114 resultados para River runoff

em CentAUR: Central Archive University of Reading - UK


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Global hydrological models (GHMs) model the land surface hydrologic dynamics of continental-scale river basins. Here we describe one such GHM, the Macro-scale - Probability-Distributed Moisture model.09 (Mac-PDM.09). The model has undergone a number of revisions since it was last applied in the hydrological literature. This paper serves to provide a detailed description of the latest version of the model. The main revisions include the following: (1) the ability for the model to be run for n repetitions, which provides more robust estimates of extreme hydrological behaviour, (2) the ability of the model to use a gridded field of coefficient of variation (CV) of daily rainfall for the stochastic disaggregation of monthly precipitation to daily precipitation, and (3) the model can now be forced with daily input climate data as well as monthly input climate data. We demonstrate the effects that each of these three revisions has on simulated runoff relative to before the revisions were applied. Importantly, we show that when Mac-PDM.09 is forced with monthly input data, it results in a negative runoff bias relative to when daily forcings are applied, for regions of the globe where the day-to-day variability in relative humidity is high. The runoff bias can be up to - 80% for a small selection of catchments but the absolute magnitude of the bias may be small. As such, we recommend future applications of Mac-PDM.09 that use monthly climate forcings acknowledge the bias as a limitation of the model. The performance of Mac-PDM.09 is evaluated by validating simulated runoff against observed runoff for 50 catchments. We also present a sensitivity analysis that demonstrates that simulated runoff is considerably more sensitive to method of PE calculation than to perturbations in soil moisture and field capacity parameters.

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We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty. We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues.

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A global river routing scheme coupled to the ECMWF land surface model is implemented and tested within the framework of the Global Soil Wetness Project II, to evaluate the feasibility of modelling global river runoff at a daily time scale. The exercise is designed to provide benchmark river runoff predictions needed to verify the land surface model. Ten years of daily runoff produced by the HTESSEL land surface scheme is input into the TRIP2 river routing scheme in order to generate daily river runoff. These are then compared to river runoff observations from the Global Runoff Data Centre (GRDC) in order to evaluate the potential and the limitations. A notable source of inaccuracy is bias between observed and modelled discharges which is not primarily due to the modelling system but instead of to the forcing and quality of observations and seems uncorrelated to the river catchment size. A global sensitivity analysis and Generalised Likelihood Uncertainty Estimation (GLUE) uncertainty analysis are applied to the global routing model. The ground water delay parameter is identified as being the most sensitive calibration parameter. Significant uncertainties are found in results, and those due to parameterisation of the routing model are quantified. The difficulty involved in parameterising global river discharge models is discussed. Detailed river runoff simulations are shown for the river Danube, which match well observed river runoff in upstream river transects. Results show that although there are errors in runoff predictions, model results are encouraging and certainly indicative of useful runoff predictions, particularly for the purpose of verifying the land surface scheme hydrologicly. Potential of this modelling system on future applications such as river runoff forecasting and climate impact studies is highlighted. Copyright © 2009 Royal Meteorological Society.

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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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On the time scale of a century, the Atlantic thermohaline circulation (THC) is sensitive to the global surface salinity distribution. The advection of salinity toward the deep convection sites of the North Atlantic is one of the driving mechanisms for the THC. There is both a northward and a southward contributions. The northward salinity advection (Nsa) is related to the evaporation in the subtropics, and contributes to increased salinity in the convection sites. The southward salinity advection (Ssa) is related to the Arctic freshwater forcing and tends on the contrary to diminish salinity in the convection sites. The THC changes results from a delicate balance between these opposing mechanisms. In this study we evaluate these two effects using the IPSL-CM4 ocean-atmosphere-sea-ice coupled model (used for IPCC AR4). Perturbation experiments have been integrated for 100 years under modern insolation and trace gases. River runoff and evaporation minus precipitation are successively set to zero for the ocean during the coupling procedure. This allows the effect of processes Nsa and Ssa to be estimated with their specific time scales. It is shown that the convection sites in the North Atlantic exhibit various sensitivities to these processes. The Labrador Sea exhibits a dominant sensitivity to local forcing and Ssa with a typical time scale of 10 years, whereas the Irminger Sea is mostly sensitive to Nsa with a 15 year time scale. The GIN Seas respond to both effects with a time scale of 10 years for Ssa and 20 years for Nsa. It is concluded that, in the IPSL-CM4, the global freshwater forcing damps the THC on centennial time scales.

