134 resultados para River regime
Resumo:
Skillful and timely streamflow forecasts are critically important to water managers and emergency protection services. To provide these forecasts, hydrologists must predict the behavior of complex coupled human–natural systems using incomplete and uncertain information and imperfect models. Moreover, operational predictions often integrate anecdotal information and unmodeled factors. Forecasting agencies face four key challenges: 1) making the most of available data, 2) making accurate predictions using models, 3) turning hydrometeorological forecasts into effective warnings, and 4) administering an operational service. Each challenge presents a variety of research opportunities, including the development of automated quality-control algorithms for the myriad of data used in operational streamflow forecasts, data assimilation, and ensemble forecasting techniques that allow for forecaster input, methods for using human-generated weather forecasts quantitatively, and quantification of human interference in the hydrologic cycle. Furthermore, much can be done to improve the communication of probabilistic forecasts and to design a forecasting paradigm that effectively combines increasingly sophisticated forecasting technology with subjective forecaster expertise. These areas are described in detail to share a real-world perspective and focus for ongoing research endeavors.
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Anthropogenic aerosols in the atmosphere have the potential to affect regional-scale land hydrology through solar dimming. Increased aerosol loading may have reduced historical surface evaporation over some locations, but the magnitude and extent of this effect is uncertain. Any reduction in evaporation due to historical solar dimming may have resulted in an increase in river flow. Here we formally detect and quantify the historical effect of changing aerosol concentrations, via solar radiation, on observed river flow over the heavily industrialized, northern extra-tropics. We use a state-of-the-art estimate of twentieth century surface meteorology as input data for a detailed land surface model, and show that the simulations capture the observed strong inter-annual variability in runoff in response to climatic fluctuations. Using statistical techniques, we identify a detectable aerosol signal in the observed river flow both over the combined region, and over individual river basins in Europe and North America. We estimate that solar dimming due to rising aerosol concentrations in the atmosphere around 1980 led to an increase in river runoff by up to 25% in the most heavily polluted regions in Europe. We propose that, conversely, these regions may experience reduced freshwater availability in the future, as air quality improvements are set to lower aerosol loading and solar dimming.
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The total reactive phosphorus (TRP) and nitrate concentrations of the River Enborne, southern England, were monitored at hourly interval between January 2010 and December 2011. The relationships between these high-frequency nutrient concentration signals and flow were used to infer changes in nutrient source and dynamics through the annual cycle and each individual storm event, by studying hysteresis patterns. TRP concentrations exhibited strong dilution patterns with increasing flow, and predominantly clockwise hysteresis through storm events. Despite the Enborne catchment being relatively rural for southern England, TRP inputs were dominated by constant, non-rain-related inputs from sewage treatment works (STW) for the majority of the year, producing the highest phosphorus concentrations through the spring–summer growing season. At higher river flows, the majority of the TRP load was derived from within-channel remobilisation of phosphorus from the bed sediment, much of which was also derived from STW inputs. Therefore, future phosphorus mitigation measures should focus on STW improvements. Agricultural diffuse TRP inputs were only evident during storms in the May of each year, probably relating to manure application to land. The nitrate concentration–flow relationship produced a series of dilution curves, indicating major inputs from groundwater and to a lesser extent STW. Significant diffuse agricultural inputs with anticlockwise hysteresis trajectories were observed during the first major storms of the winter period. The simultaneous investigation of high-frequency time series data, concentration–flow relationships and hysteresis behaviour through multiple storms for both phosphorus and nitrate offers a simple and innovative approach for providing new insights into nutrient sources and dynamics.
