A comparison of MODIS and NOHRSC snow‐cover products for simulating streamflow using the Snowmelt Runoff Model

Remote sensing is an important source of snow‐cover extent for input into the Snowmelt Runoff Model (SRM) and other snowmelt models. Since February 2000, daily global snow‐cover maps have been produced from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS). The usefulness of this snow‐cover product for streamflow prediction is assessed by comparing SRM simulated streamflow using the MODIS snow‐cover product with streamflow simulated using snow maps from the National Operational Hydrologic Remote Sensing Center (NOHRSC). Simulations were conducted for two tributary watersheds of the Upper Rio Grande basin during the 2001 snowmelt season using representative SRM parameter values. Snow depletion curves developed from MODIS and NOHRSC snow maps were generally comparable in both watersheds: satisfactory streamflow simulations were obtained using both snow‐cover products in larger watershed (volume difference: MODIS, 2·6%; NOHRSC, 14·0%) and less satisfactory streamflow simulations in smaller watershed (volume difference: MODIS, −33·1%; NOHRSC, −18·6%). The snow water equivalent (SWE) on 1 April in the third zone of each basin was computed using the modified depletion curve produced by the SRM and was compared with in situ SWE measured at Snowpack Telemetry sites located in the third zone of each basin. The SRM‐calculated SWEs using both snow products agree with the measured SWEs in both watersheds. Based on these results, the MODIS snow‐cover product appears to be of sufficient quality for streamflow prediction using the SRM in the snowmelt‐dominated basins. Copyright © 2005 John Wiley & Sons, Ltd.     

A top–down soil moisture and sap flux sampling design of a rain–snow transition mountain watershed

This paper presents a top–down approach for soil moisture and sap flux sampling design with the goal of understanding ecohydrologic response to interannual climate variation in the rain–snow transition watersheds. The design is based on a priori estimates of soil moisture and transpiration patterns using a physical distributed model, Regional Hydro‐Ecologic Simulation System (RHESSys). RHESSys was initially calibrated with existing snow depth and streamflow data. Calibrated model estimates of seasonal trajectories of snowmelt, root‐zone soil moisture storage, and transpiration were used to develop five hydrologic similarity indicators and map these at (30 m) patch scale across the study watershed. The partitioning around medoids‐clustering algorithm was then used to define six distinctive spatially explicit clusters based on the five hydrologic similarity indictors. A representative site within each cluster was identified for sampling. For each site, soil moisture sensors were installed at the 30‐ and 90‐cm depths and at the five soil pits and a sap flux sensor at the averaged‐size white fir tree for each site. The model‐based cluster analysis suggests that the elevation gradient and topographically driven flow drainage patterns are the dominant drivers of spatial patterns of soil moisture and transpiration. The comparison of model‐based calculated hydrological similarity indicators with measured‐data‐based values shows that spatial patterns of field‐sampled soil moisture data typically fell within uncertainty bounds of model‐based estimates for each cluster. There were however several notable exceptions. The model failed to capture the soil moisture and sap flux dynamics in a riparian zone site and in a site where lateral subsurface flow may not follow surface topography. Results highlight the utility of using a hypothesis driven sampling strategy, based on a physically based model, for efficiently providing new information that can drive both future measurements and strategic refinements to model inputs, parameters, or structure that might reduce these errors. Future research will focus on strategies for using of finer scale representations of microclimate, topography, vegetation, and soil properties to improve models.     

Sensitivity of nitrate concentration-discharge patterns to soil nitrate distribution and drainage properties in the vertical dimension

We propose a conceptual model that examines the ‘variable source area’ (VSA) and ‘nitrate flushing’ hypothesis in the vertical direction, and use this approach to explain nitrate concentration–discharge relationships in a semi-arid watershed. We use an eco-hydrology simulation model (RHESSys) to show that small changes in the vertical distribution of nitrate mass and their interaction with soil hydraulic conductivity can result in abrupt changes in the nitrate concentration–discharge relationship. We show that the estimated concentration–discharge relationship is sensitive to the parameters governing soil vertical nitrate distribution and soil hydraulic conductivity, at both patch scale and watershed scale, where lateral redistribution of water and nitrate is also accounted for. Given heterogeneity in nitrogen inputs, uptake processes, soil drainage and storage processes, substantial variation in parameters that describe rate of changes in vertical distribution of soil nitrate and hydraulic properties is likely both within and between watersheds. Thus, we argue that vertical ‘variable source area’ processes may be as important as lateral VSA in determining concentration discharge relationships.     

