Catchment In Belgium Research Articles

Mitigating glyphosate levels in surface waters: Long-term assessment in an agricultural catchment in Belgium

The increasing concern over pesticide pollution in water bodies underscores the need for effective mitigation strategies to support the transition towards sustainable agriculture. This study assesses the effectiveness of landscape mitigation strategies, specifically vegetative buffer strips, in reducing glyphosate loads at the catchment scale under realistic conditions. Conducted over six years (2014–2019) in a small agricultural region in Belgium, our research involved the analysis of 732 water samples from two monitoring stations, differentiated by baseflow and event-driven sampling, and before (baseline) and after the implementation of mitigation measures.The results indicated a decline in both the number and intensity of point source losses over the years. Additionally, there was a general decrease in load intensity; however, the confluence of varying weather conditions (notably dry years during the mitigation period) and management practices (the introduction of buffer strips) posed challenges for a statistically robust evaluation of each contributing factor. A reduction of loads was measured when comparing mitigation with baseline, although this reduction is not statistically significant. Glyphosate loads during rainfall events correlated with a rainfall index and runoff ratio. Overall, focusing the mitigation strategy on runoff and erosion was a valid approach. Nevertheless, challenges remain, as evidenced by the continuous presence of glyphosate in baseflow conditions, highlighting the complex dynamics of pesticide transport.The study concludes that while progress has been made towards reducing pesticide pollution, the complexity of interacting factors necessitates further research. Future directions should focus on enhancing farmer engagement in mitigation programs and developing experiments with more intense data collection that help to assess underlying dynamics of pesticide pollution and the impact of mitigation strategies in more detail, contributing towards the goal of reducing pesticide pollution in water bodies.

Comparison of measured and predicted herbicide concentrations in surface water catchments in Belgium.

In the process of approval of active substances and authorization in the European Union and at the member state level, it must be shown by the applicant that an unacceptable risk for nontarget organisms in the aquatic environment by the active substance can be excluded. To achieve this aim, standardized models, scenarios, and agreed pesticide input parameters have to be used to calculate the exposure as defined by the FOrum for the Co-ordination of pesticide fate models and their Use (FOCUS). During a period of daily surface water sampling lasting 3.5 years, a survey was conducted among farmers in the highly vulnerable catchment of Grote Kemmelbeek in Belgium to collect agronomic data on crops, application dates, and application rates of 12 applied herbicides and one metabolite. Daily surface water concentrations for the same herbicides were measured over 2.5 years for a second, much larger but less vulnerable, catchment of Kleine Aa (KAa). A comparison of realistic worst-case predicted environmental concentrations in surface water (PECsw) according to FOCUS with measured concentrations shows that, in the GKb catchment, the PECsw was never exceeded for six substances, was exceeded on only 1-2 days for five substances, and was exceeded on 9-27 days for two substances. For the KAa catchment, the PECsw was only exceeded on twodays for one compound and never for the other 12 compounds. These numbers correspond to a level of protection of the FOCUS PECsw between 100% and 97% and are much higher than the regulatory protection goal of 90%. These two case studies demonstrate the protectiveness of the FOCUS surface water approach. Integr Environ Assess Manag 2024;20:1447-1462. © 2024 Bayer AG. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments

Abstract Accurate streamflow simulations rely on good estimates of the catchment-scale soil moisture distribution. Here, we evaluated the potential of Sentinel-1 backscatter data assimilation (DA) to improve soil moisture and streamflow estimates. Our DA system consisted of the Noah-MP land surface model coupled to the HyMAP river routing model and the water cloud model as a backscatter observation operator. The DA system was set up at 0.01° resolution for two contrasting catchments in Belgium: (i) the Demer catchment dominated by agriculture and (ii) the Ourthe catchment dominated by mixed forests. We present the results of two experiments with an ensemble Kalman filter updating either soil moisture only or soil moisture and leaf area index (LAI). The DA experiments covered the period from January 2015 through August 2021 and were evaluated with independent rainfall error estimates based on station data, LAI from optical remote sensing, soil moisture retrievals from passive microwave observations, and streamflow measurements. Our results indicate that the assimilation of Sentinel-1 backscatter observations can partly correct errors in surface soil moisture due to rainfall errors and overall improve surface soil moisture estimates. However, updating soil moisture and LAI simultaneously did not bring any benefit over updating soil moisture only. Our results further indicate that streamflow estimates can be improved through Sentinel-1 DA in a catchment with strong soil moisture–runoff coupling, as observed for the Ourthe catchment, suggesting that there is potential for Sentinel-1 DA even for forested catchments. Significance Statement The purpose of this study is to improve streamflow estimation by integrating soil moisture information from satellite observations into a hydrological modeling framework. This is important preparatory work for operational centers that are responsible for producing the most accurate flood forecasts for the society. Our results provide new insights into how and where streamflow forecasting could benefit from high-spatial-resolution Sentinel-1 radar backscatter observations.

