985 resultados para Rainfall


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Rainfall variability is a challenge to sustainable and pro. table cattle production in northern Australia. Strategies recommended to manage for rainfall variability, like light or variable stocking, are not widely adopted. This is due partly to the perception that sustainability and profitability are incompatible. A large, long-term grazing trial was initiated in 1997 in north Queensland, Australia, to test the effect of different grazing strategies on cattle production. These strategies are: (i) constant light stocking (LSR) at long-term carrying capacity (LTCC); (ii) constant heavy stocking (HSR) at twice LTCC; (iii) rotational wet-season spelling (R/Spell) at 1.5 LTCC; (iv) variable stocking (VAR), with stocking rates adjusted in May based on available pasture; and (v) a Southern Oscillation Index (SOI) variable strategy, with stocking rates adjusted in November, based on available pasture and SOI seasonal forecasts. Animal performance varied markedly over the 10 years for which data is presented, due to pronounced differences in rainfall and pasture availability. Nonetheless, lighter stocking at or about LTCC consistently gave the best individual liveweight gain (LWG), condition score and skeletal growth; mean LWG per annum was thus highest in the LSR (113 kg), intermediate in the R/Spell (104 kg) and lowest in the HSR(86 kg). MeanLWGwas 106 kg in the VAR and 103 kg in the SOI but, in all years, the relative performance of these strategies was dependent upon the stocking rate applied. After 2 years on the trial, steers from lightly stocked strategies were 60-100 kg heavier and received appreciable carcass price premiums at the meatworks compared to those under heavy stocking. In contrast, LWG per unit area was greatest at stocking rates of about twice LTCC; mean LWG/ha was thus greatest in the HSR (21 kg/ha), but this strategy required drought feeding in four of the 10 years and was unsustainable. Although LWG/ha was lower in the LSR (mean 14 kg/ha), or in strategies that reduced stocking rates in dry years like the VAR(mean 18 kg/ha) and SOI (mean 17 kg/ha), these strategies did not require drought feeding and appeared sustainable. The R/Spell strategy (mean 16 kg/ha) was compromised by an ill-timed fire, but also performed satisfactorily. The present results provide important evidence challenging the assumption that sustainable management in a variable environment is unprofitable. Further research is required to fully quantify the long-term effects of these strategies on land condition and profitability and to extrapolate the results to breeder performance at the property level.

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The Wambiana grazing trial started in 1997 to test and develop sustainable and profitable grazing strategies to manage for rainfall variability. It is important that this trial continue as the results are still relatively short-term relative to rainfall cycles and significant treatment changes are still occurring. This new proposal will maintain baseline treatments but will modify others based on trial learning’s to date. It builds on treatment differences and evidence collected over the last 12 years to deliver evidence-based guidelines and principles for sustainable and productive management. The trial also links to other projects modelling water quality, climate change, methane emissions and soil C sequestration on grazing lands.

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Remote detection of management-related trend in the presence of inter-annual climatic variability in the rangelands is difficult. Minimally disturbed reference areas provide a useful guide, but suitable benchmarks are usually difficult to identify. We describe a method that uses a unique conceptual framework to identify reference areas from multitemporal sequences of ground cover derived from Landsat TM and ETM+ imagery. The method does not require ground-based reference sites nor GIS layers about management. We calculate a minimum ground cover image across all years to identify locations of most persistent ground cover in years of lowest rainfall. We then use a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. This difference estimates ground-cover change between successive below-average rainfall years, which provides a seasonally interpreted measure of management effects. We examine the approach's sensitivity to window size and to cover-index percentiles used to define persistence. The method successfully detected management-related change in ground cover in Queensland tropical savanna woodlands in two case studies: (1) a grazing trial where heavy stocking resulted in substantial decline in ground cover in small paddocks, and (2) commercial paddocks where wet-season spelling (destocking) resulted in increased ground cover. At a larger scale, there was broad agreement between our analysis of ground-cover change and ground-based land condition change for commercial beef properties with different a priori ratings of initial condition, but there was also some disagreement where changing condition reflected pasture composition rather than ground cover. We conclude that the method is suitably robust to analyse grazing effects on ground cover across the 1.3 x 10(6) km(2) of Queensland's rangelands. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.