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Satellite-based (e.g., Synthetic Aperture Radar [SAR]) water level observations (WLOs) of the floodplain can be sequentially assimilated into a hydrodynamic model to decrease forecast uncertainty. This has the potential to keep the forecast on track, so providing an Earth Observation (EO) based flood forecast system. However, the operational applicability of such a system for floods developed over river networks requires further testing. One of the promising techniques for assimilation in this field is the family of ensemble Kalman (EnKF) filters. These filters use a limited-size ensemble representation of the forecast error covariance matrix. This representation tends to develop spurious correlations as the forecast-assimilation cycle proceeds, which is a further complication for dealing with floods in either urban areas or river junctions in rural environments. Here we evaluate the assimilation of WLOs obtained from a sequence of real SAR overpasses (the X-band COSMO-Skymed constellation) in a case study. We show that a direct application of a global Ensemble Transform Kalman Filter (ETKF) suffers from filter divergence caused by spurious correlations. However, a spatially-based filter localization provides a substantial moderation in the development of the forecast error covariance matrix, directly improving the forecast and also making it possible to further benefit from a simultaneous online inflow error estimation and correction. Additionally, we propose and evaluate a novel along-network metric for filter localization, which is physically-meaningful for the flood over a network problem. Using this metric, we further evaluate the simultaneous estimation of channel friction and spatially-variable channel bathymetry, for which the filter seems able to converge simultaneously to sensible values. Results also indicate that friction is a second order effect in flood inundation models applied to gradually varied flow in large rivers. The study is not conclusive regarding whether in an operational situation the simultaneous estimation of friction and bathymetry helps the current forecast. Overall, the results indicate the feasibility of stand-alone EO-based operational flood forecasting.
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The subgrid-scale spatial variability in cloud water content can be described by a parameter f called the fractional standard deviation. This is equal to the standard deviation of the cloud water content divided by the mean. This parameter is an input to schemes that calculate the impact of subgrid-scale cloud inhomogeneity on gridbox-mean radiative fluxes and microphysical process rates. A new regime-dependent parametrization of the spatial variability of cloud water content is derived from CloudSat observations of ice clouds. In addition to the dependencies on horizontal and vertical resolution and cloud fraction included in previous parametrizations, the new parametrization includes an explicit dependence on cloud type. The new parametrization is then implemented in the Global Atmosphere 6 (GA6) configuration of the Met Office Unified Model and used to model the effects of subgrid variability of both ice and liquid water content on radiative fluxes and autoconversion and accretion rates in three 20-year atmosphere-only climate simulations. These simulations show the impact of the new regime-dependent parametrization on diagnostic radiation calculations, interactive radiation calculations and both interactive radiation calculations and in a new warm microphysics scheme. The control simulation uses a globally constant f value of 0.75 to model the effect of cloud water content variability on radiative fluxes. The use of the new regime-dependent parametrization in the model results in a global mean which is higher than the control's fixed value and a global distribution of f which is closer to CloudSat observations. When the new regime-dependent parametrization is used in radiative transfer calculations only, the magnitudes of short-wave and long-wave top of atmosphere cloud radiative forcing are reduced, increasing the existing global mean biases in the control. When also applied in a new warm microphysics scheme, the short-wave global mean bias is reduced.
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The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High-frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to three or four of the WFD classes with 95% confidence, due to random sampling effects, whereas with weekly sampling this was one or two classes for the same cases. In the most extreme case, the same water body could have been assigned to any of the five WFD quality classes. Weekly sampling considerably reduces the uncertainties compared to monthly sampling. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Low-frequency measurements will generally be unsuitable for assessing standards expressed as high percentiles. Confining sampling to the working week compared to all 7 days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.
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This article explores the relationship between the Crown, the French society and the king's financiers. It starts with a brief review of the discourses on the financiers and a survey of the work done by historians. Further to a description of the various groups of financiers, it analyses the nature of the contracts passed between the king and the traitants to pay for the Nine Years War, as well as the latter’s activities and profits. The article argues that the government supervised effectively the traitants and that, given the constraints of the Old Regime, these financiers provided essential services, but too costly to be sustainable.
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Nutrient enrichment and drought conditions are major threats to lowland rivers causing ecosystem degradation and composition changes in plant communities. The controls on primary producer composition in chalk rivers are investigated using a new model and existing data from the River Frome (UK) to explore abiotic and biotic interactions. The growth and interaction of four primary producer functional groups (suspended algae, macrophytes, epiphytes, sediment biofilm) were successfully linked with flow, nutrients (N, P), light and water temperature such that the modelled biomass dynamics of the four groups matched that of the observed. Simulated growth of suspended algae was limited mainly by the residence time of the river rather than in-stream phosphorus concentrations. The simulated growth of the fixed vegetation (macrophytes, epiphytes, sediment biofilm) was overwhelmingly controlled by incoming solar radiation and light attenuation in the water column. Nutrients and grazing have little control when compared to the other physical controls in the simulations. A number of environmental threshold values were identified in the model simulations for the different producer types. The simulation results highlighted the importance of the pelagic–benthic interactions within the River Frome and indicated that process interaction defined the behaviour of the primary producers, rather than a single, dominant driver. The model simulations pose interesting questions to be considered in the next iteration of field- and laboratory based studies.