Aquatic Risks at the Landscape Scale: A Case Study for Pyrethroid Use in Pome Fruit Orchards in Belgium.

Procedures for environmental risk assessment for pesticides are under continuous development and subject to debate, especially at higher tier levels. Spatiotemporal dynamics of both pesticide exposure and effects at the landscape scale are largely ignored, which is a major flaw of the current risk assessment system. Furthermore, concrete guidance on risk assessment at landscape scales in the regulatory context is lacking. In this regard, we present an integrated modular simulation model system that includes spatiotemporally explicit simulation of pesticide application, fate, and effects on aquatic organisms. As a case study, the landscape model was applied to the Rummen, a river catchment in Belgium with a high density of pome fruit orchards. The application of a pyrethroid to pome fruit and the corresponding drift deposition on surface water and fate dynamics were simulated. Risk to aquatic organisms was quantified using a toxicokinetic/toxicodynamic model for individual survival at different levels of spatial aggregation, ranging from the catchment scale to individual stream segments. Although the derivation of landscape-scale risk assessment end points from model outputs is straightforward, a dialogue within the community, building on concrete examples as provided by this case study, is urgently needed in order to decide on the appropriate end points and on the definition of representative landscape scenarios for use in risk assessment.

Assimilation of Backscatter Observations into a Hydrological Model: A Case Study in Belgium Using ASCAT Data

We investigated the possibilities of improving hydrological simulations by assimilating radar backscatter observations from the advanced scatterometer (ASCAT) in the hydrological model SCHEME using a calibrated water cloud model (WCM) as an observation operator. The WCM simulates backscatter based on soil moisture and vegetation data and can therefore be used to generate observation predictions for data assimilation. The study was conducted over two Belgian catchments with different hydrological regimes: the Demer and the Ourthe catchment. The main differences between the two catchments can be summarized in precipitation and streamflow levels, which are higher in the Ourthe. The data assimilation method adopted here was the ensemble Kalman filter (EnKF), whereby the uncertainty of the state estimate was described via the ensemble statistics. The focus was on the optimization of the EnKF, and possible solutions to address biases introduced by ensemble perturbations were investigated. The latter issue contributes to the fact that backscatter data assimilation only marginally improves the overall scores of the discharge simulations over the deterministic reference run, and only for the Ourthe catchment. These performances, however, considerably depend on the period considered within the 5 years of analysis. Future lines of research on bias correction, the data assimilation of soil moisture and backscatter data are also outlined.

Evaluation of SEAWAVE-QEX in a high agricultural intensity catchment in Belgium.

Pesticide surface water monitoring data have rarely been used as the only quantitative measure of exposure because the available monitoring data for most pesticides has not been considered robust enough for direct use in pesticide exposure assessments due to infrequent sampling. The cost of daily sample collection and analysis prohibits frequent sampling for most monitoring programs. In this context, a common question raised in assessments is how likely peak concentrations (i.e., annual maxima) may be missed if sampling intervals are longer than daily. The US Geological Survey developed the statistical model "seasonal wave with streamflow adjustment and extended capability" (SEAWAVE-QEX) to address the need to estimate infrequently occurring pesticide concentrations, such as annual maximum daily concentrations, for sites with nondaily monitoring data. This study compares the results of two postprocessing methods and evaluates the capability of SEAWAVE-QEX to estimate annual maximum concentrations of three commonly used herbicides and one metabolite in a catchment in Belgium. The study concludes that the appropriateness of using SEAWAVE-QEX to estimate annual maximum concentrations depends on pesticide characteristics and use and that the model can be particularly sensitive to nonflow correlated exposure events (e.g., point source contributions or drift). Integr Environ Assess Manag 2023;19:513-526. © 2022 Stone Environmental and Bayer AG Crop Science Division. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Exploring river–aquifer interactions and hydrological system response using baseflow separation, impulse response modeling, and time series analysis in three temperate lowland catchments