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Grazing by domestic livestock is one of the most widespread uses of the rangelands of Australia. There is limited information on the effects of grazing by domestic livestock on the vertebrate fauna of Australia and the establishment of a long-term grazing experiment in north-eastern Queensland at Wambiana provided an opportunity to attempt an examination of the changes in vertebrate fauna as a consequence of the manipulation of stocking rates. The aim was to identify what the relative effects of vegetation type, stocking rate and other landscape-scale environmental factors were on the patterns recorded. Sixteen 1-ha sites were established within three replicated treatments (moderate, heavy and variable stocking rates). The sites were sampled in the wet and dry seasons in 1999-2000 (T-0) and again in 2003-04 (T-1). All paddocks of the treatments were burnt in 1999. Average annual rainfall declined markedly between the two sampling periods, which made interpretation of the data difficult. A total of 127 species of vertebrate fauna comprising five amphibian, 83 bird, 27 reptile and 12 mammal species were recorded. There was strong separation in faunal composition from T-0 to T-1 although changes in mean compositional dissimilarity between the grazing stocking rate treatments were less well defined. There was a relative change in abundance of 24 bird, four mammal and five reptile species from T-0 to T-1. The generalised linear modelling identified that, in the T-1 data, there was significant variation in the abundance of 16 species explained by the grazing and vegetation factors. This study demonstrated that vertebrate fauna assemblage did change and that these changes were attributable to the interplay between the stocking rates, the vegetation types on the sites surveyed, the burning of the experimental paddocks and the decrease in rainfall over the course of the two surveys. It is recommended that the experiment is sampled again but that the focus should be on a rapid survey of abundant taxa (i.e. birds and reptiles) to allow an increase in the frequency of sampling and replication of the data. This would help to articulate more clearly the trajectory of vertebrate change due to the relative effects of stocking rates compared with wider landscape environmental changes. Given the increasing focus on pastoral development in northern Australia, any opportunity to incorporate the collection of data on biodiversity into grazing manipulation experiments should be taken for the assessment of the effects of land management on faunal species.

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A transformation is suggested which can transform a non-Gaussian monthly hydrological time series into a Gaussian one. The suggested approach is verified with data of ten Indian rainfall time series. Incidentally, it is observed that once the deterministic trends are removed, the transformation leads to an uncorrelated process for monthly rainfall. The procedure for normalization is general enough in that it should be also applicable to river discharges. This is verified to a limited extent by considering data of two Indian river discharges.

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Climate projections over the next two to four decades indicate that most of Australia’s wheat-belt is likely to become warmer and drier. Here we used a shire scale, dynamic stress-index model that accounts for the impacts of rainfall and temperature on wheat yield, and a range of climate change projections from global circulation models to spatially estimate yield changes assuming no adaptation and no CO2 fertilisation effects. We modelled five scenarios, a baseline climate (climatology, 1901–2007), and two emission scenarios (“low” and “high” CO2) for two time horizons, namely 2020 and 2050. The potential benefits from CO2 fertilisation were analysed separately using a point level functional simulation model. Irrespective of the emissions scenario, the 2020 projection showed negligible changes in the modelled yield relative to baseline climate, both using the shire or functional point scale models. For the 2050-high emissions scenario, changes in modelled yield relative to the baseline ranged from −5 % to +6 % across most of Western Australia, parts of Victoria and southern New South Wales, and from −5 to −30 % in northern NSW, Queensland and the drier environments of Victoria, South Australia and in-land Western Australia. Taking into account CO2 fertilisation effects across a North–south transect through eastern Australia cancelled most of the yield reductions associated with increased temperatures and reduced rainfall by 2020, and attenuated the expected yield reductions by 2050.

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Grasses, legumes, saltbushes and herbs were evaluated at 6 sites in southern inland Queensland to identify potential pasture and forage plants for use on marginal cropping soils. The region experiences summer heat waves and severe winter frosts. Emphasis was on perennial plants, and native species were included. Seedlings were transplanted into the unfertilized fields in either summer or autumn to suit the growing season of plants, and watered to ensure estab-lishment. Summer-growing grasses were the most successful group, while cool season-growing perennials mostly failed. Summer legumes were disappointing, with Stylosanthes scabra and Indigofera schimperi performing best. Some lines such as I. schimperi and the Eragrostis hybrid cv. Cochise were assessed as potential weeds owing to low animal acceptance. Native Rhynchosia minima grew well at some sites and deserves more study. Cenchrus ciliaris was always easy to establish and produced the highest yields. Persistence of some Digitaria and Bothriochloa species, Eragrostis curvula and Fingerhuthia africana at specific sites was encouraging, but potential weediness needs careful assessment. Standard species were identified to represent the main forage types, such as Austrostipa scabra for cool season-growing grasses, for incorporation into future trials with new genetic materials. The early field testing protocol used should be considered for use elsewhere, if unreliable rainfall poses a high risk of establishment failure from scarce seed.

