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Bromus racemosus L. is a rather rare grass species of moist meadows. It has strongly decreased in the course of the 20th century due to intensification of agricultural grassland management, and is therefore included in Red Lists of several European countries. Its winter annual life-cycle is remarkable for a species of permanent grasslands.
The aim of this study is to determine the habitat preference and optimal management of B. racemosus in the Netherlands and surrounding countries. Vegetation, soil and hydrological data from 28 sites in the Netherlands have been compared with B. racemosus cover, and with vegetation data from surrounding countries. The results indicate that B. racemosus is characteristic of Molinio-Arrhenatheretea meadows with good mineralisation and aftermath grazing. The optimum lies in grasslands of the alliance Alopecurion pratensis (Deschampsion cespitosae), but the species ranges from wetter Calthion palustris meadows to drier Arrhenatherion elatioris and Cynosurion cristati grasslands. It prefers intermediate nutrient levels and hydrological conditions (mesic sites), but within this range the highest cover is found in relatively nutrient rich and dry sites. Because of the absence of a seedbank and a low dispersal capability, B. racemosus is vulnerable to changes in grassland management. A management of mowing after 15 June and aftermath grazing is most suitable, since it enables fruit ripening and the maintenance of an open sward, needed for germination and development. The risk of extinction is likely to be higher in flat polders than in floodplain sites with natural relief, where the species may shift between belts in different years.
Floodplains and other wetlands depend on seasonal river flooding and play an important role in the terrestrial water cycle. They influence evapotranspiration, water storage and river discharge dynamics, and they are the habitat of a large number of animals and plants. Thus, to assess the Earth’s system and its changes, a robust understanding of the dynamics of floodplain wetlands including inundated areas, water storages, and water flows is required.
This PhD thesis aims at improving the modeling of large floodplains and wetlands within the global-scale hydrological model WaterGAP, in order to better estimate water flows and water storage variations in different storage compartments. Within the scope of this thesis, I have developed a new approach to simulate dynamic floodplain inundation on a global-scale. This approach introduces an algorithm into WaterGAP, which has a spatial resolution of 0.5 degree (longitude and latitude) globally. The new approach uses subgrid-scale topography, based on high-resolution digital elevation models, to describe the floodplain elevation profile within each grid cell by applying a hypsographic curve. The approach comprises the modeling of a two-way river-floodplain interaction, the separate downstream water transport within the river and the floodplain – both with temporally and spatially different variable flow velocities – and the floodplain-groundwater interactions. The WaterGAP version that includes the floodplain algorithm, WaterGAP 2.2b_fpl, estimates floodplain and river water storage, inundated area and water table elevation, and also simulates backwater effects.
WaterGAP 2.2b_fpl was applied to model river discharge, river flow velocity, water storages, water heights and surface water extent on a global-scale. Model results were comprehensively validated against ground observations and remote sensing data. Overall, the modeled and observed data are in agreement. In comparison to the former version WaterGAP 2.2b, the model performance has improved significantly. The improvements are most remarkable in the Amazon River basin. However, the seasonal variation of surface water extent and total water storage anomalies are still too low in many regions on the globe when compared to observations. A detailed analysis of the simulated results suggests that in the Amazon River basin the introduction of backwater effects is important for realistically simulating water storages and surface water extent. Future efforts should focus on the simulation of water levels in order to better model the flow routing according to water slope. To further improve the model performance in specific regions, I recommend that the globally constant model parameters that affect inundation initiation, river-floodplain interaction, DEM correction for vegetation, and backwater amount at basin or subbasin-scale be adjusted.