Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches

River water temperature is a key physical variable controlling several chemical, biological and ecological processes. Its reliable prediction is a main issue in many environmental applications, which however is hampered by data scarcity, when using data‐demanding deterministic models, and modelling limitations, when using simpler statistical models. In this work we test a suite of models belonging to air2stream family, which are characterized by a hybrid formulation that combines a physical derivation of the key equation with a stochastic calibration of parameters. The air2stream models rely solely on air temperature and streamflow, and are of similar complexity as standard statistical models. The performances of the different versions of air2stream in predicting river water temperature are compared with those of the most common statistical models typically used in the literature. To this aim, a dataset of 38 Swiss rivers is used, which includes rivers classified into four different categories according to their hydrological characteristics: low‐land natural rivers, lake outlets, snow‐fed rivers and regulated rivers. The results of the analysis provide practical indications regarding the type of model that is most suitable to simulate river water temperature across different time scales (from daily to seasonal) and for different hydrological regimes. A model intercomparison exercise suggests that the family of air2stream hybrid models generally outperforms statistical models, while cross‐validation conducted over a 30‐year period indicates that they can be suitably adopted for long‐term analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Towards more systematic perceptual model development: a case study using 3 Luxembourgish catchments

The synthesis of experimental understanding of catchment behaviour and its translation into qualitative perceptual models is an important objective of hydrological sciences. We explore this challenge by examining the cumulative understanding of the hydrology of three experimental catchments and how it evolves through the application of different investigation techniques. The case study considers the Huewelerbach, Weierbach and Wollefsbach headwater catchments of the Attert basin in Luxembourg. Subsurface investigations including bore holes and pits, analysis of soil samples and Electrical Resistivity Tomography measurements are presented and discussed. Streamflow and tracer data are used to gain further insights into the streamflow dynamics of the catchments, using end‐member mixing analysis and hydrograph separation based on dissolved silica and electrical conductivity. We show that the streamflow generating processes in all three catchments are controlled primarily by the subsolum and underlying bedrock. In the Huewelerbach, the permeable sandstone formation supports a stable groundwater component with little seasonality, which reaches the stream through a series of sources at the contact zone with the impermeable marls formation. In the Weierbach, the schist formation is relatively impermeable and supports a ‘fill and spill’‐type of flow mechanism; during wet conditions, it produces a delayed response dominated by pre‐event water. In the Wollefsbach, the impermeable marls formation is responsible for a saturation‐excess runoff generating process, producing a fast and highly seasonal response dominated by event water. The distinct streamflow generating processes of the three catchments are represented qualitatively using perceptual models. The perceptual models are in turn translated into quantitative conceptual models, which simulate the hydrological processes using networks of connected reservoirs and transfer functions. More generally, the paper illustrates the evolution of perceptual models based on experimental fieldwork data, the translation of perceptual models into conceptual models and the value of different types of data for processes understanding and model representation. Copyright © 2014 John Wiley & Sons, Ltd.     

Stable staurolite–cordierite assemblages in K‐poor metapelitic schists in Aston and Hospitalet gneiss domes of the central Pyrenees (France,Andorra)

Staurolite–cordierite assemblages are common in mica schists of the Aston and Hospitalet gneiss domes of the central Axial Zone, Pyrenees (France, Andorra). Within a 200 m wide zone, staurolite, cordierite and andalusite porphyroblasts contain inclusion trails that preserve the same stage of development of a crenulation cleavage, strongly suggesting that all three phases are contemporaneous. Their syntectonic growth occurred during a short period at the beginning of the formation of the dominant schistosity (S₂) of the domes. Staurolite and cordierite touching each other further indicates an equilibrium relationship. Whole‐rock analyses show that some staurolite–cordierite schists are depleted in K₂O compared to post‐Archean shales (PAAS) and amphibolite facies pelites. Analysis of the st‐crd paragenesis in K‐poor schists without muscovite using KFMASH and MnNCKFMASH petrogentic grids, pseudosections and AFM compatibility diagrams predicts stable conditions at pressures of ~3.5 kbar at 575 °C. For metapelites with intermediate X_Mg values (0.7 >  X_Mg >0.48) a ‘muscovite‐out window’ exists from 550–650 °C at 3.5 kbar in the KFMASH system. Conventional thermobarometry (GB‐GASP, AvT‐AvP) and petrogenetic grids show an isobaric P–T path to peak temperatures of ~650 °C, supported by the presence of sillimanite‐K‐feldspar gneiss and migmatites. LP‐HT metamorphism in the Aston dome is related to early Carboniferous (c. 339 Ma) granitic intrusions into the dome core. As metamorphism is directly linked with the formation of the main S₂ schistosity, the temporal relations demonstrated in this study conflict with previous studies which constrained LP‐HT metamorphism and the development of flat‐lying schistosity to the late Carboniferous (315–305 Ma) – at least in the eastern Axial Zone.     

