Overbank block-and-ash flow deposits and the impact of valley-derived, unconfined flows on populated areas at Merapi volcano, Java, Indonesia

Merapi, an andesitic volcanic complex in Central Java, is one of the most frequently erupting volcanoes in Indonesia and poses a permanent threat to the surrounding population of over 1 million people. With frequently recurring volcanic activity, the sixty or so reported eruptions since the mid-1500s have caused ~7,000 fatalities and destroyed numerous villages in the region. In June 2006, an eruption affected the densely populated area on the volcano’s southern and south-eastern flanks for the first time in almost a century. The resultant block-and-ash flows (BAFs) travelled down an incised river valley (Kali Gendol) to a distance of 7 km from the source, breaking out of the main channel at four main locations. Unconfined (overbank) BAFs were generated, which covered the interfluve regions on either side of the main valley and buried buildings and other infrastructure features in the village of Kaliadem, situated on the western bank of the Gendol valley ~5 km from the summit of Merapi. Using traditional volcanological field-based methods and non-invasive, high-resolution ground-penetrating radar techniques, the morphology and internal architecture of these overbank deposits were studied in detail in order to evaluate the destructive impact of these flows in a local context. The results show that complex, local-scale variations in flow dynamics and deposit architectures are apparent and that BAFs are capable of transporting significant numbers of large blocks (>1–2 m) out of the valley confines. We propose a conceptual model for the escape of these channelised BAFs onto the interfluvial terrace at Kaliadem and show, through a stratigraphic analysis of the pyroclastic successions underlying the village and adjacent areas on the volcano’s southern flank, that the area has been affected repeatedly by overbank BAFs and explosive eruptions over the past few 100 years (and more).     

The Sensitivity of Australian Fire Danger to Climate Change

Global climate change, such as that due to the proposed enhanced greenhouseeffect, is likely tohave a significant effect on biosphere-atmosphere interactions, includingbushfire regimes. Thisstudy quantifies the possible impact of climate change on fire regimes byestimating changes infire weather and the McArthur Forest Fire Danger Index (FDI), an index thatis used throughoutAustralia to estimate fire danger. The CSIRO 9-level general circulation model(CSIRO9 GCM)is used to simulate daily and seasonal fire danger for the present Australianclimate and for adoubled-CO₂ climate. The impact assessment includes validation ofthe GCMs daily controlsimulation and the derivation of correction factors which improve theaccuracy of the firedanger simulation. In summary, the general impact of doubled-CO₂is to increase firedanger at all sites by increasing the number of days of very high and extremefire danger.Seasonal fire danger responds most to the large CO₂-induced changesin maximumtemperature.     

Relative effects of multi-decadal climatic variability and changes in the mean and variability of climate due to global warming: future streamflows in Britain

Climate change impact assessments conventionally assess just the implications of a change in mean climate due to global warming. This paper compares such effects of such changes with those due to natural multi-decadal variability, and also explores the effects of changing the year-to-year variability in climate as well as the mean. It estimates changes in mean monthly flows and a measure of low flow (the flow exceeded 95% of the time) in six catchments in Britain, using the UKCIP98 climate change scenarios and a calibrated hydrological model. Human-induced climate change has a different seasonal effect on flows than natural multi-decadal variability (an increase in winter and decrease in summer), and by the 2050s the climate change signal is apparent in winter and, in lowland Britain, in summer. Superimposing natural multi-decadal variability onto the human-induced climate change increases substantially the range in possible future streamflows (in some instances counteracting the climate change signal), with important implications for the development of adaptation strategies. Increased year-to-year variability in climate leads to slight increases in mean monthly flows (relative to changes due just to changes in mean climate), and slightly greater decreases in low flows. The greatest effect on low flows occurs in upland catchments.     

