A meta-analysis on 192 peer-reviewed articles reporting applications of the Variable Infiltration Capacity (VIC) model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution. We identified six time concepts in hydrological models, which all impact the model results and conclusions. Process-based model evaluation is particularly relevant when models are applied at hyper-resolution, where stakeholders expect credible results both at a high spatial and temporal resolution.@en

Large-scale hydrological models are used to determine drought on a global scale. However, it is important to know how well these large-scale models can reproduce major drought events in the past before projections can be made. This study presents a comparison between a multi-model ensemble and reported drought events in the literature to assess the performance of large-scale models. Major drought events in the selected period (1963-2000) were reproduced by the model ensemble median, although the duration and spatial extent differed substantially from reported events. The major drought events are caused by precipitation deficits linked to oscillations in climatic patterns, such as ENSO. This implies that major drought events were simulated if these were included in the forcing data. Spatial extent and duration of simulated drought events differed from extent and duration of reported ones due to a fast runoff response in some models.@en

We present the Wageningen Lowland Runoff Simulator (WALRUS), a novel rainfall-runoff model to fill the gap between complex, spatially distributed models which are often used in lowland catchments and simple, parametric (conceptual) models which have mostly been developed for sloping catchments. WALRUS explicitly accounts for processes that are important in lowland areas, notably (1) groundwater-unsaturated zone coupling, (2) wetness-dependent flow routes, (3) groundwater-surface water feedbacks and (4) seepage and surface water supply. WALRUS consists of a coupled groundwater-vadose zone reservoir, a quickflow reservoir and a surface water reservoir. WALRUS is suitable for operational use because it is computationally efficient and numerically stable (achieved with a flexible time step approach). In the open source model code default relations have been implemented, leaving only four parameters which require calibration. For research purposes, these defaults can easily be changed. Numerical experiments show that the implemented feedbacks have the desired effect on the system variables.

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Subsurface flow and storage dynamics at hillslope scale are difficult to ascertain, often in part due to a lack of sufficient high-resolution measurements and an incomplete understanding of boundary conditions, soil properties, and other environmental aspects. A continuous and extreme rainfall experiment on an artificial hillslope at Biosphere 2's Landscape Evolution Observatory (LEO) resulted in saturation excess overland flow and gully erosion in the convergent hillslope area. An array of 496 soil moisture sensors revealed a two-step saturation process. First, the downward movement of the wetting front brought soils to a relatively constant but still unsaturated moisture content. Second, soils were brought to saturated conditions from below in response to rising water tables. Convergent areas responded faster than upslope areas, due to contributions from lateral subsurface flow driven by the topography of the bottom boundary, which is comparable to impermeable bedrock in natural environments. This led to the formation of a groundwater ridge in the convergent area, triggering saturation excess runoff generation. This unique experiment demonstrates, at very high spatial and temporal resolution, the role of convergence on subsurface storage and flow dynamics. The results bring into question the representation of saturation excess overland flow in conceptual rainfall-runoff models and land-surface models, since flow is gravity-driven in many of these models and upper layers cannot become saturated from below. The results also provide a baseline to study the role of the coevolution of ecological and hydrological processes in determining landscape water dynamics during future experiments in LEO.

