Modelling and mass balance assessments of nutrient retention in a seasonally-flowing estuary (Swan River Estuary,Western Australia)

An integrated mass balance and modelling approach for analysis of estuarine nutrient fluxes is demonstrated in the Swan River Estuary, a microtidal system with strong hydrological dependence on seasonal river inflows. Mass balance components included estimation of gauged and ungauged inputs to the estuary and losses to the ocean (outflow and tidal exchange). Modelling components included estimation of atmospheric (N fixation, denitrification) and sediment–water column nutrient exchanges. Gross and net denitrification derived using two independent methods were significantly correlated (r² = 0.49, p < 0.01) with net rates averaging 40% of gross. Annual nitrogen (N) and phosphorus (P) loads from major tributaries were linearly correlated with annual freshwater discharge and were 3-fold higher in wet years than in dry years. Urban drains and groundwater contributed, on average, 26% of N inputs and 19% of P inputs, with higher relative contributions in years of low river discharge. Overall, ungauged inputs accounted for almost 35% of total nitrogen loads. For N, elevated loading in wet years was accompanied by large increases in outflow (7x) and tidal flushing (2x) losses and resulted in overall lower retention efficiency (31%) relative to dry years (70%). For P, tidal flushing losses were similar in wet and dry years, while outflow losses (4-fold higher) were comparable in magnitude to increases in loading. As a result, P retention within the estuary was not substantially affected by inter-annual variation in water and P loading (ca. 50% in all years). Sediment nutrient stores increased in most years (remineralisation efficiency ca. 50%), but sediment nutrient releases were significant and in some circumstances were a net source of nutrients to the water column.     

Sequence stratigraphy of the Mississippi fan (Plio-Pleistocene), Gulf of Mexico

The Mississippi Fan is a large, mud-dominated submarine fan over 4 km thick, deposited in the deep Gulf of Mexico during the late Pliocene and Pleistocene. Analysis of 19,000 km of multifold seismic data defined 17 seismic sequences, each characterized by channel, levee, and associated overbank deposits, as well as mass transport deposits. At the base of nine sequences are a series of seismic facies consisting of mounded, hummocky, chaotic, and subparallel reflections, which constitute 10–20% of the sediments in each the sequences. These facies are externally mounded and occur in two general regions of the fan: (1) in the upper and middle fan they are elongate in shape and mimic the channel's distribution; (2) in the middle fan to lower fan they are characterized by a fan-shaped distribution, increasing in width downfan. These facies are interpreted to have formed as disorganized slides, debris flows, and turbidites (informally called “mass transport complexes”). Overlying this basal interval, characteristic of all sequences, are well-developed channel-levee systems that constitute 80–90% of the fan's sediments. Channels consist of high amplitude, subparallel reflections, whereas the flanking levee sediments appear as subparallel reflections that have high amplitudes at the base changing upward to low amplitude. The vertical change in amplitude may reflect a decrease in grain size and bed thicknesses. Overbank sediments are characterized by interbedded subparallel to hummocky and mounded reflections, suggesting both turbidites from the channel, as well as slides and debris flows derived both locally and from the slope updip.     

International Silica Cycle Workshop held in Hangzhou

正Silicon is the second most abundant element on the planet Earth. Its electronic configuration is close to that of carbon, but the aqueous environment prevailing on our planet gives advantages to carbon compounds at the expenses of siliceous compounds.Silicified organisms, however, are everywhere on Earth, particularly in the marine realm where siliceous diatoms play a key role in the ocean biological carbon pump. Thus, a better understanding of the processes that control the silica cycle at global scale is crucial.     

A probabilistic methodology to estimate future coastal flood risk due to sea level rise

