106 resultados para Roof runoff
Resumo:
Seven catchments of diverse size in Mediterranean Europe were investigated in order to understand the main aspects of their hydrological functioning. The methods included the analysis of daily and monthly precipitation, monthly potential evapotranspiration rates, flow duration curves, rainfall runoff relationships and catchment internal data for the smaller and more instrumented catchments. The results showed that the catchments were less dry than initially considered. Only one of them was really semi-arid throughout the year. All the remaining catchments showed wet seasons when precipitation exceeded potential evapotrans-piration, allowing aquifer recharge, wet runoff generation mechanisms and relevant baseflow contribution. Nevertheless, local infiltration excess (Hortonian) overland flow was inferred during summer storms in some catchments and urban overland flow in some others. The roles of karstic groundwater, human disturbance and low winter temperatures were identified as having an important impact on the hydrological regime in some of the catchments.
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The transfer of hillslope water to and through the riparian zone forms a research area of importance in hydrological investigations. Numerical modelling schemes offer a way to visualise and quantify first-order controls on catchment runoff response and mixing. We use a two-dimensional Finite Element model to assess the link between model setup decisions (e.g. zero-flux boundary definitions, soil algorithm choice) and the consequential hydrological process behaviour. A detailed understanding of the consequences of model configuration is required in order to produce reliable estimates of state variables. We demonstrate that model configuration decisions can determine effectively the presence or absence of particular hillslope flow processes and, the magnitude and direction of flux at the hillslope–riparian interface. If these consequences are not fully explored for any given scheme and application, the resulting process inference may well be misleading.
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Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes.
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We develop a process-based model for the dispersion of a passive scalar in the turbulent flow around the buildings of a city centre. The street network model is based on dividing the airspace of the streets and intersections into boxes, within which the turbulence renders the air well mixed. Mean flow advection through the network of street and intersection boxes then mediates further lateral dispersion. At the same time turbulent mixing in the vertical detrains scalar from the streets and intersections into the turbulent boundary layer above the buildings. When the geometry is regular, the street network model has an analytical solution that describes the variation in concentration in a near-field downwind of a single source, where the majority of scalar lies below roof level. The power of the analytical solution is that it demonstrates how the concentration is determined by only three parameters. The plume direction parameter describes the branching of scalar at the street intersections and hence determines the direction of the plume centreline, which may be very different from the above-roof wind direction. The transmission parameter determines the distance travelled before the majority of scalar is detrained into the atmospheric boundary layer above roof level and conventional atmospheric turbulence takes over as the dominant mixing process. Finally, a normalised source strength multiplies this pattern of concentration. This analytical solution converges to a Gaussian plume after a large number of intersections have been traversed, providing theoretical justification for previous studies that have developed empirical fits to Gaussian plume models. The analytical solution is shown to compare well with very high-resolution simulations and with wind tunnel experiments, although re-entrainment of scalar previously detrained into the boundary layer above roofs, which is not accounted for in the analytical solution, is shown to become an important process further downwind from the source.
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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 extent of the surface area sunlit is critical for radiative energy exchanges and therefore for a wide range of applications that require urban land surface models (ULSM), ranging from human comfort to weather forecasting. Here a computational demanding shadow casting algorithm is used to assess the capability of a simple single-layer urban canopy model, which assumes an infinitely long rotating canyon (ILC), to reproduce sunlit areas on roof and roads over central London. Results indicate that the sunlit roads areas are well-represented but somewhat smaller using an ILC, while sunlit roofs areas are consistently larger, especially for dense urban areas. The largest deviations from real world sunlit areas are found for roofs during mornings and evenings. Indications that sunlit fractions on walls are overestimated using an ILC during mornings and evenings are found. The implications of these errors are dependent on the application targeted. For example, (independent of albedo) ULSMs used in numerical weather prediction applying ILC representation of the urban form will overestimate outgoing shortwave radiation from roofs due to the overestimation of sunlit fraction of the roofs. Complications of deriving height to width ratios from real world data are also discussed.
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Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.
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Changes in the depth of Lake Viljandi between 1940 and 1990 were simulated using a lake water and energy-balance model driven by standard monthly weather data. Catchment runoff was simulated using a one-dimensional hydrological model, with a two-layer soil, a single-layer snowpack, a simple representation of vegetation cover and similarly modest input requirements. Outflow was modelled as a function of lake level. The simulated record of lake level and outflow matched observations of lake-level variations (r = 0.78) and streamflow (r = 0.87) well. The ability of the model to capture both intra- and inter-annual variations in the behaviour of a specific lake, despite the relatively simple input requirements, makes it extremely suitable for investigations of the impacts of climate change on lake water balance.
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There has been a significant increase in the skill and resolution of numerical weather prediction models (NWPs) in recent decades, extending the time scales of useful weather predictions. The land-surface models (LSMs) of NWPs are often employed in hydrological applications, which raises the question of how hydrologically representative LSMs really are. In this paper, precipitation (P), evaporation (E) and runoff (R) from the European Centre for Medium-Range Weather Forecasts (ECMWF) global models were evaluated against observational products. The forecasts differ substantially from observed data for key hydrological variables. In addition, imbalanced surface water budgets, mostly caused by data assimilation, were found on both global (P-E) and basin scales (P-E-R), with the latter being more important. Modeled surface fluxes should be used with care in hydrological applications and further improvement in LSMs in terms of process descriptions, resolution and estimation of uncertainties is needed to accurately describe the land-surface water budgets.
