SPLITAREA: an algorithm for weighted splitting of faces in the context of a planar partition

Geographic data themes modelled as planar partitions are found in many GIS applications (e.g. topographic data, land cover, zoning plans, etc.). When generalizing this kind of 2D map, this specific nature has to be respected and generalization operations should be carefully designed. This paper presents a design and implementation of an algorithm to perform a split operation of faces (polygonal areas).

The result of the split operation has to fit in with the topological data structure supporting variable-scale data. The algorithm, termed SPLITAREA, obtains the skeleton of a face using a constrained Delaunay triangulation. The new split operator is especially relevant in urban areas with many infrastructural objects such as roads. The contribution of this work is twofold: (1) the quality of the split operation is formally assessed by comparing the results on actual test data sets with a goal/metric we defined beforehand for the ‘balanced’ split and (2) the algorithm allows a weighted split, where different neighbours have different weights due to different compatibility. With the weighted split, the special case of unmovable boundaries is also explicitly addressed.

The developed split algorithm can also be used outside the generalization context in other settings. For example, to make two cross-border data sets fit, the algorithm could be applied to allow splitting of slivers.     

The effect of clay distribution on the elastic properties of sandstones

The shape and location of clay within sandstones have a large impact on the P‐wave and S‐wave velocities of the rock. They also have a large effect on reservoir properties and the interpretation of those properties from seismic data and well logs. Numerical models of different distributions of clay – structural, laminar and dispersed clay – can lead to an understanding of these effects. Clay which is located between quartz grains, structural clay, will reduce the P‐wave and S‐wave velocities of the rock. If the clay particles become aligned or form layers, the velocities perpendicular to the alignment will be reduced further. S‐wave velocities decrease more rapidly than P‐wave velocities with increasing clay content, and therefore Poisson's ratios will increase as the velocities decrease. These effects are more pronounced for compacted sandstones. Small amounts of clay that are located in the pore space will have little effect on the P‐wave velocity due to the competing influence of the density effect and pore‐fluid stiffening. The S‐wave velocity will decrease due to the density effect and thus the Poisson's ratio will increase. When there is sufficient clay to bridge the gaps between the quartz grains, P‐wave and S‐wave velocities rise rapidly and the Poisson's ratios decrease. These effects are more pronounced for under‐compacted sandstones. These general results are only slightly modified when the intrinsic anisotropy of the clay material is taken into account. Numerical models indicate that there is a strong, nearly linear relationship between P‐wave and S‐wave velocity which is almost independent of clay distribution. S‐wave velocities can be predicted reasonably accurately from P‐wave velocities based on empirical relationships. However, this does not provide any connection between the elastic and petrophysical properties of the rocks. Numerical modelling offers this connection but requires the inclusion of clay distribution and anisotropy to provide a model that is consistent with both the elastic and petrophysical properties. If clay distribution is ignored, predicting porosities from P‐wave or S‐wave data, for example, can result in large errors. Estimation of the clay distribution from P‐wave and S‐wave velocities requires good estimates of the porosity and clay volume and verification from petrographic analyses of core or cuttings. For a real data example, numerical models of the elastic properties suggest the predominance of dispersed clay in a fluvial sand from matching P‐wave and S‐wave velocity well log data using log‐based estimates of the clay volume and porosity. This is consistent with an interpretation of other log data.     

The influence of parametric uncertainty on the relationships between HBV model parameters and climatic characteristics

Abstract

An HBV rainfall–runoff model was applied to test the influence of climatic characteristics on model parameter values. The methodology consisted of the calibration and cross-validation of the HBV model on a series of 5-year periods for four selected catchments (Axe, Kamp, Wieprz and Wimmera). The model parameters were optimized using the SCEM-UA method which allowed for their uncertainty also to be assessed. Nine climatic indices were selected for the analysis of their influence on model parameters, and divided into water-related and temperature-related indices. This allowed the dependence of HBV model parameters on climate characteristics to be explored following their response to climate change conditioned on the catchment’s physical characteristics. The Pearson correlation coefficient and weighted Pearson correlation coefficient were used to test the dependence. Most parameters showed a statistically significant dependence on several climatic indices in all catchments. The study shows that the results of the correlation analysis with and without parametric uncertainty taken into account differ significantly.     

