Evaluation of ECMWF medium-range ensemble forecasts of precipitation for river basins

Providing probabilistic forecasts using Ensemble Prediction Systems has become increasingly popular in both the meteorological and hydrological communities. Compared to conventional deterministic forecasts, probabilistic forecasts may provide more reliable forecasts of a few hours to a number of days ahead, and hence are regarded as better tools for taking uncertainties into consideration and hedging against weather risks. It is essential to evaluate performance of raw ensemble forecasts and their potential values in forecasting extreme hydro-meteorological events. This study evaluates ECMWF's medium-range ensemble forecasts of precipitation over the period 1 January 2008 to 30 September 2012 on a selected midlatitude large-scale river basin, the Huai river basin (ca. 270 000 km2) in central-east China. The evaluation unit is sub-basin in order to consider forecast performance in a hydrologically relevant way. The study finds that forecast performance varies with sub-basin properties, between flooding and non-flooding seasons, and with the forecast properties of aggregated time steps and lead times. Although the study does not evaluate any hydrological applications of the ensemble precipitation forecasts, its results have direct implications in hydrological forecasts should these ensemble precipitation forecasts be employed in hydrology

Identification of Trypanosome Proteins in Plasma from African Sleeping Sickness Patients Infected with T. b. rhodesiense

Control of human African sleeping sickness, caused by subspecies of the protozoan parasite Trypanosoma brucei, is based on preventing transmission by elimination of the tsetse vector and by active diagnostic screening and treatment of infected patients. To identify trypanosome proteins that have potential as biomarkers for detection and monitoring of African sleeping sickness, we have used a ‘deep-mining” proteomics approach to identify trypanosome proteins in human plasma. Abundant human plasma proteins were removed by immunodepletion. Depleted plasma samples were then digested to peptides with trypsin, fractionated by basic reversed phase and each fraction analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This sample processing and analysis method enabled identification of low levels of trypanosome proteins in pooled plasma from late stage sleeping sickness patients infected with Trypanosoma brucei rhodesiense. A total of 254 trypanosome proteins were confidently identified. Many of the parasite proteins identified were of unknown function, although metabolic enzymes, chaperones, proteases and ubiquitin-related/acting proteins were found. This approach to the identification of conserved, soluble trypanosome proteins in human plasma offers a possible route to improved disease diagnosis and monitoring, since these molecules are potential biomarkers for the development of a new generation of antigen-detection assays. The combined immuno-depletion/mass spectrometric approach can be applied to a variety of infectious diseases for unbiased biomarker identification

Transcriptomes of <i>Trypanosoma brucei</i> rhodesiense from sleeping sickness patients, rodents and culture:Effects of strain, growth conditions and RNA preparation methods

All of our current knowledge of African trypanosome metabolism is based on results from trypanosomes grown in culture or in rodents. Drugs against sleeping sickness must however treat trypanosomes in humans. We here compare the transcriptomes of Trypanosoma brucei rhodesiense from the blood and cerebrospinal fluid of human patients with those of trypanosomes from culture and rodents. The data were aligned and analysed using new user-friendly applications designed for Kinetoplastid RNA-Seq data. The transcriptomes of trypanosomes from human blood and cerebrospinal fluid did not predict major metabolic differences that might affect drug susceptibility. Usefully, there were relatively few differences between the transcriptomes of trypanosomes from patients and those of similar trypanosomes grown in rats. Transcriptomes of monomorphic laboratory-adapted parasites grown in in vitro culture closely resembled those of the human parasites, but some differences were seen. In poly(A)-selected mRNA transcriptomes, mRNAs encoding some protein kinases and RNA-binding proteins were under-represented relative to mRNA that had not been poly(A) selected; further investigation revealed that the selection tends to result in loss of longer mRNAs

Diversity of Global Rice Markets and the Science Required for Consumer-Targeted Rice Breeding

With the ever-increasing global demand for high quality rice in both local production regions and with Western consumers, we have a strong desire to understand better the importance of the different traits that make up the quality of the rice grain and obtain a full picture of rice quality demographics. Rice is by no means a ‘one size fits all’ crop. Regional preferences are not only striking, they drive the market and hence are of major economic importance in any rice breeding / improvement strategy. In this analysis, we have engaged local experts across the world to perform a full assessment of all the major rice quality trait characteristics and importantly, to determine how these are combined in the most preferred varieties for each of their regions. Physical as well as biochemical characteristics have been monitored and this has resulted in the identification of no less than 18 quality trait combinations. This complexity immediately reveals the extent of the specificity of consumer preference. Nevertheless, further assessment of these combinations at the variety level reveals that several groups still comprise varieties which consumers can readily identify as being different. This emphasises the shortcomings in the current tools we have available to assess rice quality and raises the issue of how we might correct for this in the future. Only with additional tools and research will we be able to define directed strategies for rice breeding which are able to combine important agronomic features with the demands of local consumers for specific quality attributes and hence, design new, improved crop varieties which will be awarded success in the global market

