Sampurno Bruijnzeel Arnoud Frumau

Transcription

1 Sampurno Bruijnzeel Arnoud Frumau

2 Fog Interception for the Enhancement of Streamflow in Tropical Areas (FIESTA): Rationale Early work in N Costa Rica suggested very high runoff coefficients for Atlantic catchments, presumably due to extra inputs of cloud water. Cloud forest clearing might lead to a loss of this extra input

3 FIESTA: key issues Key question: What is the effect of replacing montane cloud forest by pasture on streamflow totals and regime for catchments of up to 100 km 2 in northern Costa Rica? Related issues: Up-scaling of point data on forest water use, fog interception, and crown drip in landscapes with complex topography and vegetation patterns.

4 FIESTA: methodological considerations Guatemala case study A direct comparison of dry season flows from cloudforested and cleared catchments in Guatemala gave (much) higher flows from the forest. This result is misleading because of contrasts in basin elevation and thus in cloud stripping / rainfall (and basin leakage?)

5 FIESTA: methodological considerations Coweeta paired catchment set-up Ideally, hydrological impacts of land-cover change are evaluated via paired catchment experiments in which control and treatment basins are intercalibrated first.

6 FIESTA: methodological considerations Recovery Pre-harvest Post-harvest Reduced summer flows after (partial) cutting of Douglas fir forest subject to frequent fog were demonstrated in the Pacific NW of the US. Flows recovered after 5-6 yrs, presumably because regrowth captured sufficient fog again ( black box!). Note long time frame

7 FIESTA: methodological considerations When a paired experiment is not possible, can one use a bottom-up, processbased (modeling) approach? Exceedingly difficult in the case of cloud forest due to complex topography, wind-blown rain and cloud, excessive humidity and abundant epiphytes

8 FIESTA: methodological approach Direct comparison of small catchments under cloud forest and pasture but coupled with intensive process measurements within catchments (1 st year, 2 nd year). Added process work in secondary forest and beneath isolated remnant trees in pasture areas (2 nd year). Process modeling coupled with spatial characterisation of topography, soils, climate & vegetation (1 st & 2 nd yr). Validation of hydrological model predictions at various scales: 4, 10, 75 (San Gerardo) and 10,000 ha (Rio Chiquito) (2 nd & 3 rd year).

9 Cloud forest vs. pasture comparison, Monteverde, Costa Rica: Forest catchment Size 3.5 ha Elevation range m Windward LMCF Canopy height at m Epiphyte biomass 16.2 t ha-1

10 Cloud forest vs. pasture comparison, Monteverde, Costa Rica: Pasture catchment Size 9.1 ha Elevation range m Scattered isolated trees

11 Forest 20 m Cloud forest vs. pasture comparison, Monteverde, Costa Rica

12 Cloud forest vs. pasture catchment comparison, Monteverde, Costa Rica Soil water measurement Continuous discharge measurement Project soil physical lab

13 Catchment comparison, intermediate scales (mixed land cover) Mixed catchment, 75 ha Rio chiquito, 100 km 2 One of four extra climate stations within Rio Chiquito basin

14 Catchment comparison, intermediate scales (mixed land cover) Rio Chiquito San Gerardo Rio Chiquito cover 2001

15 Duration of canopy wetness in 2003 Adjusted fog gauge Rainfall: 27% of total time Horizontal precipitation: 44% Leaf wetness sensor: 58% Suppressed long-wave radiation: 55% Leaf wetness sensor

16 Evaporation from forest and grassland Example day 34, dry canopy, clear day (exceptional!): Forest Et: 4.11 mm/day Pasture Et: 3.61 mm/day Mean ET over 2003: Mean ET/Rn (2003): Components of ET (2003): Forest: 1.94 mm/day Forest: 0.61: Dry: 537 mm Wet: 172 mm Dry: 597 mm Wet: 137 mm Pasture Et: 2.01 mm/day Pasture: 0.57

17 What is the best approach to quantify cloud water deposition onto a forest canopy? Quantifying cloud deposition Fog gauges useful for site comparison and timing of fog occurrence, but results need to be converted to actual catch by a forest canopy (plus time lag of up to 5 h). Typical conversion factor as low as Polypropylene screens and wire harps, Puerto Rico Wire harp

18 Quantifying fog deposition (F WB ) via the wet-canopy water budget: F WB = (TF + SF) - P + Ei Throughfall gutter Stemflow Rain gauges Roving gauge TF = throughfall SF = stemflow P = rainfall Ei = wet canopy evaporation

19 Addressing wind and topographical effects on rainfall measurement Rain R falling at an angle b on a slope with angle a has an intensity I that differs from that measured by a horizontal rain gauge orifice I 0 ; rainfall depth normal to the slope (P a ) differs from rainfall depth normal to the horizontal (P a ). Rainfall is seriously underestimated by an ordinary rain gauge when winds are strong and rainfall intensities low. Catches need to be corrected for this. Corrections based on wind speed & raindrop size (derived in turn from rainfall intensity). Spherical rain gauge: the answer?

20 High spatial variability in throughfall Large spatial variability in throughfall tends to cause underestimation of measured TF unless large number of (roving) gauges is used (>30). Drip points: concentrated TF such that TF > P Structural variation between species Typical CV: %

21 High spatial variability in throughfall Additional spatial variability in TF introduced by variations in canopy exposure to airflows and inclined rain. Rain and fog shadows created by uneven forest canopy Upscaling via canopy DEM, rainfall and vegetation properties (Mulligan)

22 High spatial variability in throughfall Plots located so as to represent different slope aspect and exposure.

23 Application of wet-canopy budget method to estimate event fog deposition, PR Eddy-covariance method gives much lower (10x) fog deposition rates than water-budget method (F WB ) ( footprint mismatch?). Direct deposition measurement, PR

24 Application of wet-canopy budget method to estimate event and period fog deposition CR Trial period of 65 days during 2003 dry season

25 Application of wet-canopy budget method to estimate event and period fog deposition CR Fog relatively unimportant compared to wind-driven rain Eddy covariance set-up

26 Relative amounts of throughfall vary seasonally Strong contrast between seasons reflects type of rainfall (convective vs. orographic).

27 Determining true precipitation input Modified Juvik Rainfall inclination increases with wind speed and decreases with rainfall intensity.

28 Water budgets for contrasting land uses: forest catchment summary

29 Water budgets for contrasting land uses: pasture catchment summary

30 Spatial precipitation input strongly controlled by slope aspect and gradient

31 Spatial precipitation input strongly controlled by slope aspect and gradient

32 Water budgets for contrasting land uses: Forest: P 5720 mm TF 6485 mm ET 710 mm Q 2755 mm Apparent leakage 3190 mm ->9mm/day Pasture: P 4135 mm ET 685 mm Q 2810 mm Apparent leakage 725 mm -> 2mm/day Conclusion: very high basin leakage (2-9 mm/day); Most of this water ends up in lake Arenal?

33 Outlook (all catchment scales) Quantify areal rainfall inputs Analyse stormflow response Rio Chiquito Determine basin leakage Analyse Penas Blancas record PB San Gerardo