Wheat investigations at Biloela regional experiment station, Central Queensland

A review of climatic conditions has been given to show the relationship between the distribution of rainfall and the production of wheat in the Callide Valley region. Data have been presented to show the total amounts and the percentage chances of receiving specific quantities of rainfall during the fallowing, planting and growing periods for wheat. Comments have been made on the selection of planting time and the suitability of varieties for grain and hay production. The influence of soil nitrogen supply and frosts upon wheat production in the Callide Valley has been discussed

Global extent of rivers and streams

The turbulent surfaces of rivers and streams are natural hotspots of biogeochemical exchange with the atmosphere. At the global scale, the total river-atmosphere flux of trace gasses such as carbon dioxide depends on the proportion of Earth’s surface that is covered by the fluvial network, yet the total surface area of rivers and streams is poorly constrained. We used a global database of planform river hydromorphology and a statistical approach to show that global river and stream surface area at mean annual discharge is 773,000 ± 79,000 square kilometers (0.58 ± 0.06%) of Earth’s nonglaciated land surface, an area 44 ± 15% larger than previous spatial estimates. We found that rivers and streams likely play a greater role in controlling land-atmosphere fluxes than is currently represented in global carbon budgets

The past and future of global river ice

More than one-third of Earth’s landmass is drained by rivers that seasonally freeze over. Ice transforms the hydrologic1,2, ecologic3,4, climatic5 and socio-economic6–8 functions of river corridors. Although river ice extent has been shown to be declining in many regions of the world1, the seasonality, historical change and predicted future changes in river ice extent and duration have not yet been quantified globally. Previous studies of river ice, which suggested that declines in extent and duration could be attributed to warming temperatures9,10, were based on data from sparse locations. Furthermore, existing projections of future ice extent are based solely on the location of the 0-°C isotherm11. Here, using satellite observations, we show that the global extent of river ice is declining, and we project a mean decrease in seasonal ice duration of 6.10 ± 0.08 days per 1-°C increase in global mean surface air temperature. We tracked the extent of river ice using over 400,000 clear-sky Landsat images spanning 1984–2018 and observed a mean decline of 2.5 percentage points globally in the past three decades. To project future changes in river ice extent, we developed an observationally calibrated and validated model, based on temperature and season, which reduced the mean bias by 87 per cent compared with the 0-degree-Celsius isotherm approach. We applied this model to future climate projections for 2080–2100: compared with 2009–2029, the average river ice duration declines by 16.7 days under Representative Concentration Pathway (RCP) 8.5, whereas under RCP 4.5 it declines on average by 7.3 days. Our results show that, globally, river ice is measurably declining and will continue to decline linearly with projected increases in surface air temperature towards the end of this century

Lithologic and tectonic controls on bedrock channel form at the northwest Himalayan front

Recognition that channel form reflects a river's ability to erode rock and transport material has spawned stream-power models that estimate incision patterns by approximating energy dissipation within a channel. These models frequently assume that channel width scales as a power law with drainage area, partly because drainage area is easily extracted from digital elevation models (DEMs). However, this assumption is often confounded by local variations in rock strength and rock-uplift rate that can cause channel constriction downstream. Here we investigate the morphological response to spatial changes in rock strength and rock-uplift rate of 10 bedrock channels traversing the Mohand range along the northwest Himalayan front. We present a new method to continuously measure and compare channel width, slope, and other hydraulic parameters that integrate satellite imagery and DEM analysis. Our method corrects for an ∼13% overestimation of average channel gradient from a 90m resolution DEM that arises from short circuits of fine-scale meanders. We find that channels (1) narrow >1 km upstream from knickpoints formed by an increase in rock strength, (2) adjust laterally more than vertically in response to downstream decreases rock erodibility and uplift rate, and (3) meander where shear stresses are high and channel widths are low. We attribute these results to a high ratio of sediment supply to transport capacity, which enhances lateral erosion relative to vertical incision. Our results suggest that substrate strength and sediment supply substantially infl uence channel form and that channel width should be explicitly measured when interpreting tectonic signals from bedrock channel morphology

RivWidthCloud: An Automated Google Earth Engine Algorithm for River Width Extraction from Remotely Sensed Imagery

The wetted width of a river is one of the most important hydraulic parameters that can be readily measured using remote sensing. Remotely sensed river widths are used to estimate key attributes of river systems, including changes in their surface area, channel storage, and discharge. Although several published algorithms automate river network and width extraction from remote sensing images, they are limited by only being able to run on local computers and do not automatically manage cloudy images as input. Here we present RivWidthCloud, a river width software package developed on the Google Earth Engine cloud computing platform. RivWidthCloud automatically extracts river centerline and widths from optical satellite images with the ability to flag observations that are obstructed by features like clouds, cloud shadows, and snow based on existing quality band classification. Because RivWidthCloud is built on a popular cloud computing platform, it allows users to easily apply the algorithm to the platform's vast archive of remote sensing images, thereby reducing the users' overhead for computing hardware and data storage. By comparing RivWidthCloud-derived widths from Landsat images to in situ widths from the U.S. and Canada, we show that RivWidthCloud can estimate widths with high accuracy (root mean square error: 99 m; mean absolute error: 43 m; mean bias:-21 m). By making RivWidthCloud publicly available, we anticipate that it will be used to address both river science questions and operational applications of water resource management

Temporally Variable Stream Width and Surface Area Distributions in a Headwater Catchment