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It has long been thought that tropical rainfall retrievals from satellites have large errors. Here we show, using a new daily 1 degree gridded rainfall data set based on about 1800 gauges from the India Meteorology Department (IMD), that modern satellite estimates are reasonably close to observed rainfall over the Indian monsoon region. Daily satellite rainfalls from the Global Precipitation Climatology Project (GPCP 1DD) and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are available since 1998. The high summer monsoon (June-September) rain over the Western Ghats and Himalayan foothills is captured in TMPA data. Away from hilly regions, the seasonal mean and intraseasonal variability of rainfall (averaged over regions of a few hundred kilometers linear dimension) from both satellite products are about 15% of observations. Satellite data generally underestimate both the mean and variability of rain, but the phase of intraseasonal variations is accurate. On synoptic timescales, TMPA gives reasonable depiction of the pattern and intensity of torrential rain from individual monsoon low-pressure systems and depressions. A pronounced biennial oscillation of seasonal total central India rain is seen in all three data sets, with GPCP 1DD being closest to IMD observations. The new satellite data are a promising resource for the study of tropical rainfall variability.

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The southern Western Ghats tropical montane cloud forest sites (Gavi, Periyar, High wavys and Venniyar), which are characterized by frequent or seasonal cloud cover at the vegetation level, are considered one of the most threatened ecosystems in India and the world. Three out of four montane cloud forest sites studied in the southern Western Ghats had experienced diminishing trends of seasonal average and total rainfall, especially during summer monsoon season. The highest level of reduction for summer monsoon season was observed at Gavi rainforest station (>20 mm/14 years) in Kerala followed by Venniyar (>20 mm/20 years) site in Tamil Nadu. Average annual and total precipitation increased during the study period irrespective of the seasons over Periyar area, and the greatest values were recorded for season 2 (>25 mm/28 years). Positive trends for winter monsoon rainfall has been observed for three stations (Periyar, High wavys and Venniyar) except Gavi, and the trend was positive and significant (90%) for Periyar and High wavys. Increase in summer monsoon rainfall was observed for Periyar site and the trend was found to be significant (95%).

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One of the most important modes of summer season precipitation variability over the Indian region, the diurnal cycle, is studied using the Tropical Rainfall Measuring Mission 3-hourly, 0.25 degrees x 0.25 degrees 3B42 rainfall product for nine years (1999-2007). Most previous studies have provided an analysis of a single year or a few years of satellite-or station-based rainfall data. Our study aims to systematically analyze the statistical characteristics of the diurnal-scale signature of rainfall over the Indian and surrounding regions. Using harmonic analysis, we extract the signal corresponding to diurnal and subdiurnal variability. Subsequently, the 3-hourly time period or the octet of rainfall peak for this filtered signal, referred to as the ``peak octet,'' is estimated, with care taken to eliminate spurious peaks arising out of Gibbs oscillations. Our analysis suggests that over the Bay of Bengal, there are three distinct modes of the peak octet of diurnal rainfall corresponding to 1130, 1430, and 1730 Indian standard time (IST), from the north central to south bay. This finding could be seen to be consistent with southward propagation of the diurnal rainfall pattern reported by earlier studies. Over the Arabian Sea, there is a spatially coherent pattern in the mode of the peak octet (1430 IST), in a region where it rains for more than 30% of the time. In the equatorial Indian Ocean, while most of the western part shows a late night/early morning peak, the eastern part does not show a spatially coherent pattern in the mode of the peak octet owing to the occurrence of a ual maxima (early morng and early/late afternoon). The imalayan foothills were found to have a mode of peak octet corresponding to 0230 IST, whereas over the Burmese mountains and the Western Ghats (west coast of India) the rainfall peaks during late afternoon/early evening (1430-1730 IST). This implies that the phase of the diurnal cycle over inland orography (e. g., Himalayas) is significantly different from coastal orography (e. g., Western Ghats). We also find that over the Gangetic plains, the peak octet is around 1430 IST, a few hours earlier compared to the typical early evening maxima over land.

