To investigate the prevalence and cause of concentration‐discharge (C‐Q) relationships for carbon, nutrients, major ions, and particulates, we analyzed 40 years of water quality data from 293 monitoring stations in France. Catchments drained diverse landscapes and ranged from 50 to 110,000 km2, together covering nearly half of France. To test for differences during low and high flows, we calculated independent C‐Q slopes above and below the median discharge. We found that 84% of all catchment‐element combinations were chemodynamic for at least half of the hydrograph and 60% of combinations showed nonlinear C‐Q curves. Only two or three of the nine possible C‐Q modalities were manifest for each parameter, and these modalities were stable through time, suggesting that intrinsic and extrinsic elemental properties (e.g., solubility, reactivity, and source dynamics) set basic C‐Q templates for each parameter, which are secondarily influenced by biological activity during low flows, and the interaction between hydrology and catchment characteristics at high flows. Several patterns challenged current C‐Q views, including low‐flow chemostasis for TSS in 66% of catchments, low‐flow biological mediation of NO3− in 71% of catchments, and positive C‐Q for dissolved organic carbon independent of catchment size in 80% of catchments. Efforts to reduce nutrient loading decreased phosphorus concentration and altered C‐Q curves, but NO3− continued to increase. While C‐Q segmentation requires more data than a single analysis, the prevalence of nonlinear C‐Q slopes demonstrates the potential information loss associated with linear or monotonic analysis of C‐Q relationships, and conversely, the value of long‐term monitoring.

Abstract. Trends and seasonality analysis from 1980 onward and longitudinal distribution, from headwaters to estuary, of chlorophyll a, nitrate and phosphate were investigated in the eutrophic Loire River. The continuous decline of phosphate concentrations which has been recorded since 1991 both in the main river and in the tributaries has led to the conclusion that it was responsible for the significant reduction in phytoplanktonic biomass across the whole river system, although Corbicula spp. clams invaded the river during the same period and probably played a significant role in the phytoplankton decline. While eutrophication remained lower in the main tributaries than in the Loire itself, they were found to contribute up to ≈ 35 % to the total nutrient load of the main river. The seasonality analysis revealed significant seasonal variations for the different eutrophication metrics and calls into question the classical monthly survey recommended by national or international authorities. Reducing P inputs impacted these seasonal variations: the decline of seasonal amplitudes of chlorophyll a reduced the seasonal amplitude of orthophosphate and of daily variations of dissolved oxygen and pH but did not significantly affect the seasonal amplitude of nitrate. Thus, the influence of phytoplankton on seasonal variations of nitrate was minor throughout the period of study.

Data on riverine fluxes are essential for calculating element cycles (carbon, nutrients, pollutants) and erosion rates from regional to global scales. At most water-quality stations throughout the world, riverine fluxes are calculated from continuous flow data (q) and discrete concentration data (C), the latter being the main cause of sometimes large uncertainties. This article offers a comprehensive approach for predicting the magnitude of these uncertainties for water-quality stations in medium to large basins (drainage basin area > 1000 km²) based on the commonly used discharge-weighted method. Uncertainty levelsbiases and imprecisionsfor sampling intervals of 3 to 60 days are correlated first through a nomograph with a flux variability indicator, the quantity of riverine material discharged in 2% of time (M 2% ). In turn, M 2% is estimated from the combination of a hydrological reactivity index, W 2% (the cumulative flow volume discharged during the upper 2% of highest daily flow) and the truncated b 50sup exponent, quantifying the concentration versus discharge relationship for the upper half of flow values (C = a q b50sup , for q > q 50 , where q 50 is the median flow): M 2% = W 2% + 27.6b 50sup . W 2% can be calculated from continuous flow measurements, and the b 50sup indicator can be calculated from infrequent sampling, which makes it possible to predict a priori the level of uncertainty at any station, for any type of riverine material either concentrated (b 50sup > 0) or diluted (b 50sup > 0) with flow. A large data base of daily surveys, 125 station variables of suspended particulate matter (SPM), total dissolved solids (TDS) and dissolved and particulate nutrients, was used to determine uncertainties from simulated discrete surveys and to establish relationships between indicators. Results show, for example, that for the same relatively reactive basin (W 2% > 25%), calculated fluxes from monthly sampling would yield uncertainties approaching AE100% for SPM (b 50sup > 1.4) fluxes and AE10% for TDS (b 50sup = À0.2). The application to the nitrate survey of the river Seine shows significant trends for the 1972-2009 records.

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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.