Headwater stream networks expand and contract in response to event-driven and seasonal catchment wetness conditions. This dynamic behavior drives variability in the width, length, and surface area of streams, important parameters for constraining a range of ecological and biogeochemical processes, such as atmospheric gas exchange. While the longitudinal expansion and contraction of streams has been studied for some time, variability in stream widths remains poorly understood. Recent studies have found that stream widths at average baseflow conditions follow a log-normal frequency distribution across diverse physiographies. To examine how the distribution of widths varies with flow conditions, we surveyed stream widths 12 times across a 48.4-ha research watershed, located in the Duke Forest in central North Carolina, USA. Here, we show that as runoff increased from the 37th to 99th percentiles of flow, flowing streams widened across the network (“lateral expansion”) and streamflow simultaneously extended upstream to reactivate dry channels (“longitudinal expansion”). In general, as runoff increased, the marginal increase in stream surface area was equally divided between longitudinal and lateral expansion. Even so, the median stream width widens on average with increasing runoff, suggesting that longitudinal and lateral expansion affect the distribution of stream width differently. We find that the form of the relationship between stream width and runoff is a power law, which can be used to refine models for surface area estimation

MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset

High-resolution raster hydrography maps are a fundamental data source for many geoscience applications. Here we introduce MERIT Hydro, a new global flow direction map at 3-arc sec resolution (~90 m at the equator) derived from the latest elevation data (MERIT DEM) and water body data sets (G1WBM, Global Surface Water Occurrence, and OpenStreetMap). We developed a new algorithm to extract river networks near automatically by separating actual inland basins from dummy depressions caused by the errors in input elevation data. After a minimum amount of hand editing, the constructed hydrography map shows good agreement with existing quality-controlled river network data sets in terms of flow accumulation area and river basin shape. The location of river streamlines was realistically aligned with existing satellite-based global river channel data. Relative error in the drainage area was <0.05 for 90% of Global Runoff Data Center (GRDC) gauges, confirming the accuracy of the delineated global river networks. Discrepancies in flow accumulation area were found mostly in arid river basins containing depressions that are occasionally connected at high water levels and thus resulting in uncertain watershed boundaries. MERIT Hydro improves on existing global hydrography data sets in terms of spatial coverage (between N90 and S60) and representation of small streams, mainly due to increased availability of high-quality baseline geospatial data sets. The new flow direction and flow accumulation maps, along with accompanying supplementary layers on hydrologically adjusted elevation and channel width, will advance geoscience studies related to river hydrology at both global and local scales

On merging the fields of neural networks and adaptive data structures to yield new pattern recognition methodologies

The aim of this talk is to explain a pioneering exploratory research endeavour that attempts to merge two completely different fields in Computer Science so as to yield very fascinating results. These are the well-established fields of Neural Networks (NNs) and Adaptive Data Structures (ADS) respectively. The field of NNs deals with the training and learning capabilities of a large number of neurons, each possessing minimal computational properties. On the other hand, the field of ADS concerns designing, implementing and analyzing data structures which adaptively change with time so as to optimize some access criteria. In this talk, we shall demonstrate how these fields can be merged, so that the neural elements are themselves linked together using a data structure. This structure can be a singly-linked or doubly-linked list, or even a Binary Search Tree (BST). While the results themselves are quite generic, in particular, we shall, as a prima facie case, present the results in which a Self-Organizing Map (SOM) with an underlying BST structure can be adaptively re-structured using conditional rotations. These rotations on the nodes of the tree are local and are performed in constant time, guaranteeing a decrease in the Weighted Path Length of the entire tree. As a result, the algorithm, referred to as the Tree-based Topology-Oriented SOM with Conditional Rotations (TTO-CONROT), converges in such a manner that the neurons are ultimately placed in the input space so as to represent its stochastic distribution. Besides, the neighborhood properties of the neurons suit the best BST that represents the data

Global Relationships Between River Width, Slope, Catchment Area, Meander Wavelength, Sinuosity, and Discharge

Using river centerlines created with Landsat images and the Shuttle Radar Topography Mission digital elevation model, we created spatially continuous maps of mean annual flow river width, slope, meander wavelength, sinuosity, and catchment area for all rivers wider than 90 m located between 60°N and 56°S. We analyzed the distributions of these properties, identified their typical ranges, and explored relationships between river planform and slope. We found width to be directly associated with the magnitude of meander wavelength and catchment area. Moreover, we found that narrower rivers show a larger range of slope and sinuosity values than wider rivers. Finally, by comparing simulated discharge from a water balance model with measured widths, we show that power laws between mean annual discharge and width can predict width typically to −35% to +81%, even when a single relationship is applied across all rivers with discharge ranging from 100 to 50,000 m3/s

Microscopic theories of neutrino-^{12}C reactions

In view of the recent experiments on neutrino oscillations performed by the LSND and KARMEN collaborations as well as of future experiments, we present new theoretical results of the flux averaged $^{12}C(\nu_e,e^-)^{12}N$ and $^{12}C(\nu_{\mu},{\mu}^-)^{12}N$ cross sections. The approaches used are charge-exchange RPA, charge-exchange RPA among quasi-particles (QRPA) and the Shell Model. With a large-scale shell model calculation the exclusive cross sections are in nice agreement with the experimental values for both reactions. The inclusive cross section for $\nu_{\mu}$ coming from the decay-in-flight of $\pi^+$ is $15.2 \times 10^{-40} cm^2$ to be compared to the experimental value of $12.4 \pm 0.3 \pm 1.8 \times 10^{-40} cm^2$, while the one due to $\nu_{e}$ coming from the decay-at-rest of $\mu^+$ is $16.4 \times 10^{-42} cm^2$ which agrees within experimental error bars with the measured values. The shell model prediction for the decay-in-flight neutrino cross section is reduced compared to the RPA one. This is mainly due to the different kind of correlations taken into account in the calculation of the spin modes and partially due to the shell-model configuration basis which is not large enough, as we show using arguments based on sum-rules.Comment: 17 pages, latex, 5 figure