Internal structure of mixed-sand-and-gravel beach deposits revealed using ground-penetrating radar

ABSTRACT Mixed‐sand‐and‐gravel beaches are a distinctive type of coarse‐clastic beach. Ground‐penetrating radar (GPR) and photographic records of previous excavations are used to investigate the stratigraphy and internal sedimentary structure of mixed‐beach deposits at Aldeburgh in Suffolk, south‐east England. The principles of radar stratigraphy are used to describe and interpret migrated radar reflection profiles obtained from the study site. The application of radar stratigraphy allows the delineation of both bounding surfaces (radar surfaces) and the intervening beds or bed sets (radar facies). The deposits of the main backshore berm ridge consist of seaward‐dipping bounding surfaces that are gently onlapped by seaward‐dipping bed sets. Good correspondence is observed between a sequence of beach profiles, which record development of the berm ridge on the backshore, and the berm ridge's internal structure. The beach‐profile data also indicate that backshore berm ridges at Aldeburgh owe their origin to discrete depositional episodes related to storm‐wave activity. Beach‐ridge plain deposits at the study site consist of a complex, progradational sequence of foreshore, berm‐ridge, overtop and overwash deposits. Relict berm‐ridge deposits, separated by seaward‐dipping bounding surfaces, form the main depositional element beneath the beach‐ridge plain. However, the beach ridges themselves are formed predominantly of vertically stacked overtop/overwash units, which lie above the berm‐ridge deposits. Consequently, beach‐ridge development in this progradational, mixed‐beach setting must have occurred when conditions favoured overtopping and overwashing of the upper beachface. Interannual to decadal variations in wave climate, antecedent beach morphology, shoreline progradation rate and sea level are identified as the likely controlling factors in the development of such suitable conditions.     

The variable impact of ENSO events on regional dengue/DHF in Indonesia

Although studies have demonstrated significant associations between ENSO events and dengue fever, few have explored regional impacts on dengue fever of separate events. This study explores the impacts of two ENSO events on regional patterns of dengue/ dengue haemorrhagic fever (DHF) incidence in Indonesia. Data consist of monthly cases of dengue/DHF from 1992 to 2001 for each of Indonesia's 27 provinces, and monthly figures for rainfall, rainfall anomalies, temperature, relative humidity and the Southern Oscillation Index (SOI). We conducted Pearson correlation analyses for each independent variable against dengue/DHF incidence, using a direct month‐by‐month correlation and applying a lag of between one and six months to each variable with respect to dengue/DHF incidence. Based on the SOI value, we identified two ENSO events between 1992 and 2001. To explore each event, we created two dummy variables and in regression analyses for eight provinces. The variance of between 12.9 per cent and 24.5 per cent in provincial dengue/DHF incidence is explained by two or three climate variables in each of the provinces (p < 0.01 to 0.1). During the 1997/98 event, the explained variance increased by between 7 per cent and 15 per cent in provinces whose climate regimes were most affected by this event. This study demonstrates that indicators of ENSO such as the SOI may assist in the forecast of potential dengue/DHF incidence and distribution in Indonesia.     

Characterizing and Predicting Traffic Accidents in Extreme Weather Environments

Motorists are vulnerable to extreme weather events, which are likely to be exacerbated by climate change throughout the world. Traffic accidents are conceptualized in this article as the result of a systemic failure that includes human, vehicular, and environmental factors. The snowstorm and concurrent accidents that occurred in the Northeastern United States on 26 January 2011 are used as a case study. Traffic accident data for Fairfax County, Virginia, are supplemented with Doppler radar and additional weather data to characterize the spatiotemporal patterns of the accidents resulting from this major snowstorm event. A kernel density smoothing method is implemented to identify and predict patterns of accident locations within this urban area over time. The predictive capability of this model increases over time with increasing accidents. Models such as these can be used by emergency responders to identify, plan for, and mitigate areas that are more susceptible to increased risk resulting from extreme weather events.     

Non-classificatory analysis and representation of heathland vegetation from remotely sensed imagery

Remotely sensed imagery are an attractive source of data for vegetation mapping. Conventional image classification routines used to produce thematic maps from remotely sensed imagery rely on a one-pixel-one-class approach and generate discrete thematic units. Where the environmental phenomena to be mapped exhibit gradients such a representation is inappropriate. This paper discusses the representation of semi-natural vegetation, drawing on examples of heathland vegetation that lie along continua. Two alternative approaches to the representation of heathland vegetation are examined, both of which aim to model the continuous character of the vegetation with measures of the strength of membership to discrete classes, namely probabilities of class membership from a maximum likelihood classification and fuzzy membership functions from the fuzzy c-means algorithm. Since both approaches imply partial class membership they can be considered as non-classificatory, even though the measures of the strength of class membership may be derived from classification routines. The measures of class membership generated from both approaches were found to be significantly correlated to the variations in heathland composition along a transect which graded from dry heath to wet heath/bog. Furthermore for cases drawn from the class end-points both approaches were able to discriminate class membership accurately.