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Fast analysis of different species of molecules in soils is investigated by capillary electrophoresis (CE). Several CE techniques for the analysis of inorganic ions and carbohydrates have been tested. With regard to the intents of pedologists and the usually large number of soil analyses a bundle of CE systems is proposed, capable of effecting time-saving soil analyses. Adapted electrolyte systems recently published and new separation systems are described. Examples of the application of these methods to two different soil samples are presented.

Throughfall measurements were made under primary terra firme rainforest in the Rio Pichis valley, in the Upper Amazon Basin of Peru. Based on 214 precipitation events over nearly 18 months, throughfall was estimated to be 83.1±8.8% of gross precipitation. Regression analysis of all events revealed that gross precipitation is the only significant explanatory variable; the use of one-burst events does not significantly improve the regression relationship. Gross precipitation is, however, a poor predictor of throughfall for small rainfall events. The two forest structure parameters, canopy capacity, S, and free throughfall coefficient, p, were determined to be 1.3±0.2 mm and 0.32±0.18 mm. Rainfall intensity was found to influence these parameters. New methods which attempt to minimize the influence of meteorologic variables are used to estimate the potential values of these canopy parameters.

What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.