Multiple P–T–d–t paths reveal the evolution of the final Nuna assembly in northeast Australia

The final assembly of the Mesoproterozoic supercontinent Nuna was marked by the collision of Laurentia and Australia at 1.60 Ga, which is recorded in the Georgetown Inlier of NE Australia. Here, we decipher the metamorphic evolution of this final Nuna collisional event using petrostructural analysis, major and trace element compositions of key minerals, thermodynamic modelling, and multi-method geochronology. The Georgetown Inlier is characterised by deformed and metamorphosed 1.70–1.62 Ga sedimentary and mafic rocks, which were intruded by c. 1.56 Ga old S-type granites. Garnet Lu–Hf and monazite U–Pb isotopic analyses distinguish two major metamorphic events (M1 at c. 1.60 Ga and M2 at c. 1.55 Ga), which allows at least two composite fabrics to be identified at the regional scale—c. 1.60 Ga S1 (consisting in fabrics S1a and S1b) and c. 1.55 Ga S2 (including fabrics S2a and S2b). Also, three tectono-metamorphic domains are distinguished: (a) the western domain, with S1 defined by low-P (LP) greenschist facies assemblages; (b) the central domain, where S1 fabric is preserved as medium-P (MP) amphibolite facies relicts, and locally as inclusion trails in garnet wrapped by the regionally dominant low-P amphibolite facies S2 fabric; and (c) the eastern domain dominated by upper amphibolite to granulite facies S2 foliation. In the central domain, 1.60 Ga MP–medium-T (MT) metamorphism (M1) developed within the staurolite–garnet stability field, with conditions ranging from 530–550°C at 6–7 kbar (garnet cores) to 620–650°C at 8–9 kbar (garnet rims), and it is associated with S1 fabric. The onset of 1.55 Ga LP–high-T (HT) metamorphism (M2) is marked by replacement of staurolite by andalusite (M2a/D2a), which was subsequently pseudomorphed by sillimanite (M2b/D2b) where granite and migmatite are abundant. P–T conditions ranged from 600 to 680°C and 4–6 kbar for the M2b sillimanite stage. 1.60 Ga garnet relicts within the S2 foliation highlight the progressive obliteration of the S1 fabric by regional S2 in the central zone during peak M2 metamorphism. In the eastern migmatitic complex, partial melting of paragneiss and amphibolite occurred syn- to post- S2, at 730–770°C and 6–8 kbar, and at 750–790°C and 6 kbar, respectively. The pressure–temperature–deformation–time paths reconstructed for the Georgetown Inlier suggest a c. 1.60 Ga M1/D1 event recorded under greenschist facies conditions in the western domain and under medium-P and medium-T conditions in the central domain. This event was followed by the regional 1.56–1.54 Ga low-P and high-T phase (M2/D2), extensively recorded in the central and eastern domains. Decompression between these two metamorphic events is ascribed to an episode of exhumation. The two-stage evolution supports the previous hypothesis that the Georgetown Inlier preserves continental collisional and subsequent thermal perturbation associated with granite emplacement.     

The resilience paradox: flooding experience,coping and climate change mitigation intentions

Climate change is projected to increase the frequency, intensity and unpredictability of extreme weather events across the globe and these events are likely to have significant mental health implications. The mental health literature broadly characterises negative emotional reactions to extreme weather experiences as undesirable impacts on wellbeing. Yet, other research in psychology suggests that negative emotional responses to extreme weather are an important motivation for personal action on climate change. This article addresses the intersection of mental health and functional perspectives on negative emotions, with a specific focus on the potential that reduced negative emotional responses to extreme weather may also translate to diminished motivation to undertake climate change mitigation actions – which we term the ‘resilience paradox’. Using survey data gathered in the aftermath of severe flooding across the UK in winter 2013/2014, we present new evidence indicating that self-appraised coping ability moderates the link between flooding experience and negative emotions and thereby attenuates the indirect link between flooding experience and climate change mitigation intentions. We conclude that support for flood victims should extend beyond addressing emotional, physical and financial stresses to include acknowledgement of the involvement of climate change and communication of the need for action to combat future climate risks.