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Drought severity and related socio-economic impacts are expected to increase due to climate change. To better adapt to these impacts, more knowledge on changes in future hydrological drought characteristics (e.g. frequency, duration) is needed rather than only knowledge on changes in meteorological or soil moisture drought characteristics. In this study, effects of climate change on droughts in several river basins across the globe were investigated. Downscaled and bias-corrected data from three General Circulation Models (GCMs) for the A2 emission scenario were used as forcing for large-scale models. Results from five large-scale hydrological models (GHMs) run within the EU-WATCH project were used to identify low flows and hydrological drought characteristics in the control period (1971-2000) and the future period (2071-2100). Low flows were defined by the monthly 20th percentile from discharge (Q20). The variable threshold level method was applied to determine hydrological drought characteristics. The climatology of normalized Q20 from model results for the control period was compared with the climatology of normalized Q20 from observed discharge of the Global Runoff Data Centre. An observation-constrained selection of model combinations (GHM and GCM) was made based on this comparison. Prior to the assessment of future change, the selected model combinations were evaluated against observations in the period 2001-2010 for a number of river basins. The majority of the combinations (82%) that performed sufficiently in the control period, also performed sufficiently in the period 2001-2010. With the selected model combinations, future changes in drought for each river basin were identified. In cold climates, model combinations projected a regime shift and increase in low flows between the control period and future period. Arid climates were found to become even drier in the future by all model combinations. Agreement between the combinations on future low flows was low in humid climates. Changes in hydrological drought characteristics relative to the control period did not correspond to changes in low flows in all river basins. In most basins (around 65%), drought duration and deficit were projected to increase by the majority of the selected model combinations, while a decrease in low flows was projected in less basins (around 51%). Even if low discharge (monthly Q20) was not projected to decrease for each month, droughts became more severe, for example in some basins in cold climates. This is partly caused by the use of the threshold of the control period to determine drought events in the future, which led to unintended droughts in terms of expected impacts. It is important to consider both low discharge and hydrological drought characteristics to anticipate on changes in droughts for implementation of correct adaptation measures to safeguard future water resources.

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The Wageningen Lowland Runoff Simulator (WALRUS) is a new parametric (conceptual) rainfall-runoff model which accounts explicitly for processes that are important in lowland areas, such as groundwater-unsaturated zone coupling, wetness-dependent flowroutes, groundwater-surface water feedbacks, and seepage and surface water supply (see companion paper by Brauer et al., 2014). Lowland catchments can be divided into slightly sloping, freely draining catchments and flat polders with controlled water levels. Here, we apply WALRUS to two contrasting Dutch catchments: the Hupsel Brook catchment and the Cabauw polder. In both catchments, WALRUS performs well: Nash-Sutcliffe efficiencies obtained after calibration on 1 year of discharge observations are 0.87 for the Hupsel Brook catchment and 0.83 for the Cabauw polder, with values of 0.74 and 0.76 for validation. The model also performs well during floods and droughts and can forecast the effect of control operations. Through the dynamic division between quick and slow flowroutes controlled by a wetness index, temporal and spatial variability in groundwater depths can be accounted for, which results in adequate simulation of discharge peaks as well as low flows. The performance of WALRUS is most sensitive to the parameter controlling the wetness index and the groundwater reservoir constant, and to a lesser extent to the quickflow reservoir constant. The effects of these three parameters can be identified in the discharge time series, which indicates that the model is not overparameterised (parsimonious). Forcing uncertainty was found to have a larger effect on modelled discharge than parameter uncertainty and uncertainty in initial conditions.@en

This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based "local" methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative "bucket-style" hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km²) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models. Key Points Sobol' and DELSA methods showed that they yield similar sensitivity results DELSA provides more information at lower calculation costs than Sobol' DELSA is recommended as effective and efficient method for parameter sensitivity

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In many rainfall-runoff models, at least some calibration of model parameters has to take place. Especially for ungauged or poorly gauged basins this can be problematic, because there is little or no data available for calibration. A possible solution to overcome the problems caused by data scarcity is to set up a measurement campaign for a limited time period. In this study, we determine the minimum amount of data required to determine robust parameter values for a simple model with two parameters. The model is constructed such that the parameters can be determined not only with automatic calibration, but also by recession analysis and a priori from Boussinesq theory. The model has been applied to a research catchment in Switzerland. For automatic calibration and recession analysis, one season (5 months) is found to be sufficient to give robust parameters for simulation of high flows over the full observation period. For automatic calibration, this should be the season with the highest precipitation, for recession analysis the season with least evapotranspiration. The Boussinesq equation is able to give good parameter estimates for modeling high flows, but detailed in situ knowledge of the catchment is required. Automatic calibration outperforms recession analysis and Boussinesq theory by far when it comes to parameter estimation with a focus on prediction of low flows. It was shown that a single set of parameters cannot simultaneously describe high and low flows with a reasonable accuracy, suggesting that more than two parameters are needed to characterize subsurface properties. Key Points Automatic calibration, recession analysis, and Boussinesq theory are compared Automatic calibration leads to the highest model efficiencies One season of data is needed for robust parameter estimation