Rain on snow induced urban floods in cold maritime climate: Risk,indicators and trends

Urban floods pose a societal and economical risk. This study evaluated the risk and hydro-meteorological conditions that cause pluvial flooding in coastal cities in a cold climate. Twenty years of insurance claims data and up to 97 years of meteorological data were analysed for Reykjavík, Iceland (64.15°N; <100 m above sea level). One third of the city's wastewater collection system is combined, and pipe grades vary from 0.5% to 10%. Results highlight semi-intensive rain (<7 mm/h; ≤3 year return period) in conjunction with snow and frozen ground as the main cause for urban flood risk in a climate which undergoes frequent snow and frost cycles (avg. 13 and 19 per season, respectively). Floods in winter were more common, more severe and affected a greater number of neighbourhoods than during summer. High runoff volumes together with debris remobilized with high winds challenged the capacity of wastewater systems regardless of their age or type (combined vs. separate). The two key determinants for the number of insurance claims were antecedent frost depth and total precipitation volume per event. Two pluvial regimes were particularly problematic: long duration (13–25 h), late peaking rain on snow (RoS), where snowmelt enhanced the runoff intensity, elongated and connected independent rainfall into a singular, more voluminous (20–76 mm) event; shorter duration (7–9 h), more intensive precipitation that evolved from snow to rain. Closely timed RoS and cooling were believed to trigger frost formation. A positive trend was detected in the average seasonal snow depth and volume of rain and snowmelt during RoS events. More emphasis, therefore, needs to be placed on designing and operating urban drainage infrastructure with regard to RoS co-acting with frozen ground. Furthermore, more detailed, routine monitoring of snow and soil conditions is important to predict RoS flood events.     

Assessment of dissolved nutrients dispersal derived from offshore fish-farm using nitrogen stable isotope ratios (δ15N) in macroalgal bioassays

In this study, the dispersal of wastes from offshore fish farms was evaluated by analyzing nitrogen stable isotope ratios (δ¹⁵N) in macroalgae incubated in the water column at sites located at an increasing distance from the fish cages. Bioassays were performed at three fish farms situated in separate localities with different nutritional conditions (Canary Islands, Murcia and Catalonia) and varying in size, species of fish reared and annual production. Macroalgal bioassays were carried out in two different directions (DI and DII) and they were replicated at each distance in order to evaluate the effect of small-scale variability on the spatial extent of fish farm wastes. The results obtained with δ¹⁵N contribute to a better understanding of the application of nitrogen stable isotopes ratios in macroalgae as an effective bioindicator for tracing the dispersion of offshore fish farm wastes, and demonstrate that fish farm wastes can be traced even over distances of some km from the pollution source. In the Canary Islands, the maximum distance obtained for detection of fish farm wastes was between 450 and 700 m. Of the three installations studied, Murcia presented the greatest distance for detection of fish farm waste influence, ranging from between 1550 and 2450 m, whilst in Catalonia this distance was less than 120 m. In Catalonia, the results were masked by the influence of other sources of nitrogen, and thus fish farm wastes were detected at more reduced distances than expected. These results confirm that fish farm wastes can be traced using the nitrogen stable isotope ratios of macroalgae and that this method can also be useful for identifying areas of potential risk to some sensitive ecosystems, and as an early signal that changes in the community structure might occur.     

