International audienceThis paper investigates three categories of models that are derived from the equilibrium temperature concept to estimate water temperatures in the Loire River in France and the sensitivity to changes in hydrology and climate. We test the models' individual performances for simulating water temperatures and assess the variability of the thermal responses under the extreme changing climate scenarios that are projected for 2081-2100. We attempt to identify the most reliable models for studying the impact of climate change on river temperature (Tw). Six models are based on a linear relationship between air temperatures (Ta) and equilibrium temperatures (Te), six depend on a logistic relationship, and six rely on the closure of heat budgets. For each category, three approaches that account for the river's thermal exchange coefficient are tested. In addition to air temperatures, an index of day length is incorporated to compute equilibrium temperatures. Each model is analysed in terms of its ability to simulate the seasonal patterns of river temperatures and heat peaks. We found that including the day length as a covariate in regression-based approaches improves the performance in comparison with classical approaches that use only Ta. Moreover, the regression-based models that rely on the logistic relationship between Te and Ta exhibit root mean square errors comparable (0.90 °C) with those obtained with a classical five-term heat budget model (0.82 °C), despite a small number of required forcing variables. In contrast, the regressive models that are based on a linear relationship Te = f(Ta) fail to simulate the heat peaks and are not advisable for climate change studies. The regression-based approaches that are based on a logistic relationship and the heat balance approaches generate notably similar responses to the projected climate changes scenarios. This similarity suggests that sophisticated thermal models are not preferable to cruder ones, which are less time-consuming and require fewer input data

Abstract. Low-flow simulation and forecasting remains a difficult issue for hydrological modellers, and intercomparisons can be extremely instructive for assessing existing lowflow prediction models and for developing more efficient operational tools. This research presents the results of a collaborative experiment conducted to compare low-flow simulation and forecasting models on 21 unregulated catchments in France. Five hydrological models (four lumped storagetype models -Gardenia, GR6J, Mordor and Presages -and one distributed physically oriented model -SIM) were applied within a common evaluation framework and assessed using a common set of criteria. Two simple benchmarks describing the average streamflow variability were used to set minimum levels of acceptability for model performance in simulation and forecasting modes. Results showed that, in simulation as well as in forecasting modes, all hydrological models performed almost systematically better than the benchmarks. Although no single model outperformed all the others for all catchments and criteria, a few models appeared to be more satisfactory than the others on average. In simulation mode, all attempts to relate model efficiency to catchment or streamflow characteristics remained inconclusive. In forecasting mode, we defined maximum useful forecasting lead times beyond which the model does not bring useful information compared to the benchmark. This maximum useful lead time logically varies between catchments, but also depends on the model used. Simple multi-model approaches that combine the outputs of the five hydrological models were tested to improve simulation and forecasting efficiency. We found that the multi-model approach was more robust and could provide better performance than individual models on average.

International audienceAccurate model predictions of water flow and solute transport in unsaturated soils require a correct representation of relevant mechanisms in a mathematical model, as well as correct solutions of the mathematical equations. Because of the complexity of boundary conditions and the nonlinearity of the processes considered, general solutions of the mathematical equations rely on numerical approximations. We evaluate a number of numerical models (WAVE, HYDRUS_1D, SWAP, MARTHE, and MACRO) that use different numerical methods to solve the flow and transport equations. Our purpose is to give an overview of analytical solutions that can be found for simple initial and boundary conditions and to define benchmark scenarios to check the accuracy of numerical solutions. Included are analytical solutions for coupled transport equations that describe flow and transport in dual-velocity media. The relevance of deviations observed in the analytical benchmarks for more realistic boundary conditions is illustrated using an intercode comparison for natural boundary conditions. For the water flow scenarios, the largest deviations between numerical models and analytical solutions were observed for the case of soil limited evaporation. The intercode differences could be attributed to the implementation of the evaporation boundary condition: the spatial discretization and the internode averaging of the hydraulic conductivity in the surface grid layer. For solute transport, accurate modeling of solute dispersion poses the most problems. Nonlinear and nonequilibrium sorption and coupled transport in pore domains with different advection velocities are in general accurately simulated

No abstract

Daily water temperature was simulated at a regional scale during the summer period using a simplified model based on the equilibrium temperature concept. The factors considered were heat exchanges at the water/atmosphere interface and groundwater inputs. The selected study area was the Loire River basin (110 000 km2), which displays contrasted meteorological, hydrological and geomorphological features. To capture the intra‐basin variability of relevant physical factors driving the hydrological and thermal response of the system, the modelling approach combined a semi‐distributed hydrological model, simulating the daily discharge at the outlet of 68 subwatersheds (drainage area between 100 and 3700 km2), and a thermal model, simulating the average daily water temperature for each Strahler order in each subwatershed. Simulations at 67 measurement stations revealed a median root mean square error (RMSE) of 1.9°C in summer between 2000 and 2006. Water temperature at stations located more than 100 km from their headwater was adequately simulated (median RMSE < 1.5°C; −0.5°C < median biases < 0.5°C). However, performance for rivers closer to their source varied because of the averaging of geomorphological and hydrological features across all the tributaries with the same Strahler order in a subwatershed, which tended to mask the specific features of the tributaries. In particular, this increased the difficulty of simulating the thermal response of groundwater‐fed rivers during the hot spells of 2003. This modelling by coupling subwatershed and Strahler order for temperature simulations is less time‐consuming and has proven to be extremely consistent for large rivers, where the addition of streambed inputs is adequate to describe the effect of groundwater inputs on their thermal regime. Copyright © 2015 John Wiley & Sons, Ltd.