939 resultados para Hydrologic variability
Resumo:
Extensive data used to quantify broad soil C changes (without information about causation), coupled with intensive data used for attribution of changes to specific management practices, could form the basis of an efficient national grassland soil C monitoring network. Based on variability of extensive (USDA/NRCS pedon database) and intensive field-level soil C data, we evaluated the efficacy of future sample collection to detect changes in soil C in grasslands. Potential soil C changes at a range of spatial scales related to changes in grassland management can be verified (alpha=0.1) after 5 years with collection of 34, 224, 501 samples at the county, state, or national scales, respectively. Farm-level analysis indicates that equivalent numbers of cores and distinct groups of cores (microplots) results in lowest soil C coefficients of variation for a variety of ecosystems. Our results suggest that grassland soil C changes can be precisely quantified using current technology at scales ranging from farms to the entire nation. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
Background: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by climatic variables. However, few studies have examined the quantitative relationship between climate variation and HFRS transmission. ---------- Objective: We examined the potential impact of climate variability on HFRS transmission and developed climate-based forecasting models for HFRS in northeastern China. ---------- Methods: We obtained data on monthly counts of reported HFRS cases in Elunchun and Molidawahaner counties for 1997–2007 from the Inner Mongolia Center for Disease Control and Prevention and climate data from the Chinese Bureau of Meteorology. Cross-correlations assessed crude associations between climate variables, including rainfall, land surface temperature (LST), relative humidity (RH), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI) and monthly HFRS cases over a range of lags. We used time-series Poisson regression models to examine the independent contribution of climatic variables to HFRS transmission. ----------- Results: Cross-correlation analyses showed that rainfall, LST, RH, and MEI were significantly associated with monthly HFRS cases with lags of 3–5 months in both study areas. The results of Poisson regression indicated that after controlling for the autocorrelation, seasonality, and long-term trend, rainfall, LST, RH, and MEI with lags of 3–5 months were associated with HFRS in both study areas. The final model had good accuracy in forecasting the occurrence of HFRS. ---------- Conclusions: Climate variability plays a significant role in HFRS transmission in northeastern China. The model developed in this study has implications for HFRS control and prevention.
Resumo:
The city of Scottsdale Arizona implemented the first fixed photo Speed Enforcement camera demonstration Program (SEP) on a US freeway in 2006. A comprehensive before-and-after analysis of the impact of the SEP on safety revealed significant reductions in crash frequency and severity, which indicates that the SEP is a promising countermeasure for improving safety. However, there is often a trade off between safety and mobility when safety investments are considered. As a result, identifying safety countermeasures that both improve safety and reduce Travel Time Variability (TTV) is a desirable goal for traffic safety engineers. This paper reports on the analysis of the mobility impacts of the SEP by simulating the traffic network with and without the SEP, calibrated to real world conditions. The simulation results show that the SEP decreased the TTV: the risk of unreliable travel was at least 23% higher in the ‘without SEP’ scenario than in the ‘with SEP’ scenario. In addition, the total Travel Time Savings (TTS) from the SEP was estimated to be at least ‘569 vehicle-hours/year.’ Consequently, the SEP is an efficient countermeasure not only for reducing crashes but also for improving mobility through TTS and reduced TTV.
Resumo:
Antipsychotic medications act as either antagonists or partial agonists of the dopamine D2 receptor (DRD2) and antipsychotic drugs vary widely in their binding affinity for the D2 receptor (Kapur and Seeman, 2000). The DRD2 957CNT (rs6277) polymorphism has previously been associated with schizophrenia (Lawford et al., 2005) and the T-allele of the 957CNT polymorphism is associated with reduced mRNA stability and synthesis of the dopamine D2 receptor (Duan et al., 2003). The aim of the study was to determine if the rs6277 polymorphism predicts some of the variability of positive and negative symptoms observed in schizophrenia patients being treated with antipsychotic medication.
