SPATIAL PATTERNS ANALYSIS OF FIELD MEASURED SOIL NITRATE

The purpose of this study was to assess the spatial variability of residual soil nitrate, measured in three contiguous 16 ha fields. Available data for residual soil nitrate were examined using conventional statistics. Data tended to be skewed with the mean greater than the median. Geostatistical methods were used to characterize and model the spatial structure. Three dimensional spatial variability was examined using two semivariograms: horizontal-spatial and vertical. Two dimensional horizontal-spatial semivariograms were also computed for each 0.3m (1ft) layer. Semivariogram analysis showed that there were similarities in the patterns of spatial variability for all fields. The results suggest that the spatial patterns in residual soil nitrate may be correlated with irrigation practices. Furthermore, a trend was found to be present along the vertical direction, which may be related to the time of sampling

Adaptation of water supply to changing climate and land-use activities, case of Ljubljana water supply, Slovenia

A risk management methodology is presented for the adaptation of water supply to changing climate and land-use activities, considering socio-economic aspects. Several management options were selected for the case of the public water supply of Ljubljana, the capital of Slovenia. The major management actions for improving drinking water safety are (1) land-use limitations within the drinking water protection areas and (2) drinking water treatment. Trends in groundwater level are decreasing, above all in the area of well fieldstherefore, artificial recharge and setting up a new independent well field were also considered. The management actions were evaluated according to several criteria, such as water supply risk reduction for the various users (drinking, agricultural, and industrial) and realization of the actions (cost, flexibility, and leg time). For management options, the ranking “Fuzzy Decimaker” tool was applied, which is based on a Multiple Criterion Decision Making (MCDM) technique. Ranking of management actions has shown that all management actions are good as they are clustering in the corner close to the ideal value. For a particular well field, farming limitations in the drinking water protection areas are the best and water treatment is the worst management action, which is due to high costs, low flexibility, and longer lag time

Development and Implementation of a Comprehensive Lake and Reservoir Strategy for Nebraska as a Model for Agricultural Dominated Ecosystems

In agriculturally dominated regions, land use practices have an unusually large impact on water bodies and, therefore, land use may reduce the utility of current ecoregion-based approaches to lake classification by dampening the signals that underlie the ecoregion framework. A team of water quality researchers has been assembled to develop a comprehensive classification scheme for agriculturally dominated ecosystems, using Nebraska as a highly representative model. Three objectives critical to achieving this goal are to establish: (1) a protocol for aggregating water bodies in agricultural ecosystems into classification strata and identifying reference conditions for these classes; (2) the role of remote sensing and the Geographic Information System in a classification strategy; and (3) a technology transfer link between the proposed classification system and end-users

A COMPLEMENTARY TOOL TO WATER QUALITY INDEX: FUZZY CLUSTERING ANALYSIS

ABSTRACT: A general methodology for fuzzy clustering analysis is developed and illustrated with a case study of water quality evaluation for Dianshan Lake, Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates multiple parameters. In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification is worked out. The methodology is relatively simple, and the results can be interpreted to provide valuable information to support decision making and to aid water quality management. Copyright © 1992, Wiley Blackwell. All rights reserve