Mosaic surface storages of a small boreal catchment

Recent studies have suggested that the hydrologic connectivity of northern headwater catchments is likely controlled by antecedent moisture conditions and land cover patterns. A water storage model (EWS), based on water levels (WLs), specific yield (Sy) and surface elevation (SE) changes, was compared with a basic water budget of a small, boreal, patterned fen (13 ha) during the ice‐free period. Results showed that the EWS model reproduced well storage variations derived from the water budget. These results suggest that storage variations can be properly represented by the fluctuations of WLs when we consider the heterogeneous soil properties. However, storage deviations occurred at the daily scale and could be explained by a lack of information on water retention in unsaturated layers, canopy interceptions and preferential flows. Despite the significant impact of SE changes on the different peatland cover storage budgets (strings and lawns), using Sy mean values had a low impact on storage estimations. This can be explained by the large proportion of pools and high WLs throughout the fen. At the fen scale, high storage in the pools seemed to reduce the Sy difference between strings and lawns. The results of this study provide new insights about the complex hydrological behaviour of northern catchments and allow for conceiving new hydrological modelling perspectives. Copyright © 2014 John Wiley & Sons, Ltd.     

Computation of the space and time evolution of equilibrium-line altitudes on Andean glaciers (10°N–55°S)

A previous study of Fox [Fox, A.N. 1993. Snowline altitude and climate at present and during the Last Pleistocene Glacial Maximum in the Central Andes (5°–28°S). Ph.D. Thesis. Cornell University.] showed that for a fixed 0 °C isotherm altitude, the equilibrium-line altitude (ELA) of the Peruvian and Bolivian glaciers from 5 to 20°S can be expressed based on a log–normal expression of local mid-annual rainfall amount (P). In order to extrapolate the function to the whole Andes (10°N to 55°S) a local 0 °C isotherm altitude is introduced. Two applications of this generalised function are presented. One concerns the space evolution of mean inter-annual ELA for three decades (1961–1990) over the whole South American continent. A high-resolution data set (grid data: 10′ for latitude/longitude) of mean monthly air surface temperature and precipitation is used. Mean annual values over the 1961–1990 period were calculated. On each grid element, the mean annual 0 °C isotherm altitude is determined from an altitudinal temperature gradient and mean annual temperature (T) at ground level. The 0 °C isotherm altitude is then associated with the annual precipitation amount to compute the ELA. Using computed ELA and the digital terrain elevation model GTOPO30, we determine the extent of the glacierised area in Andean regions under modern climatic conditions. The other application concerns the ELA time evolution on Zongo Glacier (Bolivia), where inter-annual ELA variations are computed from 1995 to 1999. For both applications, the computed values of ELA are in good agreement with those derived from glacier mass balance measurements.     

Hydroclimate variability and long-lead forecasting of rainfall over Thailand by large-scale atmospheric variables

Abstract

The development of statistical relationships between local hydroclimates and large-scale atmospheric variables enhances the understanding of hydroclimate variability. The rainfall in the study basin (the Upper Chao Phraya River Basin, Thailand) is influenced by the Indian Ocean and tropical Pacific Ocean atmospheric circulation. Using correlation analysis and cross-validated multiple regression, the large-scale atmospheric variables, such as temperature, pressure and wind, over given regions are identified. The forecasting models using atmospheric predictors show the capability of long-lead forecasting. The modified k-nearest neighbour (k-nn) model, which is developed using the identified predictors to forecast rainfall, and evaluated by likelihood function, shows a long-lead forecast of monsoon rainfall at 7–9 months. The decreasing performance in forecasting dry-season rainfall is found for both short and long lead times. The developed model also presents better performance in forecasting pre-monsoon season rainfall in dry years compared to wet years, and vice versa for monsoon season rainfall.

Editor Z.W. Kundzewicz

Citation Singhrattna, N., Babel, M.S. and Perret, S.R., 2012. Hydroclimate variability and long-lead forecasting of rainfall over Thailand by large-scale atmospheric variables. Hydrological Sciences Journal, 57 (1), 26–41.     

