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Upwelling processes bring nutrient-rich waters from the deep ocean to the surface. Areas of upwelling are often associated with high productivity, offering great economic value in terms of fisheries. The sensitivity of spring/summer-time coastal upwelling systems to climate change has recently received a lot of attention. Several studies have suggested that their intensity may increase in the future while other authors have shown decreasing intensity in their equatorward portions. Yet, recent observations do not show robust evidence of this intensification. The Senegalo-Mauritanian upwelling system (SMUS) located at the southern edge of the north Atlantic system (12°N–20°N) and most active in winter/spring has been largely excluded from these studies. Here, the seasonal cycle of the SMUS and its response to climate change is investigated in the database of the Coupled Models Inter comparison Project Phase 5 (CMIP5). Upwelling magnitude and surface signature are characterized by several sea surface temperature and wind stress indices. We highlight the ability of the climate models to reproduce the system, as well as their biases. The simulations suggest that the intensity of the SMUS winter/spring upwelling will moderately decrease in the future, primarily because of a reduction of the wind forcing linked to a northward shift of Azores anticyclone and a more regional modulation of the low pressures found over Northwest Africa. The implications of such an upwelling reduction on the ecosystems and local communities exploiting them remains very uncertain.

The basins of the Indus and Ganges rivers cover 2.20 million km2 and are inhabited by more than a billion people. The region is under extreme pressures of population and poverty, unregulated utilization of the resources and low levels of productivity. The needs are: (1) development policies that are regionally differentiated to ensure resource sustainability and high productivity; (2) immediate development and implementation of policies for sound groundwater management and energy use; (3) improvement of the fragile food security and to broaden its base; and (4) policy changes to address land fragmentation and improved infrastructure. Meeting these needs will help to improve productivity, reduce rural poverty and improve overall human development.

Ethiopia's policy of large dam construction in the Blue Nile River basin is evaluated by simulating the impact of one downscaled midrange climate change scenario (A1B) on the performance of existing and planned irrigation and hydropower schemes. The simulation finds that by 2100: 1) average basin-wide irrigation demand will increase; 2) annual hydroelectricity generation will be just 60% of potential; and 3) flow at the Ethiopia-Sudan border will be reduced from 1661 m3/s to 1301 m3/s as a consequence of climate change in combination with upstream water resource development. Adaptation to climate change and development must be considered together.

Analytical formulae are proposed to describe the first-order temporal evolution of the head in large groundwater systems (such as those found in North Africa or eastern Australia) that are subjected to drastic modifications of their recharge conditions (such as those in Pleistocene and Holocene times). The mathematical model is based on the hydrodynamics of a mixed-aquifer system composed of a confined aquifer connected to an unconfined one with a large storage capacity. The transient behaviour of the head following a sudden change of recharge conditions is computed with Laplace transforms for linear one-dimensional and cylindrical geometries. This transient evolution closely follows an exponential trend exp(−t/τ). The time constant τ is expressed analytically as a function of the various parameters characterizing the system. In many commonly occurring situations, τ depends on only four parameters: the width a c of the main confined aquifer, its transmissivity T c, the integrated storage situated upstream in the unconfined aquifer M = S u a u, and a curvature parameter accounting for convergence/divergence effects. This model is applied to the natural decay of large aquifer basins of the Sahara and Australia following the end of the mid-Holocene humid period. The observed persistence of the resource is discussed on the basis of the time constant estimated with the system parameters. This comparison confirms the role of the upstream water reserve, which is modelled as an unconfined aquifer, and highlights the significant increase of the time constant in case of converging flow.

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

This paper deals with an experimental study of angled fish-friendly trash racks with horizontal bars, using a physical model in an open channel. Head losses are investigated for 2 bar shapes, 3 ratios between bar spacing and bar thickness and 4 rack’s angles of orientation. The Froude and bar-Reynolds numbers were respectively 0.275 and 3600. The head loss coefficients decrease as the blockage ratio and the angle of orientation of the rack decrease. They are well predicted by the formula produced by Raynal et al. (2013a) for inclined rack with some adaptations. Velocity fields are characterized upstream and downstream of the racks, showing no effect of the angle of orientation and no heterogeneity over channel width. Consequently, the normal and tangential components of the velocity along the rack are in agreement with the theoretical values given by angular decomposition. These results serve to assess the compliance with biological criteria to avoid impingement risks and guide fish towards a bypass.