WEKU – a GIS-Supported stochastic model of groundwater residence times in upper aquifers for the supraregional groundwater management

 The supraregional GIS-supported stochastical model, WEKU, for the determination of groundwater residence times in the upper aquifers of large groundwater provinces is presented. Using a two-dimensional analytical model of groundwater flow, groundwater residence times are determined within two extreme cases. In the first case, maximal groundwater residence times are calculated, representing the part of groundwater, that is drained by the main surface water of a groundwater catchment area. In the second case, minimal groundwater residence times for drainage into the nearest surface water are determined. Using explicit distribution functions of the input parameters, mean values as well as potential ranges of variations of the groundwater residence times are derived. The WEKU model has been used for the determination of groundwater residence times throughout Germany. The model results – mean values and deviations of the groundwater velocity and the maximal and minimal groundwater residence times in the upper aquifers – are presented by general maps and discussed in detail. It is shown that the groundwater residence times in the upper aquifer vary regionally, differentiated between less than 1 year and more than 2000 years. Using this information, the time scales can be specified, until measures to remediate polluted groundwater resources may lead to a substantial groundwater quality improvement in the different groundwater provinces of Germany. With respect to its supraregional scale of application, the WEKU model may serve as a useful tool for the supraregional groundwater management on a state, federal or international level. Received: 15 August 1995 · Accepted: 15 October 1995     

Models for the magnitude‐distribution of brightest cluster galaxies

The brightest, or first-ranked, galaxies (BCGs) in rich clusters show a very small dispersion in luminosity, making them excellent standard candles. This small dispersion raises questions about the nature of BCGs. Are they simply the extremes of normal galaxies formed via a stochastic process, or do they belong to a special class of atypical objects? If they do, are all BCGs special, or do normal galaxies compete for the first rank? To answer these questions, we undertake a statistical study of BCG magnitudes using results from extreme value theory. Two-population models do better than one-population models. A simple scenario where a random boost in the magnitude of a fraction of bright normal galaxies forms a class of atypical galaxies best describes the observed distribution of BCG magnitudes.     

RELAXING ASSUMPTIONS OF PERFECT INFORMATION IN PARK VISITATION MODELS*

Variables related to urban park awareness are identified and methods for relaxing assumptions of perfect information in park use models are discussed. Park awareness is related to park characteristics (age and degree of development of the park), population characteristics (race, age, length of residence, recreation participation), and distance. Park attributes are stronger predictors of both park awareness and use than is distance. These findings parallel similar research on the cognitive aspects of shopping decisions.     

REVIEWS OF GEOGRAPHIC SOFTWARE

Reviews of geographic software in this article: DEMO-GRAPHICS: WORLD POPULATIONS AND PROJECTIONS. ESP GAUSS. CEMODEL S. Damus LIMDEP. William H. Greene MICROSTAT 4.1 OTIS PCIPS. (Personal Computer Image Processing System) . H.J. Meyers and R. Bernstein. REGRESSION ANALYSIS OF TIME SERIES (RATS) SPSS/PC+ URBAN DATA MANAGEMENT SOFTWARE (UDMS)     

Directions and possibilities of mathematical geology

This paper considers the present state of mathematical geology. Three directions are recognized: applied, theoretical, and mathematical. Applied mathematical geology includes formal use of mathematics to solve problems and computer processing of data. Success is achieved by a correspondence of mathematical methods used to the nature of geological data. This correspondence can be demonstrated by purely mathematical means. Theoretical mathematical geology uses mathematics as a language of geology; however, a number of methodological problems must be solved: formalization of initial geological concepts and creation of a strict conceptual basis, substantiation of initial principles of mathematical simulation, creation of theoretical geological models, problems of elementary and coincidence in geology, and methodological substantiations of possibilities of any mathematical model to approximate geological models. The essense and significance of these problems are considered. The main task of mathematical geology is to prove its correspondence to the nature of the geological objects studied, geological data obtained, and geological problems solvable. Finally, the main problems of mathematical geology are not so much mathematical as geological and methodological.