Fuzzy logic based de-noising of ultrasound signals from non-destructive testing

The paper reports on different methods of ultrasound signal de-noising. The reduction of noise is especially important for the evaluation of ultrasound transmission measurements in highly damping materials such as wood and glued laminated timber (glulam). In order to enable a reliable identification of characteristic signal parameters (such as time-of-flight or first amplitude) the poor signal to noise ratios (SNR) of ultrasound signals have to be improved by filtering methods. Conventional methods such as multiple signals averaging are used at the expense of huge data requirement, time consuming measurement procedures and signal processing. As an alternative approach in this paper a fuzzy logic based adaptive filter is applied for de-nosing in an attempt to use a lower number of experiments, i.e. to minimize data requirements. The results are compared to those of the conventional multiple signal averaging and of a moving average filter. Preliminary results demonstrate the feasibility of the application of the fuzzy filter and clearly illustrate its advantages as well as shortcomings over the conventional approach. The presented approach is one step towards the goal of real-time nondestructive testing (NDT) inspection of glulam beams by means of ultrasound methods

Flood inundation dynamics and socioeconomic vulnerability under environmental change

Floods are a major threat to human existence and historically have both caused the collapse of civilizations and forced the emergence of new cultures. The physical processes of flooding are complex. Increased population, climate variability, change in catchment and channel management, modified landuse and land cover, and natural change of floodplains and river channels all lead to changes in flood dynamics, and as a direct or indirect consequence, social welfare of humans. Section 5.16.1 explores the risks and benefits brought about by floods and reviews the responses of floods and floodplains to climate and landuse change. Section 5.08.2 reviews the existing modeling tools, and the top–down and bottom–up modeling frameworks that are used to assess impacts on future floods. Section 5.08.3 discusses changing flood risk and socioeconomic vulnerability based on current trends in emerging or developing countries and presents an alternative paradigm as a pathway to resilience. Section 5.08.4 concludes the chapter by stating a portfolio of integrated concepts, measures, and avant-garde thinking that would be required to sustainably manage future flood risk

Coupling ensemble weather predictions based on TIGGE database with Grid-Zinanjiang model for flood forecast

The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for flood forecast. The Grid-Xinanjiang distributed hydrological model, which is based on the Xinanjiang model theory and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the Grid-Xinanjiang model and the TIGGE database gives a promising tool for an early warning of flood events several days ahead

Risks associated with global warming of 1.5 to 4°C above pre-industrial levels in human and natural systems in six countries

The Topical Collection “Accrual of Climate Change Risk in Six Vulnerable Countries” provides a harmonised assessment of risks to human and natural systems due to global warming of 1.5–4 °C in six countries (China, Brazil, Egypt, Ethiopia, Ghana, and India) using a consistent set of climate change and socioeconomic scenarios. It compares risks in 2100 if warming has reached 3 °C, broadly corresponding to current global greenhouse gas emission reduction policies, including countries’ National Determined Contributions, rather than the Paris Agreement goal of limiting warming to ‘well below’ 2 °C and ‘pursuing efforts’ to limit to 1.5 °C. Global population is assumed either constant at year 2000 levels or to increase to 9.2 billion by 2100. In either case, greater warming is projected to lead, in all six countries, to greater exposure of land and people to drought and fluvial flood hazard, greater declines in biodiversity, and greater reductions in the yield of maize and wheat. Limiting global warming to 1.5 °C, compared with ~ 3 °C, is projected to deliver large benefits for all six countries, including reduced economic damages due to fluvial flooding. The greatest projected benefits are the avoidance of a large increase in exposure of agricultural land to severe drought, which is 61%, 43%, 18%, and 21% lower in Ethiopia, China, Ghana, and India at 1.5 °C than at 3 °C, whilst avoided increases in human exposure to severe drought are 20–80% lower at 1.5 °C than 3 °C across the six countries. Climate refugia for plants are largely preserved at 1.5 °C warming in Ghana, China, and Ethiopia, but refugia shrink in areal extent by a factor of 2, 3, 3, 4, and 10 in Ghana, China, India, Ethiopia, and Brazil, respectively, if warming reaches 3 °C. Economic damages associated with sea-level rise are projected to increase in coastal nations, but more slowly if warming were limited to 1.5 °C. Actual benefits on the ground will also depend on national and local contexts and the extent of future investment in adaptation.</p

Inorganic arsenic sorption by drinking-water treatment residual-amended sandy soil: effect of soil solution chemistry

Previous studies in our laboratory have demonstrated that drinking-water treatment residuals are effective sorbents of arsenic V. However, the effect of soil solution chemistry on arsenic V sorption by drinking-water treatment residuals-amended soils remains to be explored. The current study uses a batch incubation experimental set up to evaluate the effect of soil solution pH, competing ligands, and complexing metal on arsenic V sorption by a sandy soil (Immokalee series) amended with two rates (25 and 50 g kg-1) of aluminum and iron-based drinking-water treatment residuals. Experiments were conducted at three initial arsenic loads (125, 1,875, 3,750 mg kg-1) and a constant solid: solution ratio of 200 g L-1. An optimum equilibration time of 8 days, obtained from kinetic studies, was utilized for sorption experiments with both aluminum and iron drinking-water treatment residual-amended soil. Presence of phosphate decreased arsenic V sorption by both aluminum and iron drinking-water treatment residual amended soils, with a strong dependence on pH, drinking-water treatment residual types, drinking-water treatment residual application rates, and phosphate concentrations. Addition of sulfate had no effect on arsenic V sorption by aluminum or iron drinking-water treatment residual-amended soil. A complementing effect of calcium on arsenic V sorption was observed at higher pH. Results elucidating the effect of soil solution chemistry on the arsenic V sorption will be helpful in calibrating drinking-water treatment residual as a sorbent for remediation of arsenic-contaminated soils