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Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.

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This paper assesses the implications of climate policy for exposure to water resources stresses. It compares a Reference scenario which leads to an increase in global mean temperature of 4oC by the end of the 21st century with a Mitigation scenario which stabilises greenhouse gas concentrations at around 450ppm CO2e and leads to a 2oC increase in 2100. Associated changes in river runoff are simulated using a global hydrological model, for four spatial patterns of change in temperature and rainfall. There is a considerable difference in hydrological change between these four patterns, but the percentages of change avoided at the global scale are relatively robust. By the 2050s, the Mitigation scenario typically avoids between 16 and 30% of the change in runoff under the Reference scenario, and by 2100 it avoids between 43 and 65%. Two different measures of exposure to water resources stress are calculated, based on resources per capita and the ratio of withdrawals to resources. Using the first measure, the Mitigation scenario avoids 8-17% of the impact in 2050 and 20-31% in 2100; with the second measure, the avoided impacts are 5-21% and 15-47% respectively. However, at the same time, the Mitigation scenario also reduces the positive impacts of climate change on water scarcity in other areas. The absolute numbers and locations of people affected by climate change and climate policy vary considerably between the four climate model patterns.

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Interest in attributing the risk of damaging weather-related events to anthropogenic climate change is increasing1. Yet climate models used to study the attribution problem typically do not resolve the weather systems associated with damaging events2 such as the UK floods of October and November 2000. Occurring during the wettest autumn in England and Wales since records began in 17663, 4, these floods damaged nearly 10,000 properties across that region, disrupted services severely, and caused insured losses estimated at £1.3 billion (refs 5, 6). Although the flooding was deemed a ‘wake-up call’ to the impacts of climate change at the time7, such claims are typically supported only by general thermodynamic arguments that suggest increased extreme precipitation under global warming, but fail8, 9 to account fully for the complex hydrometeorology4, 10 associated with flooding. Here we present a multi-step, physically based ‘probabilistic event attribution’ framework showing that it is very likely that global anthropogenic greenhouse gas emissions substantially increased the risk of flood occurrence in England and Wales in autumn 2000. Using publicly volunteered distributed computing11, 12, we generate several thousand seasonal-forecast-resolution climate model simulations of autumn 2000 weather, both under realistic conditions, and under conditions as they might have been had these greenhouse gas emissions and the resulting large-scale warming never occurred. Results are fed into a precipitation-runoff model that is used to simulate severe daily river runoff events in England and Wales (proxy indicators of flood events). The precise magnitude of the anthropogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.

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Many atmospheric constituents besides carbon dioxide (CO2) contribute to global warming, and it is common to compare their influence on climate in terms of radiative forcing, which measures their impact on the planetary energy budget. A number of recent studies have shown that many radiatively active constituents also have important impacts on the physiological functioning of ecosystems, and thus the ‘ecosystem services’ that humankind relies upon. CO2 increases have most probably increased river runoff and had generally positive impacts on plant growth where nutrients are non-limiting, whereas increases in near-surface ozone (O3) are very detrimental to plant productivity. Atmospheric aerosols increase the fraction of surface diffuse light, which is beneficial for plant growth. To illustrate these differences, we present the impact on net primary productivity and runoff of higher CO2, higher near-surface O3, and lower sulphate aerosols, and for equivalent changes in radiative forcing.We compare this with the impact of climate change alone, arising, for example, from a physiologically inactive gas such as methane (CH4). For equivalent levels of change in radiative forcing, we show that the combined climate and physiological impacts of these individual agents vary markedly and in some cases actually differ in sign. This study highlights the need to develop more informative metrics of the impact of changing atmospheric constituents that go beyond simple radiative forcing.

