Inuence of rainfall intensity

The previously discussed observation that low intensity rainfall may have contributed to substantial differences in throughfall yields on different time scales suggested a more detailed investigation of the effect of rainfall intensity on throughfall and resulting interception patterns.

Indeed, e.g. Tobón Marin et al. (2000) showed the dependence of interception on rainfall intensity and duration for the Colombian Amazon and Manfroi et al. (2006) investigated these effects on rainfall partitioning in Borneo.

In this study, rainfall intensities were not directly assessed on a single storm basis but rather based on the integrative weekly data from the long-term observations. Data were divided into four classes of weekly gross precipitation ranging from ≤ 10 mm of Pg to > 150 mm of Pg (Table 6). Most frequently represented were weeks with Pg of 10 – 50 and 50 – 150 mm. Lowest throughfall percentages were recorded in the NF with a Tf of 46 – 52% (median) of Pg.

Generally, highest throughfall was recorded in both extreme classes of ≤ 10 mm and > 150 mm of Pg, while the lowest throughfall was recorded in all stands during 10 – 50 mm of Pg. While the effect of increased throughfall under high rainfall conditions is commonly acknowledged (e.g.

Crockford and Richardson 2000, Tobón Marin et al. 2000), Manfroi et al. (2006) also point out that after only 5 mm of rainfall occasionally high throughfall fractions have been observed in Borneo. Most likely, however, is that possibly a limited number of strong storms within the week of observation may have contributed to such high throughfall yields at ≤ 10 mm of Pg per week.

Seen as a series of land use intensity from lowest in NF to STE, LTE and ultimately AF, the throughfall fractions continuously increased independent of rainfall intensity (Fig. 15).

The variability of throughfall measurements showed a more irregular pattern. The throughfall variability was highest in the NF, STE, and LTE stands under lowest rainfall amounts and

Table 6. Rainfall partitioning on the long-term monitoring 4 plots divided up by different weekly sums of Pg.

NF 1 ≤10 12 46 37 52 73 0.6 48

a Shown are the 25^th, 50^th (median), and 75^th percentiles. ^b identical stemflow proportions result from the application of a rigid model based on regressions of stemflow, basal area distribution and gross precipitation.

Results and Discussion Rainfall Partitioning 27

decreased steadily with increasing rainfall in the NF and in STE and LTE stands. Contrastingly, the throughfall variability in the AF stand was lowest under lowest rainfall conditions, albeit consistently higher than in any other forest use type, and maintained a similarly high level under increasing rainfall intensities (Fig. 15 and Fig. 16). The spatial variability of measured throughfall in the AF stand was highest among the studied forest use types.

These results suggest that forests devoid of continuous human management (e.g. NF, STE, and LTE) with a relatively high canopy respond to rains of relatively low intensity with high variation because gaps may play an important role during the process of saturating the canopy.

Under such conditions, the variability between precipitation passing freely through existing gaps in the canopy and precipitation retained as interception is highest. This pattern loses its signicance once rainfall intensies and only a small fraction of Pg is required to saturate the canopy storage and when increasing canopy drip eventually reduces the contrast between gaps and locations shaded by the canopy (see also Hall 2003). On the other hand, the consistently high

Fig. 15. The variability of throughfall measurements on the four investigated long term plots (NF1, solid; STE2, cross-hatched; LTE4, hatched; AF3, open) in four different classes of weekly Pg. Shown are the 5^th, 25^th, 50^th (median), 75^th and 95^th percentiles. Different means between research sites (n = 30 rainfall gauges per plot) are indicated by different lower case letters (Wilcoxon signed ranks test, two-tailed, p < 0.01).

28 Rainfall Partitioning Results and Discussion

variation of throughfall in the AF may be due to the distinct layering of a dense understorey by the cacao trees which are constantly pruned to ~5 m height (see also chapter 3.2.5 on spatial variability).

Rainfall intensity can also influence the effect that structural properties have on interception (see also chapter 3.2.4). Although correlations obtained with n = 4 must generally be interpreted with caution, such highly signicant correlations as shown in Fig. 17 can demonstrate how interception may respond to different rainfall intensities. Evidently, there is little effect of rainfall intensity on the fraction of interception in NF and AF, while it was highly different between STE and LTE at low rainfall intensity but approached a similar value under highest rainfall intensities (Table 6). In the context of stand structural parameters, the basal area of all trees, which combined information on stand density and dimension of trees, had its highest impact (r² = 0.99) on interception when rainfall was low and the overall canopy storage capacity was a critical parameter. This process appeared to lose its signicance under increasing rainfall intensity (r² = 0.85) when canopy storage reached saturation. Inversely, the stem density (dbh ≥ 50 cm), i.e. the amount of large trees per hectare, correlated best with interception at highest rainfall conditions (r² = 1.00). The density of large diameter trees was shown to respond directly to forest use intensity (Fig. 10) and canopies of large trees are hypothesized to dry up fastest after rainfall which would be of highest importance during periods with high rainfall (see also chapter 3.2.6).

Fig. 16. Relationship between weekly gross precipitation as recorded in the natural forest (left) and in the agroforest (right) and its corresponding coefcient of variation from the throughfall measurements.

Results and Discussion Rainfall Partitioning 29