Key policy insights

• Psychological resilience to flooding and other extreme weather events can translate to diminished motivation to mitigate climate change

• Negative emotional reactions need to occur at an optimal level to enable people to respond appropriately to climate risks.

• Flood victims’ subjective appraisal of their ability to cope does not necessarily encompass consideration of the role played by climate change. Therefore, support for victims of extreme weather should include explicit acknowledgement of the involvement of climate change and the need for action to mitigate future climate risks.

     

Stress Shadows Determined from a Phase Dynamical Measure of Historic Seismicity

The Pattern Informatics (PI) technique (tiampo et al., 2002) is founded on the premise that changes in the seismicity rate are a proxy for changes in the underlying stress. These stress changes are correlated over large spatial regions, and can be quantified using a phase dynamical analysis of the changes in historic seismicity rates. This new approach to the study of seismicity quantifies its local and regional space-time patterns and identifies regions of local quiescence or activation. Here we study those local changes in an attempt to objectively quantify short-term stress shadow regions. We determine that, while persistent stress shadows are detectable with this method, they do not occur uniformly throughout the spatio-temporal region.     

Acceleration of Relativistic Protons During the 20 January 2005 Flare and CME

The origin of relativistic solar protons during large flare/CME events has not been uniquely identified so far. We perform a detailed comparative analysis of the time profiles of relativistic protons detected by the worldwide network of neutron monitors at Earth with electromagnetic signatures of particle acceleration in the solar corona during the large particle event of 20 January 2005. The intensity – time profile of the relativistic protons derived from the neutron monitor data indicates two successive peaks. We show that microwave, hard X-ray, and γ-ray emissions display several episodes of particle acceleration within the impulsive flare phase. The first relativistic protons detected at Earth are accelerated together with relativistic electrons and with protons that produce pion-decay γ rays during the second episode. The second peak in the relativistic proton profile at Earth is accompanied by new signatures of particle acceleration in the corona within ≈1R _⊙ above the photosphere, revealed by hard X-ray and microwave emissions of low intensity and by the renewed radio emission of electron beams and of a coronal shock wave. We discuss the observations in terms of different scenarios of particle acceleration in the corona.     

GAUGE: the GrAnd Unification and Gravity Explorer

The GAUGE (GrAnd Unification and Gravity Explorer) mission proposes to use a drag-free spacecraft platform onto which a number of experiments are attached. They are designed to address a number of key issues at the interface between gravity and unification with the other forces of nature. The equivalence principle is to be probed with both a high-precision test using classical macroscopic test bodies, and, to lower precision, using microscopic test bodies via cold-atom interferometry. These two equivalence principle tests will explore string-dilaton theories and the effect of space–time fluctuations respectively. The macroscopic test bodies will also be used for intermediate-range inverse-square law and an axion-like spin-coupling search. The microscopic test bodies offer the prospect of extending the range of tests to also include short-range inverse-square law and spin-coupling measurements as well as looking for evidence of quantum decoherence due to space–time fluctuations at the Planck scale.     

Integrating knowledge to assess coastal vulnerability to sea-level rise: The development of the DIVA tool

This paper describes the development of the DIVA tool, a user-friendly tool for assessing coastal vulnerability from subnational to global levels. The development involved the two major challenges of integrating knowledge in the form of data, scenarios and models from various natural, social and engineering science disciplines and making this integrated knowledge accessible to a broad community of end-users. These challenges were addressed by (i) creating and applying the DIVA method, an iterative, modular method for developing integrating models amongst distributed partners and (ii) making the data, scenarios and integrated model, equipped with a powerful graphical user interface, directly and freely available to end-users.