Resumo:
The variability of input parameters is the most important source of overall model uncertainty. Therefore, an in-depth understanding of the variability is essential for uncertainty analysis of stormwater quality model outputs. This paper presents the outcomes of a research study which investigated the variability of pollutants build-up characteristics on road surfaces in residential, commercial and industrial land uses. It was found that build-up characteristics vary highly even within the same land use. Additionally, industrial land use showed relatively higher variability of maximum build-up, build-up rate and particle size distribution, whilst the commercial land use displayed a relatively higher variability of pollutant-solid ratio. Among the various build-up parameters analysed, D50 (volume-median-diameter) displayed the relatively highest variability for all three land uses.
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The Queensland Department of Main Roads uses Weigh-in-Motion (WiM) devices to covertly monitor (at highway speed) axle mass, axle configurations and speed of heavy vehicles on the road network. Such data is critical for the planning and design of the road network. Some of the data appears excessively variable. The current work considers the nature, magnitude and possible causes of WiM data variability. Over fifty possible causes of variation in WiM data have been identified in the literature. Data exploration has highlighted five basic types of variability specifically: ----- • cycling, both diurnal and annual;----- • consistent but unreasonable data;----- • data jumps;----- • variations between data from opposite sides of the one road; and ----- • non-systematic variations.----- This work is part of wider research into procedures to eliminate or mitigate the influence of WiM data variability.
Resumo:
In fast bowling, cricketers are expected to produce a range of delivery lines and lengths while maximising ball speed. From a coaching perspective, technique consistency has been typically associated with superior performance in these areas. However, although bowlers are required to bowl consistently, at the elite level they must also be able to vary line, length and speed to adapt to opposition batters’ strengths and weaknesses. The relationship between technique and performance variability (and consistency) has not been investigated in previous fast bowling research. Consequently, the aim of this study was to quantify both technique (bowling action and coordination) and performance variability in elite fast bowlers from Australian Junior and National Pace Squads. Technique variability was analysed to investigate whether it could be classified as functional or dysfunctional in relation to speed and accuracy.
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The Upper Roper River is one of the Australia’s unique tropical rivers which have been largely untouched by development. The Upper Roper River catchment comprises the sub-catchments of the Waterhouse River and Roper Creek, the two tributaries of the Roper River. There is a complex geological setting with different aquifer types. In this seasonal system, close interaction between surface water and groundwater contributes to both streamflow and sustaining ecosystems. The interaction is highly variable between seasons. A conceptual hydrogeological model was developed to investigate the different hydrological processes and geochemical parameters, and determine the baseline characteristics of water resources of this pristine catchment. In the catchment, long term average rainfall is around 850 mm and is summer dominant which significantly influences the total hydrological system. The difference between seasons is pronounced, with high rainfall up to 600 mm/month in the wet season, and negligible rainfall in the dry season. Canopy interception significantly reduces the amount of effective rainfall because of the native vegetation cover in the pristine catchment. Evaporation exceeds rainfall the majority of the year. Due to elevated evaporation and high temperature in the tropics, at least 600 mm of annual rainfall is required to generate potential recharge. Analysis of 120 years of rainfall data trend helped define “wet” and “dry periods”: decreasing trend corresponds to dry periods, and increasing trend to wet periods. The period from 1900 to 1970 was considered as Dry period 1, when there were years with no effective rainfall, and if there was, the intensity of rainfall was around 300 mm. The period 1970 – 1985 was identified as the Wet period 2, when positive effective rainfall occurred in almost every year, and the intensity reached up to 700 mm. The period 1985 – 1995 was the Dry period 2, with similar characteristics as Dry period 1. Finally, the last decade was the Wet period 2, with effective rainfall intensity up to 800 mm. This variability in rainfall over decades increased/decreased recharge and discharge, improving/reducing surface water and groundwater quantity and quality in different wet and dry periods. The stream discharge follows the rainfall pattern. In the wet season, the aquifer is replenished, groundwater levels and groundwater discharge are high, and surface