Abstract. Lowland rivers and shallow aquifers are closely coupled, and their interactions are crucial for maintaining healthy stream ecological functions. To explore river–aquifer interactions and the lowland hydrological system in three Belgian catchments, we apply a combined approach of baseflow separation, impulse response modeling, and time series analysis over a 30-year study period at the catchment scale. Baseflow from hydrograph separation shows that the three catchments are groundwater-dominated systems. The recursive digital filter methods generate a smoother baseflow time series than the graphical methods. Impulse response modeling is applied using a two-step procedure. The first step of groundwater level response modeling shows that groundwater level in shallow aquifers reacts fast to the system input, with most of the wells reaching their peak response during the first day. There is an overall trend of faster response time and higher response magnitude in the wet (October–March) than the dry (April–September) periods. The second step of groundwater inflow response modeling shows that the system response is also fast and that simulated groundwater inflow can capture some variations but not the peaks of the separated baseflow time series. The time series analysis indicates that groundwater discharge to rivers is likely following groundwater level time series characteristics, with a strong trend and seasonal strengths, in contrast to the streamflow, which exhibits a weak trend and seasonality. The impulse response modeling approach from the groundwater flow perspective can be an alternative method to estimate the groundwater inflow to rivers, as it considers the physical connection between river and aquifer to a certain extent. Further research is recommended to improve the simulation, such as giving more weight to wells close to the river and adding more drainage dynamics to the model input.

Modelling soil erosion by water under future climate change: Addressing methodological gaps

Soil erosion by water from arable land poses a serious threat to on-field agricultural productivity and the wider environment through off-site damage. Multiple studies show that climate change will worsen the impacts of soil erosion in various regions. However, these studies are limited by (1) the lack of any thorough evaluation process in applying climate scenarios to drive soil erosion models, and (2) the failure to consider the role of changing land use under future climate change, despite the evidence that it is more important than rainfall changes in driving increased erosion. Using the WEPP soil erosion model, these methodological gaps are addressed in this study for a small catchment in Belgium that is both heavily impacted by soil erosion and boasting an extensive array of mitigation measures. We develop a novel and comprehensive methodology to rigorously and efficiently select suitable climate models specifically for simulating soil erosion by water, and examine the impact of a range of environmentally and economically viable land use choices on soil erosion. The main findings reveal that our climate model selection methodology is successful in generating the widest range of likely future scenarios from a small number of models, compared with other selection methods. Our novel methodology reveals that the magnitude and frequency of soil erosion events will increase considerably under the mean of all scenarios between 2041 and 2100 with existing land management. Winter wheat represents the most economically and environmentally viable land use choice to effectively mitigate future soil erosion when compared to other land use alternatives under the full range of likely future climate scenarios. This research illuminates the importance of carefully tuned climate model selection and land use changes for modelling future soil erosion by water so the best- and worst-case scenarios can be adequately prepared for under a changing climate.

Performance of the LandSoil expert‐based model to map erosion and sedimentation: application to a cultivated catchment in central Belgium

AbstractIntensive agricultural practices on sensitive soils induce high erosion rates in central Belgium. Expert‐rules models quantify runoff and erosion at catchment scale, avoiding over‐parameterization, and can include some direct or indirect connectivity features. The aim of this article is to test the ability of an expert‐based model, LandSoil, to quantify runoff and to locate erosion and sedimentation areas in a small cultivated loamy catchment in Belgium during the years 2014, 2015 and 2016. Spatialized data are important for assessing model outputs and the erosive response. Measurements of runoff and observation of spatial erosion/deposition patterns, especially around major connectivity points, permitted an assessment of the reliability of the model results. Runoff modelling gave contrasting results (good linear adjustment at the outlet of the 83 ha sub‐catchment (point 1): r2 of 0.96, Nash–Sutcliffe criterion of 0.95; less good at the outlet of the 3.9 ha sub‐catchment (point 2): r2 of 0.28, Nash–Sutcliffe criterion of –0.47). For point 2 the poor results are explained by the very few runoff events observed, a scaling effect and the small area with a single land use. Graduated rulers demonstrate that the model is able to provide a coherent pattern of erosion/deposition. The study highlights great sensitivity to the effect of land use, land allocation, landscape design and slope gradients. Grass strips induce deposition of eroded particles when slopes are gentle (< 2%). Woodland strips decrease connectivity by being in the stream but deposit thinner sediment layers. Field boundaries have a role in the transport, but not really the quantity, of sediments. This model validation in the Belgian loess context allows us to use LandSoil in other similar environments in order to estimate the effects of landscape management scenarios. © 2020 John Wiley & Sons, Ltd.

