The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems

Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models

This paper investigates the challenge of representing structural differences in river channel cross-section geometry for regional to global scale river hydraulic models and the effect this can have on simulations of wave dynamics. Classically, channel geometry is defined using data, yet at larger scales the necessary information and model structures do not exist to take this approach. We therefore propose a fundamentally different approach where the structural uncertainty in channel geometry is represented using a simple parameterization, which could then be estimated through calibration or data assimilation. This paper first outlines the development of a computationally efficient numerical scheme to represent generalised channel shapes using a single parameter, which is then validated using a simple straight channel test case and shown to predict wetted perimeter to within 2% for the channels tested. An application to the River Severn, UK is also presented, along with an analysis of model sensitivity to channel shape, depth and friction. The channel shape parameter was shown to improve model simulations of river level, particularly for more physically plausible channel roughness and depth parameter ranges. Calibrating channel Manning’s coefficient in a rectangular channel provided similar water level simulation accuracy in terms of Nash-Sutcliffe efficiency to a model where friction and shape or depth were calibrated. However, the calibrated Manning coefficient in the rectangular channel model was ~2/3 greater than the likely physically realistic value for this reach and this erroneously slowed wave propagation times through the reach by several hours. Therefore, for large scale models applied in data sparse areas, calibrating channel depth and/or shape may be preferable to assuming a rectangular geometry and calibrating friction alone

Age, extent and carbon storage of the central Congo Basin peatland complex

Peatlands are carbon-rich ecosystems that cover just three per cent of Earth's land surface, but store one-third of soil carbon. Peat soils are formed by the build-up of partially decomposed organic matter under waterlogged anoxic conditions. Most peat is found in cool climatic regions where unimpeded decomposition is slower, but deposits are also found under some tropical swamp forests. Here we present field measurements from one of the world's most extensive regions of swamp forest, the Cuvette Centrale depression in the central Congo Basin. We find extensive peat deposits beneath the swamp forest vegetation (peat defined as material with an organic matter content of at least 65 per cent to a depth of at least 0.3 metres). Radiocarbon dates indicate that peat began accumulating from about 10,600 years ago, coincident with the onset of more humid conditions in central Africa at the beginning of the Holocene. The peatlands occupy large interfluvial basins, and seem to be largely rain-fed and ombrotrophic-like (of low nutrient status) systems. Although the peat layer is relatively shallow (with a maximum depth of 5.9 metres and a median depth of 2.0 metres), by combining in situ and remotely sensed data, we estimate the area of peat to be approximately 145,500 square kilometres (95 per cent confidence interval of 131,900-156,400 square kilometres), making the Cuvette Centrale the most extensive peatland complex in the tropics. This area is more than five times the maximum possible area reported for the Congo Basin in a recent synthesis of pantropical peat extent. We estimate that the peatlands store approximately 30.6 petagrams (30.6 × 10(15) grams) of carbon belowground (95 per cent confidence interval of 6.3-46.8 petagrams of carbon)-a quantity that is similar to the above-ground carbon stocks of the tropical forests of the entire Congo Basin. Our result for the Cuvette Centrale increases the best estimate of global tropical peatland carbon stocks by 36 per cent, to 104.7 petagrams of carbon (minimum estimate of 69.6 petagrams of carbon; maximum estimate of 129.8 petagrams of carbon). This stored carbon is vulnerable to land-use change and any future reduction in precipitation

[3H]Adenine is a suitable radioligand for the labeling of G protein-coupled adenine receptors but shows high affinity to bacterial contaminations in buffer solutions

[3H]Adenine has previously been used to label the newly discovered G protein-coupled murine adenine receptors. Recent reports have questioned the suitability of [3H]adenine for adenine receptor binding studies because of curious results, e.g. high specific binding even in the absence of mammalian protein. In this study, we showed that specific [3H]adenine binding to various mammalian membrane preparations increased linearly with protein concentration. Furthermore, we found that Tris-buffer solutions typically used for radioligand binding studies (50 mM, pH 7.4) that have not been freshly prepared but stored at 4°C for some time may contain bacterial contaminations that exhibit high affinity binding for [3H]adenine. Specific binding is abolished by heating the contaminated buffer or filtering it through 0.2-μm filters. Three different, aerobic, gram-negative bacteria were isolated from a contaminated buffer solution and identified as Achromobacter xylosoxidans, A. denitrificans, and Acinetobacter lwoffii. A. xylosoxidans, a common bacterium that can cause nosocomial infections, showed a particularly high affinity for [3H]adenine in the low nanomolar range. Structure–activity relationships revealed that hypoxanthine also bound with high affinity to A. xylosoxidans, whereas other nucleobases (uracil, xanthine) and nucleosides (adenosine, uridine) did not. The nature of the labeled site in bacteria is not known, but preliminary results indicate that it may be a high-affinity purine transporter. We conclude that [3H]adenine is a well-suitable radioligand for adenine receptor binding studies but that bacterial contamination of the employed buffer solutions must be avoided

Ecomorphological correlates of twenty dominant fish species of Amazonian floodplain lakes

Fishes inhabiting Amazonian floodplain lakes exhibits a great variety of body shape, which was a key advantage to colonize the several habitats that compose these areas adjacent to the large Amazon rivers. In this paper, we did an ecomorphological analysis of twenty abundant species, sampled in May and August 2011, into two floodplain lakes of the lower stretch of the Solimões River. The analysis detected differences among species, which could be probably associated with swimming ability and habitat use preferences. © 2017, Instituto Internacional de Ecologia. All rights reserved

Controls on Eurasian coastal sea ice formation, melt onset and decay from ERS scatterometry: Regional contrasts and effects of river influx

Regional and local patterns in the formation, melt onset and disappearance of coastal first-year sea ice (FYI) are observed in the Eurasian Arctic using the C-band (5.3 GHz) European Remote Sensing Satellite (ERS) radar scatterometers. Near-daily time-series (1991-1999) of the radar backscatter coefficient normalized to an incident angle of 40° (σ040) and the backscatter-incident angle relationship (B) are examined for test sites near the Severnaya Dvina, Mezen, Pechora, Ob\u27, Yenisci, Khatanga, Lena, Indigirka and Kolyma rivers. Melt onset of the sea ice surface is associated with abrupt changes in σ040, with values converging towards ∼ -17 dB. As such, whether backscatter increases or decreases at melt onset is largely determined by contrast with pre-melt backscatter levels. The presence or absence of FYI is designated from low or high values of B, respectively, whereas the addition of an anisotropy criterion further improves discrimination of FYI from open water. A strong regional pattern is seen in the daily temporal variability of both melt onset and ice cover, with maximum variability in the Barents and Kara seas and decreasing variability eastward. Similarly, significant contrasts in the seasonal duration of ice cover are found between western and eastern sites. Seasonal ice cover persists ∼ 144 days for sites in the Barents Sea, but ∼ 293 days for sites farther east in the East Siberian Sea. We speculate that our observed west-east contrasts are due to North Atlantic modulation of salinity, air temperature and cyclone density. Rivers also exert a local effect on ice cover, causing earlier formation (∼ 4 days) and earlier disappearance (∼ 17 days) near river mouths. The hydrological influence of rivers is potentially strong in the Kara, Laptev and East Siberian seas, but weak or absent in the Barents Sea