runoff is the dominant component of streamflow. Waterhouse River contributes two thirds and Roper Creek one third to Roper River flow. As the dry season progresses, surface runoff depletes, and groundwater becomes the main component of stream flow. Flow in Waterhouse River is negligible, the Roper Creek dries up, but the Roper River maintains its flow throughout the year. This is due to the groundwater and spring discharge from the highly permeable Tindall Limestone and tufa aquifers. Rainfall seasonality and lithology of both the catchment and aquifers are shown to influence water chemistry. In the wet season, dilution of water bodies by rainwater is the main process. In the dry season, when groundwater provides baseflow to the streams, their chemical composition reflects lithology of the aquifers, in particular the karstic areas. Water chemistry distinguishes four types of aquifer materials described as alluvium, sandstone, limestone and tufa. Surface water in the headwaters of the Waterhouse River, the Roper Creek and their tributaries are freshwater, and reflect the alluvium and sandstone aquifers. At and downstream of the confluence of the Roper River, river water chemistry indicates the influence of rainfall dilution in the wet season, and the signature of the Tindall Limestone and tufa aquifers in the dry. Rainbow Spring on the Waterhouse River and Bitter Spring on the Little Roper River (known as Roper Creek at the headwaters) discharge from the Tindall Limestone. Botanic Walk Spring and Fig Tree Spring discharge into the Roper River from tufa. The source of water was defined based on water chemical composition of the springs, surface and groundwater. The mechanisms controlling surface water chemistry were examined to define the dominance of precipitation, evaporation or rock weathering on the water chemical composition. Simple water balance models for the catchment have been developed. The important aspects to be considered in water resource planning of this total system are the naturally high salinity in the region, especially the downstream sections, and how unpredictable climate variation may impact on the natural seasonal variability of water volumes and surface-subsurface interaction.
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Experimental action potential (AP) recordings in isolated ventricular myoctes display significant temporal beat-to-beat variability in morphology and duration. Furthermore, significant cell-to-cell differences in AP also exist even for isolated cells originating from the same region of the same heart. However, current mathematical models of ventricular AP fail to replicate the temporal and cell-to-cell variability in AP observed experimentally. In this study, we propose a novel mathematical framework for the development of phenomenological AP models capable of capturing cell-to-cell and temporal variabilty in cardiac APs. A novel stochastic phenomenological model of the AP is developed, based on the deterministic Bueno-Orovio/Fentonmodel. Experimental recordings of AP are fit to the model to produce AP models of individual cells from the apex and the base of the guinea-pig ventricles. Our results show that the phenomenological model is able to capture the considerable differences in AP recorded from isolated cells originating from the location. We demonstrate the closeness of fit to the available experimental data which may be achieved using a phenomenological model, and also demonstrate the ability of the stochastic form of the model to capture the observed beat-to-beat variablity in action potential duration.
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This thesis presents the outcomes of a comprehensive research study undertaken to investigate the influence of rainfall and catchment characteristics on urban stormwater quality. The knowledge created is expected to contribute to a greater understanding of urban stormwater quality and thereby enhance the design of stormwater quality treatment systems. The research study was undertaken based on selected urban catchments in Gold Coast, Australia. The research methodology included field investigations, laboratory testing, computer modelling and data analysis. Both univariate and multivariate data analysis techniques were used to investigate the influence of rainfall and catchment characteristics on urban stormwater quality. The rainfall characteristics investigated included average rainfall intensity and rainfall duration whilst catchment characteristics included land use, impervious area percentage, urban form and pervious area location. The catchment scale data for the analysis was obtained from four residential catchments, including rainfall-runoff records, drainage network data, stormwater quality data and land use and land cover data. Pollutants build-up samples were collected from twelve road surfaces in residential, commercial and industrial land use areas. The relationships between rainfall characteristics, catchment characteristics and urban stormwater quality were investigated based on residential catchments and then extended to other land uses. Based on the influence rainfall characteristics exert on urban stormwater quality, rainfall events can be