Inflow Data

The ASCII file Matthaeus MBI.csv is a complete list of identified inflow events between 

1880 and 2007 with date, duration and intensity, based on the articles of Matthaus andFranck 

FIGURE 20.10 Barotropic Transport Index Batrix in cm from 1891 to 2005, compiled from hourly sea-level differences between Hornbrek and Gedser (Section 20.3.3), filtered with the linear lOd-memory response function (Eq. 2.16). 

The ASCII file batrix.asc is the daily Barotropic Transport Index Batrix, compiled from hourly sea level differences between Hornbaek and Gedser (Section 20.3.3), filtered with the linear 10-day-memory response function (20.16) of the volume flow in reaction to the applied barotropic pressure gradient. The Batrix values are measured in cm and are taken at 24 h once a day. Data gaps are padded with the mean difference —4 cm. The Batrix time series shown in Fig. 20.10 is an alternative measure for the inflow activity during the last century. 

The files ds zzm.dat are ASCII files containing the time series of temperature, salinity, east and north component of the current velocity at the depth zz at the Darss Sill. 

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Fig. 6-3 Global water balance. Storages in km fluxes in km /yr. Turnover times calculated as storage divided by total annual inflow. (Data from Shiklomanov and Sokolov, 1983.)...

FIGURE 18.4 Cod landings and relative strength of Baltic Inflow. Data on hydrography based on Matthaus and Nausch (2003) and Matthaus (2006), landings data from the Bulletin Statistique (1909 1972) and Bulletin Statistique (1972-2005). 

Rain contains significant amounts of dissolved N, principally as NO.r , NO2 and NH4. Organic N (notably in urea and amino acids Paerl Fogel, 1994) may also be present. Precipitation may thus be an important supplier of N to some lakes, particularly large waterbodies where rain falling on the lake surface can be the dominant source of inflow. Data on the isotopic composition of rain N are sparse, but those that exist indicate that both dissolved nitrate and ammonium commonly have relatively low 5 N values, in the range of -18 to -t4%o, with local average values typically <0%o (Owens, 1987 Heaton, 1987 ... 

To model the state of the plant, a discrete Markov process is used. To calculate the transition matrix Q of a discrete Markov process, the transition probabilities between both states have to be estimated. All transitions of the recorded inflow data is used. The time series of plant states LOt are calculated by... 

From the contents discussed above, the following conclusions can be draw The prediction of water inflow in mines must follow three principles finding out different conditions, using representative calculated parameters, and selecting the proper mathematical model. No matter which method is used to predict water inflow in mines, the amount of increment of mine groundwater must be calculated., Moreover, the rationality of calculating water inflow from the water balance must be considered in mines In order to obtain accurate water inflow data successfully, it is necessary to analyze hydrogeological conditions carefully to select the... 

Pamies, M., Weiss, RE., Garnier, E., Deck, S., Sagaut, R Generation of synthetic turbulent inflow data for large eddy simulation of spatially evolving wall-bounded flows. Physics of Fluids 16, 045103 (2009)... 

On the basis of the above-mentioned assumptions, atmospheric concentrations, used as inflows to the model, in the range of 9.37 x 10 9 to 2 x 10 6 mg m 3 (data not shown) did not have a significant influence on the partitioning of DeBDE. A strong impact could be assigned to the direct discharge and to chemical concentration in inflow waters. There is, however, no information available on concentration of DeBDE in emitted waters. Consequently, different direct discharges from the e-waste sites were used as emission data and the subsequent concentrations for sediment and water concentrations in the river were calculated (Fig. 3). 

For the Hveragerdi 4 well, we follow the same procedure, using the data in Table 23.2 and the calculations already shown. In this case, the model predicts that a number of minerals in the LLNL database are supersaturated near the inflow temperature of 181 °C. Close examination reveals that each of the supersaturated minerals contains either Mg++, Ca++, or Fe++, components that are characteristically depleted in geothermal fluids. The Mg++ concentration in this fluid, for example, is just 2 p,g kg-1. 

