A new method for spatio-temporally explicit predictions of groundwater, surface water and habitat interactions in riparian ecosystems

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MaierNadine_2018_09_21.pdf (11.58 MB)

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2018

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DOI:
http://dx.doi.org/10.22029/jlupub-16738

Abstract

Floodplains are dynamic and complex systems. Their hydrological regime allows for the creation of specific conditions for flood meadows with a wide habitat heterogeneity and specialized floodplain plant species. At the same time, floodplains are the most-endangered ecosystems worldwide, as they are characterized by extremely high land loss. Therefore, they are one of the main focuses of national and international nature conservation and restoration efforts. The aim of such restoration measures is not only to restore the retention function, but also the habitat function for typical, highly specialized, and endangered species. However, compared to the importance of ecosystem services provided by floodplains and their role in biodiversity, there is little research on how scientifically-based information can be integrated in the planning and decision-making of restoration projects in order to make them more efficient and effective. Plant distribution is strongly related to hydrologic conditions on a high temporal and spatial resolution. For example, flood sensitive species prefer elevated microsites and will die during large inundation periods. To elucidate the relevance of a detailed knowledge of the hydrological regime, a parsimonious surface water-groundwater model was developed using the Catchment Modeling Framework (CMF). Further, this process-based hydrological model was linked with a species distribution model in order to predict rare and endangered species. The nature reserve Kühkopf-Knoblochsaue (34.5 km2) serves as the study area. This reserve is of particular importance for rare and endangered flora and fauna. As a first step, the model was developed, adjusted, and tested for the past 16 years. Next, the surface water-groundwater interaction model was linked with a species distribution model to predict the occurrence of rare and endangered species. A comparison study showed that the incorporation of temporally and spatially high-resolution data from a hydrological model, as developed here, results in superior model qualities. In addition, the relevance of a broad set of hydrological predictors to simulate whole plant communities with diverse specific eco-hydrological requirements was shown. Applications of different climate models to the surface water-groundwater interaction model showed large spatial and quantitative changes in the inundation characteristics in the near and far future. A linkage of these hydrological regime projections with the species distribution model pointed out the possibilities for habitat projections and the advantages for conservation measures.

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