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Sokrat Amataj Todor Anovski Ralf Benischke Romeo Eftimi Laurence L. Gourcy Liliana Kola Ioannis Leontiadis Eftim Micevski Alqiviadis Stamos Jovan Zoto 《Environmental Geology》2007,51(5):749-753
Prespa Lake and Ohrid Lake constitute a hydraulic system shared between Albania, FYR of Macedonia and Greece. Karst rocks
separate both lakes. The elevation of Prespa Lake is about 150 m higher than that of Ohrid Lake. Considering these facts,
Cvijić formulated in 1906 the hypothesis that Prespa Lake recharges the St. Naum and Tushemisht springs at Ohrid lakeside.
Environmental isotopes demonstrated that Prespa Lake recharges about 37–42 and 52–54% of water emerging in St. Naum, and Tushemisht
springs, respectively. An artificial tracer experiment carried out in 2002 physically demonstrated the underground connection
between both lakes. This experiment confirmed the supposed underground connection and brought important information about
the groundwater velocity, transit time, and karst water conduits development. 相似文献
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Regionalisation of the parameters of the log‐Pearson 3 distribution: a case study for New South Wales,Australia 下载免费PDF全文
The index flood method is widely used in regional flood frequency analysis (RFFA) but explicitly relies on the identification of ‘acceptable homogeneous regions’. This paper presents an alternative RFFA method, which is particularly useful when ‘acceptably homogeneous regions’ cannot be identified. The new RFFA method is based on the region of influence (ROI) approach where a ‘local region’ can be formed to estimate statistics at the site of interest. The new method is applied here to regionalize the parameters of the log‐Pearson 3 (LP3) flood probability model using Bayesian generalized least squares (GLS) regression. The ROI approach is used to reduce model error arising from the heterogeneity unaccounted for by the predictor variables in the traditional fixed‐region GLS analysis. A case study was undertaken for 55 catchments located in eastern New South Wales, Australia. The selection of predictor variables was guided by minimizing model error. Using an approach similar to stepwise regression, the best model for the LP3 mean was found to use catchment area and 50‐year, 12‐h rainfall intensity as explanatory variables, whereas the models for the LP3 standard deviation and skewness only had a constant term for the derived ROIs. Diagnostics based on leave‐one‐out cross validation show that the regression model assumptions were not inconsistent with the data and, importantly, no genuine outlier sites were identified. Significantly, the ROI GLS approach produced more accurate and consistent results than a fixed‐region GLS model, highlighting the superior ability of the ROI approach to deal with heterogeneity. This method is particularly applicable to regions that show a high degree of regional heterogeneity. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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