The bulge metallicity distribution also shows a rough compatibility with a Simple model (Fig. 8.22), although the exact metallicities here (based on mulhcolour photometry) depend on those of globular clusters used for calibration which are not quite certain. Nevertheless, broadly similar distributions have been derived from direct spectroscopy (Fulbright, McWilliam Rich 2006). An initial enrichment corresponding to [Fe/H] = —1.6 (as could be expected from inflow of halo gas) is not excluded by the data. 

Thus the mass of stars and that of the whole system steadily increase while z soon approaches 1 and the stellar metallicity distribution is very narrow (see Fig. 8.24). The accretion rate is constant in time if the star formation rate is any fixed function of the mass of gas. Other models in which the accretion rate is constant, but less than in the extreme model, have been quite often considered in the older literature (e.g. Twarog 1980), but are less popular now because they are not well motivated from a dynamical point of view, there is an upper limit to the present inflow rate into the whole Galaxy of about 1 M0yr 1 from X-ray data (Cox Smith 1976) and they do not provide a very good fit to the observed metallicity distribution function. 

Numerical models offer the possibility to take into account all the details of stellar nucleosynthesis and time delays in a self-consistent manner, while still relying on various assumptions about star formation, inflow etc. that have little more physical justification than the crude approximations needed for analytical modelling, but can be chosen to fit the observational data. 

Fig. 8.41. Thin curves age-metallicity relation predicted by the two-inflow model of Chiappini, Matteucci and Gratton (1997). Thick curves sketch of suggested separate AMRs for the thick and thin disks. Data points are from Edvardsson et al. (1993). Adapted from Chiappini et al. (1997) by Pagel (2004).

This formula fits the same U, Th data for 13 < T <20 Gyr, and it can be seen from Fig. 10.3 that the upper limit could be infinity for slightly different models, basically because the beginning of nucleosynthesis is something that is now assumed to happen gradually. The inflow model gives 244,23s = 0.04, much the same as in Fowler s model. Thus Solar-System actinide data do not provide any upper limit to the age of the Galaxy, nor do they strongly constrain GCE models. 

The resulting dependences of [Th/Eu] on stellar age are shown in Fig. 10.5, together with a selection of observational data from del Peloso et al. for disk stars Westin et al. (2000) for two of the r-process enriched ultra-metal-poor (UMP) halo stars and Cowan et al. (2002) for a third one. The range among disk stars is little more than can be expected from uncertainties in the determination, while the UMP stars show more or less the expected deficiency. For BD +17 0 3248, Cowan et al. used theoretical production ratios for Th relative to Eu, Ir and Pt, based on certain nuclear models, to deduce a Galactic-model-independent age of 13.8 4 Gyr, which happens to fit our two production-ratio-independent model curves simple inflow and modFowler T = 15 quite nicely, but the error bars are large so that what we have is more a test of consistency than an independent chronometer. 

Fig. 2. Triangular diagrams describing the relative concentration of H20 C02-H2 in the steam produced before re-injection in the four main subunits of the Larderello field. Different symbols represent different locations of producing wells in the same subunit. Largest symbols in each diagrams represent the chemical composition of the reference core within a single area (see text for discussion). Data for Castelnuovo result from the largest amount of meteoric water inflow observed in the entire basin.

In the simplest case, groundwater-flow rates for lakes at isotopic steady state (or those with relatively long hydraulic-residence times) can be estimated from data on average annual precipitation rates average annual evaporation rates the isotopic compositions of precipitation, lake water, and inflowing ground-water and relative humidity and lake temperature. 

To reduce the inflow of toxic substances into basin waters efficiently, the Corporation required information on which effluents posed the greatest hazard to the river. While chemical data on many of the effluents were available, their diverse composition was difficult to interpret in terms of hazard potential. Moreover, hazard is not only linked to chemical composition of an effluent, but also on the toxic effects it can have on a variety of freshwater organisms. Adverse effects on biota are also influenced by the volume of wastewater discharged at different times of the year. Hence, the Corporation searched for a cost-effective approach, based on ecotoxicological principles, to rank the various effluents (there are several hundred sources), in terms of their toxic loading, so that subsequent efforts (such as clean up actions) could be prioritized. 

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