Uncertainty Analysis of Climate Change Impact on River Flow Extremes Based on a Large Multi-Model Ensemble

Water managers are faced with a changing climate in the decision-making process while adaptation and mitigation strategies need to be developed. The climate change impact towards the end of the century, however, is highly uncertain and coping with this is a great challenge for decision makers. Over the recent years, combined efforts of hydrologists and climatologists have led to many climate change impact studies on water resources. However, most studies only use a limited ensemble size and/or focus on only one contributing source and hence possibly underestimate the total uncertainty. For two Belgian catchments, we simulated daily flow with five different lumped conceptual hydrological models and ten different parameter sets each, forced by the output of 24 global climate models covering four different emission scenarios, combined with 9 different downscaling methods over reference (1961–1990) and future (2071–2100) periods, resulting in a large multi-model ensemble with 41,850 members. Results show that both low and peak flows would become more extreme in the future, and these changes are stronger with increased radiative forcing. The most important uncertainty sources in low-flow projections are the global climate models (explaining 27–36% of the total variance) and the hydrological model structure (34–42%). For peak flow projections, these are global climate models (32–39%) and statistical downscaling methods (21–26%). Also, interaction effects account for a significant part of the uncertainty (24–38%). The results of this study illustrate that one might end up with biased results and overly confident conclusions when only focusing on some of the uncertainty sources in multi-model ensembles.

Coupling catchment runoff models to groundwater flow models in a multi-model ensemble approach for improved prediction of groundwater recharge, hydraulic heads and river discharge

Groundwater recharge plays an important role in groundwater resource sustainability. Many approaches are available for quantifying recharge, including the use of numerical hydrological models. Various studies have assessed the efficacy of integrating recharge information from rainfall-runoff models into groundwater models. These studies, however, have been mostly restricted to a single hydrological model and were not able to evaluate the impact on simulating groundwater conditions caused by different recharge inputs. Furthermore, hydrological recharge models used in these studies are often fully distributed and physically based, resulted in high complexity in model structure, and, hence, posed equifinality challenges in calibration. On the other hand, these models may be more reliable for impact studies, which often involve extrapolation beyond the range of available calibration datasets. This paper proposes a modelling approach that replaces the groundwater reservoir in conceptual rainfall-runoff models by a more detailed and more physically based groundwater component. The approach enables assessment of the impact on groundwater conditions by different recharge models and to improve the model performance on simulating baseflow. The methodology starts with three well-calibrated lumped conceptual models, which were then disaggregated into spatially distributed codes to provide spatial–temporal information on groundwater recharge. The approach was tested for three conceptual models and applied to a catchment in Belgium. Model results were found to be consistent with respect to observations when evaluated for seasonal variations of groundwater heads and for cumulative groundwater discharge. However, evaluation of river hydrograph shapes and water-table variations revealed distinct results produced by the different recharge models.

On the correlation between precipitation and potential evapotranspiration climate change signals for hydrological impact analyses

ABSTRACTState-of-the-art hydrological climate impact assessment involves ensemble approaches to address uncertainties. For precipitation, a wide range of climate model runs is available. However, for particular meteorological variables used for the calculation of potential evapotranspiration (ETo), availability of climate model runs is limited. It is preferred that climate model runs are considered coupled when calculating changes in precipitation and ETo amounts, in order to preserve the internal physical consistency. This results in constraints on the maximum ensemble size. In this paper, we investigate the correlation between climate change signals of precipitation and ETo. It is found that, for two medium-sized catchments in Belgium, uncoupling climate model runs used for calculation of change signals of precipitation and ETo amounts does not result in a significant bias for changes in extreme flow. With these results, future impact studies can be conducted with larger ensemble sizes, resulting in a more complete uncertainty estimation.