Seasonal and monthly hydrological budgets of a fen‐dominated forested watershed,James Bay region,Quebec

The hydrology of Quebec, Canada, boreal fens is poorly documented. Many peatlands are located in watersheds with impounded rivers. In such cases, their presence influences reservoir inflows. In recent years, some fens have been subjected to an increase of their wet area, a sign that they may be evolving towards an aquatic ecosystem. This dynamic process is called aqualysis. This article presents the seasonal and monthly hydrological budgets of a small watershed including a highly aqualysed fen (James Bay region). The monitoring of precipitation (P), runoff (Q) and groundwater levels (WL) was conducted during the ice‐free season. Three semiempirical equations (Thornthwaite, Priestley–Taylor and Penman–Monteith) were used and compared to calculate potential evapotranspiration. The first two equations, having fewer parameters, estimate higher potential evapotranspiration values than the third equation. The use of pressure‐level gauges installed in wells, for the calculation of peatland water storage, is inconclusive. Swelling of peat, peat decomposition and plant composition could be responsible for nonnegligible amounts of absorbed water, which are not entirely accounted for by well levels. The estimation of peat matrix water storage is potentially the largest source of error and the limiting factor to calculate water balances in this environment. The results show that the groundwater level and the water storage vary depending on the season and especially after a heavy rainfall. Finally, the results illustrate the complexity of water routing through the site and thus raise several questions to be resolved in the future. Copyright © 2012 John Wiley & Sons, Ltd.     

Raman spectroscopic properties and Raman identification of CaS‐MgS‐MnS‐FeS‐Cr2FeS4 sulfides in meteorites and reduced sulfur‐rich systems

Raman spectra were acquired on a series of natural and synthetic sulfide minerals, commonly found in enstatite meteorites: oldhamite (CaS), niningerite or keilite ((Mg,Fe)S), alabandite (MnS), troilite (FeS), and daubreelite (Cr₂FeS₄). Natural samples come from three enstatite chondrites, three aubrites, and one anomalous ungrouped enstatite meteorite. Synthetic samples range from pure endmembers (CaS, FeS, MgS) to complex solid solutions (Fe, Mg, Ca)S. The main Raman peaks are localized at 225, 285, 360, and 470 cm^?1 for the Mg‐rich sulfides; at 185, 205, and 285 cm^?1 for the Ca‐rich sulfides; at 250, 370, and 580 cm^?1 for the Mn‐rich sulfides; at 255, 290, and 365 cm^?1 for the Cr‐rich sulfides; and at 290 and 335 cm^?1 for troilite with, occasionally, an extra peak at 240 cm^?1. A peak at 160 cm^?1 is present in all Raman spectra and cannot be used to discriminate between the different sulfide compositions. According to group theory, none of the cubic monosulfides oldhamite, niningerite, or alabandite should present first‐order Raman spectra because of their ideal rocksalt structure. The occurrence of broad Raman peaks is tentatively explained by local breaking of symmetry rules. Measurements compare well with the infrared frequencies calculated from first‐principles calculations. Raman spectra arise from activation of certain vibrational modes due to clustering in the solid solutions or to coupling with electronic transitions in semiconductor sulfides.     

Validation of Forecast Cloud Parameters from Multispectral AIRS Radiances

The well-known CO₂ slicing technique which provides retrievals of cloud parameters (effective height and amount) is adapted in light of model validation using multispectral infrared sounders. The technique is applied to both real Atmospheric Infrared Sounder (AIRS) radiances and to corresponding radiances simulated from global 6 h and 12 h forecasts for the 31 days of July 2008. The forecast model is the one used operationally at the Canadian Meteorological Centre. Radiances are simulated from the Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (RTTOV) model. When compared to model output of cloud parameters, simulated retrievals help us understand systematic biases linked to the retrieval technique. Systematic errors of interest, attributed to forecast cloud parameters, are then more clearly assessed from real retrievals. This is the central idea of this paper. The proposed definition of model cloud top, based on cloud transmittance, corresponds well to the height derived from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) instrument. These lidar-derived cloud heights, in turn, confirm the nature of the biases produced by the CO₂ slicing technique (e.g., a negative bias increasing with height to about 2 km (approximately 50 hPa) for the highest clouds at 16 km (approximately 100 hPa)). Results suggest that the model has a tendency to produce an excess of low-level clouds below 2 km, compensated for by a deficit from 3 to 6 km. No significant differences are found between 6 h and 12 h forecast monthly fields, an indication that the model has sufficiently spun-up after a few hours. Retrieved global monthly cloud parameter fields are compared to independently derived products available from the Moderate Resolution Imaging Spectrometer (MODIS) and AIRS standard processing. Significant differences are noted, linked to the different retrieval approaches, input data and resolution. This is further evidence that, for validation purposes, definitions of observed and model parameters must be consistent.     

