Digital model of corrected accumulated flow for peak discharge data acquisition and drainage system design

The design of a drainage system for a roofing slate quarry was implemented by the enhancement of discharge peak estimation, and the uncertainty inevitably associated with the engineering model was reduced.

The development of a topographical, geological, and vegetation cover database developed from a Geographical Information System (GIS) allowed for the definition of the drainage network for a hydraulic system, along with the calculation of the runoff coefficient. This is applied to the digital model of accumulated flow (DMF) as a weight correction coefficient, using a matrix-based model at 5×5 m resolution. The new digital model of corrected accumulated flow (DMCF) is the result of combining the thematic maps with the map of slope <3%, which was previously created from the slope model. It is demonstrated that this new model allows to apply the “Rational Method” on cartographic units defined by the GIS.

The DMCF is compared with other traditional applications of the Rational Method based on the calculation of the discharge peak considering: (1) the drainage basin as a single watershed or (2) defining an average runoff coefficient in each sub-watershed. Both approaches have bigger discharge peaks than those obtained by the DMCF since the slope, lithology, and vegetation cover have average values, and the runoff coefficient is poorly defined, increasing the uncertainty in the discharge peak.     

Circulation characteristics of a monsoon depression during BOBMEX-99 using high-resolution analysis

The skill and efficiency of a numerical model mostly varies with the quality of initial values, accuracy on parameterization of physical processes and horizontal and vertical resolution of the model. Commonly used low-resolution reanalyses are hardly able to capture the prominent features associated with organized convective processes in a monsoon depression. The objective is to prepare improved high-resolution analysis by the use of MM5 modelling system developed by the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR). It requires the objective comparison of high and low-resolution analysis datasets in assessing the specific convective features of a monsoon depression. For this purpose, reanalysis datasets of NCAR/NCEP (National Center for Atmospheric Research/National Centers for Environmental Prediction) at a horizontal resolution of 2.5‡ (latitude/longitude) have been used as first guess in the objective analysis scheme. The additional asynoptic datasets obtained during BOBMEX-99 are utilized within the assimilation process. Cloud Motion Wind (CMW) data of METEOSAT satellite and SSM/I surface wind data are included for the improvement of derived analysis. The multiquadric (MQD) interpolation technique is selected and applied for meteorological objective analysis at a horizontal resolution of 30 km. After a successful inclusion of additional data, the resulting reanalysis is able to produce the structure of convective organization as well as prominent synoptic features associated with monsoon depression. Comparison and error verifications have been done with the help of available upper-air station data. The objective verification reveals the efficiency of the analysis scheme.     

Recent Precipitation Trends in Hungary in the Context of Larger Scale Climatic Changes

The time series of monthly precipitation totals from 14 Hungarian observing stations (1901–1998) were analysed to reveal the long term changes in precipitation characteristics occurred in the 20th century. A particular attention was given to the changes in the recent decades and their links with the larger scale climatic and circulation changes over Europe and the Atlantic.The statistical significancesof systematic changes are controlled by linear trend analysis and the Mann–Kendall test. The long term fluctuations are illustrated applying a 15-point Gaussian filter on the time series. The Standardised Precipitation Index is used to evaluate the changes in the drought event frequency. The relationships with larger scale changes are mostly discussed relying on contemporary papers, and the Grosswetterlagen Catalogue is used as well.The annual precipitation total decreased by 15–20% in Hungary during the 20th century. The decline is substantial in both halves of the century, but the precipitation sums in the transition seasons declined in the first 50 years, and the winter precipitation decreased in the latest decades. The precipitation total of the period November–February declined significantly in the last 50 years. In the same time the mean winter value of the North Atlantic Oscillation Index (NAOI) increased, the positions of the main pressure patterns over the Atlantic are shifted northeastward, and lot of other coherent changes detected in the winter climate of the European–Atlantic region. The mean summer precipitation total has hardly changed, but the frequency of summer drought events increased. There are some signs of a shift of the Hungarian summer climate towards a Mediterranean like climate.     

Observed daily large-scale rainfall patterns during BOBMEX-1999

A daily rainfall dataset and the corresponding rainfall maps have been produced by objective analysis of rainfall data. The satellite estimate of rainfall and the raingauge values are merged to form the final analysis. Associated with epochs of monsoon these rainfall maps are able to show the rainfall activities over India and the Bay of Bengal region during the BOBMEX period. The intra-seasonal variations of rainfall during BOBMEX are also seen using these data. This dataset over the oceanic region compares well with other available popular datasets like GPCP and CMAP. Over land this dataset brings out the features of monsoon in more detail due to the availability of more local raingauge stations.     

A Linear Programming Approach to Determine the Normative Composition of Sedimentary Rocks

The analysis of modal and normative composition of sedimentary rocks is widely used for studying their sources and tectonic settings. The normative calculation of the mineral composition of rocks in this study is formulated as a linear programming problem and is solved by means of the simplex method. This enables both simultaneous and successive subtraction of a set of basic minerals from a rock sample represented by its chemical composition {SiO₂...LOI}. Such an approach provides a more exact calculation of the contribution of basic minerals in the rock. This mathematical approach is used to study two representative sets of sandstones and fine-grained rocks from a Meso- to Neoproterozoic marginal basin of southeastern Siberia (Uchur–Maya region, Yakutia) and a Pennsylvanian-Lower Permian uplifted continental block in Colorado, USA. The calculated normative mineral compositions of the Siberian sandstones are consistent with the observed modal compositions. These sandstones vary from K- Feldspar rich arkoses at the base of the sequence (the Uchur Group, lower Riphean) to quartz arenites or lithic sandstones and wacke in transgressive successions of the middle-upper Riphean. Arkoses and quartz arenites are dominant in Meso- to Neoproterozoic Siberia. These samples represent craton interior uplifted basement and quartzose, recycled orogen provenance of a stable craton in Rodinia. There are higher but consistent discrepancies between the calculated and observed compositions for the Pennsylvanian to Lower-Permian arkoses and quartz arenites (Sangre de Cristo, Belden, and Maroon Formations). The differences between the predicted and observed mineralogy may be due to uncertainties in the modes in the matrix and cement of the sandstones. This normative program should supplement modal calculations and provide better genetic constructions, especially in case of matrix-rich sandstones.     

