WATER BALANCE COMPONENTS AT THE STATION SCALE

Precipitation variability throughout the four hydrological years under investigation (10/95–09/99) and between both stations is rather important. In Fig 4, the cumulated precipitation amount measured at the stations is presented. Clearly, interception processes dramatically influence the rainfall amount measured at the forest station, which is around 75 % of the rainfall at the meadow station: 2980 mm and 3950 mm respectively (it is assumed that stemflow for spruce can be neglected). More then 1030 mm precipitation is recorded at the meadow station for years 95/96 and 96/97, while less than 950 mm is recorded during the last two years. Under forest conditions the precipitation amount per year never exceeds 850 mm. It is remarkable that the interception fraction increases to 30 % in 95/96 (the most humid year) and in 97/98 (the driest year).

Forest interception recorded each month is also illustrated in Fig 4. Evidently, this process is the most pronounced during the rainiest period, i.e., the summer months.

0

01.10.95 31.12.95 31.03.96 30.06.96 30.09.96 30.12.96 31.03.97 30.06.97 30.09.97 30.12.97 31.03.98 30.06.98 30.09.98 30.12.98 31.03.99 30.06.99 30.09.99 cumulated rainfall mm]

Meadow Forest

Fig 4: Cumulated precipitation recorded at the forest and meadow stations together with the monthly interception estimated as the difference between both stations (stemflow is neglected).

Surface runoff is measured on 1 m² plots at the Höhenhansl catchment. Surface runoff measured at the meadow station is the highest only in January and April 1996. For the latter, a measurement error due to snowmelt cannot be excluded. At the forest station, surface runoff processes increase considerably during the summer 1997 and 1998 (see Fig 5). The conjunction of high rainfall intensity with extended dryness in the first centimetres of the soil can explain this phenomenon. The forest humus has a high permeability, which varies significantly with the initial moisture content. After long periods of drought, the raw humus of conifer stands is very hydrophobic and constitutes an impermeable layer for the first precipitation events. However, no trace of intense concentrated erosion is visible at the Höhenhansl soil surface.

The effects of high interception losses in the forest and increased overland flow considerably reduce the amount of water that can infiltrate in the forest area. In this study it is assumed that the difference

between the rainfall recorded at both stations is lost (interception loss). At this stage, infiltration under forest represents only 65 % of the meadow infiltration over the four years. To estimate local evapotranspiration processes on a daily time step, a simple daily water balance method is used, where (1) potential evapotranspiration (Etp) is calculated using the Haude method (1955), (2) average root depth is defined using field observations for grass and literature data for trees, and (3) the maximum available water-holding capacity of the soil zone reservoir is calculated as the difference between field capacity and wilting point integrated over the root depth. For a complete description see Ruch C. A. (2002). Under trees, the soil-water budget method allows more water to be available for “soil” evapotranspiration calculations. However, results show that evapotranspiration processes are more pronounced for grass. The reasons are twofold:

Etp calculated with the Haude method is lower for conifer trees than for grass, and less water is available for “soil” evapotranspiration at the forest station because a reduced amount of water infiltrates to fill up the soil-moisture reservoir. The highest difference in evapotranspiration between both stations is calculated for the year 97/98 where “soil” evapotranspiration at the forest station represents only 54 % of the amount calculated at the meadow station. In 98/99 this percentage is about 75 % and over the entire period, “soil”

evapotranspiration under forest represents 65 % of that calculated at the meadow station. All in all, after “soil” evapotranspiration amounts are subtracted from the infiltration amounts, deep percolation represents about 1500 mm and 1000 mm for the whole period at the meadow and forest stations respectively.

0

01.10.1995 31.12.1995 31.03.1996 30.06.1996 30.09.1996 30.12.1996 31.03.1997 30.06.1997 30.09.1997 30.12.1997 31.03.1998 30.06.1998 30.09.1998 30.12.1998 31.03.1999 30.06.1999 30.09.1999 cumulated total [mm]

Meadow Forest error due to

snowmelt ?

Fig 5: Cumulative surface runoff and monthly totals recorded at the forest and meadow stations.

-350

Fig 6: (A) Cumulated percolation water collected at the forest and meadow stations and cumulated spring discharge; (B) Water tension measured at the deepest probe at the forest and meadow stations.