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Drought propagation through the terrestrial hydrological cycle is associated with a change in drought characteristics (duration and deficit), moving from precipitation via soil moisture to discharge. Here we investigate climate controls on drought propagation with a modeling experiment in 1271 virtual catchments that differ only in climate type. For these virtual catchments we studied the bivariate distribution of drought duration and standardized deficit for the variables precipitation, soil moisture, and discharge. We found that for meteorological drought (below-normal precipitation), the bivariate distributions of drought characteristics have a linear shape in all climates and are thus not affected by seasonality in climate. Despite the linear shape of meteorological drought, soil moisture drought (below-normal storage in the unsaturated zone) and hydrological drought (below-normal water availability in aquifers, lakes, and/or streams) show strongly nonlinear shapes in drought characteristics in climates with a pronounced seasonal cycle in precipitation and/or temperature. These seasonality effects on drought propagation are found in monsoonal, savannah, and Mediterranean climate zones. In these regions, both soil moisture and discharge show deviating shapes in drought characteristics. The effect of seasonality on drought propagation is even stronger in cold seasonal climates (i.e., at high latitudes and altitudes), where snow accumulation during winter prevents recovery from summer hydrological drought, and deficit increases strongly with duration. This has important implications for water resources management in seasonal climates, which cannot solely rely on meteorology-based indices as proxies for hydrological drought duration and deficit and need to include seasonal variation in both precipitation and temperature in hydrological drought forecasting.

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Flash flooding is a potentially destructive natural hazard known to occur in the Ce´vennes-Vivarais region in southern France. HyMeX (Hydrological Cycle in the Mediterranean Experiment) is an international program focused on understanding the hydrological cycle in the Mediterranean basin. Soil moisture is known to be a useful indicator of catchment response, however, establishing a meaningful estimation of soil moisture at the catchment level can be difficult due to its high variability in space and time.In a small gauged catchment in the Ce´vennes-Vivarais region in southern France, a series of manual soil moisture measurements was taken from September to December 2012 at both the field and catchment scale during the Special Observation Period 1 (SOP1) as part of the HyMeX program. Six plots were selected along a trajectory of a microwave link installed in the catchment and were chosen to represent different elevations in the catchment. Within each field plot, surface soil moisture was measured along a 50. m transect at 2. m intervals. This allowed the study of changes in within-field variability as well as between-field variability in response to precipitation events and during the drying out phase.Several precipitation events occurred over this autumn 2012 period which caused a significant wetting-up of the catchment, allowing the study of soil moisture processes over a wide range of wetness conditions. The influence of antecedent catchment conditions (soil moisture) on rainfall-runoff dynamics is demonstrated through the comparison of storm hydrographs for the various events. Dry catchment conditions result in minimal response in event flow, whereas large precipitation events occurring during wetter conditions produce much stronger responses in event flow. This further confirms the importance of quantifying catchment initial conditions to enhance the prediction of flash flood occurrences.

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Based on a literature overview, this paper summarizes the impact and legacy of the contributions of Wilfried Brutsaert and Jean-Yves Parlange (Cornell University) with respect to the current state-of-the-art understanding in hydraulic groundwater theory. Forming the basis of many applications in catchment hydrology, ranging from drought flow analysis to surface water-groundwater interactions, hydraulic groundwater theory simplifies the description of water flow in unconfined riparian and perched aquifers through assumptions attributed to Dupuit and Forchheimer. Boussinesq (1877) derived a general equation to study flow dynamics of unconfined aquifers in uniformly sloping hillslopes, resulting in a remarkably accurate and applicable family of results, though often challenging to solve due to its nonlinear form. Under certain conditions, the Boussinesq equation can be solved analytically allowing compact representation of soil and geomorphological controls on unconfined aquifer storage and release dynamics. The Boussinesq equation has been extended to account for flow divergence/convergence as well as for nonuniform bedrock slope (concave/convex). The extended Boussinesq equation has been favorably compared to numerical solutions of the three-dimensional Richards equation, confirming its validity under certain geometric conditions. Analytical solutions of the linearized original and extended Boussinesq equations led to the formulation of similarity indices for baseflow recession analysis, including scaling rules, to predict the moments of baseflow response. Validation of theoretical recession parameters on real-world streamflow data is complicated due to limited measurement accuracy, changing boundary conditions, and the strong coupling between the saturated aquifer with the overlying unsaturated zone. However, recent advances are shown to have mitigated several of these issues. The extended Boussinesq equation has been successfully applied to represent baseflow dynamics in catchment-scale hydrological models, and it is currently considered to represent lateral redistribution of groundwater in land surface schemes applied in global circulation models. From the review, it is clear that Wilfried Brutsaert and Jean-Yves Parlange stimulated a body of research that has led to several fundamental discoveries and practical applications with important contributions in hydrological modeling.

