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This modelling study shows that chemical weathering of continental surfaces—which removes carbon dioxide from the atmosphere—is highly sensitive to a carbon dioxide doubling for the Mackenzie River Basin, the most important Arctic watershed. The findings highlight the potential role of chemical weathering processes in mitigating global warming. According to future anthropogenic emission scenarios, the atmospheric CO 2 concentration may double before the end of the twenty-first century 1 . This increase is predicted to result in a global warming of more than 6 °C in the worst case 1 . The global temperature increase will promote changes in the hydrologic cycle through redistributions of rainfall patterns and continental vegetation cover 1 , 2 . All of these changes will impact the chemical weathering of continental rocks. Long considered an inert CO 2 consumption flux at the century timescale, recent works have demonstrated its potential high sensitivity to the ongoing climate and land-use changes 3 , 4 . Here we show that the CO 2 consumption flux related to weathering processes increases by more than 50% for an atmospheric CO 2 doubling for one of the most important Arctic watersheds: the Mackenzie River Basin. This result has been obtained using a process-based model of the chemical weathering of continental surfaces forced by models describing the atmospheric general circulation and the dynamic of the vegetation 5 , 6 under increased atmospheric CO 2 . Our study stresses the potential role that weathering may play in the evolution of the global carbon cycle over the next centuries.

We present a polarisation-maintaining all-normal dispersion photonic crystal fibre designed for 1030 nm femtosecond pumping, enabling ultra-stable and coherent supercontinuum (SC) generation spanning 650–1300 nm. The fibre’s polarisation-maintaining properties are achieved through two larger central holes in the structure, which is an alternative approach to using conventional stress rods. The fibre is specifically engineered to achieve minimum dispersion near 1030 nm, making it ideal for ultrafast comb-based metrology, and widely tunable optical parametric amplifier (OPA) systems. We further investigate the influence of input pulse contrast on supercontinuum generation through both numerical simulations and experiments. Relative intensity noise (RIN) and phase noise (PN) are characterized using three complementary techniques: dispersive Fourier transform (DFT), the Bellini–Hänsch interferometric method, and the dual-reference oscillator cross-correlation technique. The results demonstrate excellent stability, with pulse-to-pulse RIN below 0.5%, an optical phase deviation under 15 mrad, and phase noise levels down to − 150 dBc/Hz at 10 kHz from the carrier, confirming the fibre’s suitability for demanding ultrafast applications.

A spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing). Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures.

Anthropogenic sources are widely accepted as the dominant cause for the increase in atmospheric CO2 concentrations since the beginning of the industrial revolution. Here we use the B‐WITCH model to quantify the impact of increased CO2 concentrations on CO2 consumption by weathering of continental surfaces. B‐WITCH couples a dynamic biogeochemistry model (LPJ) and a process‐based numerical model of continental weathering (WITCH). It allows simultaneous calculations of the different components of continental weathering fluxes, terrestrial vegetation dynamics, and carbon and water fluxes. The CO2 consumption rates are estimated at four different atmospheric CO2 concentrations, from 280 up to 1120 ppmv, for 22 sites characterized by silicate lithologies (basalt, granite, or sandstones). The sensitivity to atmospheric CO2 variations is explored, while temperature and rainfall are held constant. First, we show that under 355 ppmv of atmospheric CO2, B‐WITCH is able to reproduce the global pattern of weathering rates as a function of annual runoff, mean annual temperature, or latitude for silicate lithologies. When atmospheric CO2 increases, evapotranspiration generally decreases due to progressive stomatal closure, and the soil CO2 pressure increases due to enhanced biospheric productivity. As a result, vertical drainage and soil acidity increase, promoting CO2 consumption by mineral weathering. We calculate an increase of about 3% of the CO2 consumption through silicate weathering (mol ha−1 yr−1) for 100 ppmv rise in CO2. Importantly, the sensitivity of the weathering system to the CO2 rise is not uniform and heavily depends on the climatic, lithologic, pedologic, and biospheric settings.

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible (but which have not yet occurred) flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995–2010 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90 % of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff, due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of the CCR (Caisse Centrale de Reassurance) claim database have shown that approximately 45 % of the insured flood losses are located inside the floodplains and 45 % outside. Another 10 % is due to sea surge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: a generation of fictive river flows based on the historical records of the river gauge network and a generation of fictive rain fields on small catchments, calibrated on the 1958–2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (Macif) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

