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Ancient geographical maps are our window into the past for understanding the spatial dynamics of last centuries. This paper proposes a novel approach to address this problem using deep learning. Convolutional neural networks (CNNs) are today the state-of-the-art methods in handling a variety of problems in the fields of image processing. The Cassini map, created in the eighteenth century, is used to illustrate our methodology. This approach enables us to extract the surfaces of classes of lands in the Cassini map: forests, heaths, arboricultural, and hydrological. The evolution of land use between the end of the eighteenth century andtoday was quantified by comparison with Corine Land Cover (CLC) database. For the Rhone watershed, the results show that forests, arboriculture, and heaths are more extensive on the CLC map, in contrast to the hydrological network. These unprecedented results are new findings that reveal the major anthropo-climatic changes. Semantic segmentation allows us to identify several land use patterns from a cartographic support item such as the Cassini map. Semantic segmentation reduces the analysis time of the map by a factor of approximately 10 compared with an entirely manual segmentation, while maintaining an average accuracy equivalent to 90%. Our results illustrate a climatic and anthropic forcing on the Rhône watershed that significantly modified the landscape compared with today.

The flow of large wood among hydraulic structures in rivers, especially in urban areas, can cause many problems. Despite many statistical, morphological and hydrodynamical studies on this phenomenon, little information is available on the transient motion of floating wood pieces. In this study, we investigate theoretically and experimentally the transient motion of floating particles under a simple acceleration. From a standard advection model we identify a particle characteristic response distance to the flow, noted λ. This key parameter is then measured for different floating particles reproducing wood in rivers (logs without and with idealized roots). We show here the typical value of this parameter as a function of particle streamwise body length for different particle geometries. The influence of roots can be well captured by an equivalent frontal area, regardless of the root pattern. This response distance could provide useful information on the probability of impact on hydraulic structures depending on the floating wood characteristics.

Managers need to know how to mitigate rising stream water temperature (WT) due to climate change. This requires identifying the environmental drivers that influence thermal regime and determining the spatial area where interventions are most effective. We hypothesized that (i) extreme thermal events can be influenced by a set of environmental factors that reduce thermal sensitivity and (ii) the role played by those factors varies spatially. To test these hypotheses, we (i) determined which of the environmental variables reported to be the most influential affected WT and (ii)identified the spatial scales over which those environmental variables influenced WT. To this end, the influence of multi-scale environmental variables, namely land cover, topography (channel slope, elevation), hydromorphology (channel sinuosity, water level, watershed area, baseflow index) and shade conditions, was analyzed on the three model variables (day thermal sensitivity, night thermal sensitivity, and non-convective thermal flux) in the model developed by Georges et al. (2021) of the temporal thermal dynamics of daily maximum WT during extreme events. Values were calculated on six spatial scales (the entire upstream catchment and the associated 1 km and 2 km circular buffer, and 50 m wide corridors on each side of the stream with the associated 1 km and 2 km circular buffer). The period considered was 17 extreme days during the summer identified by Georges et al. (2021) based on WT data measured every 10 min for 7 years (2012–2018) at 92 measurement sites. Sites were located evenly throughout the Wallonia (southern Belgium) hydrological network. Results showed that shade, baseflow index (a proxy of the influence of groundwater), water level and watershed area were the most significant variables influencing thermal sensitivity. Since managers with finite financial and human resources can act on only a few environmental variables, we advocate restoring and preserving the vegetation cover that limits solar radiation on the watercourse as a cost-effective solution to reduce thermal sensitivity. Moreover, management at small spatial scale (50 m riparian buffer) should be strategically promoted (for finance and staffing) as our results show that a larger management scale is not more effective in reducing thermal sensitivity to extreme events.