Prevention of Wellbore Clogging by Intermittent Abstraction

Wellfield “Tull en ’t Waal” (water utility Vitens Midden Nederland) suffers extensively from wellbore (or mechanical) clogging. To prevent this type of clogging, wells have been operated intermittently since August 2005 using a carrousel well operation schedule. Since the introduction of this schedule, wellbore clogging has become minimal.     

A mineral and cumulate perspective to magma differentiation at Nisyros volcano,Aegean arc

Lavas and pyroclastic products of Nisyros volcano (Aegean arc, Greece) host a wide variety of phenocryst and cumulate assemblages that offer a unique window into the earliest stages of magma differentiation. This study presents a detailed petrographic study of lavas, enclaves and cumulates spanning the entire volcanic history of Nisyros to elucidate at which levels in the crust magmas stall and differentiate. We present a new division for the volcanic products into two suites based on field occurrence and petrographic features: a low-porphyricity andesite and a high-porphyricity (rhyo)dacite (HPRD) suite. Cumulate fragments are exclusively found in the HPRD suite and are predominantly derived from upper crustal reservoirs where they crystallised under hydrous conditions from melts that underwent prior differentiation. Rarer cumulate fragments range from (amphibole-)wehrlites to plagioclase-hornblendites and these appear to be derived from the lower crust (0.5–0.8 GPa). The suppressed stability of plagioclase and early saturation of amphibole in these cumulates are indicative of high-pressure crystallisation from primitive hydrous melts (≥ 3 wt% H₂O). Clinopyroxene in these cumulates has Al₂O₃ contents up to 9 wt% due to the absence of crystallising plagioclase, and is subsequently consumed in a peritectic reaction to form primitive, Al-rich amphibole (Mg# > 73, 12–15 wt% Al₂O₃). The composition of these peritectic amphiboles is distinct from trace element-enriched interstitial amphibole in shallower cumulates. Phenocryst compositions and assemblages in both suites differ markedly from the cumulates. Phenocrysts, therefore, reflect shallow crystallisation and do not record magma differentiation in the deep arc crust.     

Vario-scale data structures supporting smooth zoom and progressive transfer of 2D and 3D data

This paper introduces the concept of the smooth topological Generalized Area Partitioning (tGAP) structure represented by a space-scale partition, which we term the space-scale cube. We take the view of ‘map generalization as extrusion of data into an additional dimension’. For 2D objects the resulting vario-scale representation is a 3D structure, while for 3D objects the result is a 4D structure.

This paper provides insights in: (1) creating valid data for the cube and proof that this is always possible for the implemented 2D tGAP generalization operators (line simplification, merge and split/collapse), (2) obtaining a valid 2D polygonal map representation at arbitrary scale from the cube, (3) using the vario-scale structure to provide smooth zoom and progressive transfer between server and client, (4) exploring which other possibilities the cube brings for obtaining maps having non-homogenous scales over their domain (which we term mixed-scale maps), and (5) using the same principles also for higher dimensional data; illustrated with 3D input data represented in a 4D hypercube.

The proposed new structure has very significant advantages over existing multi-scale/multi-representation solutions (in addition to being truly vario-scale): (1) due to tight integration of space and scale, there is guaranteed consistency between scales, (2) it is relatively easy to implement smooth zoom, and (3) compact, object-oriented encoding is provided for a complete scale range.     

Extreme value statistics for annual minimum and trough-under-threshold precipitation at different spatio-temporal scales

Abstract

The aim of this paper is to quantify meteorological droughts and assign return periods to these droughts. Moreover, the relation between meteorological and hydrological droughts is explored. This has been done for the River Meuse basin in Western Europe at different spatial and temporal scales to enable comparison between different data sources (e.g. stations and climate models). Meteorological drought is assessed in two ways: using annual minimum precipitation amounts as a function of return period, and using troughs under threshold as a function of return period. The Weibull extreme value type 3 distribution has been fitted to both sources of information. Results show that the trough-under-threshold precipitation is larger than the annual minimum precipitation for a specific return period. Annual minimum precipitation values increase with spatial scale, being most pronounced for small temporal scales. The uncertainty in annual minimum point precipitation varies between 68% for the 30-day precipitation with a return period of 100 years, and 8% for the 120-day precipitation with a return period of 10 years. For spatially-averaged values, these numbers are slightly lower. The annual discharge deficit is significantly related to the annual minimum precipitation.

Citation Booij, M. J. & de Wit, M. J. M. (2010) Extreme value statistics for annual minimum and trough-under-threshold precipitation at different spatio-temporal scales. Hydrol. Sci. J. 55(8), 1289–1301.