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In the context of elevated concerns related to nuclear accidents and warfare, the lessons learnt from the Fukushima Daiichi Nuclear Power Plant accident in 2011 are important. In particular, Japanese authorities implemented an ambitious decontamination program to reduce the air dose rate in order to facilitate the return of the local inhabitants to previously evacuated areas. This approach contrasts the strategy adopted in Chernobyl, where the most contaminated areas remain off limits. Nonetheless, the effectiveness of the Japanese decontamination strategy on the dispersion of radioactive contaminant fluxes across mountainous landscapes exposed to typhoons has not been quantified. Based on the unique combination of river monitoring and modeling in a catchment representative of the most impacted area in Japan, we demonstrate that decontamination of 16% of the catchment area resulted in a decrease of 17% of sediment-bound radioactive fluxes in rivers. Decontamination operations were therefore relatively effective, although they could only be conducted in a small part of the area due to the dominance of steep forested slopes. In fact, 67% of the initial radiocesium contamination was calculated to remain stored in forested landscapes, which may contribute to future downstream radiocesium dispersion during erosive events. Given that only a limited proportion of the initial population had returned in 2019 (~30%), it raises the question as to whether decontaminating a small percentage of the contaminated area was worth the effort, the price, and the amount of waste generated? [ABSTRACT FROM AUTHOR]

Excessive sediment discharge in karstic regions can be highly disruptive to water treatment plants. It is essential for catchment stakeholders and drinking water suppliers to limit the impact of high sediment loads on potable water supply, but their strategic choices must be based on simulations integrating surface and groundwater transfers and taking into account possible changes in land use. Karstic environments are particularly challenging as they face a lack of accurate physical descriptions for the modelling process, and they can be particularly complex to predict due to the non-linearity of the processes generating sediment discharge. The aim of the study was to assess the sediment discharge variability at a water treatment plant according to multiple realistic land use scenarios. To reach that goal, we developed a new cascade modelling approach with an erosion-runoff geographic information system (GIS) model (WaterSed) and a deep neural network. The model was used in the Radicatel hydrogeological catchment (106 km 2 in Normandy, France), where karstic spring water is extracted to a water treatment plant. The sediment discharge was simulated for five design storms under current land use and compared to four land use scenarios (baseline, ploughing up of grassland, eco-engineering, best farming practices, and coupling of eco-engineering/best farming practices). Daily rainfall time series and WaterSed modelling outputs extracted at connected sinkholes (positive dye tracing) were used as input data for the deep neural network model. The model structure was found by a classical trial-and-error procedure, and the model was trained on 2 significant hydrologic years. Evaluation on a test set showed a good performance of the model (NSE = 0.82), and the application of a monthly backward-chaining nested cross-validation revealed that the model is able to generalize on new datasets. Simulations made for the four land use scenarios suggested that ploughing up 33 % of grasslands would increase sediment discharge at the water treatment plant by 5 % on average. By contrast, eco-engineering and best farming practices will significantly reduce sediment discharge at the water treatment plant (respectively in the ranges of 10 %–44 % and 24 %–61 %). The coupling of these two strategies is the most efficient since it affects the hydro-sedimentary production and transfer processes (decreasing sediment discharge from 40 % to 80 %). The cascade modelling approach developed in this study offers interesting opportunities for sediment discharge prediction at karstic springs or water treatment plants under multiple land use scenarios. It also provides robust decision-making tools for land use planning and drinking water suppliers. [ABSTRACT FROM AUTHOR]

Excessive sediment discharge at karstic springs and thus, water treatment plants, can be highly disruptive. It is essential for catchment stakeholders and drinking water supplier to reduce the impact of sediment on potable water supply, but their strategic choices must be based on simulations, integrating surface and groundwater transfers, and taking into account possible changes in land use. Karstic environments are particularly challenging as they face a lack of accurate physical description for the modelling process, and they can be seen as a black-box due to the non-linearity of the processes generating sediment discharge. The aim of the study was to assess the sediment discharge variability at a water treatment plant according to multiple realistic land use scenarios. To reach that goal, we developed a new coupled modelling approach with an erosion-runoff GIS model (WaterSed) and a deep neural network. The model was used in the Radicatel catchment (106 km2 in Normandy, France) where karstic spring water is extracted to a water treatment plant. The sediment discharge was simulated for five designed storm projects under current land use and compared to three land use scenarios (baseline, ploughing up of grassland, eco-engineering, best farming practices). Daily rainfall time series and WaterSed modelling outputs extracted at connected sinkholes were used as input data for the deep neural network model. The model structure was found by a classical trial and error procedure, and the model was trained on two significant hydrologic years. Evaluation on a test set showed a good performance of the model (NSE = 0.82), and the application of a monthly-backward chaining nested cross validation revealed that the model is able to generalize on new datasets. Simulations made for the three land use scenarios suggested that ploughing up 33 % of grasslands would not increase significantly sediment discharge at the water treatment plant (5 % in average). In the opposite, eco-engineering and best farming practices will significantly reduce sediment discharge at the water treatment plant (respectively in the range of 10-44 and 24-61 %). The coupling of these two strategies is the most efficient since it affects the hydro-sedimentary production and transfer processes (decreasing sediment discharge from 40 to 80 %). The coupled modelling approach developed in this study offers interesting opportunities for sediment discharge prediction at karstic springs or water treatment plant under multiple land use scenarios. It also provides robust decision-making tools for land use planning and drinking water suppliers. [ABSTRACT FROM AUTHOR]