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The Gongzha section of Tibet, China is located at the northern margin of the Indian Plate (SE Tethys) and is characterized by hemipelagic grey marls and marly limestones, light grey limestones and silty limestones, but no organic-rich sediments. High-resolution biostratigraphy reveals an expanded Cenomanian–Turonian (CT) boundary interval and the δ13C record includes the main features of the classical positive carbon-isotope excursion that characterizes the CT oceanic anoxic event. The biotic response inferred from the foraminifera suggests that oxic to dysoxic conditions prevailed, except for a short interval marked by peak abundance of Heterohelix that indicates a significantly dysoxic environment during the δ13C “b” peak excursion. The overall decreasing trend in redox-sensitive trace elements (RSTE) during the maximum δ13C excursion confirms the absence of significant longer-lasting anoxia in the Gongzha section. Enrichments in RSTE are linked to phases of increased detrital input. Chemical weathering indices suggest that the upper Cenomanian sediments accumulated under an increasingly hot and humid climate that culminated near the CT boundary. In the early Turonian lower weathering indices suggest a warm, drier climatic regime with reduced continental runoff. Phosphorus mass-accumulation rates show a significant peak at the onset of the positive δ13C excursion, followed by a decrease up to the basal Turonian. This pattern is positively correlated with the long-term decrease in detrital index as also observed in numerous other CT boundary sections (e.g., Eastbourne, Pueblo, and Whadi El Ghaib, Sinaï). Long-term phosphorus accumulation in the Gongzha section is therefore associated with changes in detrital input. The overall decreased detrital input can be explained by the increasingly remote continental sources due to the major transgression at the end of Cenomanian, coupled with changes in continental weathering intensity linked to increasingly more arid climate conditions.
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Determining the internal layout of archaeological structures and their uses has always been challenging, particularly in timber-framed or earthen walled buildings where doorways and divisions are difficult to trace. In temperate conditions however, soil formation processes may hold the key to understanding how buildings were used. The abandoned Roman town of Silchester, UK, provides a perfect case study for testing a new approach combining experimental archaeology and micromorphology. The results show that this technique can resolve previously uncertain features of urban architecture such as the presence of a roof and the changes in internal organisation and use over time.
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A present day control integration performed with the Hadley Centre's coupled climate model HadGEM1.2 experiences a large salinity bias in the Arctic Ocean when compared to in situ observations. Such a large salinity bias may have implications for both Arctic and Atlantic Ocean circulation. Large differences are seen between the runoff in HadGEM and the observations from the Global Runoff Data Centre, in particular in the Lena catchment, which could account for this salinity bias. We suggest that this discrepancy in runoff is, at least in part, due to a lack of snow accumulation in the model. The model climatology is very different to those obtained by remote sensing, such as the Global Snow Water Equivalent Climatology (NSIDC) and GlobSnow (ESA).
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Building roofs play a very important role in the energy balance of buildings, especially in summer, when they are hit by a rather high solar irradiance. Depending on the type of finishing layer, roofs can absorb a great amount of heat and reach quite high temperatures on their outermost surface, which determines significant room overheating. However, the use of highly reflective cool materials can help to maintain low outer surface temperatures; this practice may improve indoor thermal comfort and reduce the cooling energy need during the hot season.This technology is currently well known and widely used in the USA, while receiving increasing attention in Europe. In order to investigate the effectiveness of cool roofs as a passive strategy for passive cooling in moderately hot climates, this paper presents the numerical results of a case study based on the dynamic thermal analysis of an existing office building in Catania (southern Italy, Mediterranean area). The results show how the application of a cool paint on the roof can enhance the thermal comfort of the occupants by reducing the operative temperatures of the rooms and to reduce the overall energy needs of the building for space heating and cooling.
Resumo:
Roofs are severely hit by solar radiation in summer; hence the use of cool materials on the finishing layer provides a significant reduction in the heat flow entering the building, with sensible attenuation in the building cooling load. In this paper, a case study is presented, based on the dynamic simulation of an existing office building in Catania (southern Italy). Here, a part of the roof has been recently treated with a commercial cool paint, with the aim of improving thermal comfort in summer. Hence, the simulations represent a preliminary study that will allow assessing the expected effectiveness of the intervention. More in detail, the results of the simulations will be discussed in terms of both thermal comfort and energy savings, through the evaluation of parameters such as the roof surface temperature, the operative temperature and the cooling load for both conditions, i.e. with and without the cool paint. The paper also discusses the potential increase in the energy needs for winter heating, and looks at the overall annual balance in terms of primary energy; this is made by considering different climatic conditions and envelope characteristics. These aspects are usually not well highlighted in the current scientific literature.
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Cool materials are characterized by high solar reflectance and high thermal emittance; when applied to the external surface of a roof, they make it possible to limit the amount of solar irradiance absorbed by the roof, and to increase the rate of heat flux emitted by irradiation to the environment, especially during nighttime. However, a roof also releases heat by convection on its external surface; this mechanism is not negligible, and an incorrect evaluation of its entity might introduce significant inaccuracy in the assessment of the thermal performance of a cool roof, in terms of surface temperature and rate of heat flux transferred to the indoors. This issue is particularly relevant in numerical simulations, which are essential in the design stage, therefore it deserves adequate attention. In the present paper, a review of the most common algorithms used for the calculation of the convective heat transfer coefficient due to wind on horizontal building surfaces is presented. Then, with reference to a case study in Italy, the simulated results are compared to the outcomes of a measurement campaign. Hence, the most appropriate algorithms for the convective coefficient are identified, and the errors deriving by an incorrect selection of this coefficient are discussed.