These results can be connected to the pressure head values measured at similar depths at both stations (see Fig 6B). In this figure it is very clear that pressure head values are similar until the winter of 1997.

Due to the snowmelt in April 1996 the whole underground can be considered saturated. As already mentioned above, hydrometeorological conditions, high temperatures, and low precipitation in January and February 1998 favour water release processes so that the saturation deficit increases. This phenomenon could be well observed at the forest station: as is shown for example in Fig 6B for summer 1998 and 1999.

It is also striking to observe that the cumulated percolation amount collected at this station over the period of four years (about 1400 mm, see Fig 6A) is similar to the cumulated discharge from the spring. It can be recognised that a difference of approximately 400 mm is built up only during the humid phase between October 1996 and June 1997 and remains constant until September 1999. It is assumed that water is removed laterally during the humid period so that also upslope water is collected at the suction plate.

This is a good indication that the deep infiltration amount at this station is in good accordance with the spatial deep percolation under forest cover, so that the water balance components measured and calculated at this station can be assumed to be representative for the total forested area from the Höhenhansl watershed.

At the meadow station the pressure heads measured at the deepest probe were never lower than -120 cm between 1995 and 1999. The water collected at the suction plate was even higher than the rainfall amount (see Figs 6A and 4). This water tension constancy near saturation is an indication of local conditions that are not in good accordance with the general conditions in this catchment: grassland (only about 30 % of the land cover) and, in particular, a low slope inclination. On the one hand grass water uptake is not as deep as for trees, on the other hand this station is located in a “flat” area compared to the whole catchment.

Accordingly, it is assumed that the upslope amount of water inflow is larger than the amount removed downslope. If this hypothesis is correct, the pressure head patterns measured at this station are not representative for the general situation but for small areas like that on the left side of the riverbed.

CONCLUSION

Comparison of the water balance components for forest and meadow evidently demonstrate that the canopy interception (estimated to be totally lost in this work) is the key process in explaining the differences in deep percolation amounts. Although about 25 % of the precipitation is intercepted, overland flow is more pronounced under forest cover. This is due to the local larger slope and to the increasing hydrophobic characteristics of the raw humus layer related to growing dry conditions of 97/98. A huge difference is found for deep percolation volumes: for forest they represent only 2/3 of the meadow volumes (over the four years 1000 mm and 1500 mm respectively). Analyses of spring discharge demonstrate that data from the forest station can be assumed to be representative for the headwater catchment Höhenhansl, whereas the constant humid conditions under grassland are influenced by local factors that are not in good accordance with the general situation for this catchment.

REFERENCES

Bergmann, H., Fank, J., Harum, T., Papesch, W., Rank, D., Richtig, G., Zojer H. (1996) Abfluss-komponenten und Speichereigenschaften, Konzeption und Auswertemethoden. Österr. Wasser-u. Abfallwirtschaft, 48, Heft 1/2, 27-45.

Bergmann, H., Schatzl, R., Ruch, C. A., Pozarnik, H., Harum T. (2000) Calibration of Weather Radar Data in Different Space and Time Scales. Proc. of Remote Sens. & Hydro. 2000, IAHS Publ. no. 267.

Bourjot, L., Boissier, J.M., Dobremez, J.F., Fank, J., Fourneaux, C., Gallet, C., Habsburg-Lothringen, C., Harum T., Marmonier P., Parriaux A., Pelissier F., Schaffter N. & W. Stichler (1999) AGREAUALP - Agri-environmental measures and water quality in mountain catchments. Final report 1995-1998. Unpublished EU-report, 74 p, Chambéry – Graz – Grenoble – Lausanne.

Haude, W. (1955) Zur Bestimmung der Verdunstung auf möglichst einfache Weise. In: Mitt. d. Deutschen Wetterdienstes, vol. 11, Bad Kissingen.

Ruch, C. A. (2002) Study of the groundwater flow dynamics in a crystalline headwater catchment and the factors that govern its variability at the sub-catchment scale. Dissertation, K. Franzens Uni., Graz, Austria, pp. 198.

Zojer, H., Fank, J., Harum, T., Papesch, W., Rank D. (1996) Erfahrung mit dem Einsatz von Umwelttracern in der Abflußanalyse. Österr. Wasser- u. Abfallwirtschaft, 48, Heft 5/6, 145-156.