Identification of uncertainty sources in distributed hydrological modelling: Case study of the Grote Nete catchment in Belgium

The quest for good practice in modelling merits thorough and sustained attention since good practice increases the credibility and impact of the information, and insight that modelling seeks to generate. This paper presents the findings of an evaluation whose goal was to understand the uncertainty in applying a distributed hydrological model to the Grote Nete catchment in Flanders, Belgium. Uncertainties were selected for investigation depending on how significantly they affected the model's decision variables. A Fault Tree was used to determine various combinations of inputs, mathematical code, and human error failures that could result in a specified risk. A combination of forward and backward approaches was used in developing the Fault Tree. Eleven events were identified as contributing to the top event. A total of 7 gates were used to describe the Fault Tree. A critical path analysis was carried out for the events and established their rank or order of significance. Three measures of importance were applied, namely the F-Vesely, the Birnbaum, and the B-Proschan importance measures. Model development of distributed models involves considerable uncertainty. Many of these dependencies arise naturally and their correct evaluation is crucial to the accurate analysis of the modelling system reliability.

Comparison of perturbation methods for rainfall and temperature data: case of a Belgian catchment

Analyses of hydrological impacts of climate change require appropriate methods for perturbing meteoric time-series to represent future climate conditions. Two readily available tools for perturbing rainfalls and temperatures are tested for a medium-sized catchment in Belgium. CCI-HYDR provides three scenarios, tailored for Belgium every decade until 2100. In contrast, KNMI-ADC tool provides 191 scenarios, at a regional level and for two horizons (near and far future). With its three contrasted scenarios of possible future climate conditions, CCI-HYDR is found suitable for forcing computationally intensive detailed hydrological models. With its broader spectrum of climate scenarios, KNMI-ADC tool is suitable for forcing multiple runs of fast conceptual hydrological models. As the two perturbation tools deliver stationary time-series, they are also compared to an alternate method producing transient time-series. Transient stochastic tools are particularly computationally demanding due to their stochastic nature, which is not optimal when combined with detailed distributed hydrological models.

Comparison of perturbation methods for rainfall and temperature data: case of a Belgian catchment

Analyses of hydrological impacts of climate change require appropriate methods for perturbing meteoric time-series to represent future climate conditions. Two readily available tools for perturbing rainfalls and temperatures are tested for a medium-sized catchment in Belgium. CCI-HYDR provides three scenarios, tailored for Belgium every decade until 2100. In contrast, KNMI-ADC tool provides 191 scenarios, at a regional level and for two horizons (near and far future). With its three contrasted scenarios of possible future climate conditions, CCI-HYDR is found suitable for forcing computationally intensive detailed hydrological models. With its broader spectrum of climate scenarios, KNMI-ADC tool is suitable for forcing multiple runs of fast conceptual hydrological models. As the two perturbation tools deliver stationary time-series, they are also compared to an alternate method producing transient time-series. Transient stochastic tools are particularly computationally demanding due to their stochastic nature, which is not optimal when combined with detailed distributed hydrological models.

Spatially Distributed Conceptual Hydrological Model Building: A Generic Top‐Down Approach Starting From Lumped Models

AbstractChanging environmental conditions might have severe impacts on future flood frequencies and water availability. In order to develop mitigation strategies by carrying out impact studies, lumped hydrological models might not suffice anymore and the need for flexibility in spatial resolution arises. Recent developments already allow to change the grid size of hydrological models depending on the needs and to use different spatial resolutions in parallel for different applications. These developments, however, still face some challenges such as the following: how to avoid strong or sudden changes in simulation results when level of spatial details is changed and how to limit the problem of overparameterization/equifinality while increasing the spatial resolution. We developed a methodology to partially meet these challenges by building parsimonious distributed conceptual hydrological models with a flexible spatial resolution. The methodology starts with calibrated lumped conceptual models. Parameters are then spatially disaggregated based on spatially variable catchment properties, introducing only few additional calibration parameters. The approach is demonstrated for three different conceptual rainfall‐runoff models for two medium‐sized Belgian catchments. The resulting spatial models are found to be accurate with respect to the observations and consistent with the lumped conceptual model results, when evaluated for peak, low, and cumulative total runoff and subflows at downstream and internal gauging stations. A climate change impact analysis further shows consistency of lumped and spatial model results for changing conditions.

