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Abstract. Several studies have used the temperature dependence of gas solubilities in water to derive paleotemperatures from noble gases in groundwaters. We present a general method to infer environmental parameters from concentrations of dissolved atmospheric noble gases in water. Our approach incorporates statistical methods to quantify uncertainties of the deduced parameter values. The equilibration temperatures of water equilibrated with the atmosphere under controlled conditions could be inferred with a precision and accuracy of +_0.2øC. The equilibration temperatures of lake and river samples were determined with a similar precision. Most of these samples were in agreement with atmospheric equilibrium at the water temperature. In groundwaters either recharge temperature or altitude could be determined with high precision (+_0.3øC and +_60 m, respectively) despite the presence of excess air. However, typical errors increase to +_3øC and +_700 m if both temperature and altitude are determined at the same time, because the two parameters are correlated. In some groundwater samples the composition of the excess air deviated significantly from atmospheric air, which was modeled by partial reequilibration. In this case the achievable precision of noble gas temperatures was significantly diminished (typical errors of +_ iøC).

The design, setup, and performance of a mass spectrometric system for the analysis of noble gas isotopes ( 3 He, 4 He, 20 Ne, 21 Ne, 22 Ne, 36 Ar, 40 Ar, 84 Kr, 136 Xe) and tritium ( 3 H) from water samples are described. The 3 H concentration is measured indirectly by the 3 He ingrowth from radioactive decay. After extraction, purification, and separation, the noble gases are measured in two noncommercial doublecollector 90°magnetic sector mass spectrometers. We present a new approach for the analysis of the heavy noble gas isotopes that enables, in principle, simultaneous measurement of Ar, Kr, and Xe. Typical precisions of the measurements of 3 H, He, Ne, Ar, Kr, and Xe concentrations are (2.7%, (0.3%, (0.9%, (0.3%, (0.8%, and (1.0%, respectively. For the isotopic ratios 3 He/ 4 He, 20 Ne/ 22 Ne, and 40 Ar/ 36 Ar the typical precisions are (0.7%, (0.3%, and (0.2%. These values express the reproducibility of the measurement of an internal freshwater standard and include the overall stability of the system as well as of the extraction procedure. To verify the method, the noble gas concentrations of air-saturated water samples prepared under controlled conditions are compared with noble gas solubility data. The 20 Ne/ 22 Ne and 36 Ar/ 40 Ar fractionation during solution is estimated from 70 surface water samples to be -2.0 ( 0.2‰ and -1.3 ( 0.2‰, respectively.

Knowing the travel-time distributions from infiltrating rivers to pumping wells is important in the management of alluvial aquifers. Commonly, travel-time distributions are determined by releasing a tracer pulse into the river and measuring the breakthrough curve in the wells. As an alternative, one may measure signals of a time-varying natural tracer in the river and in adjacent wells and infer the travel-time distributions by deconvolution. Traditionally this is done by fitting a parametric function such as the solution of the one-dimensional advection-dispersion equation to the data. By choosing a certain parameterization, it is impossible to determine features of the travel-time distribution that do not follow the general shape of the parameterization, i.e., multiple peaks. We present a method to determine travel-time distributions by nonparametric deconvolution of electric-conductivity time series. Smoothness of the inferred transfer function is achieved by a geostatistical approach, in which the transfer function is assumed as a second-order intrinsic random time variable. Nonnegativity is enforced by the method of Lagrange multipliers. We present an approach to directly compute the best nonnegative estimate and to generate sets of plausible solutions. We show how the smoothness of the transfer function can be estimated from the data. The approach is applied to electric-conductivity measurements taken at River Thur, Switzerland, and five wells in the adjacent aquifer, but the method can also be applied to other time-varying natural tracers such as temperature. At our field site, electric-conductivity fluctuations appear to be an excellent natural tracer.

The (Lower) Lake of Zurich provides an ideal system for studying the long-term impact of environmental change on deep-water hypoxia because of its sensitivity to climatic forcing, its history of eutrophication and subsequent oligotrophication, and the quality and length of its data set. Based on 39 years (1972-2010) of measured profiles of temperature, oxygen concentration and phosphorus (P) concentration, the potentially confounding effects of oligotrophication and climatic forcing on the occurrence and extent of deep-water hypoxia in the lake were investigated. The time-series of Nürnberg's hypoxic factor (HF) for the lake can be divided into three distinct segments: (i) a segment of consistently low HF from 1972 to the late-1980s climate regime shift (CRS); (ii) a transitional segment between the late-1980s CRS and approximately 2000 within which the HF was highly variable; and (iii) a segment of consistently high HF thereafter. The increase in hypoxia during the study period was not a consequence of a change in trophic status, as the lake underwent oligotrophication as a result of reduced external P loading during this time. Instead, wavelet analysis suggests that changes in the lake's mixing regime, initiated by the late-1980s CRS, ultimately led to a delayed but abrupt decrease in the deep-water oxygen concentration, resulting in a general expansion of the hypoxic zone in autumn. Even after detrending to remove long-term effects, the concentration of soluble reactive P in the bottom water of the lake was highly correlated with various measures of hypoxia, providing quantitative evidence supporting the probable effect of hypoxia on internal P loading. Such climate-induced, ecosystem-scale changes, which may result in undesirable effects such as a decline in water quality and a reduction in coldwater fish habitats, provide further evidence for the vulnerability of large temperate lakes to predicted increases in global air temperature.

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A unique data set of 50 years of monthly temperature profiles from Lake Zurich, a normally ice-free lake located on the Swiss Plateau, allowed the one-dimensional numerical k-lake model ''SIMSTRAT'' to be calibrated (1948-1957) and validated (1958-1997). Hindcasts of temperature profiles agree excellently with the measured data. Both interannual and intraannual variations in thermal structure are reproduced well during the entire 50-yr simulation, thus demonstrating the stability and good prognostic qualities of the model. Simulations conducted with raised and lowered air temperatures (T air ) suggest that an increase in T air will lead to an increase in lake water temperature at all depths. In comparison to the continuous modeling approach taken in this study, the commonly employed discontinuous modeling approach (with no heat carryover during winter) substantially underestimated the degree of long-term hypolimnetic warming that can be expected to result from an increase in T air . Thus, whereas the discontinuous approach yields valid predictions for strictly dimictic lakes that are ice-covered each winter, heat carryover during winter makes a continuous approach necessary in lakes like Lake Zurich that are only facultatively dimictic. The significant degree of hypolimnetic warming found in this study suggests that the response of facultatively dimictic lakes to increases in T air is likely to differ from that of the strictly dimictic lakes modeled in other investigations. In Lake Zurich, an increase in T air is predicted to result in more frequent suppression of deeply penetrative winter mixing events, with a potentially negative impact on the lake ecosystem.