A probabilistic approach for computing water retention of particulate systems from statistics of grain size and tessellated pore network

The paper offers an analytical determination of the hydraulic properties of an unsaturated soil with reference to its retention curve, which describes the relationship between the volumetric water content and capillarity through matric suction. The analysis combines a particulate approach focused on the physics at the pore scale, including microstructural aspects, with a probabilistic approach where the void space and grain size are considered as random variables. In the end, the soil water characteristic curve of an unsaturated granular medium along a drying path can be derived analytically based on the sole information of particle size distribution. The analysis hinges on the tessellation of a wet granular system into an assemblage of tetrahedral unit cells revealing a pore network upon which capillary physics are computed with respect to pore throat invasion by a non-wetting fluid with evolving pendular capillary bridges. The crux of the paper is to pass from particle size probability distribution to a matching void space distribution to eventually reveal key information such as void cell and solid volume statistics. Making reasonable statistically based assumptions to render calculations tractable, the water retention curve can be readily constructed. Model predictions compare quite favourably with experimental data available for actual soils, especially in the high saturation range. Having a sound scientific basis, the model can be made amenable to address a variety of soils with a wider range of particle sizes.     

Analysis of the interannual variability of annual daily extreme water levels in the St Lawrence River and Lake Ontario from 1918 to 2010

We compared the interannual variability of annual daily maximum and minimum extreme water levels in Lake Ontario and the St Lawrence River (Sorel station) from 1918 to 2010, using several statistical tests. The interannual variability of annual daily maximum extreme water levels in Lake Ontario is characterized by a positive long‐term trend showing two shifts in mean (1929–1930 and 1942–1943) and a single shift in variance (in 1958–1959). In contrast, for the St Lawrence River, this interannual variability is characterized by a negative long‐term trend with a single shift in mean, which occurred in 1955–1956. As for annual daily minimum extreme water levels, their interannual variability shows no significant long‐term change in trend. However, for Lake Ontario, the interannual variability of these water levels shows two shifts in mean, which are synchronous with those for maximum water levels, and a single shift in variance, which occurred in 1965–1966. These changes in trend and stationarity (mean and variance) are thought to be due to factors both climatic (the Great Drought of the 1930s) and human (digging of the Seaway and construction of several dams and locks during the 1950s). Despite this change in means and variance, the four series are clearly described by the generalized extreme value distribution. Finally, annual daily maximum and minimum extreme water levels in the St Lawrence and Lake Ontario are negatively correlated with Atlantic multidecadal oscillation over the period from 1918 to 2010. Copyright © 2013 John Wiley & Sons, Ltd.     

Combining two filter paper‐based analytical methods to monitor temporal variations in the geochemical properties of fluvial suspended particulate matter

Many of the commonly used analytical techniques for assessing the properties of fluvial suspended particulate matter (SPM) are neither cost effective nor time efficient, making them prohibitive to long‐term high‐resolution monitoring. We present an in‐depth methodology utilizing two types of spectroscopy which, when combined with automatic water samplers, can generate accurate, high‐temporal resolution SPM geochemistry data, inexpensively and semi‐destructively, directly from sediment covered filter papers. A combined X‐ray fluorescence spectroscopy and diffuse reflectance infrared Fourier transform spectroscopy approach is developed to estimate concentrations for a range of elements (Al, Ca, Ce, Fe, K, Mg, Mn, Na, P, Si, Ti) and compounds (organic carbon, Al_dithionate, Al_oxalate, Fe_dithionate, and Fe_oxalate) within SPM trapped on quartz fibre filters at masses as low as 3 mg. Calibration models with small prediction errors are derived, along with mass correction factor models to account for variations in retained SPM mass. Spectral pre‐processing methods are shown to enhance the reproducibility of results for some compounds, and the importance of filter paper selection and homogeneous sample preparation in minimizing spectral interference is emphasized. The geochemical signal from sediment covered filter papers is demonstrated to be time stable enabling samples to be stored for several weeks prior to analysis. Example results obtained during a heavy precipitation event in October 2012 demonstrate the methodology presented here has considerable potential to be utilized for high‐resolution monitoring of SPM geochemistry under a range of in‐stream hydrological conditions. Copyright © 2013 John Wiley & Sons, Ltd.