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During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether thesemodels are suitable to capture hydrological drought, in terms of runoff, on a global scale. Amultimodel ensemble analysis was carried out to evaluate if 10 such large-scalemodels agree on major drought events during the second half of the twentieth century. Time series of monthly precipitation, monthly total runofffrom 10 global hydrologicalmodels, and their ensemblemedian have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoffand smallest in regions with high runoff. In vast regions, correlation between runoffdrought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoffdrought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoffresponse to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoffresponse was partly overcome and delay in drought propagating from meteorological drought to drought in runoffwas included. Finally, an ensemble of models also allows for consideration of uncertainty associated with individual model structures.

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The relation between storage and discharge is an essential characteristic of many rainfall-runoff models. The simple dynamical systems approach, in which a rainfall-runoff model is constructed from a single storage-discharge relation, has been successfully applied to humid catchments. Here we investigate (1) if and when the less humid lowland Hupsel Brook catchment also behaves like a simple dynamical system by hydrograph fitting, and (2) if system parameters can be inferred from streamflow recession rates or more directly from soil moisture storage observations. Only 39% of the fitted monthly hydrographs yielded Nash-Sutcliffe efficiencies above 0.5, from which we can conclude that the Hupsel Brook catchment does not always behave like a simple dynamical system. Model results were especially poor in summer, when evapotranspiration is high and the thick unsaturated zone attenuates the rainfall input. Using soil moisture data to obtain system parameters is not trivial, mainly because there is a discrepancy between local and catchment storage. Parameters obtained with direct storage-discharge fitting led to a strong underestimation of the response of runoff to rainfall, while recession analysis leads to an overestimation.@en

On 26 August 2010 the eastern part of The Netherlands and the bordering part of Germany were struck by a series of rainfall events lasting for more than a day. Over an area of 740 km2 more than 120 mm of rainfall were observed in 24 h. This extreme event resulted in local flooding of city centres, highways and agricultural fields, and considerable financial loss. In this paper we report on the unprecedented flash flood triggered by this exceptionally heavy rainfall event in the 6.5 km2 Hupsel Brook catchment, which has been the experimental watershed employed by Wageningen University since the 1960s. This study aims to improve our understanding of the dynamics of such lowland flash floods. We present a detailed hydrometeorological analysis of this extreme event, focusing on its synoptic meteorological characteristics, its space-time rainfall dynamics as observed with rain gauges, weather radar and a microwave link, as well as the measured soil moisture, groundwater and discharge response of the catchment. At the Hupsel Brook catchment 160 mm of rainfall was observed in 24 h, corresponding to an estimated return period of well over 1000 years. As a result, discharge at the catchment outlet increased from 4.4 × 10-3 to nearly 5 m3 s-1. Within 7 h discharge rose from 5 × 10-2 to 4.5 m3 s -1. The catchment response can be divided into four phases: (1) soil moisture reservoir filling, (2) groundwater response, (3) surface depression filling and surface runoff and (4) backwater feedback. The first 3 5 mm of rainfall were stored in the soil without a significant increase in discharge. Relatively dry initial conditions (in comparison to those for past discharge extremes) prevented an even faster and more extreme hydrological response.@en