This study explores the relationship between streamflow time variability and precipitation and air temperature variability, in the upper reaches of the Ürümqi River in northwestern China. Wavelet analyses are adopted to analyse the multi-time scale features of monthly temperatures, monthly precipitations and monthly runoffs during the years between 1958 and 2006. Results of continuous wavelet transform imply a statistically significant cycle over an approximately 12-month period in the temporal fluctuations of monthly air temperature, precipitation and runoff. Furthermore, monthly temperature shows 66-month and 96-month cycles while monthly precipitation shows 6-month, 30-month and 72-month cycles. Monthly runoff has 6-month, 24-month, 36-month and 72-month cycles. The results of cross wavelet transform and wavelet coherence show that monthly runoff variability correlates with precipitation and air temperature fluctuations at 6-month and 12-month respectively. Other time-scale correlations at 1-year, 2-year, 3-year and 6-year marks are also highlighted between the different time series. These correlations are then explained considering the alpine characteristics of the catchment. Higher air temperatures in the upper reaches of the Ürümqi River accelerate snow melt and intensify evaporation, thus the relationship between air temperature and runoff is uncertain during different seasons. Overall, summer air temperature controls the annual runoff and precipitation provides a sustained water supply to the upper Ürümqi River. They constitute the dominant factors that explain the temporal variations of streamflow in the upper Ürümqi River. Univariate and cross-wavelet analyses on runoff and climate variability clearly offer a useful tool in hydro-meteorological issues in alpine areas.

The significant worldwide increase in observed river runoff has been tentatively attributed to the stomatal \"antitranspirant\" response of plants to rising atmospheric CO₂ [Gedney N, Cox PM, Betts RA, Boucher O, Huntingford C, Stott PA (2006) Nature 439: 835-838]. However, CO₂ also is a plant fertilizer. When allowing for the increase in foliage area that results from increasing atmospheric CO₂ levels in a global vegetation model, we find a decrease in global runoff from 1901 to 1999. This finding highlights the importance of vegetation structure feedback on the water balance of the land surface. Therefore, the elevated atmospheric CO₂ concentration does not explain the estimated increase in global runoff over the last century. In contrast, we find that changes in mean climate, as well as its variability, do contribute to the global runoff increase. Using historic land-use data, we show that land-use change plays an additional important role in controlling regional runoff values, particularly in the tropics. Land-use change has been strongest in tropical regions, and its contribution is substantially larger than that of climate change. On average, land-use change has increased global runoff by 0.08 mm/year² and accounts for [almost equal to]50% of the reconstructed global runoff trend over the last century. Therefore, we emphasize the importance of land-cover change in forecasting future freshwater availability and climate.

Hydrological models are fundamental tools for the characterization and management of karst systems. We propose an updated version of KarstMod, software dedicated to lumped-parameter rainfall–discharge modelling of karst aquifers. KarstMod provides a modular, user-friendly modelling environment for educational, research, and operational purposes. It also includes numerical tools for time series analysis, model evaluation, and sensitivity analysis. The modularity of the platform facilitates common operations related to lumped-parameter rainfall–discharge modelling, such as (i) setup and parameter estimation of a relevant model structure and (ii) evaluation of internal consistency, parameter sensitivity, and hydrograph characteristics. The updated version now includes (i) external routines to better consider the input data and their related uncertainties, i.e. evapotranspiration and solid precipitation; (ii) enlargement of multi-objective calibration possibilities, allowing more flexibility in terms of objective functions and observation type; and (iii) additional tools for model performance evaluation, including further performance criteria and tools for model error representation.

Methane (CH4) emissions from hydroelectric reservoirs could represent a significant fraction of global CH4 emissions from inland waters and wetlands. Although CH4 emissions downstream of hydroelectric reservoirs are known to be potentially significant, these emissions are poorly documented in recent studies. We report the first quantification of emissions downstream of a subtropical monomictic reservoir. The Nam Theun 2 Reservoir (NT2R), located in the Lao People's Democratic Republic, was flooded in 2008 and commissioned in April 2010. This reservoir is a trans-basin diversion reservoir which releases water into two downstream streams: the Nam Theun River below the dam and an artificial channel downstream of the powerhouse and a regulating pond that diverts the water from the Nam Theun watershed to the Xe Bangfai watershed. We quantified downstream emissions during the first 4 years after impoundment (2009–2012) on the basis of a high temporal (weekly to fortnightly) and spatial (23 stations) resolution of the monitoring of CH4 concentration. Before the commissioning of NT2R, downstream emissions were dominated by a very significant degassing at the dam site resulting from the occasional spillway discharge for controlling the water level in the reservoir. After the commissioning, downstream emissions were dominated by degassing which occurred mostly below the powerhouse. Overall, downstream emissions decreased from 10 GgCH4 yr−1 after the commissioning to 2 GgCH4 yr−1 4 years after impoundment. The downstream emissions contributed only 10 to 30 % of total CH4 emissions from the reservoir during the study. Most of the downstream emissions (80 %) occurred within 2–4 months during the transition between the warm dry season (WD) and the warm wet season (WW) when the CH4 concentration in hypolimnic water is maximum (up to 1000 µmol L−1) and downstream emissions are negligible for the rest of the year. Emissions downstream of NT2R are also lower than expected because of the design of the water intake. A significant fraction of the CH4 that should have been transferred and emitted downstream of the powerhouse is emitted at the reservoir surface because of the artificial turbulence generated around the water intake. The positive counterpart of this artificial mixing is that it allows O2 diffusion down to the bottom of the water column, enhancing aerobic methane oxidation, and it subsequently lowered downstream emissions by at least 40 %.