Abstract

Abstract Spatial and temporal variability of the interception in the natural wetland valley, the lower Biebrza basin case study. The paper presents the research carried out in the lower basin of Biebrza River valley in order to identify interception for natural wetland plant communities. Maximum interception, i.e. the largest amount of water, expressed in millimeters, which can be captured and retained by plant canopy from rainfall is one of the key parameters of the water cycle modeling. Maximum interception was determined based on the difference of the masses of wet and dry fresh plant samples. Collection of plant material samples took place during the five measurement sessions, which began immediately after the flood recedes, and then lasted until the end of the growing season. Interception spatial variability was analyzed on the basis of the results of maximum interception measured for selected plant aggregations in the different sampling points. The obtained values were extrapolated to the area of the lower basin of Biebrza River using vegetation map of the Biebrza National Park. By conducting a test sessions in the five coming months, the maps of the spatial variability also show changes over time. Methodology used in the described tests allowed for obtaining of satisfactory results. They present, in a correct way, variation occurring between the plant aggregations due to their morphology. In most cases the results are consistent with data from the literature. As results of the analysis of spatial variability of the maximum interception, the highest values were found for the plant communities located in the immediate vicinity of the river channel. With the increase of the distance from river towards the valley edges the maximum interception values decrease. These changes can be seen in the form of strips parallel to the river channel, which corresponds to the plant zones. Obtained map of spatial variability of the maximum interception, which is the results of extrapolation of the values assigned to plant communities, has a high correlation with the map resulting from the analysis of satellite images

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