River restoration efforts require interdisciplinary approaches involving fluvial geomorphology, hydraulic engineering, ecology, sedimentology, chemistry, social geography, and sociology. We investigated the functioning of artificial structures called “Casiers Girardon” (groyne fields) in the Rhône River. We assessed potential benefits and risks linked to removing the Rhône groyne fields in a restoration context, with particular focus on the potential for increased bank erosion. Hydraulic, morphological, chemical, ecological, and social issues resulting from dismantlement were studied for terrestrialized and aquatic Casiers Girardon. Only 10% of Casiers Girardon have maintained their aquatic features, whereas most of the Casiers are terrestrialized. Our results help to confirm the effectiveness of restoration actions; however, they also indicate uncertainties and additional knowledge needs, especially in regard to potential incompatibilities between Casier restoration and conservation. Then, an interdisciplinary conceptual model was developed to identify interventions to be considered in Casiers Girardon, according to their terrestrialization rate and physiochemical characteristics (connectivity, amount of gravel vs. fine sediment, contamination level). This model synthetizes scientific results and expert judgment and provides management recommendations based on ecological and sociological expectations about the restoration of Casiers Girardon. The model highlights high heterogeneity in functioning and ecological potential between terrestrialized and aquatic Casiers. Dismantling of terrestrialized Casiers has strong potential to provide multiple benefits, whereas aquatic Casiers could be maintained as valuable backwaters. The managing guidelines for the Casiers Girardon of the Rhône River should be adapted according to local conditions, as well as expected benefits and needs, and conducted in co-ordination with all actors involved in and affected by the restoration.

Riparian forests are critically endangered many anthropogenic pressures and natural hazards. The importance of riparian zones has been acknowledged by European Directives, involving multi-scale monitoring. The use of this very-high-resolution and hyperspatial imagery in a multi-temporal approach is an emerging topic. The trend is reinforced by the recent and rapid growth of the use of the unmanned aerial system (UAS), which has prompted the development of innovative methodology. Our study proposes a methodological framework to explore how a set of multi-temporal images acquired during a vegetative period can differentiate some of the deciduous riparian forest species and their health conditions. More specifically, the developed approach intends to identify, through a process of variable selection, which variables derived from UAS imagery and which scale of image analysis are the most relevant to our objectives.The methodological framework is applied to two study sites to describe the riparian forest through two fundamental characteristics: the species composition and the health condition. These characteristics were selected not only because of their use as proxies for the riparian zone ecological integrity but also because of their use for river management.The comparison of various scales of image analysis identified the smallest object-based image analysis (OBIA) objects (ca. 1 m²) as the most relevant scale. Variables derived from spectral information (bands ratios) were identified as the most appropriate, followed by variables related to the vertical structure of the forest. Classification results show good overall accuracies for the species composition of the riparian forest (five classes, 79.5 and 84.1 % for site 1 and site 2). The classification scenario regarding the health condition of the black alders of the site 1 performed the best (90.6 %).The quality of the classification models developed with a UAS-based, cost-effective, and semi-automatic approach competes successfully with those developed using more expensive imagery, such as multi-spectral and hyperspectral airborne imagery. The high overall accuracy results obtained by the classification of the diseased alders open the door to applications dedicated to monitoring of the health conditions of riparian forest. Our methodological framework will allow UAS users to manage large imagery metric datasets derived from those dense time series.

Wetlands in dryland regions are rapidly degrading under the combined effects of climate change and human regulation, yet long-term, seasonally resolved assessments of surface water extent (SWE) and its dynamics remain scarce. Here, we map and analyze seasonal surface water extent (SWE) over the period 2000–2024 in the Ile River Delta (IRD), south-eastern Kazakhstan, using Landsat TM/ETM+/OLI data within the Google Earth Engine (GEE) framework. We integrate multiple indices using the modified Normalized Difference Water Index (mNDWI), Automated Water Extraction Index (AWEI) variants, Water Index 2015 (WI2015), and Multi-Band Water Index (MBWI) with dynamic Otsu thresholding. The resulting index-wise binary water maps are merged via ensemble agreement (intersection, majority, union) to delineate three SWE regimes: stable (persists most of the time), periodic (appears regularly but not in every season), and ephemeral (appears only occasionally). Validation against Sentinel-2 imagery showed high accuracy F1-Score/Overall accuracy (F1/OA ≈ 0.85/85%), confirming our workflow to be robust. Hydroclimatic drivers were evaluated through modified Mann–Kendall (MMK) and Spearman’s (r) correlations between SWE, discharge (D), water level (WL), precipitation (P), and air temperature (AT), while a hybrid ensemble–occurrence framework was applied to identify degradation and transition patterns. Trend analysis revealed significant long–term declines, most pronounced during summer and fall. Discharge is predominantly controlled by stable spring SWE, while discharge and temperature jointly influence periodic SWE in summer–fall, with warming reducing the delta surface water. Ephemeral SWE responds episodically to flow pulses, whereas precipitation played a limited role in this semi–arid region. Spatially, area(s) of interest (AOI)-II/III (the main distributary system) support the most extensive yet dynamic wetlands. In contrast, AOI-I and AOI-IV host smaller, more constrained wetland mosaics. AOI-I shows persistence under steady low flows, while AOI-IV reflects a stressed system with sporadic high-water levels. Overall, the results highlight the dominant influence of flow regulation and distributary allocation on IRD hydrology and the need for ecologically timed releases, targeted restoration, and transboundary cooperation to sustain delta resilience.