classified into three different types, namely, high average intensity-short duration (Type 1), high average intensity-long duration (Type 2) and low average intensity-long duration (Type 3). This provides an innovative approach to conventional modelling which does not commonly relate stormwater quality to rainfall characteristics. Additionally, it was found that the threshold intensity for pollutant wash-off from urban catchments is much less than for rural catchments. High average intensity-short duration rainfall events are cumulatively responsible for the generation of a major fraction of the annual pollutants load compared to the other rainfall event types. Additionally, rainfall events less than 1 year ARI such as 6- month ARI should be considered for treatment design as they generate a significant fraction of the annual runoff volume and by implication a significant fraction of the pollutants load. This implies that stormwater treatment designs based on larger rainfall events would not be feasible in the context of cost-effectiveness, efficiency in treatment performance and possible savings in land area needed. This also suggests that the simulation of long-term continuous rainfall events for stormwater treatment design may not be needed and that event based simulations would be adequate. The investigations into the relationship between catchment characteristics and urban stormwater quality found that other than conventional catchment characteristics such as land use and impervious area percentage, other catchment characteristics such as urban form and pervious area location also play important roles in influencing urban stormwater quality. These outcomes point to the fact that the conventional modelling approach in the design of stormwater quality treatment systems which is commonly based on land use and impervious area percentage would be inadequate. It was also noted that the small uniformly urbanised areas within a larger mixed catchment produce relatively lower variations in stormwater quality and as expected lower runoff volume with the opposite being the case for large mixed use urbanised catchments. Therefore, a decentralised approach to water quality treatment would be more effective rather than an "end-of-pipe" approach. The investigation of pollutants build-up on different land uses showed that pollutant build-up characteristics vary even within the same land use. Therefore, the conventional approach in stormwater quality modelling, which is based solely on land use, may prove to be inappropriate. Industrial land use has relatively higher variability in maximum pollutant build-up, build-up rate and particle size distribution than the other two land uses. However, commercial and residential land uses had relatively higher variations of nutrients and organic carbon build-up. Additionally, it was found that particle size distribution had a relatively higher variability for all three land uses compared to the other build-up parameters. The high variability in particle size distribution for all land uses illustrate the dissimilarities associated with the fine and coarse particle size fractions even within the same land use and hence the variations in stormwater quality in relation to pollutants adsorbing to different sizes of particles.
Resumo:
The temporal variations in CO2, CH4 and N2O fluxes were measured over two consecutive years from February 2007 to March 2009 from a subtropical rainforest in south-eastern Queensland, Australia, using an automated sampling system. A concurrent study using an additional 30 manual chambers examined the spatial variability of emissions distributed across three nearby remnant rainforest sites with similar vegetation and climatic conditions. Interannual variation in fluxes of all gases over the 2 years was minimal, despite large discrepancies in rainfall, whereas a pronounced seasonal variation could only be observed for CO2 fluxes. High infiltration, drainage and subsequent high soil aeration under the rainforest limited N2O loss while promoting substantial CH4 uptake. The average annual N2O loss of 0.5 ± 0.1 kg N2O-N ha−1 over the 2-year measurement period was at the lower end of reported fluxes from rainforest soils. The rainforest soil functioned as a sink for atmospheric CH4 throughout the entire 2-year period, despite periods of substantial rainfall. A clear linear correlation between soil moisture and CH4 uptake was found. Rates of uptake ranged from greater than 15 g CH4-C ha−1 day−1 during extended dry periods to less than 2–5 g CH4-C ha−1 day−1 when soil water content was high. The calculated annual CH4 uptake at the site was 3.65 kg CH4-C ha−1 yr−1. This is amongst the highest reported for rainforest systems, reiterating the ability of aerated subtropical rainforests to act as substantial sinks of CH4. The spatial study showed N2O fluxes almost eight times higher, and CH4 uptake reduced by over one-third, as clay content of the rainforest soil increased from 12% to more than 23%. This demonstrates that for some rainforest ecosystems, soil texture and related water infiltration and drainage capacity constraints may play a more important role in controlling fluxes than either vegetation or seasonal variability