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The water quality of rainfall and runoff is described for two catchments of two tributaries of the River Thames, the Pang and Lambourn. Rainfall chemistry is variable and concentrations of most determinands decrease with increasing volume of catch probably due to 'wash out' processes. Two rainfall sites have been monitored, one for each catchment. The rainfall site on the Lambourn shows higher chemical concentrations than the one for the Pang which probably reflects higher amounts of local inputs from agricultural activity, Rainfall quality data at a long-term rainfall site on the Pang (UK National Air Quality Archive) shows chemistries similar to that for the Lambourn site. but with some clear differences. Rainfall chemistries show considerable variation on an event-to-event basis. Average water quality concentrations and flow-weighted concentrations as well as fluxes vary across the sites, typically by about 30%. Stream chemistry is much less variable due to the main Source of water coming from aquifer sources of high storage. The relationship between rainfall and runoff chemistry at the catchment outlet is described in terms of the relative proportions of atmospheric and within-catchment sources. Remarkably, in view of the quantity of agricultural and sewage inputs to the streams, the catchments appear to be retaining both P and N.

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Across Europe, elevated phosphorus (P) concentrations in lowland rivers have made them particularly susceptible to eutrophication. This is compounded in southern and central UK by increasing pressures on water resources, which may be further enhanced by the potential effects of climate change. The EU Water Framework Directive requires an integrated approach to water resources management at the catchment scale and highlights the need for modelling tools that can distinguish relative contributions from multiple nutrient sources and are consistent with the information content of the available data. Two such models are introduced and evaluated within a stochastic framework using daily flow and total phosphorus concentrations recorded in a clay catchment typical of many areas of the lowland UK. Both models disaggregate empirical annual load estimates, derived from land use data, as a function of surface/near surface runoff, generated using a simple conceptual rainfall-runoff model. Estimates of the daily load from agricultural land, together with those from baseflow and point sources, feed into an in-stream routing algorithm. The first model assumes constant concentrations in runoff via surface/near surface pathways and incorporates an additional P store in the river-bed sediments, depleted above a critical discharge, to explicitly simulate resuspension. The second model, which is simpler, simulates P concentrations as a function of surface/near surface runoff, thus emphasising the influence of non-point source loads during flow peaks and mixing of baseflow and point sources during low flows. The temporal consistency of parameter estimates and thus the suitability of each approach is assessed dynamically following a new approach based on Monte-Carlo analysis. (c) 2004 Elsevier B.V. All rights reserved.

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A regional overview of the water quality and ecology of the River Lee catchment is presented. Specifically, data describing the chemical, microbiological and macrobiological water quality and fisheries communities have been analysed, based on a division into river, sewage treatment works, fish-farm, lake and industrial samples. Nutrient enrichment and the highest concentrations of metals and micro-organics were found in the urbanised, lower reaches of the Lee and in the Lee Navigation. Average annual concentrations of metals were generally within environmental quality standards although, oil many occasions, concentrations of cadmium, copper, lead, mercury and zinc were in excess of the standards. Various organic substances (used as herbicides, fungicides, insecticides, chlorination by-products and industrial solvents) were widely detected in the Lee system. Concentrations of ten micro-organic substances were observed in excess of their environmental quality standards, though not in terms of annual averages. Sewage treatment works were the principal point source input of nutrients. metals and micro-organic determinands to the catchment. Diffuse nitrogen sources contributed approximately 60% and 27% of the in-stream load in the upper and lower Lee respectively, whereas approximately 60% and 20% of the in-stream phosphorus load was derived from diffuse sources in the upper and lower Lee. For metals, the most significant source was the urban runoff from North London. In reaches less affected by effluent discharges, diffuse runoff from urban and agricultural areas dominated trends. Flig-h microbiological content, observed in the River Lee particularly in urbanised reaches, was far in excess of the EC Bathing Water Directive standards. Water quality issues and degraded habitat in the lower reaches of the Lee have led to impoverished aquatic fauna but, within the mid-catchment reaches and upper agricultural tributaries, less nutrient enrichment and channel alteration has permitted more diverse aquatic fauna.

