patterns and flow paths demonstrate the relevance of lateral groundwater flow in GHMs. Inter-basin groundwater flows can be a significant part of a basin's water budget and help to sustain river baseflows, especially during droughts. Also, water availability of larger aquifer systems can be positively affected by additional recharge from inter-basin groundwater flows.

Throughout its historical development, hydrology as an earth science, but especially as a problem-centred engineering discipline has largely relied (quite successfully) on the assumption of stationarity. This includes assuming time invariance of boundary conditions such as climate, system configurations such as land use, topography and morphology, and dynamics such as flow regimes and flood recurrence at different spatio-temporal aggregation scales. The justification for this assumption was often that when compared with the temporal, spatial, or topical extent ofthe questions posed to hydrology, such conditions could indeed be considered stationary, and therefore the neglect of certain long-term non-stationarities or feedback effects (even if they were known) would not introduce a large error. However, over time two closely related phenomena emerged that have increasingly reduced the general applicability of the stationarity concept: the first is the rapid and extensive global changes in many parts of the hydrological cycle, changing formerly stationary systems to transient ones. The second is that the questions posed to hydrology have become increasingly more complex, requiring the joint consideration of increasingly more (sub-) systems and their interactions across more and longer timescales, which limits the applicability of stationarity assumptions. Therefore, the applicability of hydrological concepts based on stationarity has diminished at the same rate as the complexity of the hydrological problems we are confronted with and the transient nature of the hydrological systems we are dealing with has increased. The aim of this paper is to present and discuss potentially helpful paradigms and theories that should be considered as we seek to better understand complex hydrological systems under change. For the sake of brevity we focus on catchment hydrology. We begin with a discussion of the general nature of explanation in hydrology and briefly review the history of catchment hydrology. We then propose and discuss several perspectives on catchments: as complex dynamical systems, self-organizing systems, co-evolving systems and open dissipative thermodynamic systems. We discuss the benefits of comparative hydrology and of taking an informationtheoretic view of catchments, including the flow of information from data to models to predictions. In summary, we suggest that these perspectives deserve closer attention and that their synergistic combination can advance catchment hydrology to address questions of change.

We explore the possibility of using remotely sensed soil moisture data and in situ discharge observations to calibrate a large-extent hydrological model. The model used is PCR-GLOBWB-MOD, which is a physically based and fully coupled groundwater-land surface model operating at a daily basis and having a resolution of 30 arc sec (about 1 km at the equator). As a test bed, we use the combined Rhine-Meuse basin (total area: about 200,000 km2), where there are 4250 point-scale observed groundwater head time series that are used to verify the model results. Calibration is performed by simulating 3045 model runs with varying parameter values affecting groundwater head dynamics. The simulation results of all runs are evaluated against the remotely sensed soil moisture time series of SWI (Soil Water Index) and field discharge data. The former is derived from European Remote Sensing scatterometers and provides estimates of the first meter profile soil moisture content at 30 arc min resolution (50 km at the equator). From the evaluation of these runs, we then introduce a stepwise calibration approach that considers stream discharge first, then soil moisture, and finally verify the resulting simulation to groundwater head observations. Our results indicate that the remotely sensed soil moisture data can be used for the calibration of upper soil hydraulic conductivities determining simulated groundwater recharge of the model. However, discharge data should be included to obtain full calibration of the coupled model, specifically to constrain aquifer transmissivities and runoff-infiltration partitioning processes. The stepwise approach introduced in this study, using both discharge and soil moisture data, can calibrate both discharge and soil moisture, as well as predicting groundwater head dynamics with acceptable accuracy. As our approach to parameterize and calibrate the model uses globally available data sets only, it opens up the possibility to set up large-extent coupled groundwater-land surface models in other basins or even globally. Key Points Soil moisture data can be used to calibrate upper soil conductivities Yet, discharge data should be included to fully calibrate the coupled model The combined calibration approach reproduces groundwater head dynamics well