Spatial and temporal variability of biological indicators of soil quality in two forest catchments in Belgium

Biological indicators, measurements based on the presence and activity of soil organisms, are increasingly being considered in assessments of forest soil quality. In addition to chemical indicators, such as soil organic carbon and pH, biological indicators can provide an early diagnosis of changes in soil quality and processes in response to environmental change and forest management actions. We investigated the spatial and temporal variability of selected bio-indicators in the forest floor of two catchments over three years. We further evaluated the sensitivity of these indicators to changes in the dominant tree species following reforestation and natural regeneration. Indicators of microbial abundance and activity (microbial biomass, potential respiration) and carbon maintenance costs (metabolic quotient) were higher under young spruce and mixed deciduous stands than pure stands of oak and beech. Our results indicate a greater microbial activity in autumn but a wider range of carbon substrate utilisation in spring. Assessment of seasonal differences in bio-indicator values is vital for the evaluation and planning of long-term studies and the development of reference values for forest soils in Belgium. Our results highlight the usefulness of these bio-indicators in identifying changes in soil quality, particularly in response to management activities, at small spatial scales.

The impact of land use and spatial mediated processes on the water quality in a river system

River systems are highly complex, hierarchical and patchy systems which are greatly influenced by both catchment surroundings and in-stream processes. Natural and anthropogenic land uses and processes affect water quality (WQ) through different pathways and scales. Understanding under which conditions these different river and catchment properties become dominant towards water chemistry remains a challenge. In this study we analyzed the impact of land use and spatial scales on a range of WQ variables within the Kleine Nete catchment in Belgium. Multivariate statistics and spatial descriptors (Moran's and Asymmetric Eigenvector Maps) were used to assess changes in water chemistry throughout the catchment. Both land use and complex mixes of spatial descriptors of different scales were found to be significantly associated to WQ parameters. However, unidirectional, upstream-downstream changes in water chemistry, often described in river systems, were not found within the Kleine Nete catchment. As different sources and processes obscure and interact with each other, it is generally difficult to understand the correct impact of different pollution sources and the predominant pathways. Our results advocate for WQ management interventions on large and small scales where needed, taking the predominate pathways in to account.

Bridging rigorous assessment of water availability from field to catchment scale with a parsimonious agro-hydrological model

While simple crop and hydrological models are limited with respect to the number and accuracy of the processes they incorporate, complex models have high demand for data. Due to the limitations of both categories of models, there is a need for new agro-hydrological models that simulate both crop productivity and water availability in agricultural catchments, with low data and calibration requirements. This study aimed at developing a widely applicable parsimonious agro-hydrological model, AquaCrop-Hydro, which couples the AquaCrop crop water productivity model with a conceptual hydrological model. AquaCrop-Hydro, simulating crop productivity, the daily soil water balance and discharge at the catchment outlet, performed well for an agricultural catchment in Belgium. The model can be used to investigate the effect of agricultural management and environmental changes from field to catchment scale in support of sustainable water management in agricultural areas.

Looking beyond general metrics for model comparison – lessons from an international model intercomparison study

Abstract. International collaboration between research institutes and universities is a promising way to reach consensus on hydrological model development. Although model comparison studies are very valuable for international cooperation, they do often not lead to very clear new insights regarding the relevance of the modelled processes. We hypothesise that this is partly caused by model complexity and the comparison methods used, which focus too much on a good overall performance instead of focusing on a variety of specific events. In this study, we use an approach that focuses on the evaluation of specific events and characteristics. Eight international research groups calibrated their hourly model on the Ourthe catchment in Belgium and carried out a validation in time for the Ourthe catchment and a validation in space for nested and neighbouring catchments. The same protocol was followed for each model and an ensemble of best-performing parameter sets was selected. Although the models showed similar performances based on general metrics (i.e. the Nash–Sutcliffe efficiency), clear differences could be observed for specific events. We analysed the hydrographs of these specific events and conducted three types of statistical analyses on the entire time series: cumulative discharges, empirical extreme value distribution of the peak flows and flow duration curves for low flows. The results illustrate the relevance of including a very quick flow reservoir preceding the root zone storage to model peaks during low flows and including a slow reservoir in parallel with the fast reservoir to model the recession for the studied catchments. This intercomparison enhanced the understanding of the hydrological functioning of the catchment, in particular for low flows, and enabled to identify present knowledge gaps for other parts of the hydrograph. Above all, it helped to evaluate each model against a set of alternative models.