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There is a need for better links between hydrology and ecology, specifically between landscapes and riverscapes to understand how processes and factors controlling the transport and storage of environmental pollution have affected or will affect the freshwater biota. Here we show how the INCA modelling framework, specifically INCA-Sed (the Integrated Catchments model for Sediments) can be used to link sediment delivery from the landscape to sediment changes in-stream. INCA-Sed is a dynamic, process-based, daily time step model. The first complete description of the equations used in the INCA-Sed software (version 1.9.11) is presented. This is followed by an application of INCA-Sed made to the River Lugg (1077 km2) in Wales. Excess suspended sediment can negatively affect salmonid health. The Lugg has a large and potentially threatened population of both Atlantic salmon (Salmo salar) and Brown Trout (Salmo trutta). With the exception of the extreme sediment transport processes, the model satisfactorily simulated both the hydrology and the sediment dynamics in the catchment. Model results indicate that diffuse soil loss is the most important sediment generation process in the catchment. In the River Lugg, the mean annual Guideline Standard for suspended sediment concentration, proposed by UKTAG, of 25 mg l− 1 is only slightly exceeded during the simulation period (1995–2000), indicating only minimal effect on the Atlantic salmon population. However, the daily time step simulation of INCA-Sed also allows the investigation of the critical spawning period. It shows that the sediment may have a significant negative effect on the fish population in years with high sediment runoff. It is proposed that the fine settled particles probably do not affect the salmonid egg incubation process, though suspended particles may damage the gills of fish and make the area unfavourable for spawning if the conditions do not improve.

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We study the contemporaneous relationship between the intensity of the Indian Summer Monsoon (ISM) and runoff in the major rivers of the Aral Sea basin (Amudarya, Syrdarya) and some of their subcatchments. To this end, we use All-India rainfall (AIR) data, CRU surface observations of precipitation and temperature, ERA40 atmospheric data, and natural discharge data corrected for human interference. We show that there is a highly significant positive correlation between ISM intensity and Amudarya runoff. This finding cannot be explained by the spill-over of ISM precipitation over the Hindu Kush into the Amudarya basin. Instead, we suggest that the observed co-variability is mediated by tropospheric temperature variations due to fluctuations in the ISM intensity. These variations are known to be due to Rossby-wave propagation in response to condensational heating during monsoon precipitation. We hypothesise that the corresponding anomalies in surface temperatures imply anomalies in meltwater formation.

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This paper presents an assessment of the impacts of climate change on a series of indicators of hydrological regimes across the global domain, using a global hydrological model run with climate scenarios constructed using pattern-scaling from 21 CMIP3 (Coupled Model Intercomparison Project Phase 3) climate models. Changes are compared with natural variability, with a significant change being defined as greater than the standard deviation of the hydrological indicator in the absence of climate change. Under an SRES (Special Report on Emissions Scenarios) A1b emissions scenario, substantial proportions of the land surface (excluding Greenland and Antarctica) would experience significant changes in hydrological behaviour by 2050; under one climate model scenario (Hadley Centre HadCM3), average annual runoff increases significantly over 47% of the land surface and decreases over 36%; only 17% therefore sees no significant change. There is considerable variability between regions, depending largely on projected changes in precipitation. Uncertainty in projected river flow regimes is dominated by variation in the spatial patterns of climate change between climate models (hydrological model uncertainty is not included). There is, however, a strong degree of consistency in the overall magnitude and direction of change. More than two-thirds of climate models project a significant increase in average annual runoff across almost a quarter of the land surface, and a significant decrease over 14%, with considerably higher degrees of consistency in some regions. Most climate models project increases in runoff in Canada and high-latitude eastern Europe and Siberia, and decreases in runoff in central Europe, around the Mediterranean, the Mashriq, central America and Brasil. There is some evidence that projecte change in runoff at the regional scale is not linear with change in global average temperature change. The effects of uncertainty in the rate of future emissions is relatively small