In this paper we present a methodology to estimate the probability of future coastal flooding given uncertainty over possible sea level rise. We take as an example the range of sea level rise magnitudes for 2100 contained in the IPCC Third Assessment Report [Church, J.A., Gregory, J.M., Huybrechts, P., Kuhn, M., Lambeck, K., Nhuan, M.T., Qin, D., Woodworth, P.L., Anisimov, O.A., Bryan, F.O., Cazenave, A., Dixon, K.W., Fitzharris, B.B., Flato, G.M., Ganopolski, A., Gornitz, V., Lowe, J.A., Noda, A., Oberhuber, J.M., O'Farrell, S.P., Ohmura, A., Oppenheimer, M., Peltier, W.R., Raper, S.C.B., Ritz, C., Russell, G.L., Schlosser, E., Shum, C.K., Stocker, T.F., Stouffer, R.J., van de Wal, R.S.W., Voss, R., Wiebe, E.C., Wild, M., Wingham, D.J. and Zwally, H.J., 2001. Changes in sea level. In Houghton, J.T. et al. (eds), Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom, 881pp.] and infer a plausible probability distribution for this range. We then use a Monte Carlo procedure to sample from this distribution and use the resulting values as an additional boundary forcing for a two-dimensional model of coastal inundation used to simulate a 1 in 200 year extreme water level event. This yields an ensemble of simulations for an event of this magnitude occurring in 2100, where each member represents a different possible scenario of sea level rise by this time. We then develop a methodology to approximate the probability of flooding in each model grid cell over the ensemble and by combining these hazards maps with maps of land use values (consequence) we are able to estimate spatial contributions to flood risk that can aid planning and investment decisions. The method is then applied to a 32 km section of the UK coast in Somerset, South-West England and used to estimate the monetary losses and risk due a 1 in 200 year recurrence interval event under: (a) current conditions; (b) with the IPCC's most plausible value for sea level rise by 2100 (0.48 m) and (c) using the above methodology to fully account for uncertainty over possible sea level rise. The analysis shows that undertaking a risk assessment using the most plausible sea level rise value may significantly underestimate monetary losses as it fails to account for the impact of low probability, high consequence events. The developed method provides an objective basis for decisions regarding future defence spending and can be easily extended to consider other sources of uncertainty such as changing event frequency–magnitude distribution, changing storm surge conditions or model structural uncertainty, either singly or in combination as joint probabilities.     

Structural identification using linear models and earthquake records

The problem of determining linear models of structures from seismic response data is investigated using ideas from the theory of system identification. The approach is to determine the optimal estimates of the model parameters by minimizing a selected measure-of-fit between the responses of the structure and the model. Because earthquake records are normally available from only a small number of locations in a structure, and because of noise in the records, it is necessary in practice to estimate parameters of the dominant modes in the records, rather than the stiffness and damping matrices of the linear model. A new algorithm is developed to determine the optimal estimates of the modal parameters. After tests with simulated data, the method is applied to a multi-storey building using records from the 1971 San Fernando earthquake in California. New information is obtained concerning the properties of the lower modes of the building and the time-varying character of the equivalent linear parameters.     

Inverse groundwater modelling in the Willunga Basin,South Australia

A new inverse technique for modelling groundwater flow, based on a functional minimization technique, has been used to calibrate a groundwater flow model of a subregion of the Port Willunga aquifer within the Willunga Basin in South Australia. The Willunga Basin is the location of extensive viticulture, irrigated primarily by groundwater, the levels and quality of which have declined significantly over the last 40 years. The new method is able to generate estimates of transmissivity, storativity and groundwater recharge over the whole subregion as a time-varying continuous surface; previous methods estimate local discrete parameter values at specific times. The new method has also been shown to produce accurate head values for the subregion and very good estimates of groundwater recharge. Its ultimate goal will be to provide a new and invaluable tool for significantly improved groundwater resource management. Supported in part by US National Science Foundation grants, DMS-0107492 and DMS-0079478.     

Enhancing the relevance of Shared Socioeconomic Pathways for climate change impacts,adaptation and vulnerability research

This paper discusses the role and relevance of the shared socioeconomic pathways (SSPs) and the new scenarios that combine SSPs with representative concentration pathways (RCPs) for climate change impacts, adaptation, and vulnerability (IAV) research. It first provides an overview of uses of social–environmental scenarios in IAV studies and identifies the main shortcomings of earlier such scenarios. Second, the paper elaborates on two aspects of the SSPs and new scenarios that would improve their usefulness for IAV studies compared to earlier scenario sets: (i) enhancing their applicability while retaining coherence across spatial scales, and (ii) adding indicators of importance for projecting vulnerability. The paper therefore presents an agenda for future research, recommending that SSPs incorporate not only the standard variables of population and gross domestic product, but also indicators such as income distribution, spatial population, human health and governance.