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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 interactions between water, sediment and biology in fluvial systems are complex and driven by multiple forcing mechanisms across a range of spatial and temporal scales. In a changing climate, some meteorological drivers are expected to become more extreme with, for example, more prolonged droughts or more frequent flooding. Such environmental changes will potentially have significant consequences for the human populations and ecosystems that are dependent on riverscapes, but our understanding of fluvial system response to external drivers remains incomplete. As a consequence, many of the predictions of the effects of climate change have a large uncertainty that hampers effective management of fluvial environments. Amongst the array of methodological approaches available to scientists and engineers charged with improving that understanding, is physical modelling. Here, we review the role of physical modelling for understanding both biotic and abiotic processes and their interactions in fluvial systems. The approaches currently employed for scaling and representing fluvial processes in physical models are explored, from 1:1 experiments that reproduce processes at real-time or time scales of 10−1-100 years, to analogue models that compress spatial scales to simulate processes over time scales exceeding 102–103 years. An important gap in existing capabilities identified in this study is the representation of fluvial systems over time scales relevant for managing the immediate impacts of global climatic change; 101 – 102 years, the representation of variable forcing (e.g. storms), and the representation of biological processes. Research to fill this knowledge gap is proposed, including examples of how the time scale of study in directly scaled models could be extended and the time scale of landscape models could be compressed in the future, through the use of lightweight sediments, and innovative approaches for representing vegetation and biostabilisation in fluvial environments at condensed time scales, such as small-scale vegetation, plastic plants and polymers. It is argued that by improving physical modelling capabilities and coupling physical and numerical models, it should be possible to improve understanding of the complex interactions and processes induced by variable forcing within fluvial systems over a broader range of time scales. This will enable policymakers and environmental managers to help reduce and mitigate the risks associated with the impacts of climate change in rivers.

Low bar spacing trash racks have been widely investigated in order to guide fish toward bypasses. In addition to this biological function, the formulae to predict head losses, for hydropower plants, are still being discussed. This paper investigates and models the global head losses generated by inclined trash racks with six different bar shapes and two different supports, in an open channel for six angles and two low bar spacings. The girders that supported the trash racks were U-shaped and different profile shapes. In addition to the previously studied rectangular and “hydrodynamic” bars, four new bar shapes, combining different leading and trailing edges, were investigated. Water depths were measured upstream and downstream of the rack for each configuration, and head loss coefficients were characterized and modeled. Three of these new bar shapes generated lower head losses than the hydrodynamic bar shape. The most efficient bar profile reduced the shape coefficient by 40% compared to the hydrodynamic profile and by 67% compared to the conventional rectangular profile. Concerning the supports, the use of a profiled girder to replace a conventional U-shaped girder also significantly reduced the head losses. The addition of the girder effect in a global formula increased its accuracy in predicting head losses of inclined trash racks upstream of hydropower plants.

Summary The 1970s abrupt lake level rise of Laguna Mar Chiquita in central Argentina was shown to be driven by an increase in the Rio Sali-Dulce discharge outflowing from the northern part of the lake catchment. This regional hydrological change was consistent with the 20th century hydroclimatic trends observed in southeastern South America. However, little is known about the impacts of climate or land cover changes on this regional hydrological change causing the sharp lake level rise. To address this question, the present study aims to provide an integrated basin-lake model. We used the physically-based SWAT model in order to simulate streamflow in the Sali-Dulce Basin. The ability of SWAT to simulate non-stationary hydrological conditions was evaluated by a cross-calibration exercise. Based on observed daily meteorological data over 1973–2004, two successive 9-year periods referred to as wet (P1976–1985 = 1205 mm/yr) and dry (P1986–1995 = 796 mm/yr) periods were selected. The calibration yielded similar Nash–Sutcliffe efficiencies (NSE) at the monthly time scale for both periods (NSEwet = 0.86; NSEdry = 0.90) supporting the model’s ability to adapt its structure to changing climatic situations. The simulation was extended in scarce data conditions over 1931–1972 and the simulation of monthly discharge values was acceptable (NSE = 0.71). When precipitation in the model was increased until it reach the change observed in the 1970s ( Δ P / P ¯ = 22 % ), the resulting increase in streamflow was found to closely match the 1970s hydrological change ( Δ Q / Q ¯ = 45 % ). Sensitivity analyses revealed that the land cover changes had a minor impact on the 1970s hydrological changes in the Sali-Dulce Basin. Integrating the SWAT simulations within the lake model over 1973–2004 provided lake level variations similar to those obtained using observed discharge values. Over the longer period, going back to 1931, the main features of lake levels were still adequately reproduced, which suggests that this basin-lake model is a promising approach for simulating long-term lake level fluctuations in response to climate.

AbstractAttribution of trends in streamflow is complex, but essential, in identifying optimal management options for water resources. Disagreement remains on the relative role of climate change and human factors, including water abstractions and land cover change, in driving change in annual streamflow. We construct a very dense network of gauging stations (n = 1,874) from Ireland, the United Kingdom, France, Spain, and Portugal for the period of 1961–2012 to detect and then attribute changes in annual streamflow. Using regression‐based techniques, we show that climate (precipitation and atmospheric evaporative demand) explains many of the observed trends in northwest Europe, while for southwest Europe human disturbances better explain both temporal and spatial trends. For the latter, large increases in irrigated areas, agricultural intensification, and natural revegetation of marginal lands are inferred to be the dominant drivers of decreases in streamflow.

Abstract The Amazon region has been undergoing profound transformations since the late ‘70s through forest degradation, land use changes and effects of global climate change. The perception of such changes by local communities is important for risk analysis and for subsequent societal decision making. In this study, we compare and contrast observations and perceptions of climate change by selected Amazonian communities particularly vulnerable to alterations in precipitation regimes. Two main points were analysed: (i) the notion of changes in the annual climate cycle and (ii) the notion of changes in rainfall patterns. About 72% of the sampled population reports perceptions of climate changes, and there is a robust signal of increased perception with age. Other possible predictive parameters such as gender, fishing frequency and changes in/planning of economic activities do not appear overall as contributing to perceptions. The communities’ perceptions of the changes in 2013–2014 were then compared to earlier results (2007–2008), providing an unprecedented cohort study of the same sites. Results show that climate change perceptions and measured rainfall variations differ across the basin. It was only in the southern part of the Amazon that both measured and perceived changes in rainfall patterns were consistent with decreased precipitation. However, the perception of a changing climate became more widespread and frequently mentioned, signalling an increase in awareness of climate risk.