Climate and terrain factors explaining streamflow response and recession in Australian catchments

Daily streamflow data were analysed to assess which climate and terrain factors best explain streamflow response in 183 Australian catchments. Assessed descriptors of catchment response included the parameters of fitted baseflow models, and baseflow index (BFI), average quick flow and average baseflow derived by baseflow separation. The variation in response between catchments was compared with indicators of catchment climate, morphology, geology, soils and land use. Spatial coherence in the residual unexplained variation was investigated using semi-variogram techniques. A linear reservoir model (one parameter; recession coefficient) produced baseflow estimates as good as those obtained using a non-linear reservoir (two parameters) and for practical purposes was therefore considered an appropriate balance between simplicity and explanatory performance. About a third (27–34%) of the spatial variation in recession coefficients and BFI was explained by catchment climate indicators, with another 53% of variation being spatially correlated over distances of 100–150 km, probably indicative of substrate characteristics not captured by the available soil and geology data. The shortest recession half-times occurred in the driest catchments and were attributed to intermittent occurrence of fast-draining (possibly perched) groundwater. Most (70–84%) of the variation in average baseflow and quick flow was explained by rainfall and climate characteristics; another 20% of variation was spatially correlated over distances of 300–700 km, possibly reflecting a combination of terrain and climate factors. It is concluded that catchment streamflow response can be predicted quite well on the basis of catchment climate alone. The prediction of baseflow recession response should be improved further if relevant substrate properties were identified and measured

Selection of an appropriately simple storm runoff model

An appropriately simple event runoff model for catchment hydrological studies was derived. The model was selected from several variants as having the optimum balance between simplicity and the ability to explain daily observations of streamflow from 260 Australian catchments (23–1902 km<sup>2</sup>). Event rainfall and runoff were estimated from the observations through a combination of baseflow separation and storm flow recession analysis, producing a storm flow recession coefficient (<i>k</i><sub>QF</sub>). Various model structures with up to six free parameters were investigated, covering most of the equations applied in existing lumped catchment models. The performance of alternative structures and free parameters were expressed in Aikake's Final Prediction Error Criterion (FPEC) and corresponding Nash-Sutcliffe model efficiencies (NSME) for event runoff totals. For each model variant, the number of free parameters was reduced in steps based on calculated parameter sensitivity. The resulting optimal model structure had two or three free parameters; the first describing the non-linear relationship between event rainfall and runoff (<i>S</i><sub>max</sub>), the second relating runoff to antecedent groundwater storage (<i>C</i><sub>Sg</sub>), and a third that described initial rainfall losses (<i>L</i><sub>i</sub>), but which could be set at 8 mm without affecting model performance too much. The best three parameter model produced a median NSME of 0.64 and outperformed, for example, the Soil Conservation Service Curve Number technique (median NSME 0.30–0.41). Parameter estimation in ungauged catchments is likely to be challenging: 64% of the variance in <i>k</i><sub>QF</sub> among stations could be explained by catchment climate indicators and spatial correlation, but corresponding numbers were a modest 45% for <i>C</i><sub>Sg</sub>, 21% for <i>S</i><sub>max</sub> and none for <i>L</i><sub>i</sub>, respectively. In gauged catchments, better estimates of event rainfall depth and intensity are likely prerequisites to further improve model performance

The role of climatic and terrain attributes in estimating baseflow recession in tropical catchments

The understanding of low flows in rivers is paramount more than ever as demand for water increases on a global scale. At the same time, limited streamflow data to investigate this phenomenon, particularly in the tropics, makes the provision of accurate estimations in ungauged areas an ongoing research need. This paper analysed the potential of climatic and terrain attributes of 167 tropical and sub-tropical unregulated catchments to predict baseflow recession rates. Daily streamflow data (m<sup>3</sup> s<sup>–1</sup>) from the Global River Discharge Center (GRDC) and a linear reservoir model were used to obtain baseflow recession coefficients (<i>k</i><sub>bf</sub>) for these catchments. Climatic attributes included annual and seasonal indicators of rainfall and potential evapotranspiration. Terrain attributes included indicators of catchment shape, morphology, land cover, soils and geology. Stepwise regression was used to identify the best predictors for baseflow recession coefficients. Mean annual rainfall (MAR) and aridity index (AI) were found to explain 49% of the spatial variation of <i>k</i><sub>bf</sub>. The rest of climatic indices and the terrain indices average catchment slope (SLO) and tree cover were also good predictors, but co-correlated with MAR. Catchment elongation (CE), a measure of catchment shape, was also found to be statistically significant, although weakly correlated. An analysis of clusters of catchments of smaller size, showed that in these areas, presumably with some similarity of soils and geology due to proximity, residuals of the regression could be explained by SLO and CE. The approach used provides a potential alternative for <i>k</i><sub>bf</sub> parameterisation in ungauged catchments