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The annual cycle of rainfall over the Korean Peninsula is marked by two peaks: one during July and the other during August. Since the mid-1970s, the maximum rainfall over the Korean Peninsula has shifted from July to August. This shift in rainfall peak was caused by a significant increase of August rainfall after the mid-1970s. The basic reason for this shift has been traced to a change in teleconnection between El Nino-Southern Oscillation (ENSO) and August rainfall. The relationship between August rainfall over Korea and ENSO changed from 1954-1975 (PI) to 1976-2002 (PII). The variability of August rainfall was significantly associated with sea surface temperature (SST) variation over the eastern equatorial Pacific during PI, but this relationship is absent during the PII period. In El Nino years during PI, low-level westerly and southerly wind anomalies are dominant around the East China Sea, which relates to strong August rainfall. In La Nina years during PI, easterly and northerly wind anomalies are dominant. During the PII period, however, westerly and southerly wind anomalies around the East China Sea were responsible for the high August rainfall over the East Asian region, even though La Nina SST conditions were in effect over the eastern Pacific.

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Variability in rainfall is known to be a major influence on the dynamics of tropical forests, especially rates and patterns of tree mortality. In tropical dry forests a number of contributing factors to tree mortality, including dry season fire and herbivory by large herbivorous mammals, could be related to rainfall patterns, while loss of water potential in trees during the dry season or a wet season drought could also result in enhanced rates of death. While tree mortality as influenced by severe drought has been examined in tropical wet forests there is insufficient understanding of this process in tropical dry forests. We examined these causal factors in relation to inter-annual differences in rainfall in causing tree mortality within a 50-ha Forest Dynamics Plot located in the tropical dry deciduous forests of Mudumalai, southern India, that has been monitored annually since 1988. Over a 19-year period (1988-2007) mean annual mortality rate of all stems >1 cm dbh was 6.9 +/- 4.6% (range = 1.5-17.5%); mortality rates broadly declined from the smaller to the larger size classes with the rates in stems >30 cm dbh being among the lowest recorded in tropical forest globally. Fire was the main agent of mortality in stems 1-5 cm dbh, elephant-herbivory in stems 5-10 cm dbh, and other natural causes in stems > 10 cm dbh. Elephant-related mortality did not show any relationship to rainfall. On the other hand, fire-related mortality was significantly negatively correlated to quantity of rainfall during the preceding year. Mortality due to other causes in the larger stem sizes was significantly negatively correlated to rainfall with a 2-3-year lag, suggesting that water deficit from mild or prolonged drought enhanced the risk of death but only with a time lag that was greater than similar lags in tree mortality observed in other forest types. In this respect, tropical dry forests growing in regions of high rainfall variability may have evolved greater resistance to rainfall deficit as compared to tropical moist or temperate forests but are still vulnerable to drought-related mortality.

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The current approach for protecting the receiving water environment from urban stormwater pollution is the adoption of structural measures commonly referred to as Water Sensitive Urban Design (WSUD). The treatment efficiency of WSUD measures closely depends on the design of the specific treatment units. As stormwater quality is influenced by rainfall characteristics, the selection of appropriate rainfall events for treatment design is essential to ensure the effectiveness of WSUD systems. Based on extensive field investigations in four urban residential catchments based at Gold Coast, Australia, and computer modelling, this paper details a technically robust approach for the selection of rainfall events for stormwater treatment design using a three-component model. The modelling results confirmed that high intensity-short duration events produce 58.0% of TS load while they only generated 29.1% of total runoff volume. Additionally, rainfall events smaller than 6-month average recurrence interval (ARI) generates a greater cumulative runoff volume (68.4% of the total annual runoff volume) and TS load (68.6% of the TS load exported) than the rainfall events larger than 6-month ARI. The results suggest that for the study catchments, stormwater treatment design could be based on the rainfall which had a mean value of 31 mm/h average intensity and 0.4 h duration. These outcomes also confirmed that selecting smaller ARI rainfall events with high intensity-short duration as the threshold for treatment system design is the most feasible approach since these events cumulatively generate a major portion of the annual pollutant load compared to the other types of events, despite producing a relatively smaller runoff volume. This implies that designs based on small and more frequent rainfall events rather than larger rainfall events would be appropriate in the context of efficiency in treatment performance, cost-effectiveness and possible savings in land area needed.

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The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

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Generally average rainfall over meteorological subdivisions is used for assessment of the variability of monsoon rainfall. It is shown here that variations of seasonal rainfall over the meteorological subdivisions of interior Karnataka are not coherent. A methodology for delineating coherent rainfall zones is developed in this paper and applied to derive such zones for the State of Karnataka.