The natural wood regime forms the third leg of a tripod of physical processes that supports river science and management, along with the natural flow and sediment regimes. The wood regime consists of wood recruitment, transport, and storage in river corridors. Each of these components can be characterized in terms of magnitude, frequency, rate, timing, duration, and mode. We distinguish the natural wood regime, which occurs where human activities do not significantly alter the wood regime, and a target wood regime, in which management emphasizes wood recruitment, transport, and storage that balance desired geomorphic and ecological characteristics with mitigation of wood-related hazards. Wood regimes vary across space and through time but can be inferred and quantified via direct measurements, reference sites, historical information, and numerical modeling. Classifying wood regimes with respect to wood process domains and quantifying the wood budget are valuable tools for assessing and managing rivers.

Following the major floods of the early 2000s, the Rhône river has been the focus of an integrated management plan, the Plan Rhône . This plan advocates a new way of managing the river from a sustainable development perspective. The Rhône Valley Human-Environment Observatory (OHM VR) was set up in 2010 with sustainable development as a foundation applied to the scale of the river. The scientific objectives of the OHM VR have been to monitor the effects of this new management approach in a perspective of a highly anthropised socio-ecosystem, by studying the socio-environmental responses and adaptations in the Rhône corridor following a change in the mode of river management. Priority scientific themes were developed with the aim of covering most of the questions raised by this new mode of management: to achieve a better understanding of the geo-historical trajectory of the river to situate temporally the crisis events and their consequences; to provide insight into the new modes of management from a socio-political point of view and their reception by the local populations; to study the socio-economic processes in a context of ecological restoration actions; to analyse the environmental risks, in particular pollution; and to develop new tools to support the research works and the diffusion of scientific results. Interdisciplinarity and relations with local stakeholders provide the framework for these investigations. This article provides an overview of the activities of the OHM VR and their evolution since its creation, with a particular focus on two interdisciplinary case studies that have shaped collective scientific thinking in recent years.

Over the last three decades, many regional studies in mountain ranges under temperate climate revealed that it is possible to discriminate debris-flow and fluvial fans from morphometric indicators measured at the scale of the catchment and the fan itself. The most commonly used indicators are the Melton index (R), a normalized index of the gravitational energy of the catchment, and the fan slope (S). A wide range of thresholds have been proposed for discriminating purpose, but these are generally based on a small population of catchments and may be highly influenced by ambiguous fans included in the data set. A database of 620 upland catchments from several mountain ranges under temperate climate was compiled from the literature to propose robust discriminant morphometric thresholds for debris-flow versus fluvial responses. Linear discriminant analysis (LDA) and logistic regression (LR) were performed using the whole data set, and a leave-one-out cross-validation was used to evaluate performances of the models. Sensitivity and specificity scores obtained for LDA and LR were 0.96 and 0.73, and 0.95 and 0.75, respectively. It is also shown that the channel slope above which debris-flow is observed decreases with the gravitational energy of the catchment. Limitations of the morphometric discrimination are discussed.

Bedload transport modelling in rivers takes into account the size and density of pebbles to estimate particle mobility, but does not formally consider particle shape. To address this issue and to compare the relative roles of the density and shape of particles, we performed original sediment transport experiments in an annular flume using molded artificial pebbles equipped with a radio frequency identification tracking system. The particles were designed with four distinct shapes and four different densities while having the same volume, and their speeds and distances traveled under constant hydraulic conditions were analyzed. The results show that particle shape has more influence than particle density on the resting time between particle displacement and the mean traveling distance. For all densities investigated, the particle shape systematically induced differences in travel distance that were strongly correlated (R-2 = 0.94) with the Sneed and Folks shape index. Such shape influences, although often mentioned, are here quantified for the first time, demonstrating why and how they can be included in bedload transport models.