In recent decades, stream valleys have been profoundly modified by the construction of weirs and dams and by channelisation. Channelisation modifies the morphology of streams and induces changes in their energy regime and sediment transport capacity. These types of changes in the channel morphology have to be quantified to allow the implementation of management strategies to regulate sediment transfer. However, studies over an entire stream using historical comparisons remain scarce, and the associated uncertainties have not yet been resolved. In this study, the sedimentary response to channelisation on a medium time scale (42 years) of a French river known as the Ligoire is investigated. This river is the main channel of a small rural headwater catchment that has been channelised over 21 km. We have used the historical cross sections before and after channelisation and the current ones, and the objectives of this study were as follows: (1) to develop a methodology of cross section superposition and the associated uncertainties; (2) to quantify the erosion and aggradation processes in the bed and on the banks along the bed profile; and (3) to calculate a sediment budget for the entire stream and determine the relative contributions of the banks and the streambed to this budget. A comparison of the cross sections before and after the channelisation shows that the morphology of the stream has been completely altered: the main channel length was reduced by 10%, the bankfull width was increased on average by 63%, and the slopes were smoothed. A total of 60,000 m 3 of sediments was excavated during the channelisation works. Our results indicate that erosion is the dominant process: over 63% of its length, the streambed was incised by 0.41 m on average; and over 60% of its length, the banks were eroded by 0.20 m on average. The successive patterns of erosion and deposition along the stream are the result of the cumulative effects of channelisation and of the presence of weirs and artificial knickpoints in the Ligoire channel. The vertical uncertainty of the elevation of the historical cross section is an important parameter for controlling the areas and sediment budget values. Using Monte Carlo methods, we found that 1000 sediment budgets from different profile shiftings are necessary to obtain a variation coefficient below 0.1%. The overall mean stream sediment budget for the period 1970–2012 is -9358 ± 412 m 3 , with 66% originating from the banks and 34% from the streambed. Relative to the Ligoire watershed surface, the stream sediment yield is 2.71 ± 0.12 m 3 .km − 2 .y − 1 . The approach developed in this study is easily replicable and relatively cheap and provides an integrated quantified, overview of the morphological adjustments after channelisation works on a stream. [ABSTRACT FROM AUTHOR]

A major challenge in geomorphology is reconciling the disparity between runoff coefficients and erosion rates from the field to the catchment scale. In the European loess belt, a decrease of runoff coefficients and erosion rates occurs with increasing spatial scales. Indeed, it is important to understand the scale dependency of run-off and erosion to manage the off-site impacts of accelerated soil erosion. Accordingly, a continuous simulation of the scale dependency of runoff and erosion, from the field scale to the catchment scale (100 – 1000 km²) was conducted with the Water and Sediment (WaterSed) model for two catchments (Andelle-756 km², and Austreberthe-214 km²) over 12 years (>1000 events). Scale effects were evident with a 100-fold decrease in runoff coefficients and sediment delivery ratios between the field scale and the catchment scale. In spite of a low variability of the annual rainfall (19%), the inter-annual variability of the runoff volume (37%) and erosion rates (92%) at catchment outlets were high. The inter-annual variability of runoff and erosion was closely linked to the number of extreme events per year and their distribution through the year, in particular during periods with highly crusted soil surface states. For these high magnitude events, a complex distributed modelling approach was not necessary as the ability of the soil surface and of the landscape to retain overland flows are largely exceeded. The seasonality of soil surface characteristics also affected the scale dependency of runoff and erosion, from the field scale to the catchment scale. However, this is only observed up to a certain spatial extent, i.e. where hillslope erosion processes are governed by hortonian overland flow. When saturation flows are generated, topography and soil depth become the dominant factors. Understanding runoff and sediment response at different scales should focus on the location and amount of runoff and sediment production within the catchment and the capacity of the downstream flow path to retain or transfer overland flow and sediment. Furthermore, this study demonstrates the need to implement model that represent both hortonian and saturation flows when simulating erosion events at the catchment scale. [ABSTRACT FROM AUTHOR]