Space-based passive microwave soil moisture retrievals and the correction for a dynamic open water fraction

The large observation footprint of low-frequency satellite microwave emissions complicates the interpretation of near-surface soil moisture retrievals. While the effect of sub-footprint lateral heterogeneity is relatively limited under unsaturated conditions, open water bodies (if not accounted for) cause a strong positive bias in the satellite-derived soil moisture retrieval. This bias is generally assumed static and associated with large, continental lakes and coastal areas. Temporal changes in the extent of smaller water bodies as small as a few percent of the sensor footprint size, however, can cause significant and dynamic biases. We analysed the influence of such small open water bodies on near-surface soil moisture products derived from actual (non-synthetic) data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) for three areas in Oklahoma, USA. Differences between on-ground observations, model estimates and AMSR-E retrievals were related to dynamic estimates of open water fraction, one retrieved from a global daily record based on higher frequency AMSR-E data, a second derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and a third through inversion of the radiative transfer model, used to retrieve soil moisture. The comparison demonstrates the presence of relatively small areas (<0.05) of open water in or near the sensor footprint, possibly in combination with increased, below-critical vegetation density conditions (optical density <0.8), which contribute to seasonally varying biases in excess of 0.2 (m<sup>3</sup> m<sup>−3</sup>) soil water content. These errors need to be addressed, either through elimination or accurate characterisation, if the soil moisture retrievals are to be used effectively in a data assimilation scheme

A Multiwavelength Investigation of the Relationship Between 2CG135+1 and LSI+61o 303

We present the results of a multiwavelength monitoring campaign targeting the gamma-ray source 2CG 135+1 in an attempt to confirm the association of this object with the radio/Be/X-ray binary system LSI +61o 303. The campaign included simultaneous radio, optical, infrared, and hard x-ray/gamma-ray observations carried out with a variety of instruments, covering (not continously) almost three binary cycles of LSI +61o 303 during the period April-July 1994. Three separate OSSE observations of the gamma-ray source were carried out, covering different phases of the radio lightcurve. Hard X-ray/gamma-ray emission was detected from the direction of 2CG 135+1 during the first of these OSSE observations. The signal to noise ratio of the OSSE observations was insufficient to establish a spectral or intensity correlation of the high-energy emission with simultaneous radio, optical and infrared emission of LSI +61o 303. We briefly discuss the theoretical implications of our observations.Comment: 17 pages, 9 figures, 6 tables to be published in Astrophysical Journal, 10 April 199

Numerical description of discharge characteristics of the plasma needle

The plasma needle is a small atmospheric, nonthermal, radio-frequency discharge, generated at the tip of a needle, which can be used for localized disinfection of biological tissues. Although several experiments have characterized various qualities of the plasma needle, discharge characteristics and electrical properties are still not well known. In order to provide initial estimates on electrical properties and quantities such as particle densities, we employed a two-dimensional, time-dependent fluid model to describe the plasma needle. In this model the balance equation is solved in the drift-diffusion approach for various species and the electron energy, as well as Poisson's equation. We found that the plasma production occurs in the sheath region and results in a steady flux of reactive species outwards. Even at small (< 0.1%) admixtures of N-2 to the He background, N-2(+) is the dominant ion. The electron density is typically 10(11) cm(-3) and the dissipated power is in the order of 10 mW. These results are consistent with the experimental data available and can give direction to the practical development of the plasma needle. (c) 2005 American Institute of Physics

Structural insight into African horsesickness virus infection

African horsesickness (AHS) is a devastating disease of horses. The disease is caused by the double-stranded RNA-containing African horsesickness virus (AHSV). Using electron cryomicroscopy and three-dimensional image reconstruction, we determined the architecture of an AHSV serotype 4 (AHSV-4) reference strain. The structure revealed triple-layered AHS virions enclosing the segmented genome and transcriptase complex. The innermost protein layer contains 120 copies of VP3, with the viral polymerase, capping enzyme, and helicase attached to the inner surface of the VP3 layer on the 5-fold axis, surrounded by double-stranded RNA. VP7 trimers form a second, T 13 layer on top of VP3. Comparative analyses of the structures of bluetongue virus and AHSV-4 confirmed that VP5 trimers form globular domains and VP2 trimers form triskelions, on the virion surface. We also identified an AHSV-7 strain with a truncated VP2 protein (AHSV-7 tVP2) which outgrows AHSV-4 in culture. Comparison of AHSV-7 tVP2 to bluetongue virus and AHSV-4 allowed mapping of two domains in AHSV-4 VP2, and one in bluetongue virus VP2, that are important in infection. We also revealed a protein plugging the 5-fold vertices in AHSV-4. These results shed light on virus-host interactions in an economically important orbivirus to help the informed design of new vaccines