Integration of simulated and observed states through data assimilation as well as model evaluation requires a realistic representation of soil moisture in land surface models (LSMs). However, soil moisture in LSMs is sensitive to a range of uncertain input parameters, and intermodel differences in parameter values are often large. Here, the effect of soil parameters on soil moisture and evapotranspiration are investigated by using parameters from three different LSMs participating in the European Land Data Assimilation System (ELDAS) project. To prevent compensating effects from other than soil parameters, the effects are evaluated within a common framework of parsimonious stochastic soil moisture models. First, soil parameters are shown to affect soil moisture more strongly than the average evapotranspiration. In arid climates, the effect of soil parameters is on the variance rather than the mean, and the intermodel flux differences are smallest. Soil parameters from the ELDAS LSMs differ strongly, most notably in the available moisture content between the wilting point and the critical moisture content, which differ by a factor of 3. The ELDAS parameters can lead to differences in mean volumetric soil moisture as high as 0.10 and an average evapotranspiration of 10%-20% for the investigated parameter range. The parsimonious framework presented here can be used to investigate first-order parameter sensitivities under a range of climate conditions without using full LSM simulations. The results are consistent with many other studies using different LSMs under a more limited range of possible forcing conditions.@en

Characterization of the space-time variability of soil moisture is important for land surface and climate studies. Here we develop an analytical model to investigate how, at the dry-end of the soil moisture range, the main characteristics of the soil moisture field (spatial mean and variability, steady state distribution) depend on the intermittent character of low intensity rain storms. Our model is in good agreement with data from the recent National Airborne Field Experiment (NAFE'06) held in the semiarid Australian Murrumbidgee catchment. We find a positive linear relationship between mean soil moisture and its associated variability, and a strong dependency of the temporal soil moisture distribution to the amount and structure of precipitation.

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We investigate the role of interannual climate variability on spatial soil moisture variability dynamics for a field site in Louvain-la-Neuve, Belgium. Observations were made during 3 years under intermediate (1999), wet (2000), and extremely dry conditions (2003). Soil moisture variability dynamics are simulated with a comprehensive model for the period 1989-2003. The results show that climate variability induces non-uniqueness and two distinct hysteresis modes in the yearly relation between the spatial mean soil moisture and its variability. We demonstrate that the direction of hysteresis is related to a yearly climate index that does not require soil moisture observations.

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Root zone soil moisture is a key variable in many land surface hydrology models. Often, however, there is a mismatch in the spatial scales at which models simulate soil moisture and at which soil moisture is observed. This complicates model validation. The increased availability of detailed datasets on space-time variability of root-zone soil moisture allows for a posteriori analysis of the uncertainties in the relation between point-scale observations and the spatial mean. In this paper we analyze three comprehensive datasets from three different regions. We identify different strategies to select observation sites. For instance, sites can be located randomly or according to the rank stability concept. For each strategy, we present methods to quantify the uncertainty that is associated with this strategy. In general there is a large correspondence between the different datasets with respect to the relative uncertainties for the different strategies. For all datasets, the uncertainty can be strongly reduced if some information is available that relates soil moisture content at that site to the spatial mean. However this works best if the space-time dynamics of the soil moisture field are known. Selection of the site closest to the spatial mean on a single random date only leads to minor reduction of the uncertainty with respect to the spatial mean over seasonal timescales. Since soil moisture variability is the result of a complex interaction between soil, vegetation, and landscape characteristics, the soil moisture field will be correlated with some of these characteristics. Using available information, we show that the correlation with leaf area index or a wetness coefficient alone is insufficient to predict if a site is representative for the spatial mean soil moisture content.@en

Experiments have shown that plants can compensate for water stress in the upper, more densely rooted, soil layers by increasing the water uptake from deeper layers. By adapting root water uptake to water availability, plants are able to extend the period of unstressed transpiration. This strategy conflicts with the approach in many land surface schemes, where plant water uptake is treated as a static process. Here we derive expressions for the typical drydown trajectories of evapotranspiration and soil moisture for both strategies. We show that the maximum difference in evapotranspiration between the two strategies during drydown can exceed 50%. This in turn leads to a difference in root zone soil moisture of up to 25%. The results stress the importance of incorporating realistic root water uptake concepts in land surface schemes.@en

It has recently been suggested that the bimodality in warm season soil moisture observations in Illinois is evidence of a soil moisture-precipitation feedback. Other studies however provide little evidence for a strong feedback in this region. Here we show that seasonality in the meteorological conditions in combination with the nonlinearity of the soil moisture response alone can induce this bimodality. The existence of preferred wet and dry soil moisture states may have implications for the understanding and modeling of soil moisture dynamics in mid-latitude regions.

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