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A major challenge in runoff and soil erosion modelling is the adequate representation of the most relevant processes in models while avoiding over parameterization. In the European loess belt, progressive soil crusting during rainfall events, resulting in infiltration-excess runoff, is usually considered the dominant process generating runoff on catchments covered with silty soils. Saturation-excess may also occur and affect their runoff and erosion behavior. However, saturation-excess runoff occurrence and quantification have rarely been performed and is usually not taken into account when modelling runoff and erosion in these environments. Accordingly, a continuous simulation of the Austreberthe catchment (214 km2), located in the European loess belt (Normandy, France), was conducted with the new Water and Sediment (WaterSed) model over 12 years, corresponding to more than 780 individual rainfall events, at a 25 m spatial resolution. The inter-annual variability of runoff and erosion was closely linked to the number of intense events per year and their distribution through the year. The model was properly calibrated over a representative set of 35 rainfall events, considering either infiltration-excess and/or saturation-excess runoff. It was also able to reproduce the measured runoff volume for most of the monitoring period. However, the three years with most rainfall were adequately modelled only including saturation-excess runoff. An analysis performed at the seasonal scale revealed that saturation was modelled in the catchment during almost all of the modelling period, suggesting the importance of this often overlooked process in current modelling attempts.

Past primary productivity is tracked in lake sediments to reconstruct environmental changes. However, the resolution of the routinely used destructive techniques is not suitable for the analysis of a large number of samples due to cost. Non-destructive analysis of chlorophyll-a performed by hyperspectral imagery enables the quick determination of indices of past primary productivity. Eighteen indices used in paleo-environmental reconstruction were inventoried to define the best index capable of tracking chlorophyll-a by this technique. All the indices were applied to hyperspectral data measured on the sediment of Lake Bresson, in which detrital organic matter input is likely to skew chlorophyll-a identification, and the results were compared with concentrations measured by a routinely used destructive analysis. The 18 indices all produced a different result and only three indices were positively correlated with chlorophyll-a concentrations (n = 28, p < 0.0001). The detrital organic matter impacts chlorophyll-a characterization and shows the bias produced by the sediment matrix variations. Moreover, artificial modification of the sediment matrix revealed an impact of the mineral phase. To tackle this issue, the indices are normalized by two proxies of the sediment components. This new approach reduces the impact of detrital organic matter, hence the sediment matrix variations also reduce the normalization of the chlorophyll-a indices by a specific proxy of the mineral phase. These results identify the impact of local geochemical features that limit past primary productivity assessment and show the necessity of characterizing the sediment composition prior to tracking the chlorophyll-a by hyperspectral imaging.