► Model parameters were calibrated on climatically contrasted sub-periods. ► Four optimal and 2000 posterior parameter sets were identified for each catchment. ► Model robustness was the major source ...of variability in streamflow projections.
This paper investigates the uncertainty of hydrological predictions due to rainfall-runoff model parameters in the context of climate change impact studies. Two sources of uncertainty were considered: (i) the dependence of the optimal parameter set on the climate characteristics of the calibration period and (ii) the use of several posterior parameter sets over a given calibration period. The first source of uncertainty often refers to the lack of model robustness, while the second one refers to parameter uncertainty estimation based on Bayesian inference. Two rainfall-runoff models were tested on 89 catchments in northern and central France. The two sources of uncertainty were assessed in the past observed period and in future climate conditions. The results show that, given the evaluation approach followed here, the lack of robustness was the major source of variability in streamflow projections in future climate conditions for the two models tested. The hydrological projections generated by an ensemble of posterior parameter sets are close to those associated with the optimal set. Therefore, it seems that greater effort should be invested in improving the robustness of models for climate change impact studies, especially by developing more suitable model structures and proposing calibration procedures that increase their robustness.
•Hydrological impacts of urbanization are assessed on 142 catchments.•High, low and mean flows were impacted at a threshold of a 10% impervious area.•Waste water treatment facilities highly impact ...low flow but also mean flow.•Urban landscape patterns help interpret the divergent impacts of urbanization.
The impacts of urbanization on floods, droughts and the overall river regime have been largely investigated in the past few decades, but the quantification and the prediction of such impacts still remain a challenge in hydrology. We gathered a sample of 142 catchments that have a documented increase in urban areas over the hydrometeorological record period in the United States. The changes in river flow regimes due to urban spread were differentiated from climate variability using the GR4J conceptual hydrological model. High, low and mean flows were impacted at a threshold of a 10% total impervious area. Moreover, the historical evolution of urban landscape spatial patterns was used to further detail the urbanization process in terms of extent and fragmentation of urban areas throughout the catchment and to help interpret the divergent impacts observed in streamflow behaviors. Regression analysis pointed out the importance of major wastewater treatment facilities that might overpass the effects of imperviousness, and therefore further research should either take them explicitly into account or select a wastewater facility-free catchment sample to clearly evaluate the impacts of urban landscape on low flows.
Given the contradictory results from recent studies, this paper compares classical regionalization schemes of catchment model parameters over the wide range of hydroclimates found in France. To ...ensure the generality of the conclusions, we used two lumped rainfall-runoff models applied to daily data over a large set of 913 French catchments. Three types of approaches were considered: regionalization using regression, regionalization based on spatial proximity and regionalization based on physical similarity. This comparison shows that in France, where a dense network of gauging stations is available, spatial proximity provides the best regionalization solution. The regression approach is the least satisfactory, with results very close to those obtained using one median parameter set for the whole country. The physical similarity approach is intermediary. However, the results obtained with these three methods lag far behind those obtained by full model calibration. Our results also show that some improvement could be made by combining spatial proximity and physical similarity, and that there is still considerable room for progress in the field of ungaged catchment modeling.
This study investigated the potential of random forest (RF) algorithms for regionalizing the parameters of an hourly hydrological model. The relationships between model parameters and ...climate/landscape catchment descriptors were multidimensional and exhibited nonlinear features. In this case, machine-learning tools offered the option of efficiently handling such relationships using a large sample of data. The performance of the regionalized model using RF was assessed in comparison with local calibration and two benchmark regionalization approaches. Two catchment sets were considered: (1) A target pseudo-ungauged catchment set was composed of 120 urban ungauged catchments and (2) 2105 gauged American and French catchments were used for constructing the RF. By using pseudo-ungauged urban catchments, we aimed at assessing the potential of the RF to detect the specificities of the urban catchments. Results showed that RF-regionalized models allowed for slightly better streamflow simulations on ungauged sites compared with benchmark regionalization approaches. Yet, constructed RFs were weakly sensitive to the urbanization features of the catchments, which prevents their use in straightforward scenarios of the hydrological impacts of urbanization.
•Paired catchments are used to investigate the effect of urbanization.•Hydrological simulation is used to replace non-urban neighbor catchments.•Significantly trends on urban hydrology catchments are ...analyzed from 1940 to 2010.
Paired catchment approach probably provides the most robust method to detect the effects of land-use change on catchments’ flow characteristics. This approach is limited by the availability of two neighbor catchments with and without land-use change under similar climate conditions. This paper uses a hydrological model to detect the hydrological change caused by urbanization. This study describes (1) use a statistical method to evaluate change detection relative to variation of land use change, (2) simulation of non-urban condition for the urban catchment with an alternative approach, to this aim stream flow series of urban catchments have been reconstructed from the period that urbanization had not taken place yet, and (3) the model validation with observed data.
This paper intends to compare the flow changes detected by two different approaches: a regional statistical approach (the paired-catchment approach) and a conceptual modeling approach (the residual approach) on the particular case of urbanized catchments. To investigate the sensitivity of the results to the settings of both approaches, the comparison is made on a relatively large number of 43 catchments located in the United States, with relatively large gradients in terms of geomorphology and hydroclimatic characteristics. Results show that the two approaches are generally in relative good agreement in terms of detection and quantification of changes for the three flow characteristics analyzed (mean annual flow, high and low flow characteristics). Besides, it is found that the impact of urbanization on the catchment’s hydrologic response is difficult to generalize: the proportion of nonsignificant trends, significantly increasing decreasing trends are on the same order of magnitude, even if an increase in urban areas generally has a greater impact on mean flows and high flows than on low flows.