Constraining groundwater modeling with magnetic resonance soundings

Magnetic resonance sounding (MRS) is a noninvasive geophysical method that allows estimating the free water content and transmissivity of aquifers. In this article, the ability of MRS to improve the reliability of a numerical groundwater model is assessed. Thirty-five sites were investigated by MRS over a ～5000 km(2) domain of the sedimentary Continental Terminal aquifer in SW Niger. Time domain electromagnetic soundings were jointly carried out to estimate the aquifer thickness. A groundwater model was previously built for this section of the aquifer and forced by the outputs from a distributed surface hydrology model, to simulate the observed long-term (1992 to 2003) rise in the water table. Uncertainty analysis had shown that independent estimates of the free water content and transmissivity values of the aquifer would facilitate cross-evaluation of the surface-water and groundwater models. MRS results indicate ranges for permeability (K = 1 × 10(-5) to 3 × 10(-4) m/s) and for free water content (w = 5% to 23% m(3) /m(3) ) narrowed by two orders of magnitude (K) and by ～50% (w), respectively, compared to the ranges of permeability and specific yield values previously considered. These shorter parameter ranges result in a reduction in the model's equifinality (whereby multiple combinations of model's parameters are able to represent the same observed piezometric levels), allowing a better constrained estimate to be derived for net aquifer recharge (～22 mm/year).     

Mixing law versus discharge and electrical conductivity relationships: application to an alpine proglacial stream

Mixing laws have been used in hydrogeology for decades. In glacial hydrology, they are used to determine the contributions of the different reservoirs supplying the proglacial stream. However, some assumptions about discharge–solute matter and discharge–electrical conductivity (EC) relationships have led to erroneous conclusions. Analysis of a theoretical example indicated a hyperbolic relationship between discharge and solute matter concentration/EC for two reservoirs. We applied this approach to experimental data from the Baounet Glacier (Savoie, France), assuming that the proglacial stream is provided by a combination of watershed groundwater flow (diurnally stable and with high EC) and quick drainage from the glacier (low EC and discharge that change very quickly). Applying mixing laws allowed us to characterise these two flows and to separate the quick flows (glacial ablation and rainfalls). Copyright © 2011 John Wiley & Sons, Ltd.     

Linear geophysical inversion via the discrete cosine pseudo‐inverse: application to potential fields

In this paper, we present a methodology to perform geophysical inversion of large‐scale linear systems via a covariance‐free orthogonal transformation: the discrete cosine transform. The methodology consists of compressing the matrix of the linear system as a digital image and using the interesting properties of orthogonal transformations to define an approximation of the Moore–Penrose pseudo‐inverse. This methodology is also highly scalable since the model reduction achieved by these techniques increases with the number of parameters of the linear system involved due to the high correlation needed for these parameters to accomplish very detailed forward predictions and allows for a very fast computation of the inverse problem solution. We show the application of this methodology to a simple synthetic two‐dimensional gravimetric problem for different dimensionalities and different levels of white Gaussian noise and to a synthetic linear system whose system matrix has been generated via geostatistical simulation to produce a random field with a given spatial correlation. The numerical results show that the discrete cosine transform pseudo‐inverse outperforms the classical least‐squares techniques, mainly in the presence of noise, since the solutions that are obtained are more stable and fit the observed data with the lowest root‐mean‐square error. Besides, we show that model reduction is a very effective way of parameter regularisation when the conditioning of the reduced discrete cosine transform matrix is taken into account. We finally show its application to the inversion of a real gravity profile in the Atacama Desert (north Chile) obtaining very successful results in this non‐linear inverse problem. The methodology presented here has a general character and can be applied to solve any linear and non‐linear inverse problems (through linearisation) arising in technology and, particularly, in geophysics, independently of the geophysical model discretisation and dimensionality. Nevertheless, the results shown in this paper are better in the case of ill‐conditioned inverse problems for which the matrix compression is more efficient. In that sense, a natural extension of this methodology would be its application to the set of normal equations.