Gravel augmentation has become common practice to mitigate the effects of decline in upstream sediment supply in gravel-bed rivers. The success of such rehabilitation schemes relies partly on the monitoring strategy and efforts. When long-term monitoring is lacking, some aspects of rehabilitation initiatives suffer more than others, such as insights into functions and functionalities of the river system. Despite temperature being a fundamental parameter determining the general health of river ecosystems, a limited number of studies have tested whether gravel-augmentation can aid restoring thermal functions. With the help of airborne thermal infrared (TIR) imagery, this paper explores the potential positive feedbacks through the monitoring of gravel augmentation actions, of different magnitude, taken on 3 rivers of the Rhône basin in France. A specific trajectory-based Before-After-Control-Impact (BACI) framework using simple indicators, combined with a TIR-based Control-Impact strategy, was designed to assess the success of thermal function restorations based on dynamic fuzzy references. Results indicate that restoring forms is not sufficient to restore thermal functions. The control-impact strategy shows limitations in the sense that two neighbouring reaches can display similar planform characteristics but different thermal functions; what is observed in a control reach should not necessarily be expected following rehabilitation. When assessing thermal processes, a before-after strategy is needed to either serve as a target or help define an adequate target in accordance with changes in the catchment and channel adjustments and responsiveness. We therefore recommend a trajectory-based BACI assessment to identify current biogeophysical conditions within which rehabilitation can be assessed. From a technical perspective, airborne TIR proved to be useful to rapidly map surface temperature over dozens of kilometres at high resolution, and can be advocated as a powerful tool to monitor and diagnose thermal functions of gravel-bed rivers. With an increasing number of rehabilitation schemes, and increasing pressure of global changes on rivers, we suggest that monitoring of water temperature, even with simple but well-designed sampling strategies, becomes a routine part of river rehabilitation projects.

Groundwater pumping influences the rate of River-Aquifer (R-A) exchanges and alters the water budget of the aquifer. Therefore, fulfilling the total water demand of the area, with an optimal pumping rate of wells and optimal R-A exchanges rate, is important for the sustainable management of water resources and aquatic ecosystems. Meanwhile, comparison of the output of different simulation-optimization techniques, which is used for the solution of water resource management problems, is a very challenging task where different Pareto fronts are compared to identify the best results. In the present work, mathematical models were developed to simulate the R-A exchanges for the lower part of the River Ain, France. The developed models were coupled with optimization models in MATLAB environment and were executed to solve the multi-objective optimization problem based on the maximization of pumping rates of wells and maximization of groundwater input into the river Ain through R-A exchanges. The Pareto front developed by different simulation-optimization models was compared and analyzed. The Pareto fronts were juxtaposed based on the convergence, total diversity, and uniformity with the help of different performance metrics like hypervolume, generational distance, inverted generational distance, etc. The impact of different groundwater models based on domain size and boundary conditions was also examined. Results show the dominance of MOPSO over other optimization algorithms and concluded that the maximization of pumping rates significantly changes after considering the R-A exchanges-based objective function. It is observed that the model domain also alters the output of simulation-optimization, therefore the model domain and corresponding boundary conditions should be selected carefully for the field application of management models. ANN models were also developed to deal with the computationally expensive simulation model by reducing the processing time and were found efficient. Keywords: Simulation-Optimization, Multi-Objective optimization, Artificial Neural Network, River-Aquifer exchanges.

In this study, we unveiled the lumped effects at the reach spatial scale over three decades in one of the braided rivers in the Qinghai-Tibet Plateau of China, the Upper Lancang River (ULR). Using Landsat images obtained in 13 years between 1989 and 2018, we extracted flowing and non-flowing channels, active channel widths (unvegetated bars and flowing channels), and calculated lateral shifting rates of the main channel for the 13 periods. We also developed an empirical equation between vegetation area (Av) calculated from the high-resolution ortho-photo derived from an Unmanned Aerial Vehicle survey and Normalized Difference Vegetation Index for pixels of the Landsat image obtained at the same time. This relationship allowed us to estimate Av for other 12 selected years. We found that (1) braiding intensity increases with low discharges, indicating that the ULR is a very well-connected braided system with groundwater providing a large set of aquatic habitats, (2) this braided system is very well-supplied and actively shifting in relation to peak flow and flood duration, and (3) The ULR supports a progressive vegetation encroachment, which seems to be linked to temperature rising. Our study showed several similar morphological patterns to those in other braided rivers, such as the ones observed in the European Alps but much more active, well-supplied and highly connected. These similarities suggest that similar morphodynamic processes might take effect in the braided rivers with very high elevations and potentially high spots of biodiversity, indicating the ULR may be a reference for this region similarly to the Tagliamento in the Alps, but it seems that this system can be very sensitive to global change due to vegetation encroachment following temperature rising and decreases of low flows.