This paper investigates the link between vegetation types and long-term water balance in catchment areas. We focus on the most widely used water balance formulas – or models – that relate long-term ...annual streamflow to long-term annual rainfall and long-term potential evapotranspiration estimates. Our investigation seeks to assess whether long-term streamflow can be explained by land cover attributes. As all but one of these formulas do not use land cover information, we develop a methodology to introduce land cover information into the models’ formulations. Then, the modified formulas are compared to the original ones in terms of performance and a sensitivity analysis is performed, with a special focus on the parameters representing vegetation characteristics. In line with the global coverage of long-term water balance models, we base our work on as many basins as possible (1508) representing as large a hydroclimatic variety as possible.
Results show that introducing additional degrees of freedom within the original formulas improves overall model efficiency, and that land cover information makes only a small but nonetheless significant contribution to this improvement.
Study region: French part of the Moselle catchment
Study focus: By relying on hydrological simulations forced by climate change scenarios, stakeholders can assess the magnitude of future changes in ...the rainfall–runoff relationship. The inclusion of human influences in water resources modelling in a non-stationary context is a way to improve the accuracy and usefulness of climate change impact studies. Here, we propose a modelling approach that explicitly considers water uses to evaluate adaptation measures for water management at the French Moselle catchment scale.
New hydrological insights for the region: The results highlight the decrease in future low flows but also the change in the balance between demand and supply. Over the Moselle catchment, whatever the water use scenario considered, climate change induces lower water availability both for environmental flows and for human uses. This leads to a potential increase in the duration of water restriction of up to 8 weeks for RCP 8.5 in the long term (2070–2099) compared to 1976–2005. This study could provide water managers with more appropriate climate impact results and potentially help them to design adequate adaptation measures.
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•Inclusion of human influences in water resources modelling improves the usefulness of climate change impact studies.•This approach explicitly considers water uses to assess adaptation measures for water management for the French Moselle.•We show a decrease in future low flows but also a change in the balance between water demand and supply.•The duration of water restriction could increase up to 8 weeks for RCP8.5 in the long term (2070-2099) compared to 1976-2005.
Soil moisture is a key hydrological variable in flood forecasting: it largely influences the partition of rain between runoff and infiltration and thus controls the flow at the outlet of a catchment. ...The methodology developed in this paper aims at improving the commonly used hydrological tools in an operational forecasting context by introducing soil moisture data into streamflow modelling. A sequential assimilation procedure, based on an extended Kalman filter, is developed and coupled with a lumped conceptual rainfall–runoff model. It updates the internal states of the model (soil and routing reservoirs) by assimilating daily soil moisture and streamflow data in order to better fit these external observations. We present in this paper the results obtained on the Serein, a Seine sub-catchment (France), during a period of about 2 years and using Time Domain Reflectivity probe soil moisture measurements from 0–10 to 0–100 cm and stream gauged data. Streamflow prediction is improved by assimilation of both soil moisture and streamflow individually and by coupled assimilation. Assimilation of soil moisture data is particularly effective during flood events while assimilation of streamflow data is more effective for low flows. Combined assimilation is therefore more adequate on the entire forecasting period. Finally, we discuss the adequacy of this methodology coupled with Remote Sensing data.
In this paper, we analyze how our evaluation of the capacity of a rainfall-runoff model to represent low or high flows depends on the objective function used during the calibration process. We ...present a method to combine models to produce a more satisfactory streamflow simulation, on the basis of two different parameterizations of the same model. Where we previously had to choose between a more efficient simulation for either high flows or low flows (but inevitably less efficient in the other range), we show that a balanced simulation can be obtained by using a seasonal index to weigh the two simulations, providing good efficiency in both low and high flows.
•Four classes of flow intermittency based on mean number of dry months per year.•Forty-nine catchments are studied in Burkina-Faso over 30 years (1955–1985).•Lithology is a crucial control of flow ...intermittency in Burkina Faso.•Flow intermittency classes also explained by catchment area and mean precipitation.•Ephemeral rivers have shorter response times than other flow intermittency classes.
This study focused mainly on Burkina Faso in West Africa.
This study aims to identify environmental variables that best explain the geographic variations of the flow intermittency regime, focusing on intermittency duration. Discharge data from 49 gauging stations were considered, mostly over large rivers. The mean number of dry months (Ndry¯) was used as a predictor to define four classes of flow intermittency, for which the potential explanatory environmental variables were assessed based on correlation analysis and principal component analysis (PCA).
The first two components (PCs) account for 82 % of the total variance with PC1 (52 %), and most of the catchments with similar flow intermittency are ordered according to PC2 (30 %), predominantly related to catchment permeability. Moreover, permeability was highly correlated with Ndry¯ (r = - 0.75). Results suggest that catchment permeability and catchment areas are the most critical variables in determining flow intermittency classes in Burkina Faso, as the effect of precipitation can be overruled by the ones of permeability, catchment area, and Strahler order. This study is a first step in understanding the controls of river intermittency in data-scarce and poorly gauged regions of West Africa. The identified variables could be used as input in statistical models to predict and map river intermittency and provide valuable information for stream conservation.
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