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Microbial degradation is a major determinant of the fate of pollutants in the environment. para-Nitrophenol (PNP) is an EPA listed priority pollutant with a wide environmental distribution, but little is known about the microorganisms that degrade it in the environment. We studied the diversity of active PNP-degrading bacterial populations in river water using a novel functional marker approach coupled with [13C6]PNP stable isotope probing (SIP). Culturing together with culture-independent terminal restriction fragment length polymorphism analysis of 16S rRNA gene amplicons identified Pseudomonas syringae to be the major driver of PNP degradation in river water microcosms. This was confirmed by SIP-pyrosequencing of amplified 16S rRNA. Similarly, functional gene analysis showed that degradation followed the Gram-negative bacterial pathway and involved pnpA from Pseudomonas spp. However, analysis of maleylacetate reductase (encoded by mar), an enzyme common to late stages of both Gram-negative and Gram-positive bacterial PNP degradation pathways, identified a diverse assemblage of bacteria associated with PNP degradation, suggesting that mar has limited use as a specific marker of PNP biodegradation. Both the pnpA and mar genes were detected in a PNP-degrading isolate, P. syringae AKHD2, which was isolated from river water. Our results suggest that PNP-degrading cultures of Pseudomonas spp. are representative of environmental PNP-degrading populations.
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Inspired by the commercial desires of global brands and retailers to access the lucrative green consumer market, carbon is increasingly being counted and made knowable at the mundane sites of everyday production and consumption, from the carbon footprint of a plastic kitchen fork to that of an online bank account. Despite the challenges of counting and making commensurable the global warming impact of a myriad of biophysical and societal activities, this desire to communicate a product or service's carbon footprint has sparked complicated carbon calculative practices and enrolled actors at literally every node of multi-scaled and vastly complex global supply chains. Against this landscape, this paper critically analyzes the counting practices that create the ‘e’ in ‘CO2e’. It is shown that, central to these practices are a series of tools, models and databases which, in building upon previous work (Eden, 2012 and Star and Griesemer, 1989) we conceptualize here as ‘boundary objects’. By enrolling everyday actors from farmers to consumers, these objects abstract and stabilize greenhouse gas emissions from their messy material and social contexts into units of CO2e which can then be translated along a product's supply chain, thereby establishing a new currency of ‘everyday supply chain carbon’. However, in making all greenhouse gas-related practices commensurable and in enrolling and stabilizing the transfer of information between multiple actors these objects oversee a process of simplification reliant upon, and subject to, a multiplicity of approximations, assumptions, errors, discrepancies and/or omissions. Further the outcomes of these tools are subject to the politicized and commercial agendas of the worlds they attempt to link, with each boundary actor inscribing different meanings to a product's carbon footprint in accordance with their specific subjectivities, commercial desires and epistemic framings. It is therefore shown that how a boundary object transforms greenhouse gas emissions into units of CO2e, is the outcome of distinct ideologies regarding ‘what’ a product's carbon footprint is and how it should be made legible. These politicized decisions, in turn, inform specific reduction activities and ultimately advance distinct, specific and increasingly durable transition pathways to a low carbon society.
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This section of the report outlines the effect of different levels of climate change on exposure to river flood risk, at national and watershed scales.
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With a focus on key themes and debates, this article aims to illustrate and assess how the interaction between justice and politics has shaped the international regime and defined the nature of the international agreement that was signed in COP21 Paris. The work demonstrates that despite the rise of neo-conservatism and self-interested power politics, questions of global distributive justice remain a central aspect of the international politics of climate change. However, while it is relatively easy to demonstrate that international climate politics is not beyond the reach of moral contestations, the assessment of exactly how much impact justice has on climate policies and the broader normative structures of the climate governance regime remains a very difficult task. As the world digests the Paris Agreement, it is vital that the current state of justice issues within the international climate change regime is comprehensively understood by scholars of climate justice and by academics and practitioners, not least because how these intractable issues of justice are dealt with (or not) will be a crucial factor in determining the effectiveness of the emerging climate regime.