Stepwise Conditional Transformation for Simulation of Multiple Variables

Most geostatistical studies consider multiple-related variables. These relationships often show complex features such as nonlinearity, heteroscedasticity, and mineralogical or other constraints. These features are not handled by the well-established Gaussian simulation techniques. Earth science variables are rarely Gaussian. Transformation or anamorphosis techniques make each variable univariate Gaussian, but do not enforce bivariate or higher order Gaussianity. The stepwise conditional transformation technique is proposed to transform multiple variables to be univariate Gaussian and multivariate Gaussian with no cross correlation. This makes it remarkably easy to simulate multiple variables with arbitrarily complex relationships: (1) transform the multiple variables, (2) perform independent Gaussian simulation on the transformed variables, and (3) back transform to the original variables. The back transformation enforces reproduction of the original complex features. The methodology and underlying assumptions are explained. Several petroleum and mining examples are used to show features of the transformation and implementation details.     

Impact of horizontal resolution on prediction of tropical cyclones over Bay of Bengal using a regional weather prediction model

The present study is carried out to examine the performance of a regional atmospheric model in forecasting tropical cyclones over the Bay of Bengal and its sensitivity to horizontal resolution. Two cyclones, which formed over the Bay of Bengal during the years 1995 and 1997, are simulated using a regional weather prediction model with two horizontal resolutions of 165 km and 55 km. The model is found to perform reasonably well towards simulation of the storms. The structure, intensity and track of the cyclones are found to be better simulated by finer resolution of the model as compared to the coarse resolution. Rainfall amount and its distribution are also found to be sensitive to the model horizontal resolution. Other important fields, viz., vertical velocity, horizontal divergence and horizontal moisture flux are also found to be sensitive to model horizontal resolution and are better simulated by the model with finer horizontal grids.     

Stability analysis of the Vallcebre translational slide,Eastern Pyrenees (Spain) by means of a GIS

The stability of the landslide of Vallcebre has been evaluated by means of a GIS. The landslide mechanism is a translational failure which has been analysed as an infinite slope. Soil strength parameters and groundwater conditions are obtained from laboratory tests and monitoring devices. Geometric parameters necessary to compute the factor of safety at each individual cell are generated by interpolation from the boreholes present in the landslide. The results have been checked with the actual behaviour of the landslide and are consistent. The comparison between a conventional slope stability analysis and the GIS-based approach gives similar results, showing the feasibility of the latter.     

Disjunctive Kriging with Hard and Imprecise Data

This paper presents a methodology for assessing local probability distributions by disjunctive kriging when the available data set contains some imprecise measurements, like noisy or soft information or interval constraints. The basic idea consists in replacing the set of imprecise data by a set of pseudohard data simulated from their posterior distribution; an iterative algorithm based on the Gibbs sampler is proposed to achieve such a simulation step. The whole procedure is repeated many times and the final result is the average of the disjunctive kriging estimates computed from each simulated data set. Being data-independent, the kriging weights need to be calculated only once, which enables fast computing. The simulation procedure requires encoding each datum as a pre-posterior distribution and assuming a Markov property to allow the updating of pre-posterior distributions into posterior ones. Although it suffers some imperfections, disjunctive kriging turns out to be a much more flexible approach than conditional expectation, because of the vast class of models that allows its computation, namely isofactorial models.     

Predictive GIS-Based Model of Rockfall Activity in Mountain Cliffs

Rockfall susceptibility has been analysed in mountain cliffs of the Cantabrian Range, North Spain. The main aim of this analysis has been to build a predictive model of rockfall activity from a low number of environmental and geological variables. The rockfall activity has been quantified in a GIS. The cartographic information used shows the spatial distribution of all the recent talus screes as well as their associated source areas in the rock-slopes. The area relation At/Ar (recent talus scree polygon/source basins) in the rock slopes has been used as the rockfall activity indicator. This relation has been validated in 50 pilot rock-slopes and compared with the relation number of recent rock fragments/source basin, obtained from field work. The environmental factors causing rockfall depend on the rock slope situation, and these are: altitude and sun radiation on the rock cliff. The geological factors considered are: lithology, relative position of the main discontinuities with respect to the topographic surface and two morphologic parameters: the roughness and slope gradient. A logistic regression analysis has been applied to a population of 442 limestone and quartzite rock cliffs. The dependent variable is the rockfall activity indicator, which allows the definition of two classes of rock cliff units: low and high activity. The independent variables are altitude, sun radiation (equinox radiation, summer solstice radiation, winter solstice radiation), slope roughness, slope gradient,anisotropy and lithology. Results suggest that it is possible tobuild a valid cartographic predictive model for rockfall activity in mountain rock cliffs from a limited number of easily obtainable variables. The method is especially applicable in massive rock slopes or in regions with uniform rock mass characteristics.